Targeted resource allocation

Target resource allocation

[0001] The application for the present invention is a divisional application for an invention patent with an application date of September 28, 2008, an application number of "200810168873.8", and an invention title of "target resource allocation".

Technical field

[0002] The subject invention generally relates to industrial network systems using multiple network traffic analyzers, and more particularly relates to the sharing of resources, which are used by embedded historians for collection and Process historical data. Specifically, the present invention relates to an industrial automation system and a method of collecting data in an industrial factory.

Background technique

[0003] Advances in computer network technology continue to share information between increasingly efficient and popular systems. These advancements have prompted more and more developments in network systems, in which new transmission infrastructures including wireless networks have emerged. With the increase in the number, speed and complexity of network systems, corresponding network problems have appeared. Typically, the introduction of dedicated, independent, diagnostic equipment connected to what is often referred to as a network traffic analyzer can help solve some network problems.

[0004] Generally, a network traffic analyzer acquires key information about network traffic parameters and can acquire and record these data to provide a permanent record of communication information on the network bus. Based on the existence of certain conditions, the network traffic analyzer can be controlled to start and/or end recording. Traditionally, the network traffic analyzer is a separate, dedicated support device. The network traffic analyzer is usually based on a PC or is a special tool and requires special network interface hardware and software modules to suit a specific network standard or configuration. When users use the network in a real-time environment, they often need to analyze the network and collect diagnostic information. Diagnosing network problems requires the configuration of a network traffic analyzer with appropriate network interface modules and associated software.

[0005] Generally, a network traffic analyzer acquires key information about network traffic parameters and can acquire and record these data to provide a permanent record of communication on the data bus. Based on the occurrence of specific conditions, the network traffic analyzer can be controlled to start and/or end recording. Traditionally, the network traffic analyzer is a separate, dedicated support device. The network traffic analyzer is usually based on a PC or is a special tool and requires special network interface hardware and software modules to suit a specific network standard or configuration. When users use the network in a real-time environment, they often need to analyze the network and collect diagnostic information. To solve network problems, you need to configure a network traffic analyzer with appropriate network interface modules and related software.

[0006] In addition, in an industrial environment, manufacturers particularly need to collect, analyze, and optimize real-time data from multiple websites around the world. One known solution for recording this data involves providing a local recording module that often occupies a slot on the control system backplane. For example, as a history-recording device, it can directly communicate with the controller through the backplane, or communicate remotely through a network interface. In addition, the recorded history can enable data archiving from the controller to the archiving engine, where the archiving engine provides additional storage capabilities.

[0007] In a distributed control system, the industrial controller can be divided into multiple control elements to facilitate the controller hardware configuration, and each control element can perform different functions. In a rack and/or through a network or other communication medium, specific control modules required for control tasks can be connected together on the backplane. Different control modules can also be spatially distributed in several locations along a common communication link. Such a modular structure can further provide different numbers and types of output

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Different applications of input/output (I/O) circuits, which can be determined by the specific equipment or process being controlled. This stored control program runs in real time to provide output to the controlled process (for example, electrical signal to output such as transmission mechanism, etc.).

[0008] On a public communication link or network, data can communicate with these remote modules, where any or all modules on the network communicate through a public and/or industrial communication protocol. Multiple controllers in one control system can communicate with one another, with controllers residing in other control systems, or with applications outside the system or control environment (for example, transactions related to systems and applications). Therefore, management processes such as diagnosis/prediction methods for fault control are becoming more and more complex.

[0009] In addition, in such an environment, analysis and cooperation particularly require the interaction of two information streams, namely "internal" data (collected from industrial units, such as through history, log collectors, etc.), and " "External" data (in conjunction with data traffic serving the network). In a conventional system, these two information streams are collected and analyzed separately-for example, the first set of equipment/analyzers collect internal data from modules/units, and the second set of equipment/analyzers collect data about network traffic. Usually, the available relationships between these two data streams (for example, synchronization relationships, sequence counts, etc.) are not immediately obvious and are often interpreted manually, thus increasing the inefficiency of the system. In addition, in conventional systems, these two information streams are not synchronized, and their collection does not depend on the criticality of the collection phase. Further, typically, in these systems, the allocation of system resources (eg, memory allocation, recovery memory, and allocation decisions for data collection) does not rely on dual data stream evaluation/determination analysis. Therefore, in general, the system is likely to be negatively compressed by over-allocation and under-allocation, resulting in slower data collection and/or failed attempts.

Summary of the invention

[0010] In order to provide a basic understanding of some aspects of the present invention, a simplified overview is presented next. This overview is neither an extensive overview, nor is it intended to identify key/important elements or delineate the scope of the different aspects described herein. Its sole purpose is to present some concepts in a simplified form as a prelude to the detailed description presented later.

[0011] Embodiments of the present invention provide an industrial automation system, including: a memory configured to store computer-executable components; and a processor, communicatively coupled to the memory, configured to execute the computer-executable components or facilitate Execution of computer-executable components, computer-executable components include: coordination components configured to synchronize data streams associated with the industrial automation system to determine at least one of the correlations or relationships between events in the indicated data streams The data stream includes at least one internal data stream and at least one external data stream, at least one internal data stream provides process data related to at least a part of the industrial automation process controlled by the controller device of the industrial automation system, and at least one The external data stream provides traffic data associated with the network equipment of the industrial automation system, and wherein the coordination component is further configured to present the associated information based on the defined data granularity level; and the distribution component determines the history of the controller device based on the associated information The data collection bandwidth of the machine.

[0012] Embodiments of the present invention provide a method for collecting data in an industrial factory, including: receiving first data from an internal data stream through a system including a processor, and the internal data stream is provided with a controller device of the industrial factory. Process data related to at least a part of the industrial automation process, and receive second data from an external data stream through the system. The external data stream is associated with traffic data on one or more network services of the industrial plant; by adopting shared printing At least one of the time stamp or the shared sequence count to synchronize the first data and the second data; based on the relationship between the first event in the internal data stream and the second event in the external data stream based on the indication determined according to the synchronization Determine the respective data collection bandwidth of a group of historical machines associated with the controller device; and promote the display of relational data based on the defined data granularity level.

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[0013] The subject innovation provides a system and method that can automatically allocate and manage resources in an industrial system through the allocation component that determines the available resources, and further manage its allocation. For example, a platform can be used based on the use of explicit correlation (for example, a predetermined model/external data source set by the user) and/or implicit correlation (which is automatically deduced in the event/possible cause), To provide high speed, time series, data storage and recovery using local or remote control processors. These industrial systems can take advantage of both "internal" data streams (for example, historical data collected from industrial units, automatic or process data, etc.) and "external" data streams (for example, traffic data on one or more networks, or communication Data, etc.), which can be partly collected based on the degree of risk/importance criteria assigned to each collection stage.

[0014] Correspondingly, various industrial units (for example, controllers, built-in historians, etc.) can thus communicate with each other or with distribution components, where the resources related to each industrial unit can be described by metadata , And aggregated conceptually (for example, in a database) followed by the next assignment, according to one or more algorithms (for example, probabilistic). Moreover, the distribution component can be dynamically trained based on the dependencies existing between the respective sources, and requests from multiple industrial units (which can change automatically during the process).

[0015] Such an automatic and dynamic allocation device can allocate resources from the available resource pool to the industrial system, and thus provide efficient operation (for example, automatically increase/decrease resources based on usage). Multiple allocation rules and/or algorithms for different resource types can be predetermined and/or automatically prepared via artificial intelligence components. For example, the allocation rules may include numerical balancing across resource instances and group optimization algorithms. When determining resource requirements, such a rule may consider the actual resource usage of each unit of the industrial unit.

[0016] Available resources can be determined in a related method, where in the entire operation of the industrial system, these resources and related allocation rules and algorithms can be redefined to make more efficient use of available resources for allocation. For example, the resources to be allocated can vary in number, characteristics, and types (for example, the combination of available resources for a unit like a built-in history machine can vary). Such a determined resource pool may be subsequently operated during the operation of the industrial system (for example, resources are automatically increased/decreased based on usage) to be managed according to the relationship between the industrial unit and the available resources.

[0017] In related aspects, the coordination component can simultaneously collect and analyze "internal" data streams and "external" data streams. It will be understood that each data stream can further include multiple data streams associated with industrial automation systems. The coordination component can synchronize and maintain the timing and sequence relationship between time and network traffic. Therefore, for example, in the multiple data streams, the association or causality between seemingly random events can be easily estimated/decided. Similarly, the coordination component can synchronize and maintain the timing and sequence relationship between events in multiple data streams or a mixture of internal and external data streams. Therefore, in multiple data streams, it is easy to estimate/determine seemingly random The association or causality between events, some of which have an effect on the event while others have no effect. The coordination component can further record the initial combined data together (for example, based on sequence relationship, time stamp) and then predict the level based on the data interval size (for example, nanosecond interval, millisecond interval), and present these related data to the user. In related aspects, in such a synchronized industrial positioning, the matching component can pre-determine the module/industrial zone with a predictive trigger event. Based on defined zones and/or event triggers, data can be displayed sequentially to the user.

[0018] According to a further aspect, the automated industrial system of the subject innovation may include identification components that analyze "internal" data streams and "external" data streams, and identify patterns in data trends affecting industrial processes. The pattern recognition can be based on: a predetermined pattern (for example, comparison of the factory operation status in multiple previous batch results), and/or a regularly updated interrupt control program. The recognition component can further use complex associations (for example, a predetermined module set by the user/external data source), and/or

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Simple associations dynamically deduced in events/possible causal links.

[0019] In addition, a centralized or distributed data collection system that uses synchronization capabilities between historical data (for example, internal unit logs) and network traffic analyzer data can form a unified database (for example, a single compressed form). Log files, binary data in flat files, different forms of databases, etc.). Correspondingly, historical data can be retained for future predictive diagnosis and finding problem events, where the data source is not loaded at the display level (for example, decoded data at a level that requires an interval size), nor is it in the collection stage. Based on data importance, usage similarity, etc., the centralized data collection system combined with binary information flow can selectively decompose stored data (for example, gradually clear). Correspondingly, the interface with the network can be promoted, in which different configurations of network interfaces such as control network, device network, Ethernet, and wireless network can be used.

[0020] In order to accomplish the foregoing and related ends (ends), certain exemplary aspects are described here in connection with the following and the accompanying drawings. These aspects are indications of different ways that can be practiced, and it is intended to cover all of them here. When considered in conjunction with the drawings, other advantages and novel features will become apparent from the detailed description below.

Description of the drawings

[0021] FIG. 1 shows a functional block diagram of a distribution component of an industrial system according to an aspect of the subject innovation.

[0022] FIG. 2 shows a block diagram of the coordination components that facilitate the data collection and management process of the innovative industrial system of the subject.

[0023] Figure 3 shows a network interface with an embedded network traffic analyzer capable of interacting with the subject innovation distribution component.

[0024] FIG. 4 shows the matching components that are part of the industrial system of the subject innovation.

[0025] FIG. 5 shows the recognition components of the recognition pattern in the data trend that affects the industrial process in accordance with an aspect of the subject innovation.

[0026] Figures 6a and 6b show an industrial system with a network analyzer at various levels of the subject innovation.

[0027] FIG. 7 shows a related method of allocating resources according to a specific aspect of the subject innovation.

[0028] FIG. 8 shows a further method of resource allocation in one aspect of the subject innovation.

[0029] FIGS. 9a and 9b show an exemplary industrial automation network for resource allocation using allocating components.

[0030] FIG. 10 illustrates an exemplary computing environment that can be used to perform different aspects of the subject innovation.

[0031] FIG. 11 shows an industrial device with a bottom plate and associated modules capable of using distribution components according to an aspect of the subject innovation.

Detailed ways

[0032] Different aspects of the subject innovation will now be described with reference to the accompanying drawings, in which the same reference numerals represent the same or corresponding elements. However, it should be understood that the drawings and detailed descriptions related to them are not intended to limit the claims to the specific form disclosed. Precisely, the intention is to cover all modifications, equivalents and substitutions falling within the spirit and scope of the claims.

[0033] FIG. 1 shows an allocation component 110 that automatically allocates resources from a pool of resources 131 available to the industrial system 100. The distribution component 110 may be a part of application software running on a control unit (not shown), where the control unit may serve as a management control center of the industrial network system 100. The available resources 131 may include a variety of resources, which are used by units of the industrial unit to complete their functions. For example, the available resources 131 may include storage space, data collection bandwidth, processing capabilities, parameters that affect data collection speed, operating characteristics, and so on. Moreover, such available resources 131 can be identified/recorded with metadata, and are conceptually aggregated into databases, tables, and so on. For example, the resource identification data may include: resource name, resource size, resource capacity, resource speed, and resource bandwidth.

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Such a resource pool can use additional identifiers. For example, the available resource instance data further includes instance identifiers, instance availability status (for example, whether the resource is online), capacity information (for example, the number of users supported by a resource), Allocation statistics (for example, the number of users allocated to a resource), grouping information (for example, a resource group, which can be used to allocate resources), and other resources (for example, allocation order, close relationship, etc.). As shown, the data set for this industrial system 100 includes data from an "internal" data stream 102 (for example, historical data collected from an industrial unit) and an "external" data stream 104 (for example, on a web server). Traffic data).

[0034] FIG. 2 illustrates a coordination component 225 capable of simultaneously collecting and analyzing an "internal" data stream 202 and an "external" data stream 204. The coordination component 220 can synchronize and maintain the timing and sequence relationship between events and network traffic. Therefore, in the two data streams 202, 204, the association or causality between seemingly random events can be easily estimated/decided. It will be understood that the synchronization and maintenance of the timing and number sequence relationship can also occur between multiple internal data streams, multiple external data streams, and so on. In addition, the data stream can include data related to controller alarms, events, and audits, where the alarms and events in the data stream can further correlate system changes.

[0035] The coordination component 225 can further initially combine data from the internal data stream 220 and the external data stream 204 to record together (for example, based on sequence relationship, time stamp), and then based on the data interval size (for example, nanosecond interval, millisecond interval) ) Prediction level, presenting these relevant data to the user. According to a further aspect of the subject innovation, the feedback/monitoring component 220 monitors resources 250ai to 250an (collectively referred to as resources 250), and generates feedback information about a plurality of resources 250 to the allocation component 230. The feedback/monitoring component 220 can monitor the following attributes, for example, the use of multiple resources 250 by the distributed embedded history machine 210, the interaction between the multiple resources 250 and the embedded history network 210, the allocation status of the multiple resources 250, The maintenance status of the multiple resources 250, the load balance between the multiple resources 250 and the predicted usage of the multiple resources 250, and other similar attributes. These information and multiple monitoring attributes can be fed back to the distribution component 230, where the component can then selectively take actions based on the feedback information. For example, if the feedback/monitoring component 220 determines that the resource 250ai provides 95% of it to the distributed embedded historian 210, and one resource 250A2, the resource can provide the embedded historian 210 with substantially the same multiple resources. 5% capacity operation, the allocation component 230 can guide the next resource request To resource 250a2o

[0036] In addition, the distribution unit 230 may also shift the load from the resource 250ai to 250A2. Via the feedback/monitoring component 220, monitoring available resources 250 can facilitate updates such as resource allocation rules, resource instance catalogs, resource dependencies, and so on. This update can increase the sensitivity of the system 200 for automatic and dynamic resource allocation, and reduce the problems associated with static allocation methods. The feedback/monitoring component 220 may also receive feedback information from an external feedback information generator (not shown), and use the information in combination with the available resources 250 in the distributed built-in historian 210.

[0037] FIG. 3 illustrates a network interface 320 with an embedded network traffic analyzer capable of interacting with the subject innovation coordination component. Generally, most embedded devices have an event recording mechanism to track interesting and/or abnormal behaviors in the device, where when a problem occurs, the event information can be downloaded to a PC for estimation and analysis. Similarly, when a problem occurs, multiple communication and control networks have the capability of a traffic analyzer that allows capturing or downloading network traffic to a PC.

[0038] As previously explained, these two data streams are collected separately in traditional systems, usually using different equipment and software. Once collected, conventionally, data streams are analyzed separately and the timing relationship between events and network traffic in the log is implied and manually determined (if possible). Figure 3 illustrates the network interface that performs the functionality of the traffic analyzer, the host CPU that performs the event recording functionality, the shared time stamp/sequence count generator 370, and the external that retains traffic analyzer (TA) data and event log data. The relationship between RAM332. The coordination associated with the innovative industrial system of this topic can collect event logs and network traffic data streams and coordinate them through the public time stamp/sequence count generator 370

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Relationship between. This coordination maintains the timing and sequence relationship between events and network traffic, and provides a mechanism for determining the cause and effect between the two data streams. Differently share the common time stamp/sequence count generator between the event recorder and the traffic analyzer to mark the collected individual data. By marking the data with a common mark to indicate that it has been collected, for example, even when the event log and the traffic analyzer data stream are collected and uploaded independently, the order of the content can be recreated by the application software in the PC. In addition, data streams uploaded from multiple modules can be coordinated if the time stamp/sequence count generator (for example, via IEEE1588) is synchronized.

[0039] Consistent with one aspect of the subject innovation, the network interface 320 includes different components that implement standard network interface protocols and additional components that need to implement an embedded network traffic analyzer. Standard components include, for example, a reception modem 322, a reception filter/filter 324 (or Ethernet addressing), a network operation control component 326, a memory interface 328, and a transmission modem 330. The receiving modem 322 may be connected to the network bus 340 to receive signals transmitted to the network by other devices. Similarly, the transmission modem 330 may be connected to the network bus 340 to transmit a signal from a device including a network interface to the network. Although the receiving modem 322 and the transmitting modem 330 are illustrated as separate components, it should be understood that these two components may be implemented in a radio transceiver component capable of simultaneously transmitting information to and receiving information from the network. The receiving modem 322 may be connected to the receiving filter/filter 324. The reception filter/filter 324 determines whether the information placed on the network is intended for that particular device. Each device on the network is typically assigned a unique identifier. The receiver filter/filter 324 recognizes the unique identifier and determines whether the information on the network is intended for the respective device. The receiver filter/filter 324 can be further connected to the receiving modem 322, the network operation control part 326, and the memory interface 328. Once it is determined that the data on the network is planned for the device, the network operation control component 326 then interprets and responds to the information accordingly. The memory interface 328 is connected to the reception filter/filter 324, the normal operation control part 326, the transmission modem 330, and an external random access memory (RAM) 332. Although RAM 332 is illustrated as being external to the network interface, it should be understood that RAM can also be implemented internally, or RAM 332 can be implemented as a combination of internal memory and external memory. As commanded by the network operation control unit 326, the memory interface 328 uploads data from the RAM 332 or downloads data from the RAM 332 if necessary. If necessary, the data is then transferred from RAM332 to the transmission modem 330 and network through the memory interface 328, or from the receiving filter/filter 324 to the RAM332 through the memory interface 328_O

[0040] The network interface 320 with an embedded network traffic analyzer can be implemented as an application specific integrated circuit (ASIC). The specific component composition of the ASIC is different due to the needs of different network standards and protocols. Although illustrated as being implemented in an ASIC, it should be understood that the present invention can be implemented on a standard integrated circuit, discrete components, multiple ASICs, their combination or duplication of required functions, and the present invention plans to include all of these configurations in any manner.

[0041] By adding an additional component 334 to the network interface, any suitable device including an interface between the network and the additional component can be used as a network traffic analyzer. The additional components 334 include a flow analyzer filter component 336 and a flow analyzer control component 338. The receiving modem 322 receives the network data and transmits the data to the flow analyzer filter part (not shown). It will be understood that FIG. 3 is exemplary in nature, and other instruments including external analyzer devices, such as external devices, may be connected to the network.

[0042] The traffic analyzer filter can include, for example, a medium access control (MAC) identifier (ID) filter component, a target MAC ID filter component, a packet filter component (periodic, non-periodic, etc.) , And other filter components to capture the information related to the IP address/broadcast address of the network protocol or Ethernet situation. For example, these other filter components may include sequence number filter components, packet length filter components, inspection and data components, and any other information typically associated with known network protocols. The combination of all filters allows the network interface to determine which device is the source of the data being transmitted,

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Which device is the destination of the data being transmitted, the type of information being transmitted, the length of the data being transmitted, and other information related to diagnosing network problems. The network flow analyzer control is completed by the flow analyzer control component 338. The flow analyzer control component 338 further includes a monitoring component, a collection start/stop component, a storage configuration and status component, and a storage upload/download component. The monitoring component monitors normal device operation to determine the memory access bandwidth available to the processor and the network traffic analyzer function. The collection start/stop component determines the conditions under which data collection will start and end. The start and end conditions can be triggered by a variety of different conditions, including but not limited to, time, duration, occurrence of specific conditions, package type, or data or missing of specific conditions, package type or data. The memory configuration and status components work with the memory upload/download components to help control the management of the collected data in and out of the memory.

[0043] Additional components include hardware and firmware to achieve operation as an embedded network traffic analyzer. The additional firmware includes an interface to the network traffic analyzer. The additional firmware includes the necessary information for a specific network, including filter configuration, memory configuration association status, collection start and stop, and network traffic analyzer memory upload. With the additional hardware and firmware components, the interface device can start and end the collection, collection and analysis of data in accordance with a set of prescribed conditions.

[0044] FIG. 4 illustrates the matching component 410 as part of the subject innovative industrial system 400. The matching component 410 can reserve a module/industrial area with a predetermined trigger event in the synchronous industrial setting, and facilitate resource allocation based on trigger events in different areas. Based on the specified area and/or event trigger, the data can then be displayed to the user. The industrial areas 411, 413, 415 may be designated and/or recognized as areas in the industrial automation environment 400. You can specify any area number (1 to m, where m is an integer) for area recognition, and each area 411,413,415 can be of any shape, size, etc. And/or connected to any machine, process, as part of an industrial system, where each area can always remain stationary, change over time, and so on.

[0045] Trigger events 421, 423, and 425 (1 to k, where k is an integer) may include events such as: receiving a message to execute a specific function module, positioning data input for the function module, executing a predetermined instruction for the function module, and so on. In related aspects, the allocation of resources can be automatically started by triggering events to start actions on functional modules. Similarly, data collection can automatically end based on the completion of the functional module. Correspondingly, relevant data at different execution stages can be automatically collected, although users (for example, unit operators, equipment engineers) do not need to know what data is important for addressing the collection of future troubleshooting.

[0046] FIG. 5 illustrates an industrial system 500 consistent with one aspect of the subject innovation, which further includes an identification component. The identification component 510 identifies patterns in data trends affecting industrial processes consistent with an aspect of the subject innovation. In addition, the identification component 510 analyzes the "internal" data stream 511 and the "external" data stream 512 to identify patterns that affect the data trend of the industrial process. The pattern recognition of events (1 to L is an integer) can be based on: predetermined conditions (for example, comparison of the operating status of a factory with multiple previous batches of results), and/or a regularly updated interrupt control program. The identification component 510 further uses detailed associations 514 (for example, predetermined modules set by the user/external data source), and/or simple associations 515 dynamically deduced in the event/possible causal link.

[0047] FIG. 6a illustrates an industrial system consistent with one aspect of the subject innovation. The system uses an embedded traffic network analyzer one by one in which by adding additional components to a device with a network interface, the device can be configured as network traffic Analyzer. The system 600 includes a processor 602 and a network interface 604 with an embedded network traffic analyzer 606 consistent with the present invention. The embedded network traffic analyzer 606 further includes a traffic analyzer filter part 608 and a traffic analyzer control part 610, hardware and auxiliary firmware. When connected to the network, the device will act as a network traffic analyzer for the network to which it is connected. This is illustrated in FIG. 6b, where the device 650 includes an embedded network traffic analyzer 652 connected to the network interface of the network 654. The device 650 can be a standard PC, a network printer, a network scanner, or any device with a network interface to which a network traffic analyzer component has been added. Consistent with one aspect of the present invention, the device 650 can operate in different modes. For example, the operation of the device 650 in one mode is for the normal mode (eg, PC, printing, scanning, etc.). In another mode, the device 650 acts as a private network

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Flow analyzer operation. In another mode, the device 650 combines normal functions with network traffic analyzer functionality. In this mode, priority is usually given to the normal operation of the device; the network traffic analyzer function can utilize excess device resources such as processing and memory bandwidth. In any mode, complex classification and retrieval tasks can be performed at a later point in time, for example, due to past computer processing operations including the subject innovation, or data collected by the device through the network can be transferred to another processor for processing and analysis in the past .

[0048] FIG. 7 illustrates a related method 700 for collecting data based on multiple levels of granularity used in an industrial process. While the exemplary method here is illustrated and described as a series of modules representing different events, the present invention is not limited by the ordering of these modules. For example, consistent with the present invention, some behaviors or events may appear in a different order or at the same time as other behaviors or events, except for the order illustrated here. In addition, not all modules, events, or behaviors shown need to implement methods consistent with the present invention. In addition, it will be understood that the exemplary methods and other methods according to the present invention can be combined with the methods illustrated and described herein, and perform the same as other systems and devices not illustrated and described.

[0049] Initially at 710, the available resources to the industrial system are identified. These resources may include, for example, storage space, data collection bandwidth, processing capabilities, parameters that affect the speed of data collection, operating characteristics, and so on. Next at 720, these resources may be conceptually assembled together in the form of, for example, a catalog and/or database. Subsequently, at 730, the requirements of the industrial system for the respective operations can be determined via the allocation components (for example, probabilistic algorithms, cross-resource instance value balancing, and group optimization algorithms). When determining resource requirements, these allocation algorithms can further consider the actual use of resources. Moreover, the allocation component can be automatically improved based on the correlations that exist in the case of these resources and multiple built-in histories. At 740, such an arrangement can achieve the efficiency of resource allocation among multiple units of the industrial system.

[0050] FIG. 8 shows a method 800 related to the monitoring and allocation of multiple resources in an industrial unit according to an aspect of the subject innovation. First, at 810, you can monitor changes related to the resource pool. At 820, a determination is made to check whether the resource has been changed, such as increase in processing capacity, storage capacity, and so on. If so, the method 800 proceeds to act 830, where the available resources are updated and then allocated at 840. Otherwise, the method 800 returns to step 810 for viewing resources.

[0051] FIG. 9a shows an exemplary industrial automation network using an allocation component 965 that allocates resources based on data analysis, where the data comes from an internal data stream (for example, from an embedded historian) and an external data stream (for example, From the flow analyzer). Such an allocation component 965 can allocate resources from the available resource pool of the industrial system, and thus provide efficient operation (for example, automatically increase/decrease resources based on usage).

[0052] In one aspect, the distribution component may be part of the module 955. The industrial setting 900 may further include, for example, a database 910, a human machine interface (HMI) 920 and a programmable logic controller (PLC) 930, and a management interface 940. The allocation component 965 may be further connected with the artificial intelligence (AI) component 950 to facilitate the allocation of resources in the industrial system 900.

[0053] For example, in relation to determining resource allocation methods and/or resource allocation with control algorithms, the subject innovation can use different artificial intelligence solutions. The process for explicitly or implicitly learning whether to download historical data can be facilitated by automatic classification systems and processes. Classification can use probabilistic or statistical-based analysis (for example, factorization into decomposing utility and cost) to predict or infer actions that users want to automate. For example, a support vector machine (SVM) classifier can be used. Other classification methods include Bayesian networks, decision-making, and classification models based on probability theory if different independent models can be provided. The classification as used herein also includes statistical regression, which is used to develop a priority model.

[0054] As is readily appreciated from the subject, the subject of the invention may include explicit training (e.g., by

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Ordinary exercise data) and secretly trained (for example, by observing user behavior, receiving foreign information) classifier, so that the classifier can be used to automatically determine which answer to a question to return based on predetermined criteria. For example, regarding well-understood support vector machine SVM's, SVM's are configured in a classifier builder and feature selection module through a learning or training phase. A classifier is a function of mapping an input attribute vector x= (xl, x2, x3, x4, xn) to the confidence of the class to which the input belongs-that is, f(x) = confidence (class). As shown in Figure 9a, an artificial intelligence (AI) component 950 may be included to facilitate inference and/or determination of when, where, and how to change the allocation of resources. The AI component 950 may include any of a number of suitable AI-based solutions, as described above in relation to promoting various aspects of the subject matter of the present invention.

[0055] In addition, the management interface 940 can be used to provide data from an appropriate location, such as the data source 960, the server 970, and/or the proxy server 980. Therefore, the management interface 940 can point to a source of data based on the needs (needs) of the task and the requester (for example, the database 910ΉΜΙ920, PLC930, etc.). The database 910 can be of many various types such as related, web, flat file, or hierarchical systems. Typically, this kind of database can be used to connect to various enterprise resource planning (ERP)-related application software, which can serve many different business-related processes within a company. For example, ERP application software can be related to human resources, budgets, forecasts, purchases, and so on. At this point, specific ERP application software may require data to have certain desired attributes related to it. Therefore, in one aspect of the subject matter of the present invention, the management interface 940 can provide data from the server 970 to the database 910, where the server 970 can provide data having attributes desired by the database 910.

[0056] Moreover, the HMI 920 can use the management interface 940 to point to data located within the range of the system 900_oThe HMI 920 can be used to graphically display various aspects of a process, system, plant, etc., to provide a simple and/or user-friendly view of the system. Therefore, various data pointing to a system can be displayed as graphical representations (for example, bitmaps, JPEGs, vector-based graphics, cell logic mapping processor (clip) technology, etc.), with desired color schemes, The presentation method of animation and layout.

[0057] The HMI 920 may require the data to have specific visualization attributes related to the data in order to display such data there. For example, the HMI 920 may query the management interface 940 for a specific data point with related visualization attributes. The management interface 940 may determine that the proxy server 980 includes attribute data points with desired visualization attributes. For example, the attribute data point may have a specific graphic, which is referenced or sent with the data, so that the graphic replaces the data value or appears together with the data value in the HMI environment.

[0058] The PLC930 can be any number of models, such as Allen Bradley Logix, PLC5, SLC-500, MicoLogix and similar other models. The PLC930 is usually defined as a dedicated device used to provide high-speed, low-level control for a process and/or system_oPLC930 can be programmed in ladder logic or some form of structured language or other appropriate language. Representatively, the PLC 930 can directly utilize process data from a data source (for example, the process data source 990 or the data source 960), which can be a sensor, an encoder, a measurement sensor, a switch, a valve, etc. The data source 990 or 960 can provide data to registers in the PLC, and if necessary, such data can be stored in the PLC. In addition, the data can be updated (e.g., based on clock cycles) and/or output to other devices for further processing.

9b shows a related exemplary industrial assembly 901, which may include: a programmable logic controller (PLC) 911, a computer (PC) 921, an industrial network bridge (network bridge) 931 and two Industrial network adapters 951 and 961 with multiple I/O modules associated with them. These components and modules can be connected through two industrial automation networks 971 and 981. The distribution and AI components can be arranged on one module (for example, the industrial network bridge 931), and control another module of the industrial network adapter 951 (for example, the history and traffic analysis of the industrial network adapter 951)

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(TA)) data collection component. Similarly, the allocation and AI components of the PC 921 can control the allocation of resources to multiple units, such as the data collection component of the PLC 911 and the industrial network adapter 961, for example. It must be understood that the distribution and ΑΙ components do not need to be arranged together in the same module/component. The internal and external data stream collection mechanisms do not need to be arranged together in the same module/component. For example, the internal data flow of one module (e.g., a module with history but not TA) may be associated with the external data flow of another module with TA.

[0060] FIG. 10 shows an exemplary environment 1010 for performing various aspects of the subject innovation, which may include a computer 1012 as part of the distribution component. The computer 1012 includes a processing unit 1014, a system memory 1016, and a system bus 1018. The system bus 1018 couples system components, including but not limited to, the system memory 1016 to the processing unit 1014. The processing unit 1014 may be any one of various available processors. Dual microprocessors and other microprocessor mechanisms can also be used as the processing unit 1014.

[0061] The system bus 1018 may be any of several types of bus structures, including a memory bus or a memory controller, a peripheral bus or an external bus, and/or a local bus using any of the available bus structures, The available bus structures include, but are not limited to, 9-bit bus, industry standard structure (ISA), microchannel structure (MSA), extended ISA (EISA), intelligent drive electronics (IDE), VESA local bus (VLB), peripheral Component Interconnect (PCI), Universal Serial Bus (USB), Accelerated Graphics Interface (AGP), Personal Computer Memory Card International Association Bus (PCMCIA), Small Computer System Interface (SCSI) or all other buses.

[0062] The system memory 1016 includes a volatile memory 1020 and a non-volatile memory 1022. The basic input output system, which includes a plurality of basic programs to transfer information among the various components in the computer 1012 when it is started, is stored in the non-volatile memory 1022. For example, the nonvolatile memory 1022 may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory 1020 includes random access memory (RAM), which acts as external cache memory. In addition, RAM is used in various forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), high-speed SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and Direct memory bus (Rambus) RAM (DRRAM).

[0063] The computer 1012 also includes removable/non-removable, volatile/nonvolatile computer storage media. FIG. 10 shows a disk storage 1024, for example. The disk storage 1024 includes, but is not limited to, devices like disk drives, floppy disk drives, tape drives, Jaz drives, Zip drives, LS-60 drives, flash memory cards, or memory sticks. In addition, the magnetic disk storage 1024 may separately include storage media or be combined with other storage media, where other storage media include, but are not limited to, optical disk drive devices such as compact disk ROM devices (CD-ROM), and CD-R Drives (CD-R Drive). , Rewriteable CD drive (CD-RW Drive) or digital versatile disc ROM drive (DVD-ROM). In order to simplify the connection between the disk storage 1024 and the system bus 1018, a removable or non-removable interface such as the interface 1026 is typically used.

[0064] It must be understood that FIG. 10 depicts the software that acts as an intermediary between the user and the basic computer resources (described in the appropriate operating environment 1010). This software includes an operating system 1028. The operating system 1028, which can be stored in the disk storage 1024, controls and allocates the resources of the computer system 1012. The system application software 1030 utilizes the allocation of resources through the operating system 1028 via the program module 1032 and the program data 1034 stored in the system memory 1016 or the disk memory 1024. It must be understood that the various components described herein can use various operating systems or combinations of operating systems.

[0065] The user inputs commands or information to the computer 1012 through one or more input devices 1036. The input device 1036 includes, but is not limited to, a pointing device such as a mouse, a trackball, a stylus, a touchpad, a keyboard, and an expansion device.

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Sounders, joysticks, game pads, disc-type satellite TV antennas, scanners, TV tuner cards, digital cameras, digital video cameras, web cameras, etc. These and other input devices are connected to the processing unit 1014 via a system bus 1018 via one or more interface ports 1038. The one or more interface ports 1038 include, for example, a serial port, a parallel port, a game port, and a universal bus (USB). One or more output devices 1040 use some of the same type of ports as one or more input devices 1036. In this way, for example, a USB port can be used to provide input to the computer 1012 and output information from the computer 1012 to the output device 1040. Among other output devices 1040 that require a special adapter, an output adapter 1042 is provided to indicate that there are some output devices 1040, such as monitors, speakers, and printers. For the sake of example and not limitation, the output adapter 1042 includes devices that provide a connection between the output device 1040 and the system bus 1018-a graphics card and a sound card. It should be noted that other devices and/or device systems such as one or more remote computers 1044 have input and output capabilities.

[0066] The computer 1012 may operate in a network environment that is logically connected to one or more remote computers, such as the remote computer 1044. One or more remote computers 1044 may be personal computers, servers, routers, network PCs, workstations, microprocessor-based devices, peer devices or other common network nodes, etc., and usually include some or all of the above and Computer 1012 related components. For brevity, only one storage device 1046 is shown together with one or more remote computers 1044. The remote computer 1044 is logically connected to the computer 1012 through a network interface 1048, and then physically connected to the computer 1012 via the communication connector 1050. The network interface 1048 includes communication networks such as a local area network (LAN) and a wide area network (WAN). LAN technology includes optical fiber distributed data interface (FDDI), copper distributed data interface (CDDI), Ethernet/IEEE802.3, token network/IEEE802.5 and so on. WAN technologies include, but are not limited to, point-to-point connections, circuit-switched networks such as integrated services digital networks and their variants, packet-switched networks, and digital subscriber lines (DSL).

[0067] The communication connector 1050 refers to hardware/software for connecting the network interface 1048 to the bus 1018. Although the communication connector 1050 is shown inside the computer 1012 for clarity, it can also be outside the computer 1012. For illustrative purposes only, the necessary hardware/software for connecting to the bus 1018 includes internal and external technologies, for example, multiple modems including multiple ordinary telephone-level modems, multiple cable modems, and DSL modems, multiple ISDN adapters And multiple Ethernet cards.

[0068] As used herein, the terms "component", "system", etc., in addition to electromechanical devices, can also refer to computer-related entities, which can be hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to, a program running on a processor, a processor, an object, an executable program, a thread, a program, and/or a computer. By showing, the application software running on the computer and the computer can both be a component. One or more components can belong to one process and/or thread, and one component can be located on one computer and/or distributed between two or more computers. The word "exemplary" is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "exemplary" is not necessarily interpreted as preferred or advantageous over other aspects or designs.

[0069] FIG. 11 also shows an exemplary environment that can use distribution components that collect data according to different aspects of the subject innovation. Each functional module 1114 relies on a detachable junction box 1130 that allows the module 1114 to be removed from the rear wiring board 1116 to be attached to the rear wiring board 1116 so that it can be replaced or repaired without disturbing other modules 1114. The rear wiring board 1116 provides the module 1114 with power and communication circuits to other modules 1114. The local communication between the rear wiring board 1116 and the other modules 1114 is completed by electrically connecting to the rear wiring board interface 1132 of the rear wiring board 1116 through the connector 1130. The rear connector board interface 1132 monitors the messages on the rear connector board 1116, based on the information as part of the message

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The message address, which indicates the destination address of the message, identifies those messages for the specific module 1114. The message received by the rear connection panel interface 1132 is transmitted to the internal bus 1134 on the module 1114.

[0070] The internal bus 1134 connects the rear wiring board interface 1132 with the memory 1136, the microprocessor 1128, the front panel circuit 1138, the I/O interface circuit 1139, and the communication network interface circuit 1141. The microprocessor 1128 may be a comprehensive-purpose microprocessor that provides serial or parallel execution of instructions contained in the memory 1136, and reads and writes data to and from the memory 1136 and other devices connected to the internal bus 1134 . The microprocessor 1128 includes a clock circuit (not shown) that provides the timing of the microprocessor 1128, but may also communicate with an external clock 1143 with improved accuracy. This clock 1143 can be a crystal oscillator or other time reference including a wireless link to an external time reference. The accuracy of the clock 1143 can be recorded in the memory 1136 as a quality factor. The panel circuit 1138 includes, for example, a status indicator light known in the prior art and a manual operation switch for locking the module 1114 in an inoperative state, for example.

[0071] The memory 1136 may include control programs or routines that can be executed by the microprocessor 1128 to provide control functions and variables and data necessary to execute those programs or routines. As for the I/O module, the memory 1136 may also include an I/O table to maintain the current state of receiving input from or transmitting output to the industrial controller 1110 through the I/O module 1120, where the I/O module 1120 is as shown in this article. For example, located on the I/O network 1122. The module 1114 can be used to implement various methods of this innovation through hardware configuration technology and/or software programming technology.

[0072] It should be recognized that although the different aspects have been preliminarily described in terms of the relationship between the two data streams, the present invention is not limited to this, and multiple data streams also fall within the scope of the present invention. Moreover, although an internal data stream and an external data stream are described, it should be recognized that the data stream can include any combination of multiple internal, multiple external, internal and external, or multiple internal and external data streams. The content described above includes different exemplary aspects. Of course, it is impossible to explain every possible combination of multiple components or methods for the purpose of explaining these aspects, but a person of ordinary skill in the art can recognize that many further combinations and substitutions are possible. Especially with regard to the different functions performed by the above-mentioned multiple components (multiple components, devices, circuits, systems, etc.), the terms used to describe these components (including the "device" mentioned) are intended to correspond to (unless otherwise specified ) Any component that performs the function of the component (eg, functional equivalent), even if it is not structurally equivalent to the disclosed structure, it performs the exemplary aspects of the present invention described herein Features. In this regard, it should also be recognized that the present invention includes a system and a computer-readable medium having multiple computer-executable instructions for performing multiple actions and actions of different methods of the present invention. /event. Moreover, the meaning of the term "includes" used in the detailed description or claims In other words, this term is intended to be inclusive in a similar way to the term "comprising", as explained when "comprising" is used as a transitional word in the claims.

[0073] According to the above description, the technical solutions of the present invention include but are not limited to the following:

[0074] Scheme 1. An industrial automation system, including:

[0075] A coordination component (225) that synchronizes multiple data streams (102, 104, 202, 204, 511, 512) associated with the industrial automation system; and

[0076] A distribution component (110,230,965), the distribution component is based on the multiple data streams (102,104,202,

204, 511, 512) to allocate resources.

[0077] Solution 2. The industrial automation system according to claim 1, further comprising a feedback and monitoring component that monitors resources and generates feedback information related to these resources.

[0078] Solution 3. The industrial automation system according to claim 1, further comprising an identification component that identifies trends in the multiple data streams.

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[0079] Solution 4. The industrial automation system according to claim 1, further comprising a centralized data collection that stores a unified data repository from the multiple data streams.

[0080] Solution 5. The industrial automation system according to claim 1, wherein the multiple data streams include a set of multiple internal data streams or multiple external data streams or a combination thereof.

[0081] Solution 6. The industrial automation system according to claim 1, further comprising a network with an embedded network traffic analyzer (NTA).

[0082] Solution 7. The industrial automation system according to claim 1, further comprising a matching component that reserves multiple modules or industrial areas with multiple predetermined trigger events or stages of an industrial process.

[0083] Scheme 8. A method of collecting data in an industrial factory, including:

[0084] Identify a process for collecting multiple data streams (102, 104, 202, 204, 511, 512);

[0085] Maintain an order relationship between multiple streams of internal data (102, 202) and external data (104, 204); and

[0086] Various resources (131) used in the industrial plant are pooled into a resource pool.

[0087] Solution 9. The method according to claim 8, further comprising allocating the resource pool among a plurality of units of the industrial plant.

[0088] Scheme 10.-Kind of industrial system, including:

[0089] A collection device (911) for collecting multiple data streams (102, 104, 202, 204, 511, 512) related to an industrial process; and

[0090] A device (110, 230, 965) for allocating resources in the industrial system.

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