Edge Intelligent Collaborative Processing Method and System for PLCs and Instruments

Abstract

This invention relates to the field of collaborative control technology, and discloses an edge intelligent collaborative processing method and system for PLCs and instruments. The method includes: real-time capture of the control instruction sequence of the PLC and the asynchronous event data stream connected to the instrument; reconstructing the extended cycle coverage of the control instruction sequence and extracting the key offset window in the asynchronous event data stream, and establishing a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage; calibrating the instruction execution phase and event triggering phase within the spatiotemporal coupling zone to obtain a synchronization margin index, and converting the synchronization margin index into event-driven execution instructions. This invention can solve the problem that most existing technologies separately manage PLC memory resources and instrument communication links, without analyzing the two in conjunction, making it difficult to find the points of resource contention and conflict during the collaborative process.

Description

Technical Field

[0001] This invention relates to the field of collaborative control technology, and in particular to an edge intelligent collaborative processing method and system for PLCs and instruments. Background Technology

[0002] In industrial automation production scenarios, PLC is the core unit of field control, and it usually issues control commands at fixed intervals. Various field instruments are responsible for collecting operating data and reporting events. The synergistic effect of the two directly determines the control accuracy and operational stability of the production line.

[0003] However, in the existing technology, the periodic control instructions of PLC and the asynchronous event data stream of instruments do not have a matching time and space mechanism. They cannot accurately align the time phase of instruction execution and event triggering, nor can they quantify the synchronization deviation range between the two. As a result, the problem of asynchronous instruction execution and data acquisition often occurs. They also cannot adapt to dynamic working conditions on site in a timely manner, and the real-time performance and accuracy of control are difficult to guarantee.

[0004] In addition, most existing PLC and instrument collaboration solutions manage PLC memory resources and instrument communication links separately, without analyzing them together. This makes it difficult to find the conflict points of resource contention during collaboration and to trace the path of conflict generation. Summary of the Invention

[0005] This invention provides an edge intelligent collaborative processing method and system for PLCs and instruments, the main purpose of which is to address the problems raised in the background art above.

[0006] To achieve the above objectives, the present invention provides an edge intelligent collaborative processing method for PLCs and instruments, comprising: S1: Real-time capture of PLC control command sequences and asynchronous event data streams from connected instruments; S2: Reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage. S3: Calibrate the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction; S4: Map the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points; S5: Reverse trace the conflict source path of the resource contention mutual exclusion point. When the synchronization margin index corresponding to the conflict source path exceeds the preset tolerance boundary, reconstruct the sampling frequency of the instrument to obtain the anti-conflict coordination strategy. S6: Execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

[0007] Preferably, the real-time capture of the PLC's control command sequence and the asynchronous event data stream of the connected instruments includes: Establish an instruction buffer for the control bus corresponding to the PLC, and continuously monitor the instruction output timing of the instruction buffer to obtain the control instruction sequence; Access the event queue interface of the instrument to capture the asynchronous event data stream of the instrument.

[0008] Preferably, the reconstructing of the extended cycle coverage of the control instruction sequence and the extraction of key offset windows from the asynchronous event data stream includes: Analyze the real-time attributes of the corresponding execution nodes in the control instruction sequence to clarify the basic cycle boundary; Integrate the potential delay factors of the PLC; By combining the basic cycle boundary and the delay influencing factors, the extended cycle coverage of the control command sequence is reconstructed; Scan the timestamp distribution of the asynchronous event data stream to identify the time offset of the event trigger point in the asynchronous event data stream; By comparing the time offset with the key connection points of the extended period coverage, the comparison results are filtered to obtain the key offset window.

[0009] Preferably, the step of establishing a spatiotemporal coupling region for instructions and events centered on the key offset window, in conjunction with the extended cycle coverage, includes: The center of the critical offset window is bound to the extended period coverage area, and the center of the window is set as the phase alignment reference point; By associating the execution nodes in the control command sequence with the phase alignment reference point, the relative vector distribution of the control command sequence is obtained; By filtering the event points within the key offset window in the asynchronous event data stream, the clustered density cloud is obtained; The spatiotemporal coupling region is determined by the vector distribution and the clustered density cloud.

[0010] Preferably, calibrating the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index includes: Statistically analyze the absolute phase difference sequence between the control command execution time point and the event trigger time point in the spatiotemporal coupling region; Determine the high-frequency concentrated interval in the absolute phase difference sequence to obtain the core synchronization band boundary of the absolute phase difference sequence; The positive and negative buffer margin values ​​of the time domain boundary and the core synchronization band boundary of the spatiotemporal coupling region are calculated step by step. The core synchronization band boundary, positive buffer margin value, and negative buffer margin value are encapsulated in triplets to obtain the synchronization margin index.

[0011] Preferably, the mapping of the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points includes: Extract the precise execution period of the event-driven execution instruction; The peak occupancy rate of the PLC is scanned by combining the precise execution period and the memory resource allocation map; The memory conflict hotspot period of the PLC is determined based on the peak occupancy rate; The load change rate gradient of the instrument is analyzed by the precise execution period and the communication link load map to obtain the communication load period of the instrument; Filter the resource contention mutual exclusion points of the memory conflict hot zone period and the communication load period.

[0012] Preferably, the reverse tracing of the conflict source path of the resource contention mutual exclusion point includes: The conflict event chain of the resource contention mutual exclusion point is traced through the control instruction sequence and the asynchronous event data stream. The phase offset path of the conflict event chain is dynamically generated based on the synchronization margin index to obtain the conflict tracing path.

[0013] Preferably, when the synchronization margin index corresponding to the conflict tracing path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain an anti-conflict coordination strategy, including: Based on the conflict tracing path and synchronization margin index, a tolerance boundary breach scan operation is performed to obtain the set of tolerance breach instrument nodes in the conflict tracing path. Based on the synchronization margin index, a tolerance boundary breach scan is performed on the conflict tracing path to obtain the tolerance breach instrument node in the conflict tracing path. Based on the tolerance breakthrough instrument node, the sampling frequency gradient of the communication link load map is reconstructed to obtain the sampling frequency gradient value of the communication channel corresponding to each instrument; The sampling frequency gradient value and the memory resource allocation map are encapsulated into an anti-conflict cooperative strategy.

[0014] Preferably, the step of executing the anti-conflict cooperative strategy and feeding back the execution result to the spatiotemporal coupling region includes: The rationality of the aforementioned anti-conflict coordination strategy is verified, and the verified anti-conflict coordination strategy is fed back to the spatiotemporal coupling region.

[0015] An edge intelligent collaborative processing system for PLCs and instruments, used to implement the aforementioned edge intelligent collaborative processing method for PLCs and instruments, the system comprising: Capture module 101: Used to capture the control command sequence of the PLC and the asynchronous event data stream of the connected instruments in real time; Reconstruction module 102: used to reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage; Instruction conversion module 103: used to calibrate the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction; Contention identification module 104: used to map the memory resource allocation map of the event-driven execution instructions to the PLC and the communication link load map of the instrument, so as to identify resource contention mutual exclusion points; Strategy generation module 105: used to reverse trace the conflict source path of the resource contention mutual exclusion point. When the synchronization margin index corresponding to the conflict source path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain the anti-conflict coordination strategy. Feedback module 106: Used to execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention captures the PLC control instruction sequence and the asynchronous event data stream of instruments in real time, reconstructs the extended cycle coverage of the instructions, extracts the key offset window of the event stream, and establishes a spatiotemporal coupling zone between instructions and events. This breaks the limitation of the traditional PLC fixed-cycle control and the asynchronous event of instruments being unable to be effectively matched. By calibrating the phase of instruction execution and event triggering, a synchronization margin index is quantified and converted into event-driven execution instructions. This achieves precise phase alignment between the control logic and the field-acquired data, and the synchronization deviation between the two can be quantified and controlled, greatly improving the synchronization and real-time performance of the PLC and instruments working together.

[0017] This invention maps event-driven execution instructions to a PLC memory resource allocation map and an instrument communication link load map, which can accurately identify resource contention and mutual exclusion points in the collaborative process and trace the source path of the conflict in reverse, thus achieving accurate location and root cause tracing of resource conflicts. When the synchronization margin index exceeds the preset tolerance boundary, an anti-conflict collaborative strategy can be generated by reconstructing the instrument sampling frequency, thereby avoiding problems such as instruction stuttering, data packet loss, and communication congestion caused by resource contention from the source. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating an edge intelligent collaborative processing method for PLCs and instruments provided in an embodiment of the present invention. Figure 2 This is a functional block diagram of an edge intelligent collaborative processing system for PLCs and instruments provided in an embodiment of the present invention; The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides an edge intelligent collaborative processing method for PLCs and instruments. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the edge intelligent collaborative processing method for PLCs and instruments can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0021] Reference Figure 1 The diagram shown is a flowchart illustrating an edge intelligent collaborative processing method for PLCs and instruments according to an embodiment of the present invention. In this embodiment, the edge intelligent collaborative processing method for PLCs and instruments includes: S1: Real-time capture of the PLC's control command sequence and the asynchronous event data stream of the connected instruments.

[0022] In this embodiment, the real-time capture of the PLC's control command sequence and the asynchronous event data stream of the connected instruments includes: Establish an instruction buffer for the control bus corresponding to the PLC, and continuously monitor the instruction output timing of the instruction buffer to obtain the control instruction sequence; Access the event queue interface of the instrument to capture the asynchronous event data stream of the instrument.

[0023] Specifically, a PLC is a programmable logic controller, which is the main body responsible for generating and issuing control instructions. In industrial automation production scenarios, it is responsible for completing the periodic control of field equipment according to preset logic.

[0024] A control instruction sequence is a collection of multiple control instructions that are output by a PLC through a control bus in a fixed sequence and have a clear order of execution. It is the core carrier for PLC to realize industrial field control.

[0025] Instruments are industrial field instruments that are connected to PLCs. They are terminal devices responsible for collecting field operating data, monitoring equipment status, and reporting abnormal events.

[0026] Asynchronous event data streams are collections of event data that are generated by instruments based on changes in field operating conditions and real-time data acquisition results. They have no fixed distribution cycle and are dynamically generated according to the status of field equipment.

[0027] The control bus is a dedicated communication bus used to transmit control commands between the PLC and field devices. It is the core transmission channel for the PLC control command sequence.

[0028] The instruction buffer is a storage area specifically established for the control bus corresponding to the PLC, used to temporarily store all control instructions output by the PLC. It can retain the entire process and content of the PLC control instruction output.

[0029] The instruction output timing sequence refers to the order and timing pattern of when the PLC outputs control instructions to the control bus through the instruction buffer. It reflects the rhythm of issuing control instructions and the execution logic of the PLC.

[0030] The event queue interface is a standardized communication interface built into the instrument, used to output asynchronous event data generated by itself.

[0031] In detail, firstly, for the control bus corresponding to the target PLC, a dedicated instruction buffer is established to create a special temporary storage area for the control instructions that the PLC is about to output, ensuring that all issued control instructions can be retained; The instruction buffer is continuously monitored to track the entire output process of each PLC control instruction in the instruction buffer. The output time point, output sequence and instruction content of each control instruction are recorded. Based on the instruction output timing obtained by continuous monitoring, the PLC control instruction sequence is compiled and generated. Simultaneously, the field instruments connected to the PLC are connected to the PLC. By interfacing with the event queue interface built into the instrument, a stable connection between the collaborative processing system and the instrument event reporting channel is achieved, ensuring smooth data transmission. After the event queue interface is successfully connected, all asynchronous event data actively reported by the instrument through the event queue interface is continuously captured, the captured event data is summarized, and a continuous stream of asynchronous event data of the instrument is generated.

[0032] S2: Reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage.

[0033] In this embodiment, reconstructing the extended cycle coverage of the control instruction sequence and extracting the key offset window from the asynchronous event data stream includes: Analyze the real-time attributes of the corresponding execution nodes in the control instruction sequence to clarify the basic cycle boundary; Integrate the potential delay factors of the PLC; By combining the basic cycle boundary and the delay influencing factors, the extended cycle coverage of the control command sequence is reconstructed; Scan the timestamp distribution of the asynchronous event data stream to identify the time offset of the event trigger point in the asynchronous event data stream; By comparing the time offset with the key connection points of the extended period coverage, the comparison results are filtered to obtain the key offset window.

[0034] Specifically, the extended cycle coverage is a time boundary range that is redefined after incorporating various potential delay factors in the industrial field, and can cover the entire execution process of control commands. It is the effective coverage range of the command cycle under the actual operating conditions of the industrial field.

[0035] The critical offset window is a time window interval centered on the event trigger point, which is strongly correlated with the extended cycle coverage of the PLC control instructions and is obtained from the asynchronous event data stream.

[0036] The spatiotemporal coupling zone of the instruction-event is established by combining the extended cycle coverage of the PLC control instruction with the key offset window of the instrument asynchronous event, which can simultaneously cover the spatiotemporal correlation interval of the control instruction execution sequence and the asynchronous event triggering sequence.

[0037] An execution node is the specific action and execution point in the industrial field corresponding to a single control instruction in the control instruction sequence. It is the smallest execution unit in which the PLC control logic is implemented in the field.

[0038] Real-time attributes are execution attribute information related to the real-time operating status of each execution node in the control instruction sequence, including core information such as the start time of the execution node, execution duration, and execution sequence logic.

[0039] The basic cycle boundary is determined by analyzing the real-time attributes of the execution node and is the start and end time boundary of the fixed execution cycle of the original design of the PLC control instruction sequence.

[0040] Potential delay factors in PLCs are various field factors that can cause timing deviations between the actual execution time of PLC control instructions and the design's basic cycle. These include control bus transmission delays, instruction execution stutters, and field device response delays, which are common timing factors in industrial scenarios.

[0041] Timestamp distribution refers to the distribution of trigger timestamps corresponding to each asynchronous event data in an asynchronous event data stream along the time axis.

[0042] An event trigger point is a specific time node in the asynchronous event data stream where a single asynchronous event is triggered and generated by an industrial field instrument.

[0043] The time offset is the time difference between the actual trigger time of the event trigger point in the asynchronous event data stream and the reference time of the extended cycle coverage of the PLC control instruction.

[0044] The critical connection point is the core time node within the extended cycle coverage that is strongly correlated with the triggering of asynchronous events of the instrument. It is the key time anchor point connecting the execution sequence of PLC control instructions and the triggering sequence of asynchronous events of the instrument.

[0045] In detail, firstly, a full-scale in-depth analysis operation is carried out on the PLC control instruction sequence acquired in real time. The real-time attributes of each corresponding execution node in the control instruction sequence are disassembled, read and sorted out one by one to accurately determine the basic cycle boundary originally designed for the control instruction sequence and complete the delineation of the standard execution cycle benchmark of PLC control instructions. After clarifying the basic cycle boundary, all potential delay factors that may affect the execution timing of PLC control instructions in the field are collected, summarized and integrated to ensure that all field factors that may cause deviations in instruction execution timing are taken into consideration. After defining the basic cycle boundary and integrating potential delay factors, the two are deeply combined to readjust, supplement and define the original basic cycle boundary of the PLC control instruction sequence, and complete the reconstruction operation of the extended cycle coverage of the control instruction sequence to obtain a cycle range that is adapted to the actual operating conditions of the industrial site. While carrying out the PLC control instruction cycle reconstruction operation, a full traversal scan operation is simultaneously performed on the asynchronous event data stream of the instrument. The timestamp distribution of all event data in the asynchronous event data stream is checked and statistically analyzed one by one. The time offset corresponding to each event trigger point in the asynchronous event data stream is accurately identified, and the trigger time deviation and distribution pattern of all asynchronous events of the instrument are understood. After identifying the time offsets of all event trigger points, each time offset is compared and matched with the key connection points in the previously reconstructed extended cycle coverage area. A full screening operation is performed on all comparison results to remove invalid event intervals that are not strongly related to the extended cycle coverage area. Finally, the key offset window that is strongly related to the PLC control instruction cycle is obtained. After obtaining the extended cycle coverage and the key offset window, the establishment of the spatiotemporal coupling zone of the instruction-event is completed by using the key offset window as the core benchmark and combining it with the extended cycle coverage.

[0046] In this embodiment, establishing a spatiotemporal coupling region for instructions and events centered on the key offset window, based on the extended periodic coverage, includes: The center of the critical offset window is bound to the extended period coverage area, and the center of the window is set as the phase alignment reference point; By associating the execution nodes in the control command sequence with the phase alignment reference point, the relative vector distribution of the control command sequence is obtained; By filtering the event points within the key offset window in the asynchronous event data stream, the clustered density cloud is obtained; The spatiotemporal coupling region is determined by the vector distribution and the clustered density cloud.

[0047] Specifically, the spatiotemporal coupling zone of instruction-event refers to the core area established by combining the execution timing of PLC control instructions and the triggering timing of asynchronous events of instruments to achieve spatiotemporal correlation matching between the two. It is the core scope of action for subsequent phase calibration and collaborative processing.

[0048] The window center refers to the midpoint of the critical offset window in time. It is the core time anchor point for marking the triggering sequence of the instrument's core events and the core object for binding the PLC's extended cycle coverage and setting the phase alignment reference.

[0049] The phase alignment reference point refers to the unified reference point set after binding the window center to the extended cycle coverage range, used to calibrate the timing phase of PLC control instructions and instrument asynchronous events.

[0050] An execution node refers to the specific action and execution point in the industrial field corresponding to a single control instruction in the control instruction sequence. It is the smallest execution unit of PLC control logic in the industrial field and the core object for timing correlation with the phase alignment reference point.

[0051] Relative vector distribution refers to the distribution of the timing sequence and time interval of each execution node relative to the reference point after timing association of all execution nodes in the control instruction sequence with the phase alignment reference point. It can reflect the timing position relationship of each execution node of the PLC control instruction relative to the reference event.

[0052] An event point refers to a specific time node in an asynchronous event data stream that is triggered by an industrial field instrument. It is the smallest time unit that marks a change in the instrument's state and is also the core object for generating a clustered density cloud.

[0053] Clustered density cloud refers to the clustered distribution of event points on the time axis after filtering out all event points within the key offset window.

[0054] Vector distribution is the relative vector distribution of the control instruction sequence, and it is the core basis for determining the spatiotemporal coupling zone on the instruction side.

[0055] In detail, firstly, for the extended cycle coverage range of the reconstructed PLC control instruction sequence and the key offset window of the extracted instrument asynchronous event data stream, the window center of the key offset window is accurately located, and the binding operation between the window center and the extended cycle coverage range is completed, so that the window center is firmly anchored within the effective execution cycle range of the PLC control instruction. At the same time, the center of the window that has been bound will be officially set as the phase alignment reference point for subsequent timing matching, thus establishing a unified timing alignment reference between PLC control instructions and instrument asynchronous events. After setting the phase alignment reference point, for each execution node in the PLC control instruction sequence, a full timing association operation is performed between the set phase alignment reference point and the sequence. The relative timing relationship of each execution node relative to the reference point, such as the time sequence and interval distance, is accurately marked. After summarizing the relative timing relationship of all execution nodes, the relative vector distribution of the control instruction sequence is generated, and the timing distribution status of all PLC control execution actions relative to the core event reference point is understood. While performing the control command execution node association operation, a range filtering operation is simultaneously performed on the asynchronous event data stream of the instrument. Using the start and end time boundaries of the key offset window as the filtering criteria, all event points falling within the time range of the key offset window are extracted, and invalid event points outside the window are eliminated. Based on all the valid event points obtained by filtering, their distribution and clustering on the time axis are sorted out, and the corresponding clustering density cloud is generated to understand the concentrated distribution status of the instrument's core events within the reference window. After obtaining the vector distribution of the control command sequence and the cluster density cloud of instrument events, the final delineation and determination of the command-event spatiotemporal coupling zone is completed by combining the temporal coverage range and concentrated distribution interval of the two.

[0056] S3: Calibrate the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction.

[0057] In this embodiment, calibrating the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index includes: Statistically analyze the absolute phase difference sequence between the control command execution time point and the event trigger time point in the spatiotemporal coupling region; Determine the high-frequency concentrated interval in the absolute phase difference sequence to obtain the core synchronization band boundary of the absolute phase difference sequence; The positive and negative buffer margin values ​​of the time domain boundary and the core synchronization band boundary of the spatiotemporal coupling region are calculated step by step. The core synchronization band boundary, positive buffer margin value, and negative buffer margin value are encapsulated in triplets to obtain the synchronization margin index.

[0058] Specifically, the instruction execution phase refers to the position and state in the time domain of the actual execution time point corresponding to each execution node in the PLC control instruction sequence within the spatiotemporal coupling region. It is the core parameter characterizing the execution timing of PLC control actions and determines the execution timing reference of PLC field control actions.

[0059] The event trigger phase refers to the position and state of the actual trigger time point corresponding to each event point in the asynchronous event data stream of the instrument in the time domain within the spatiotemporal coupling zone. It is the core parameter characterizing the changes in the operating conditions of instruments in the industrial field and the timing of status reporting.

[0060] Synchronization margin index refers to the core indicator obtained by calibrating the execution phase of the instruction and the trigger phase of the event. It is used to quantitatively characterize the synchronization matching capability and the acceptable range of timing deviation between PLC control instructions and asynchronous events of instruments.

[0061] Event-driven execution instructions refer to PLC control execution instructions obtained by converting synchronization margin indicators and driven by asynchronous instrument events. They are the core control carrier that adapts to dynamic working conditions in industrial sites, breaks the limitations of traditional fixed-cycle PLC control, and realizes real-time collaboration between PLC and instruments.

[0062] The control instruction execution time point refers to the specific time point within the spatiotemporal coupling zone when the execution node corresponding to a single PLC control instruction actually completes the field control execution action. It is the smallest time unit that marks the actual occurrence of the PLC control action.

[0063] The event trigger time point refers to the specific time point at which the event point corresponding to a single asynchronous event of an industrial field instrument is actually triggered and generated within the spatiotemporal coupling zone. It is the smallest time unit that marks the actual occurrence time of changes in the instrument's field operating conditions and status reporting events.

[0064] An absolute phase difference sequence refers to a complete set of sequences formed by arranging the absolute timing deviations between the execution time points of all corresponding matching control commands and the event triggering time points within the spatiotemporal coupling region in chronological order.

[0065] The high-frequency concentrated range refers to the range of values ​​in which the timing phase difference value appears most frequently and is most concentrated in the absolute phase difference sequence. It reflects the most common and stable timing deviation range between PLC control instructions and instrument asynchronous events.

[0066] The core synchronization band boundary refers to the start and end boundaries of the timing deviation range that can be effectively synchronized between PLC control instructions and instrument asynchronous events, determined based on the high-frequency concentrated interval of the absolute phase difference sequence.

[0067] The time domain boundary refers to the start and end time boundaries of the time domain corresponding to the spatiotemporal coupling region. It defines the complete time range for phase calibration and margin calculation in this step and is the core range benchmark for calculating positive and negative buffer margin values.

[0068] The positive buffer margin value refers to the maximum timing deviation buffer range that PLC control instructions and instrument asynchronous events can accept in the positive timing direction, calculated based on the time domain boundary of the spatiotemporal coupling zone and the core synchronization band boundary. It is the core parameter characterizing the synchronous positive fault tolerance capability of the two.

[0069] The negative buffer margin value refers to the maximum timing deviation buffer range that PLC control instructions and instrument asynchronous events can accept in the negative timing direction, calculated based on the time domain boundary of the spatiotemporal coupling zone and the core synchronization band boundary. It is the core parameter characterizing the synchronous negative fault tolerance capability of the two.

[0070] Triple pack packaging refers to a standardized processing method that integrates and packages three core parameters: core synchronization band boundary, positive buffer margin value, and negative buffer margin value.

[0071] In detail, firstly, a full extraction operation of timing data is performed across the entire time domain. The execution time points of all PLC control instructions within the coupling zone, as well as the event triggering time points of all asynchronous instrument events matching the PLC instructions, are collected. The timing deviations between the execution time points of each set of control instructions and the event triggering time points are statistically analyzed one by one, and a complete absolute phase difference sequence is generated according to the timing sequence. The original data of all timing deviations between PLC instruction execution and instrument event triggering are retained. After the statistical generation of the absolute phase difference sequence is completed, the distribution characteristics of the entire sequence are sorted out to locate the high-frequency concentrated interval where the phase difference value appears most frequently and is most concentrated. Based on the start and end range of this high-frequency concentrated interval, the core synchronization band boundary corresponding to the absolute phase difference sequence is defined, and the core timing deviation range that enables effective synchronization matching between PLC control instructions and instrument asynchronous events is clarified. After determining the core synchronization zone boundary, the time domain boundary corresponding to the spatiotemporal coupling zone is used as the overall range benchmark, and the core synchronization zone boundary is used as the core reference benchmark. The buffer margin statistical operation in both positive and negative directions is carried out step by step to obtain the positive buffer margin value and negative buffer margin value that can characterize the synchronization fault tolerance capability of the two, and to understand the acceptable buffer range of timing deviation in the PLC and instrument coordination process. Then, a triplet encapsulation operation is performed on the core synchronization band boundary, positive buffer margin value, and negative buffer margin value to integrate the three into a standardized synchronization margin indicator that can be directly used for collaborative management and control. After obtaining the synchronization margin index, the index is transformed into an event-driven execution instruction that can be directly sent to the PLC for execution, with the asynchronous event triggering of the instrument as the core.

[0072] S4: Map the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points.

[0073] In this embodiment, mapping the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points includes: Extract the precise execution period of the event-driven execution instruction; The peak occupancy rate of the PLC is scanned by combining the precise execution period and the memory resource allocation map; The memory conflict hotspot period of the PLC is determined based on the peak occupancy rate; The load change rate gradient of the instrument is analyzed by the precise execution period and the communication link load map to obtain the communication load period of the instrument; Filter the resource contention mutual exclusion points of the memory conflict hot zone period and the communication load period.

[0074] Specifically, the memory resource allocation map is a panoramic data map of the allocation rules, occupancy status, and usage plans of memory resources in different time domains. It can clearly reflect the usage distribution pattern and occupancy pressure changes of PLC memory resources throughout the entire time period.

[0075] A communication link load map is a panoramic data map of load status, bandwidth usage, and data transmission volume changes in different time domains. It can clearly reflect the load fluctuation patterns and transmission pressure changes of communication links throughout the entire time period.

[0076] Resource contention and mutual exclusion points refer to the time points and resource locations where PLC memory resources and instrument communication links simultaneously experience resource overload, making it impossible to simultaneously meet the stable execution requirements of event-driven instructions and the data transmission requirements of instruments.

[0077] The precise execution period refers to the start and end time range of the actual execution of event-driven instructions in the PLC. It is the core time anchor point for matching the PLC memory resource usage status with the load status of the instrument communication link.

[0078] Peak utilization rate refers to the highest value of PLC memory resource utilization reached within a specific execution period of event-driven instructions, directly reflecting the maximum pressure on PLC memory resources during that period. The memory conflict hotspot period refers to the time range determined based on the peak value of PLC memory occupancy, during which the PLC memory resource occupancy is too high and the stable and smooth execution of event-driven instructions cannot be guaranteed.

[0079] The load change rate gradient refers to the magnitude and trend of the load status of the instrument communication link changing over time within the precise execution period of the event-driven execution command. It can clearly reflect the degree of fluctuation and pressure increase trend of the communication link load.

[0080] The communication load period refers to the time range during which the communication link load is too high, the data transmission pressure is too great, and the stable communication between the instrument and the PLC cannot be guaranteed, as determined by the gradient analysis of the load change rate of the instrument communication link.

[0081] In detail, for event-driven execution instructions, time-domain decomposition and extraction are performed to pinpoint the start and end time nodes of the actual execution of the instruction in the PLC, thereby capturing the precise execution period corresponding to the event-driven execution instruction; Simultaneously perform bidirectional matching analysis of PLC-side memory resources and instrument-side communication links. On the PLC side, bind and match the captured execution time period with the pre-generated PLC memory resource allocation map, traverse and scan the real-time occupancy of PLC memory resources, locate the peak occupancy rate of PLC memory resources during the execution time period, and understand the maximum usage pressure and pressure distribution of PLC memory during the execution of event-driven instructions. After locating the peak occupancy rate, based on the magnitude and time-domain distribution range of the peak, further identify the hot periods of memory conflict where PLC memory resource occupancy pressure is too high, event-driven instruction execution cannot be guaranteed to be stable, and there is no lag in execution, and clarify the high-incidence time domain range of PLC memory resource conflict. Simultaneously, on the instrument side, the captured execution time period is bound and matched with the pre-generated instrument communication link load map. Taking the execution time period as the analysis scope, the real-time load status of the communication link between the instrument and the PLC is analyzed throughout the entire time period. The load change amplitude and trend of the communication link within the execution time period are sorted out, the corresponding load change rate gradient is obtained, and the load fluctuation and transmission pressure change of the instrument communication link during the execution of event-driven execution instructions are understood. After completing the analysis of the load change rate gradient, based on the change magnitude and time domain distribution range of the gradient, the communication load periods of excessive load on the instrument communication link, excessive data transmission pressure, and inability to guarantee stable data interaction between the instrument and the PLC are further identified, and the high-incidence time domain range of instrument communication link congestion is clarified. After obtaining the memory conflict hotspot period of the PLC and the communication load period of the instrument, a full matching comparison and screening is carried out on the time domain range of the two periods. The time domain overlap intervals of the two periods are checked one by one to locate the time nodes and corresponding resource points where the two periods overlap and simultaneously experience resource occupancy pressure overload. Finally, the identification of resource contention and mutual exclusion points is completed.

[0082] In this embodiment, the formula for calculating the communication load period is: in: For the period of information load, Configure constants for the system. The average absolute magnitude of the load change rate. The average absolute magnitude of the load change rate gradient The duration of the critical offset window. The exact length of the execution period.

[0083] More specifically, the communication load time period is measured in seconds. It represents the gradient of the rate of change of the communication link load within a precise execution period, i.e., the acceleration of load change. The length of a significant time period is used to identify resource contention and mutual exclusion points.

[0084] The system configuration constant is a dimensionless parameter used to calibrate the formula to adapt to the hardware characteristics of different PLC-instrument systems, such as communication link bandwidth or processing delay. The typical value range is 0.5~1.5, and it is calibrated through system historical data or experiments.

[0085] The average absolute magnitude of the load change rate is expressed in bits per second. 2 This represents the average absolute value of the instantaneous load change rate within a precise execution period, reflecting the overall intensity of the load change. Based on the communication link load map, the numerical derivative is calculated within the precise execution period: First, the finite difference method is used to find... Then, take the absolute value and calculate the average over time.

[0086] The average absolute magnitude of the load change rate gradient is expressed in bits per second. 3 This represents the average absolute value of the second derivative of the acceleration of load change within a precise execution period, reflecting the degree of acceleration of load change. The higher the gradient, the stronger the time sensitivity.

[0087] The critical offset window, measured in seconds, represents the time offset cluster window of the event trigger point, used to modulate communication load periods. It is obtained by scanning the timestamp distribution of the asynchronous event data stream and comparing it with the critical connection points within the extended period coverage. For example, it can be used to identify the time offset of event points in the event queue and extract their cluster window length.

[0088] The precise execution time period, measured in seconds, is derived from the precise execution time period of the event-driven execution instructions and is obtained directly from them.

[0089] The dimensionless coefficient of the event cluster modulation coefficient represents the weight of the critical offset window relative to the precise execution period. The extended communication load period reflects the sensitivity to resource contention.

[0090] S5: Tracing the conflict source path of the resource contention mutual exclusion point in reverse. When the synchronization margin index corresponding to the conflict source path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain the anti-conflict coordination strategy.

[0091] In this embodiment, the step of tracing the conflict source path of the resource contention mutual exclusion point in reverse includes: The conflict event chain of the resource contention mutual exclusion point is traced through the control instruction sequence and the asynchronous event data stream. The phase offset path of the conflict event chain is dynamically generated based on the synchronization margin index to obtain the conflict tracing path.

[0092] Specifically, the conflict tracing path refers to the path obtained by tracing back along the time sequence from the point of mutual exclusion in resource competition. It fully records the entire causal path of resource competition conflict from its generation and transmission to its final outbreak, and can accurately locate the root cause of the conflict and the entire transmission process.

[0093] The preset tolerance boundary is a pre-set synchronization margin index that ensures the stable and coordinated operation of the PLC and the instrument. It is the maximum acceptable deviation critical boundary and the core judgment threshold for determining whether the current resource conflict exceeds the controllable range and whether the sampling frequency reconstruction operation needs to be performed.

[0094] Sampling frequency refers to the frequency at which industrial field instruments collect field operating data and report status events. It directly determines the frequency of instrument data transmission and the load pressure on the communication link.

[0095] Anti-conflict coordination strategy refers to a standardized management and control strategy generated by reconstructing the instrument sampling frequency, which can fundamentally avoid resource competition conflicts between PLC and instrument and ensure stable collaborative operation of the two in the industrial field.

[0096] The conflict event chain refers to the complete causal chain of all PLC control instruction execution events and instrument asynchronous triggering events that lead to resource competition conflicts, traced backward from the point of mutual exclusion of resource competition. It is a complete reconstruction of the entire event process of the conflict.

[0097] Phase offset path refers to the complete timing path in which the deviation between the PLC instruction execution phase and the instrument event trigger phase is gradually transmitted and accumulated, extracted from the conflict event chain based on the synchronization margin index. It is the core content of the conflict tracing path.

[0098] In detail, firstly, for the resource contention and mutual exclusion point, a full-link reverse tracing operation is carried out. Taking the resource contention and mutual exclusion point as the starting point of tracing, combined with the complete PLC control instruction sequence and instrument asynchronous event data stream captured in real time, starting from the time node where the conflict occurred, the process is reversed along the time sequence to sort out all PLC control instruction execution events and instrument asynchronous trigger events that are causally related to the resource contention and mutual exclusion point one by one. All events with causal transmission relationship are connected in sequence according to the logical sequence to trace and form a complete conflict event chain, and fully restore the entire causal process of the resource contention conflict from its generation, transmission to its final outbreak. After completing the full tracing of the conflict event chain, and combining the synchronization margin index, a full-link timing phase analysis operation is carried out on the conflict event chain. The deviation change process between the PLC instruction execution phase and the instrument event trigger phase corresponding to each event node in the conflict event chain is dynamically tracked. The complete path of phase deviation gradually propagation and accumulation is sorted out, and the phase offset path corresponding to the conflict event chain is generated. Finally, a complete conflict tracing path is integrated to accurately locate the root cause of resource competition conflict and the full-link propagation process. After the conflict tracing path is generated, the synchronization margin index corresponding to the entire link of the conflict tracing path is compared and verified with the pre-set tolerance boundary at all times. The synchronization margin index is checked throughout the process to see if it exceeds the preset acceptable deviation range and to determine if there is a situation that exceeds the preset tolerance boundary. When the verification finds that the synchronization margin index corresponding to the conflict tracing path exceeds the preset tolerance boundary, confirming that the current resource conflict has exceeded the controllable range and will affect the stable collaborative operation of the PLC and the instrument, the sampling frequency of the field instrument associated with the conflict tracing path is immediately reconstructed and adjusted. By optimizing and adjusting the sampling and data reporting frequency of the instrument, the resource competition conflict between the PLC memory resources and the instrument communication link is avoided from the root.

[0099] In this embodiment, when the synchronization margin index corresponding to the conflict tracing path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain an anti-conflict coordination strategy, including: Based on the conflict tracing path and synchronization margin index, a tolerance boundary breach scan operation is performed to obtain the set of tolerance breach instrument nodes in the conflict tracing path. Based on the synchronization margin index, a tolerance boundary breach scan is performed on the conflict tracing path to obtain the tolerance breach instrument node in the conflict tracing path. Based on the tolerance breakthrough instrument node, the sampling frequency gradient of the communication link load map is reconstructed to obtain the sampling frequency gradient value of the communication channel corresponding to each instrument; The sampling frequency gradient value and the memory resource allocation map are encapsulated into an anti-conflict cooperative strategy.

[0100] Specifically, sampling frequency refers to the frequency at which industrial field instruments collect field operating data and report status events, directly determining the frequency of instrument data transmission and the load pressure of the corresponding communication link.

[0101] Anti-conflict coordination strategy refers to a standardized management and control strategy generated by reconstructing the instrument sampling frequency, which can fundamentally avoid resource competition conflicts between PLC and instrument and ensure stable collaborative operation of the two in the industrial field.

[0102] The tolerance boundary breach scanning operation refers to a standardized traversal operation that uses the conflict tracing path as the scanning range, the synchronization margin index as the judgment basis, and the preset tolerance boundary as the judgment standard to check whether the synchronization status of the instrument nodes exceeds the controllable range across the entire link.

[0103] The tolerance breach instrument node set refers to the complete set of all field instrument nodes whose synchronization margin indicators have exceeded the preset tolerance boundary and are directly related to resource competition conflicts, obtained after completing the full-link tolerance boundary breach scanning operation.

[0104] A tolerance-breakout instrument node refers to a field instrument node that, after completing a tolerance boundary breakout scan, is precisely located and breaks through the preset tolerance boundary, directly triggering or participating in resource competition conflicts.

[0105] A communication link load map is a panoramic data map that fully records the load status, bandwidth usage, and data transmission volume changes of the communication link between the instrument and the PLC in different time domains. It can clearly reflect the load fluctuation pattern and transmission pressure changes of the communication link throughout the entire time period.

[0106] Sampling frequency gradient reconstruction refers to the reconstruction operation that adjusts the sampling frequency of an instrument in a gradient, differentiated, and adaptive manner, based on the load of the corresponding communication link, for instrument nodes that have exceeded tolerance limits.

[0107] The sampling frequency gradient value refers to the differentiated sampling frequency adjustment value obtained after the sampling frequency gradient reconstruction is completed, which is adapted to the current load and can avoid resource conflicts for each instrument's corresponding communication channel.

[0108] A memory resource allocation map is a panoramic data map that fully records the allocation rules, occupancy status, and usage plan of memory resources in different time domains during PLC operation. It can reflect the distribution pattern and occupancy pressure of PLC memory resources throughout the entire time period.

[0109] A communication channel refers to a dedicated communication link between a single instrument and a PLC for transmitting acquired data and event reporting information. Each instrument has its own dedicated communication channel.

[0110] In detail, using the pre-set tolerance boundary as the judgment standard, a tolerance boundary breach scan is performed. The synchronization margin indicators of all field instrument nodes associated with the conflict tracing path are verified for compliance. All instrument nodes whose synchronization margin indicators have breached the preset tolerance boundary are completely screened out and summarized to form a complete set of tolerance breach instrument nodes, clarifying the overall scope of all instruments that need to be adjusted and optimized. After completing the full-link scan and node set aggregation, based on the synchronization margin index, a second tolerance boundary breach scan is carried out on the conflict tracing path. Each independent tolerance breach instrument node in the tolerance breach instrument node set that has a direct causal relationship with the resource competition conflict is located one by one, and each field instrument individual that needs to be adjusted is identified. After accurately locating all tolerance-breaking instrument nodes, for each locked tolerance-breaking instrument node, an adaptive sampling frequency gradient reconstruction operation is carried out in conjunction with the pre-generated communication link load map of the corresponding instrument. Based on the real-time load status and pressure fluctuation pattern of the corresponding communication channel, the sampling frequency of the instrument is adjusted and optimized in a gradient manner. Finally, the sampling frequency gradient value of the corresponding communication channel of each instrument is adapted to the current working condition, thereby reducing the load pressure of the communication link from the root and avoiding resource competition conflicts. After determining the sampling frequency gradient values ​​of all instruments, the obtained full sampling frequency gradient values ​​are integrated and packaged with the pre-generated PLC memory resource allocation map.

[0111] S6: Execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

[0112] In this embodiment, executing the anti-conflict cooperative strategy and feeding back the execution result to the spatiotemporal coupling region includes: The rationality of the aforementioned anti-conflict coordination strategy is verified, and the verified anti-conflict coordination strategy is fed back to the spatiotemporal coupling region.

[0113] Specifically, after the anti-conflict collaboration strategy is generated, its rationality is first verified to ensure that the strategy will not introduce new conflicts or anomalies during execution. After the verification is passed, the anti-conflict collaboration strategy is executed, and the execution result is fed back to the spatiotemporal coupling zone as a basic reference for the next round of collaborative processing.

[0114] like Figure 2 The diagram shown is a functional block diagram of an edge intelligent collaborative processing system for PLCs and instruments provided in an embodiment of the present invention.

[0115] The edge intelligent collaborative processing system 100 for PLCs and instruments described in this invention can be installed in electronic devices. Depending on the functions implemented, the edge intelligent collaborative processing system 100 for PLCs and instruments may include a capture module 101, a reconfiguration module 102, an instruction conversion module 103, a contention identification module 104, a strategy generation module 105, and a feedback module 106. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0116] In this embodiment, the functions of each module / unit are as follows: Capture module 101: Used to capture the control command sequence of the PLC and the asynchronous event data stream of the connected instruments in real time; Reconstruction module 102: used to reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage; Instruction conversion module 103: used to calibrate the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction; Contention identification module 104: used to map the memory resource allocation map of the event-driven execution instructions to the PLC and the communication link load map of the instrument, so as to identify resource contention mutual exclusion points; Strategy generation module 105: used to reverse trace the conflict source path of the resource contention mutual exclusion point. When the synchronization margin index corresponding to the conflict source path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain the anti-conflict coordination strategy. Feedback module 106: Used to execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

[0117] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0118] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0119] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0120] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0121] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An edge intelligent collaborative processing method for PLCs and instruments, characterized in that, The method includes: S1: Real-time capture of PLC control command sequences and asynchronous event data streams from connected instruments; S2: Reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage. S3: Calibrate the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction; S4: Map the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points; S5: Reverse trace the conflict source path of the resource contention mutual exclusion point. When the synchronization margin index corresponding to the conflict source path exceeds the preset tolerance boundary, reconstruct the sampling frequency of the instrument to obtain the anti-conflict coordination strategy. S6: Execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

2. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 1, characterized in that, The real-time capture of the PLC's control command sequence and the asynchronous event data stream of the connected instruments includes: Establish an instruction buffer for the control bus corresponding to the PLC, and continuously monitor the instruction output timing of the instruction buffer to obtain the control instruction sequence; Access the event queue interface of the instrument to capture the asynchronous event data stream of the instrument.

3. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 1, characterized in that, The process of reconstructing the extended cycle coverage of the control command sequence and extracting the key offset window from the asynchronous event data stream includes: Analyze the real-time attributes of the corresponding execution nodes in the control instruction sequence to clarify the basic cycle boundary; Integrate the potential delay factors of the PLC; By combining the basic cycle boundary and the delay influencing factors, the extended cycle coverage of the control command sequence is reconstructed; Scan the timestamp distribution of the asynchronous event data stream to identify the time offset of the event trigger point in the asynchronous event data stream; By comparing the time offset with the key connection points of the extended period coverage, the comparison results are filtered to obtain the key offset window.

4. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 3, characterized in that, The establishment of the instruction-event spatiotemporal coupling region centered on the key offset window, based on the extended cycle coverage, includes: The center of the critical offset window is bound to the extended period coverage area, and the center of the window is set as the phase alignment reference point; By associating the execution nodes in the control command sequence with the phase alignment reference point, the relative vector distribution of the control command sequence is obtained; By filtering the event points within the key offset window in the asynchronous event data stream, the clustered density cloud is obtained; The spatiotemporal coupling region is determined by the vector distribution and the clustered density cloud.

5. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 1, characterized in that, The calibration of the instruction execution phase and event triggering phase within the spatiotemporal coupling region to obtain a synchronization margin index includes: Statistically analyze the absolute phase difference sequence between the control command execution time point and the event trigger time point in the spatiotemporal coupling region; Determine the high-frequency concentrated region in the absolute phase difference sequence to obtain the core synchronization band boundary of the absolute phase difference sequence; The positive and negative buffer margin values ​​of the time domain boundary and the core synchronization band boundary of the spatiotemporal coupling region are calculated step by step. The core synchronization band boundary, positive buffer margin value, and negative buffer margin value are encapsulated in triplets to obtain the synchronization margin index.

6. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 5, characterized in that, The mapping of the event-driven execution instructions to the PLC's memory resource allocation map and the instrument's communication link load map to identify resource contention and mutual exclusion points includes: Extract the precise execution time period of the event-driven execution instruction; The peak occupancy rate of the PLC is scanned by combining the precise execution period and the memory resource allocation map; The memory conflict hotspot period of the PLC is determined based on the peak occupancy rate; The load change rate gradient of the instrument is analyzed by the precise execution period and the communication link load map to obtain the communication load period of the instrument; Filter the resource contention mutual exclusion points of the memory conflict hot zone period and the communication load period.

7. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 1, characterized in that, The reverse tracing of the conflict source path of the resource contention mutual exclusion point includes: The conflict event chain of the resource contention mutual exclusion point is traced through the control instruction sequence and the asynchronous event data stream. The phase offset path of the conflict event chain is dynamically generated based on the synchronization margin index to obtain the conflict tracing path.

8. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 7, characterized in that, When the synchronization margin index corresponding to the conflict tracing path exceeds the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain an anti-conflict coordination strategy, including: Based on the conflict tracing path and synchronization margin index, a tolerance boundary breach scan operation is performed to obtain the set of tolerance breach instrument nodes in the conflict tracing path. Based on the synchronization margin index, a tolerance boundary breach scan is performed on the conflict tracing path to obtain the tolerance breach instrument node in the conflict tracing path. Based on the tolerance breakthrough instrument node, the sampling frequency gradient of the communication link load map is reconstructed to obtain the sampling frequency gradient value of the communication channel corresponding to each instrument; The sampling frequency gradient value and the memory resource allocation map are encapsulated into an anti-conflict cooperative strategy.

9. The edge intelligent collaborative processing method for PLCs and instruments as described in claim 1, characterized in that, The execution of the anti-conflict cooperative strategy and the feedback of the execution result to the spatiotemporal coupling region include: The rationality of the aforementioned anti-conflict coordination strategy is verified, and the verified anti-conflict coordination strategy is fed back to the spatiotemporal coupling region.

10. An edge intelligent collaborative processing system for PLCs and instruments, used to implement the edge intelligent collaborative processing method for PLCs and instruments as described in any one of claims 1-9, characterized in that, The system includes: Capture module (101): Used to capture the control command sequence of the PLC and the asynchronous event data stream of the connected instruments in real time; Reconstruction module (102): used to reconstruct the extended cycle coverage of the control instruction sequence, extract the key offset window in the asynchronous event data stream, and establish a spatiotemporal coupling zone of instruction-event centered on the key offset window in combination with the extended cycle coverage; Instruction conversion module (103): used to calibrate the instruction execution phase and event triggering phase in the spatiotemporal coupling region to obtain a synchronization margin index, and convert the synchronization margin index into an event-driven execution instruction; Contention identification module (104): used to map the event-driven execution instructions to the memory resource allocation map of the PLC and the communication link load map of the instrument in order to identify resource contention mutual exclusion points; Strategy generation module (105): used to reverse trace the conflict source path of the resource contention mutual exclusion point. When the synchronization margin index corresponding to the conflict source path breaks through the preset tolerance boundary, the sampling frequency of the instrument is reconstructed to obtain the anti-conflict coordination strategy. Feedback module (106): used to execute the anti-conflict coordination strategy and feed back the execution result to the spatiotemporal coupling region.

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