A parameter acquisition method, device, apparatus and storage medium

Abstract

The application discloses a parameter collection method and device, equipment and a storage medium, and relates to the field of industrial parameter collection. The method comprises the following steps: defining each service state to determine an overall control process of parameter collection, and determining a corresponding periodic parameter collection mechanism based on available communication capability and the overall control process; acquiring original parameter data transmitted by a plurality of to-be-collected devices by using a plurality of IO channels, and respectively analyzing each original parameter data by using a plurality of HART protocol analyzers to obtain analyzed parameter data; updating different types of parameters in the analyzed parameter data according to a parameter updating rule, and caching various types of updated parameters in a HART data cache of an IO module which is preconfigured; and collecting corresponding parameters cached in the HART data cache based on the periodic parameter collection mechanism. It can be seen that the application solves the problem of real-time periodic parameter collection of large-scale intelligent devices, and can dynamically configure parameters for communication.

Description

Technical Field

[0001] This invention relates to the field of industrial parameter acquisition, and in particular to a parameter acquisition method, apparatus, equipment, and storage medium. Background Technology

[0002] In chemical plant site management, control valves are typical instrumentation devices. Many critical valve parameters need to be collected on a second-by-second basis for production management and maintenance. For example, the valve stroke from 0 to 100% typically takes 3 to 5 seconds, and the corresponding process flow is designed according to this execution time. If abnormalities occur during this process, such as failure to execute, slow execution, or incomplete execution, timely identification and handling are necessary. Traditional HART intelligent device parameter acquisition usually involves manual triggering or periodic acquisition in equipment management software. However, the acquisition time of both methods is much longer than the effective acquisition time of critical valve parameters, thus making it impossible to use these parameters for effective management. There is no strict standard for the effective acquisition time of parameters, but the closer the acquisition time is to the real-time time of the parameter, the more effective it is; ideally, there should be no delay. Due to the limited communication capabilities of the HART protocol, the parameter acquisition time for HART intelligent devices is usually much longer than the real-time time of the parameters. Existing technologies cannot meet the following requirements: it is impossible to configure a large number of intelligent devices simultaneously, each intelligent device can be configured with different parameters and parameter update cycles, and all of these parameters must be collected synchronously within an update cycle while meeting the effective acquisition time of these intelligent devices. The host computer's device management software primarily focuses on simple interaction with the managed smart devices, lacking a management method for high-performance acquisition of numerous parameters from a large number of diverse smart devices. Under current technological conditions, the key to solving the problem of large-scale, high-performance HART parameter synchronous acquisition lies in addressing the single-channel parsing limitation of existing solutions from the source. This means resolving the issue where multiple channels connected to smart devices in the I / O module can only process HART data from one channel at a time. Summary of the Invention

[0003] In view of this, the purpose of this invention is to provide a parameter acquisition method, apparatus, device, and storage medium that can add an I / O module supporting multi-channel communication, enabling one I / O module to simultaneously parse HART data from multiple channels of smart devices, thereby improving unit acquisition efficiency and thus enhancing overall efficiency. The specific solution is as follows:

[0004] Firstly, this application provides a parameter acquisition method, including:

[0005] Define the service states during the parameter acquisition process to determine the overall control process of parameter acquisition, and determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process;

[0006] The original parameter data transmitted by multiple devices to be acquired is obtained by using multiple IO channels in the IO module, and multiple pre-configured HART protocol parsers corresponding to the multiple IO channels are used to parse each of the original parameter data to obtain the corresponding parsed parameter data.

[0007] According to the preset parameter update rules, the parameters of different types in the parsed parameter data are updated, and the updated parameters of various types are cached in the pre-configured HART data cache in the IO module;

[0008] Based on the aforementioned periodic parameter acquisition mechanism, the corresponding parameters cached in the HART data cache under the target service state are acquired.

[0009] Optionally, the step of determining the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process includes:

[0010] Based on the current controller's communication capabilities when transmitting data, the communication capabilities of the protocol between the controller and the IO module, and the overall control process, a corresponding periodic parameter acquisition mechanism is determined.

[0011] Optionally, before acquiring the raw parameter data transmitted by the corresponding multiple devices to be acquired using the multiple IO channels in the IO module, the method further includes:

[0012] Based on the currently available communication capabilities, determine the number of IO channels in the current IO module, and then determine the number of HART protocol parsers that need to be pre-configured for each IO channel.

[0013] Optionally, before updating different types of parameters in the parsed parameter data according to a preset parameter update rule, the method further includes:

[0014] According to the preset parameter type classification rules, the parameters in the parsed parameter data are divided into dynamic parameters and static parameters;

[0015] Accordingly, updating different types of parameters in the parsed parameter data according to preset parameter update rules includes:

[0016] According to the preset parameter update rules, the dynamic parameters and static parameters in the parsed parameter data are updated respectively to obtain the updated dynamic parameters and updated static parameters.

[0017] Optionally, updating the dynamic parameters and static parameters in the parsed parameter data according to a preset parameter update rule to obtain updated dynamic parameters and updated static parameters includes:

[0018] Different parameter update times are configured for the dynamic parameters and static parameters in the parsed parameter data, and update operations are performed on the dynamic parameters and static parameters based on the parameter update times to obtain the updated dynamic parameters and updated static parameters.

[0019] Optionally, the step of configuring different parameter update times for the dynamic parameters and static parameters in the parsed parameter data, and performing update operations on the dynamic parameters and static parameters based on the parameter update times to obtain updated dynamic parameters and updated static parameters, includes:

[0020] Based on preset time rules, a first type of time and a second type of time are respectively configured for the dynamic parameters and the static parameters in the parsed parameter data;

[0021] The update operation of the dynamic parameters in the parsed parameter data is completed within the first type of time.

[0022] Once the dynamic parameters have been updated, the update operation of the static parameters in the parsed parameter data is completed within the second type of time.

[0023] Optionally, the second type of time is longer than the first type of time.

[0024] Secondly, this application provides a parameter acquisition device, including...

[0025] The acquisition mechanism determination module is used to define the status of each service during the parameter acquisition process to determine the overall control process of parameter acquisition, and to determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process.

[0026] The data acquisition module is used to acquire raw parameter data transmitted by multiple devices to be acquired using multiple IO channels in the IO module, and to parse each of the raw parameter data using multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to obtain the corresponding parsed parameter data.

[0027] The data caching module is used to update different types of parameters in the parsed parameter data according to preset parameter update rules, and cache the updated parameters of various types to the pre-configured HART data cache in the IO module.

[0028] The parameter acquisition module is used to acquire the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism.

[0029] Thirdly, this application discloses an electronic device, including:

[0030] Memory, used to store computer programs;

[0031] A processor is used to execute the computer program to implement the aforementioned parameter acquisition method.

[0032] Fourthly, this application discloses a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the aforementioned parameter acquisition method.

[0033] This application, when collecting parameters, first defines the various service states in the parameter collection process to determine the overall control process of parameter collection, and determines the corresponding periodic parameter collection mechanism based on the currently available communication capabilities and the overall control process. It utilizes multiple IO channels in the IO module to acquire the raw parameter data transmitted by multiple devices to be collected, and uses multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to parse each of the raw parameter data to obtain the corresponding parsed parameter data. According to preset parameter update rules, different types of parameters in the parsed parameter data are updated, and the updated parameters of various types are cached in the pre-configured HART data cache in the IO module. Based on the periodic parameter collection mechanism, the corresponding parameters cached in the HART data cache under the target service state are collected. Therefore, this application realizes periodic parameter collection state flow management, completing all process states of large-scale, high-performance collection of intelligent device parameters. Furthermore, through multi-dimensional management parameter interaction, the effective collection time is clarified to determine the priority and importance of parameter collection. This solves the problem that serial communication and only having multiple HART parsing IO channels can only perform simple state interactions. The system categorizes parameters, establishing a one-to-one correspondence between effective acquisition time and actual parameters, simplifying the concept of effective acquisition time. By managing available communication capacity, it dynamically determines the available communication capacity to support dynamic parameter updates for different types of hardware and communication links. Dynamic and flexible calculation is not limited to fixed hardware models or communication links. Finally, the HAMS periodic acquisition and interaction mechanism enables high-performance acquisition of parameters from intelligent devices at large scale, covering every process state. HAMS, the controller, and the IO module interact in each state. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0035] Figure 1 A flowchart of a parameter acquisition method provided in this application;

[0036] Figure 2 This application provides a schematic diagram of the state transition of periodic parameter acquisition.

[0037] Figure 3 A schematic diagram of a HART IO module supporting multi-channel concurrency provided for this application;

[0038] Figure 4 A schematic diagram of a HAMS periodic parameter acquisition interaction mechanism provided in this application;

[0039] Figure 5 A flowchart of a specific parameter acquisition method provided in this application;

[0040] Figure 6 This is a schematic diagram of a common HART parsing scheme for HART IO modules;

[0041] Figure 7 This is a schematic diagram of data interaction in a common device management software.

[0042] Figure 8 A schematic diagram for calculating parameter update time provided in this application;

[0043] Figure 9 A flowchart of a specific parameter acquisition method provided in this application;

[0044] Figure 10 This is a schematic diagram of the structure of a parameter acquisition device disclosed in this application;

[0045] Figure 11 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Under current technological conditions, the key to solving the problem of large-scale, high-performance HART parameter synchronous acquisition lies in addressing the single-channel parsing limitation of existing solutions from the source. This means resolving the issue where multiple channels of an I / O module connect to smart devices, yet only one channel of HART data can be processed at a time. To address this problem, this application provides a parameter acquisition method that adds an I / O module supporting multi-channel communication, enabling a single I / O module to simultaneously parse HART data from multiple channels of smart devices. This improves the unit acquisition efficiency and thus enhances overall efficiency.

[0048] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a parameter acquisition method, including:

[0049] Step S11: Define the service states in the parameter acquisition process to determine the overall control process of parameter acquisition, and determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process.

[0050] In this embodiment, a parameter acquisition state transition is defined to control and manage all processes involved in large-scale parameter acquisition. This process is the overall control process for parameter acquisition, and the managed objects include HAMS, controllers, IO modules, and intelligent devices. HAMS (HOLLiAS Asset Management System) typically refers to a host computer software system that performs batch comprehensive management of intelligent instrument devices using industrial bus protocols for industrial field management. The complete state transition mechanism is as follows: Figure 2As shown, A: Preparation: In this state, it is used to confirm whether HAMS, the controller, the IO module, and the smart device have normal communication status. Normal communication status means that the physical link is unobstructed and the physical device status is normal and has the conditions to execute subsequent processes. After all device statuses have completed communication preparation, it enters the next state "Initialization". If an abnormality occurs in communication and status self-check, it enters "Diagnosis". If the abnormality is eliminated after diagnosis, it switches back to "Preparation". B: Initialization: Initialization is the preparation state for large-scale periodic data acquisition. HAMS will complete the parameter interaction preparation through "weighted periodic parameter interaction management" according to the actual hardware situation, and distribute the parameters to the controller and IO module cache according to the method. After completion, it can enter the next state "Running". If an abnormality occurs in communication and status self-check, it enters "Diagnosis". If the abnormality is eliminated after diagnosis, it switches back to "Preparation". C: Running: In the running state, HAMS, the controller, and the IO module perform parameter management according to the parameter management method determined in the previous state. If an abnormality occurs in communication and status self-check, it enters "Diagnosis". If the abnormality is eliminated after diagnosis, it switches back to "Preparation". D: Suspended: In HAMS use, except for the use case of periodic parameter acquisition. Users may need to temporarily upload full parameters for a specific smart device to view its complete parameters, depending on the actual situation. They may also need to download parameters (write operations) to a specific smart device. In these cases, performing these temporary operations will occupy the smart device's communication channel. Therefore, the system enters a "suspended" state, suspending the currently executing periodic parameter acquisition of the smart device in HAMS. The command interactions required for the temporary operations are executed first. After the temporary communication operations are completed, HAMS releases the "suspended" state and continues periodic parameter acquisition for the smart device. E: Diagnosis: During the state interactions from A to D, abnormal states may occur due to various circumstances, such as: controller communication not ready, controller network abnormality, IO module communication not ready, IO module network abnormality, etc. These abnormal states are divided into two categories: Recoverable abnormalities: These refer to situations where, after an abnormality occurs, HAMS or relevant hardware can continue communication after handling according to the agreed-upon procedures, without affecting subsequent interactions. After handling recoverable abnormalities, the system will return to the previous state from the "diagnosis" state. Unrecoverable abnormalities: In this case, HAMS or relevant hardware cannot continue communication after handling according to the agreed-upon procedures, and interaction cannot continue. At this time, the system will transition from "diagnosis" to "termination". End of periodic parameter acquisition state. F: Terminate: Indicates termination of periodic parameter acquisition state, and will not switch to other states. Manual handling of exceptions is required to re-trigger the "Ready" state.

[0051] In this embodiment, before HAMS manages the state transition of periodic parameter acquisition, it needs to determine the available communication capabilities: that is, how many intelligent instrument devices under IO modules can HAMS guarantee high-weight dynamic parameter acquisition at one time. Finally, based on the currently available communication capabilities and the overall control process, the corresponding periodic parameter acquisition mechanism is determined. In this way, by defining the state transition management of periodic parameter acquisition, the process required to complete large-scale, high-performance acquisition of intelligent device parameters is defined. The interactions required in each process state are clarified, and how each process state transitions to meet the needs of the acquisition process is explained.

[0052] Step S12: Use multiple IO channels in the IO module to acquire the raw parameter data transmitted by the corresponding multiple devices to be acquired, and use multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to parse each of the raw parameter data to obtain the corresponding parsed parameter data.

[0053] In this embodiment, the fundamental bottleneck in synchronous acquisition of large-scale, high-performance HART (Highway Addressable Remote Transducer) parameters lies at the acquisition source. Existing single-channel parsing schemes involve multiple channels of the IO module connected to HART instruments, but can only process HART data from one channel of the smart device at a time. It is necessary to improve the unit acquisition efficiency to enhance overall efficiency. Therefore, the IO module needs to be equipped with multi-channel HART parsing capabilities, enabling one IO module to simultaneously parse HART data from multiple channels of smart devices. However, the shift from single-channel to multi-channel HART data parsing is not simply a matter of adding parallel parsing to serial parsing. Because compared to the enormous number of parameters in smart instruments, the DCS (Distributed Control Systems) controllers, IO modules, and network bandwidth in industrial settings are limited, and simply expanding hardware capabilities cannot solve the problem. The amount of data from intelligent devices increases dramatically from bottom to top in the communication hierarchy: a single instrument needs to collect P parameters, a module needs to support data from N channels of intelligent instrument devices, a controller needs to support data from K modules of intelligent instruments, and a HAMS LAN server needs to support the number of intelligent devices from L controllers: P*N*K*L. Typically, an intelligent instrument device has dozens to hundreds of parameters. Using 100 as the average, if a HAMS LAN server manages 10,000 intelligent instrument devices, the total number of parameters would be: 100*10000 = 1,000,000. If only periodic data collection is performed, the update cycle will be extremely slow, or all devices cannot be updated simultaneously. Furthermore, it will directly affect the normal communication of non-HART data on the entire communication link. Therefore, dynamic management of periodic parameter interactions by type is necessary. It can be understood that periodic parameters refer to the parameters that must be updated and collected within the DCS system control cycle, and can be configured according to actual process requirements. Common control cycles are 500ms, 100ms, and 50ms. A shorter control cycle results in a smaller data volume, which contrasts with aperiodic parameters. It should be noted that a DCS system is a new type of control system developed to meet the requirements of large-scale industrial production and increasingly complex process control. From a comprehensive automation perspective, it integrates process control and monitoring, combining 4C technologies: Computer, Communication, Display (CRT), and Control.DCS systems have evolved to a point where they largely adopt a modular design. All core components, such as CPUs, power supplies, I / O modules, communication modules, and AI / AO modules, are modular. These devices are designed as independent modules. Assembling a rack simply involves installing the module bases and then mounting the corresponding modules onto them. Each module integrates its own CPU with processing capabilities, resulting in faster processing speeds. Furthermore, modules operate independently, meaning a problem in one module will not affect others, and hot-swapping is supported. Meanwhile, the HART protocol, originally developed by Rosemount in the US, uses FSK (Frequency-shift keying) technology to superimpose a frequency signal onto a 4-20mA signal, successfully enabling bidirectional communication between analog and digital signals without interference. The HART protocol utilizes the OSI (Open System Interconnection) standard's first physical layer, second data link layer, and seventh application layer. The HART protocol is a master-slave protocol that defines the physical form of transmission, message structure, data format, and a series of operational commands. HART supports dual masters, and up to 15 slave devices can be connected on a single cable. Following the IOS layering, the HART protocol is divided into the physical layer, data link layer, and application layer. The host computer software interacts with the devices according to the application layer commands defined by the HART protocol. A single HART read command typically reads one or more parameters.

[0054] In this embodiment, a conventional IO module has only one HART protocol parser, which can only communicate with one HART smart device on one channel at a time. For high-performance HART parameter synchronous acquisition on a large scale, concurrent multi-channel HART parsing must be supported. That is, each IO module channel must have HART parsing capability, so at the physical layer, an additional HART protocol parser equal to the number of channels is needed to support concurrency. That is, as follows... Figure 3 As shown, multiple IO channels in the IO module are used to acquire raw parameter data transmitted from multiple devices to be acquired. Then, multiple pre-configured HART protocol parsers corresponding to the multiple IO channels are used to parse each of the raw parameter data to obtain the corresponding parsed parameter data. In this way, the problem of insufficient timeliness in serial updates is fundamentally solved by concurrent multi-channel HART parsing.

[0055] Step S13: Update different types of parameters in the parsed parameter data according to the preset parameter update rules, and cache the updated parameters of various types in the pre-configured HART data cache in the IO module.

[0056] In this embodiment, since multi-channel HART concurrency only eliminates the time consumed by serial communication, each smart meter device needs to acquire multiple parameters, corresponding to multiple HART commands needing to be exchanged. Further elimination of this latency is required. Therefore, the HART data cache of the IO module needs to be added. Each communication of a HART command occupies one byte, and the command originates from the top-level HAMS. The multi-level interaction during this process causes latency, which is eliminated through caching. According to a preset parameter update rule, different types of parameters in the parsed parameter data are updated. It should be noted that different types of parameters include dynamic parameters and static parameters. The updated dynamic and static parameters are then cached in the pre-configured HART data cache of the IO module.

[0057] Step S14: Collect the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism.

[0058] In this embodiment, HAMS determines the number of IO modules for each interaction based on available communication management. Therefore, after completing the "Preparation" state, during the "Initialization" state, HAMS sends HART commands corresponding to the dynamic parameters of the smart devices under C_U IO modules each time. The controller sends these commands to the IO modules periodically after receiving batch buffering. The IO modules buffer the commands that need to be collected. After K / C_U batches of sending, communication ends, and the "Initialization" state is entered into the "Running" state. The IO modules immediately begin concurrent dynamic parameter interaction with the smart devices under each channel. Each time a smart device returns response data, the IO module buffers the data. This continues until HAMS retrieves the buffered data from the IO modules at a period interval of T_C / 2. Simultaneously, if the user needs to perform temporary manual operations such as uploading to a smart device, the entire system enters a "Suspended" state. At this time, HAMS sends commands to the IO modules for uploading operations on the smart devices; these commands use the static parameters of the IO modules for interaction. When a smart device uploads data, all parameters need to be updated. The amount of data for these parameters far exceeds the static parameter cache space of the IO module. Therefore, during each interaction, once the static parameter space is exhausted, the IO module returns all cached data, and HAMS continues to issue the remaining commands until the end. After the temporary operation concludes, HAMS notifies the entire system, and the system switches from a "suspended" state back to a "running" state. However, if the user does not perform periodic parameter collection, an operation triggered by HAMS puts the entire system into a "terminated" state. If it needs to be reactivated, triggering HAMS restarts the entire system from the "ready" state. Key interactions include... Figure 4 As shown, this solves the problem of not being able to collect parameters from a large number of smart devices in the later stages, and also enables dynamic configuration of smart device parameters that require periodic communication based on hardware capabilities and communication link capabilities.

[0059] As can be seen from the above, when performing parameter acquisition, this application first defines the various service states in the parameter acquisition process to determine the overall control process of parameter acquisition, and determines the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process; it uses multiple IO channels in the IO module to obtain the original parameter data transmitted by multiple devices to be acquired, and uses multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to parse each of the original parameter data to obtain the corresponding parsed parameter data; according to the preset parameter update rules, it updates different types of parameters in the parsed parameter data, and caches the updated parameters of various types in the pre-configured HART data cache in the IO module; based on the periodic parameter acquisition mechanism, it acquires the corresponding parameters cached in the HART data cache under the target service state. Therefore, this application realizes periodic parameter acquisition state flow management, completing all process states of large-scale, high-performance acquisition of intelligent device parameters. Furthermore, through multi-dimensional management parameter interaction, the effective acquisition time is clarified to determine the priority and importance of parameter acquisition. This solves the problem that serial communication and only having multiple HART parsing IO channels can only perform simple state interactions. The system categorizes parameters, establishing a one-to-one correspondence between effective acquisition time and actual parameters, simplifying the concept of effective acquisition time. By managing available communication capacity, it dynamically determines the available communication capacity to support dynamic parameter updates for different types of hardware and communication links. Dynamic and flexible calculation is not limited to fixed hardware models or communication links. Finally, the HAMS periodic acquisition and interaction mechanism enables high-performance acquisition of parameters from intelligent devices at large scale, covering every process state. HAMS, the controller, and the IO module interact in each state.

[0060] See Figure 5 As shown, this embodiment of the invention discloses a specific parameter acquisition method, including:

[0061] Step S21: Define the service states in the parameter acquisition process to determine the overall control process of parameter acquisition, and determine the corresponding periodic parameter acquisition mechanism based on the communication capability of the current controller when transmitting data, the communication capability of the protocol between the controller and the IO module, and the overall control process.

[0062] In this embodiment, during the periodic data acquisition management process of HAMS, the controller and IO module only transmit the data after acquiring it, without any intermediate data processing time. Therefore, it is only necessary to determine the communication capability of the controller when transmitting data and the communication capability of the protocol between the controller and the IO module to determine how HAMS performs data acquisition. However, the parameter acquisition of smart devices is all non-periodic data. Therefore, the available non-periodic data volume must be determined based on the amount of periodic data. The controller's processing cycle defines the total amount of data that can be processed as M_C bytes, with each cycle being T_C milliseconds. The amount of periodic data processed within the control cycle is M_C1 bytes, so the amount of non-periodic data that can be processed is:

[0063] M_C2=M_C-M_C1

[0064] The actual industrial protocol between the controller and I / O allows for the communication of M_BW of data bytes per controller cycle. Different controller models and types support different industrial protocols. Each industrial protocol has a different communication bandwidth capability. Therefore, for HAMS, the amount of non-periodic data that can be processed, or the amount of data that can be acquired, per controller control cycle is...

[0065] M_U = min(M_C2, M_BW)

[0066] Therefore, the amount of data that can be collected within the strictly effective update time is:

[0067] M_UT=(T_S / T_C)*M_U, and M_UT>M_IOD

[0068] The actual amount of data that can be used and updated for static parameters is:

[0069] M_IOS1 = M_UT - M_IOD

[0070] Therefore, the number of IO modules that HAMS can complete dynamic command updates within each strict acquisition cycle can be calculated as follows:

[0071] C_U = M_UT / (M_IO + M_IOS1).

[0072] The corresponding periodic parameter acquisition mechanism can then be determined based on the communication capability of the current controller when transmitting data, the communication capability of the protocol between the controller and the IO module, and the overall control process.

[0073] Step S22: Use multiple IO channels in the IO module to acquire the raw parameter data transmitted by the corresponding multiple devices to be acquired, and use multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to parse each of the raw parameter data to obtain the corresponding parsed parameter data.

[0074] In this embodiment, the HART protocol parsing chip in the DCS's IO module needs to parse the instrument's HART communication data. Common HART IO module HART parsing schemes include... Figure 6 As shown, the module has multiple channels, each connecting to a smart device. However, only one HART protocol parsing chip communicates with the smart device connected to one channel at a time. Therefore, if there are multiple channels and each device needs to collect multiple parameters, it is necessary to communicate with each smart device sequentially, one parameter at a time. Performance is poor under large-scale data acquisition, and the collected parameter values ​​are often only used as trend references. A representative foreign competitor's 16-channel DCS IO module requires each smart device on each channel to exchange parameters for two HART commands. Therefore, completing the parameter collection for 16 smart devices under this module involves 32 HART commands, and each acquisition cycle takes 17 seconds. This time is far greater than the typical valve execution cycle time of 3 to 5 seconds for execution-type smart valve devices. This application fundamentally solves the problem of insufficient timeliness in serial updates by using multi-channel HART parsing concurrency and command caching. Before acquiring the raw parameter data transmitted by the corresponding multiple devices to be acquired using multiple IO channels in the IO module, the method further includes: determining the number of IO channels in the current IO module based on the currently available communication capabilities, and thus determining the number of HART protocol parsers corresponding to the IO channels that need to be pre-configured. This allows the pre-configured multiple HART protocol parsers corresponding to the multiple IO channels to parse each of the raw parameter data to obtain the corresponding parsed parameter data.

[0075] Step S23: According to the preset parameter type classification rules, the parameters in the parsed parameter data are divided into dynamic parameters and static parameters.

[0076] In this embodiment, updating different types of parameters in the parsed parameter data according to a preset parameter update rule can include: updating the dynamic parameters and static parameters in the parsed parameter data separately according to the preset parameter update rule to obtain updated dynamic parameters and updated static parameters. It should be noted that it is impossible to update all smart device parameters under a HAMS server according to the strict validity period of the smart devices at once. Therefore, it is necessary to classify parameter types into dynamic parameters and static parameters.

[0077] Step S24: Configure different parameter update times for the dynamic parameters and static parameters in the parsed parameter data, and perform update operations on the dynamic parameters and static parameters based on the parameter update times to obtain the updated dynamic parameters and updated static parameters.

[0078] In this embodiment, control valves are typical instrumentation devices in chemical plant site management. Many key valve parameters need to be collected in seconds for production management and maintenance. For example, the valve stroke from 0 to 100% typically takes 3 to 5 seconds, and the corresponding process flow is designed according to this execution time. If abnormalities occur during this process, such as non-execution, slow execution, or incomplete execution, timely identification and handling are necessary. Traditional HART smart device parameter acquisition is usually manually triggered or periodically collected in equipment management software. However, the acquisition time of both methods is much longer than the effective acquisition time of key valve parameters, thus making it impossible to use these parameters for effective management. There is no strict standard for the effective acquisition time of parameters, but the closer the acquisition time is to the real-time time of the parameter, the more effective it is; ideally, there should be no delay. Due to the limited communication capabilities of the HART protocol, the parameter acquisition time for HART smart devices is usually much longer than the real-time time of the parameters. Currently, some solutions manage smart devices in batches through equipment management software, such as... Figure 7 As shown, the physical medium and path of communication are common: HAMS -> DCS controller -> DCS IO module -> smart device. Different smart devices have different valid periods for their parameters based on their characteristics and usage scenarios. Therefore, different parameter update times are configured for the dynamic parameters and static parameters in the parsed parameter data, and update operations are performed on the dynamic parameters and static parameters based on the parameter update times to obtain the updated dynamic parameters and updated static parameters.

[0079] Step S25: Cache the updated parameters of various types into the pre-configured HART data cache in the IO module.

[0080] In this embodiment, multi-channel HART concurrency only eliminates the time consumed by serial communication. Each smart meter device has multiple parameters to acquire, corresponding to multiple HART commands to interact. Further elimination of this latency is needed. Therefore, the HART data cache of the IO module needs to be increased. Each HART command occupies one byte, and the command comes from the top-level HAMS. Multiple levels of interaction cause latency, which is eliminated through caching. Each HART command has the same request format length L1 and response format length L2. The available cached data volume of the IO module is M_IO bytes. The amount of dynamic parameter data that the IO module needs to cache is: M_IOD = L1 + 2 + L2 * 3 bytes. Therefore, the cache for static parameters is: M_IOS = M_IOD - M_IOS. The IO module updates dynamic and static parameters sequentially, prioritizing dynamic parameter updates. This eliminates the interaction process of HAMS issuing commands to acquire parameters in serial mode when HAMS obtains smart device parameters from the IO module via the controller. Figure 8 As shown, the time required for this process is negligible (0) under multi-path concurrency.

[0081] Step S26: Collect the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism.

[0082] In this embodiment, there are three ways in the prior art for smart devices to acquire parameters. The first method is to directly connect to the smart device using a handheld device and obtain the latest parameter values ​​by executing the parameter upload function of the handheld device. However, this method can only connect to one smart device at a time and requires local operation, making it difficult to transmit the acquired parameters to the device management software or other host computer platforms in real time. The second method is to use the DCS or communication master station as the transmission channel in the device management software and obtain the latest parameter values ​​for one or several smart devices by executing the smart device parameter upload function in the device management software. However, this process is a single active trigger, and the time to update all smart device parameters is usually much longer than the effective acquisition time of smart device real-time parameters. The third method is to configure a limited number of smart device parameters to be acquired periodically in the device management software. The communication master station (DCS controller or MUX) is used as the transmission channel to collect smart device parameters. However, slave devices under the communication master station, such as the DCS IO module or the MUX slave, only communicate with one smart device at a time, and communication with multiple smart devices needs to be executed sequentially. Ultimately, all parameters are executed and updated sequentially, and the time to complete one update of all smart device parameters is far greater than the effective data acquisition time of the smart devices. Furthermore, the more smart devices and parameters are configured, the slower the update time becomes. The update cycles of multiple parameters under a single smart device do not distinguish priority. Most importantly, these parameters are acquired serially, not synchronously. This means that the refresh times of each parameter after each update are different and vary significantly across all devices under a single controller. This prevents further processing and application using parameter values ​​at the same moment, such as for fault warnings of smart devices. However, there is no way to configure a large number of smart devices simultaneously, nor is it possible to configure different parameters and update cycles for each smart device. In other words, it is impossible to achieve effective data acquisition of device parameters for a large number of smart devices, and it is impossible to perform high-performance periodic data acquisition on demand for different parameters within smart devices. This application solves the problem of not being able to perform post-processing parameter acquisition for large-scale smart devices by acquiring the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism described above. It also has the ability to dynamically configure the parameters of smart devices requiring periodic communication based on hardware capabilities and communication link capabilities.

[0083] As shown above, this application achieves large-scale, high-performance acquisition of all process states of intelligent device parameters by implementing periodic parameter acquisition state flow management. Furthermore, through multi-dimensional parameter management interaction, it solves the problem that serial communication and simple state interaction are limited to multi-channel HART parsing IO. Parameter types are categorized to correspond one-to-one with effective acquisition time and actual parameters, simplifying the concept of effective acquisition time. Available communication capacity management dynamically determines the actual available communication capacity to support dynamic parameter updates under different hardware types and communication links. Dynamic and flexible calculation is not limited to fixed hardware models or communication links. Finally, the HAMS periodic acquisition interaction mechanism completes the large-scale, high-performance acquisition of intelligent device parameters across each process state, with HAMS, the controller, and the IO module interacting in each state.

[0084] See Figure 9 As shown, this embodiment of the invention discloses a specific parameter acquisition method, including:

[0085] Step S31: Based on the preset time rules, configure the first type of time and the second type of time for the dynamic parameters and static parameters in the parsed parameter data, respectively.

[0086] In this embodiment, different intelligent devices have different effective times for their parameters based on their characteristics and usage scenarios. In chemical plants, valve-type intelligent devices, which are generally the most time-sensitive, are ideal standard examples. In a specific implementation, the average execution time of a HART command is constrained to 500ms according to the HART protocol. Taking a typical valve intelligent device as a standard, the number of HART commands required for fault alarms, fault warnings, and equipment status judgments is defined as 3. It can be deduced that updating these 3 commands (corresponding parameters) takes 1.5s. Therefore, 1.5s is defined as the strict effective time T_S for intelligent device parameter acquisition, i.e., the first type of time. Within this time range, the corresponding intelligent device parameters need to be updated. At this point, these parameters can be understood as being updated at the same time. Simultaneously, a relative effective time for intelligent device parameter acquisition is defined, i.e., the second type of time. For example, in practice, 4 commands are needed to complete the interaction. In this case, updating these 4 commands (corresponding parameters) takes 2s. This 2s is the relative effective time, i.e., the second type of time, which is greater than the first type of time. Due to the large number of parameters configured in actual use, limitations in communication channel capacity, HART protocol performance, hardware communication capabilities, and software communication capabilities mean that it's impossible to guarantee that all smart device parameters adhere to a strictly valid timeframe when there are many parameters configured. Therefore, a relative validity time is defined to ensure that smart device parameters are updated according to the strictly valid timeframe during periodic parameter updates. Furthermore, based on actual hardware, network, and computer configurations, other smart device parameters are updated according to the relatively valid timeframe. It can be understood that dynamic parameters guarantee HART command interaction with the corresponding smart device within a strictly valid timeframe, while static parameters only guarantee updates within a relatively valid timeframe. This ensures that all parameters are updated within their valid timeframes.

[0087] Step S32: Control the execution of the update operation of the dynamic parameters in the parsed parameter data within the first type of time.

[0088] In this embodiment, the IO module updates the dynamic parameters and static parameters sequentially, and it needs to control the execution of the update operation of the dynamic parameters in the parsed parameter data within the first type of time.

[0089] Step S33: Once the dynamic parameters have been updated, the update operation of the static parameters in the parsed parameter data is completed within the second type of time.

[0090] In this embodiment, once the dynamic parameters have been updated, the static parameters are updated, and the update operation of the static parameters in the parsed parameter data is completed within the second type of time. That is, when the IO module updates the static parameters and the dynamic parameters, it prioritizes updating the dynamic parameters.

[0091] As can be seen from the above, this application determines the priority and importance of parameter acquisition by specifying the effective acquisition time. In this way, when HAMS obtains parameters of the smart device through the controller and IO module, the interactive process of HAMS issuing commands to obtain parameters in serial mode is eliminated.

[0092] See Figure 10 As shown in the figure, an embodiment of the present invention discloses a parameter acquisition device, characterized in that it includes:

[0093] The acquisition mechanism determination module 11 is used to define the status of each service in the parameter acquisition process to determine the overall control process of parameter acquisition, and to determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process.

[0094] The data acquisition module 12 is used to acquire the raw parameter data transmitted by the corresponding multiple devices to be acquired using multiple IO channels in the IO module, and to parse each of the raw parameter data using multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to obtain the corresponding parsed parameter data.

[0095] The data caching module 13 is used to update different types of parameters in the parsed parameter data according to preset parameter update rules, and cache the updated parameters of various types to the HART data cache pre-configured in the IO module.

[0096] The parameter acquisition module 14 is used to acquire the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism.

[0097] As can be seen from the above, when performing parameter acquisition, this application first defines the various service states in the parameter acquisition process to determine the overall control process of parameter acquisition, and determines the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process; it uses multiple IO channels in the IO module to obtain the original parameter data transmitted by multiple devices to be acquired, and uses multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to parse each of the original parameter data to obtain the corresponding parsed parameter data; according to the preset parameter update rules, it updates different types of parameters in the parsed parameter data, and caches the updated parameters of various types in the pre-configured HART data cache in the IO module; based on the periodic parameter acquisition mechanism, it acquires the corresponding parameters cached in the HART data cache under the target service state. Therefore, this application realizes periodic parameter acquisition state flow management, completing all process states of large-scale, high-performance acquisition of intelligent device parameters. Furthermore, through multi-dimensional management parameter interaction, the effective acquisition time is clarified to determine the priority and importance of parameter acquisition. This solves the problem that serial communication and only having multiple HART parsing IO channels can only perform simple state interactions. The system categorizes parameters, establishing a one-to-one correspondence between effective acquisition time and actual parameters, simplifying the concept of effective acquisition time. By managing available communication capacity, it dynamically determines the available communication capacity to support dynamic parameter updates for different types of hardware and communication links. Dynamic and flexible calculation is not limited to fixed hardware models or communication links. Finally, the HAMS periodic acquisition and interaction mechanism enables high-performance acquisition of parameters from intelligent devices at large scale, covering every process state. HAMS, the controller, and the IO module interact in each state.

[0098] In some specific embodiments, the acquisition mechanism determination module 11 may include:

[0099] The acquisition mechanism determination unit is used to determine the corresponding periodic parameter acquisition mechanism based on the communication capability of the current controller when transmitting data, the communication capability of the protocol between the controller and the IO module, and the overall control process.

[0100] In some specific embodiments, the data acquisition module 12 further includes:

[0101] The parser quantity determination unit is used to determine the number of IO channels in the current IO module based on the currently available communication capabilities, so as to determine the number of HART protocol parsers corresponding to the IO channels that need to be pre-configured.

[0102] In some specific embodiments, the data caching module 13 further includes:

[0103] The parameter partitioning unit is used to divide the parameters in the parsed parameter data into dynamic parameters and static parameters according to a preset parameter type partitioning rule.

[0104] In some specific embodiments, the data caching module 13 may include:

[0105] The parameter update unit is used to update the dynamic parameters and the static parameters in the parsed parameter data according to the preset parameter update rules, so as to obtain the updated dynamic parameters and the updated static parameters.

[0106] In some specific embodiments, the data caching module 13 may include:

[0107] The first update time configuration unit is used to configure different parameter update times for the dynamic parameters and the static parameters in the parsed parameter data, and to perform update operations on the dynamic parameters and the static parameters based on the parameter update times to obtain the updated dynamic parameters and the updated static parameters.

[0108] In some specific embodiments, the data caching module 13 may include:

[0109] The second update time configuration unit is used to configure a first type of time and a second type of time for the dynamic parameters and the static parameters in the parsed parameter data respectively based on preset time rules;

[0110] The first parameter update unit is used to control the execution of the update operation of the dynamic parameters in the parsed parameter data within the first type of time.

[0111] The second parameter update unit is used to control the execution of the update operation of the static parameters in the parsed parameter data within the second type of time when the dynamic parameters have been updated.

[0112] In some specific embodiments, the parameter acquisition device may include:

[0113] A time-limiting unit is used when the second type of time is greater than the first type of time.

[0114] Furthermore, embodiments of this application also disclose an electronic device, Figure 11 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0115] Figure 11This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the parameter acquisition method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0116] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0117] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0118] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the parameter acquisition method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.

[0119] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned parameter acquisition method. The specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0120] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0121] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0122] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0123] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0124] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A parameter acquisition method, characterized in that, include: Define the service states during the parameter acquisition process to determine the overall control process of parameter acquisition, and determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process; The original parameter data transmitted by multiple devices to be acquired is obtained by using multiple IO channels in the IO module, and the original parameter data is parsed by using multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to obtain the corresponding parsed parameter data. According to the preset parameter update rules, different types of parameters in the parsed parameter data are updated, and the updated parameters of various types are cached in the pre-configured HART data cache in the IO module; Based on the aforementioned periodic parameter acquisition mechanism, the corresponding parameters cached in the HART data cache under the target service state are acquired; The various service states include at least the following: preparation state, initialization state, running state, suspended state, diagnostic state, and termination state; the overall control process includes: In the preparation state, it is confirmed whether the device management system, controller, IO module and smart device have normal communication status. After all devices have completed communication preparation, the initialization state is entered. In the initialization state, the device management system completes parameter interaction preparation through weighted periodic parameter interaction management based on the actual hardware situation, and sends the parameters to the controller and IO module cache according to the method. After completion, it enters the running state. In the operating state, the device management system, controller, and IO module perform parameter management according to the parameter management method determined in the initialization state; In the suspended state, the communication of the smart device currently performing periodic data collection is suspended, and the command interaction required for temporary operations is executed first. After the temporary communication operation is completed, the suspension is lifted and the periodic parameter collection continues. In the diagnostic state, any abnormal state that occurs is processed. If the abnormal state can be recovered, the system will return to the previous state from the diagnostic state. If the abnormal state cannot be recovered, the system will enter the termination state. In the terminated state, the periodic parameter acquisition state is terminated and will not switch to other states.

2. The parameter acquisition method according to claim 1, characterized in that, The mechanism for determining the corresponding periodic parameter acquisition based on the currently available communication capabilities and the overall control process includes... Based on the current controller's communication capabilities when transmitting data, the communication capabilities of the protocol between the controller and the IO module, and the overall control process, a corresponding periodic parameter acquisition mechanism is determined.

3. The parameter acquisition method according to claim 1, characterized in that, Before acquiring the raw parameter data transmitted from the corresponding multiple devices using multiple IO channels in the IO module, the method further includes: Based on the currently available communication capabilities, determine the number of IO channels in the current IO module, and then determine the number of HART protocol parsers that need to be pre-configured for each IO channel.

4. The parameter acquisition method according to any one of claims 1 to 3, characterized in that, Before updating different types of parameters in the parsed parameter data according to preset parameter update rules, the process further includes: According to the preset parameter type classification rules, the parameters in the parsed parameter data are divided into dynamic parameters and static parameters; Accordingly, updating different types of parameters in the parsed parameter data according to preset parameter update rules includes: According to the preset parameter update rules, the dynamic parameters and static parameters in the parsed parameter data are updated respectively to obtain the updated dynamic parameters and updated static parameters.

5. The parameter acquisition method according to claim 4, characterized in that, The step of updating the dynamic parameters and static parameters in the parsed parameter data according to a preset parameter update rule to obtain updated dynamic parameters and updated static parameters includes: Different parameter update times are configured for the dynamic parameters and static parameters in the parsed parameter data, and update operations are performed on the dynamic parameters and static parameters based on the parameter update times to obtain the updated dynamic parameters and updated static parameters.

6. The parameter acquisition method according to claim 5, characterized in that, The step involves configuring different parameter update times for the dynamic parameters and static parameters in the parsed parameter data, and performing update operations on the dynamic parameters and static parameters based on the parameter update times to obtain the updated dynamic parameters and updated static parameters, including: Based on preset time rules, a first type of time and a second type of time are respectively configured for the dynamic parameters and the static parameters in the parsed parameter data; The update operation of the dynamic parameters in the parsed parameter data is completed within the first type of time. Once the dynamic parameters have been updated, the update operation of the static parameters in the parsed parameter data is completed within the second type of time.

7. The parameter acquisition method according to claim 6, characterized in that, The second type of time is longer than the first type of time.

8. A parameter acquisition device, characterized in that, include: The acquisition mechanism determination module is used to define the status of each service during the parameter acquisition process to determine the overall control process of parameter acquisition, and to determine the corresponding periodic parameter acquisition mechanism based on the currently available communication capabilities and the overall control process. The data acquisition module is used to acquire raw parameter data transmitted by multiple devices to be acquired using multiple IO channels in the IO module, and to parse each of the raw parameter data using multiple pre-configured HART protocol parsers corresponding to the multiple IO channels to obtain the corresponding parsed parameter data. The data caching module is used to update different types of parameters in the parsed parameter data according to preset parameter update rules, and cache the updated parameters of various types to the pre-configured HART data cache in the IO module. The parameter acquisition module is used to acquire the corresponding parameters cached in the HART data cache under the target service state based on the periodic parameter acquisition mechanism. The various service states include at least a preparation state, an initialization state, a running state, a suspended state, a diagnostic state, and a termination state. The overall control process includes: in the preparation state, confirming whether the device management system, controller, IO module, and smart device have normal communication capabilities; after all device states have completed communication preparation, entering the initialization state; in the initialization state, the device management system completes parameter interaction preparation through weighted periodic parameter interaction management based on the actual hardware situation, and distributes the parameters to the controller and IO module cache according to the method, and then enters the running state; in the running state, the device management system, controller, and IO module manage parameters according to the parameter management method determined in the initialization state; in the suspended state, suspending the communication of the smart device currently performing periodic data collection, prioritizing the execution of command interactions required for temporary operations, and releasing the suspension after the temporary communication operation is completed to continue periodic parameter collection; in the diagnostic state, handling any abnormal states; if the abnormality can be recovered, the system will return to the previous state from the diagnostic state; if the abnormality cannot be recovered, the system will enter the termination state; in the termination state, the periodic parameter collection state is terminated, and no further transitions to other states are made.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the parameter acquisition method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the parameter acquisition method as described in any one of claims 1 to 7.

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