Boiler data transmission method based on distributed control system platform

Abstract

The invention discloses a boiler data transmission method based on a distributed control system platform, and the method is applied to the communication interaction between a control service platform and a distributed control system, and comprises the steps: S1, obtaining point location data about boiler control in the distributed control system platform, and taking the point location data as boiler data; s2, an improved self-adaptive cyclic redundancy algorithm is used in the distributed control system platform to calculate the boiler data to obtain a verification result, and if verification succeeds, the boiler data is transmitted to a control service platform; and S3, the control service platform analyzes the boiler data, outputs optimized boiler data, and transmits the optimized boiler data back to the distributed control system platform through the improved OPC protocol, and the distributed control system platform adopts the optimized boiler data to adjust the parameters of the boiler. By adopting the method, the optimization data obtained by the distributed control system platform can be ensured to be correct and legal, and the safe and stable operation of the system can be ensured.

Description

Technical Field

[0001] The invention relates to the technical field of computer data processing, and in particular to a boiler data transmission method based on a distributed control system platform. Background Art

[0002] DCS (Digital Control System) is the central system for modern unit operation. Unlike traditional control systems, DCS has a complete communication system that can transmit large amounts of data in a timely and accurate manner. Although the DCS of nuclear power plants and conventional power plants both have monitoring, control and protection functions, there are great differences between the two. The DCS of nuclear power plants is designed and operated based on the nuclear power safety quality assurance system, and has higher requirements in terms of safety, reliability and maintainability.

[0003] In the distributed control system of thermal power plant boiler control, manual control or automatic control is usually adopted for some subsystems. Regardless of the control method, the next action needs to be planned based on the various data collected by the sensor. Therefore, communication is particularly important. Once the communication fails or an error occurs, the wrong data is uploaded, which will cause the next action to be wrong, resulting in serious consequences. Therefore, it is very necessary to verify the communication data and verify the consistency, legality and correctness of the network transmission data. If there is an abnormality in the communication, the alarm will be issued immediately and corresponding measures will be taken, which can also minimize the risk caused by abnormal communication. Summary of the invention

[0004] The purpose of the present invention is to overcome the consequences caused by the above-mentioned communication anomalies, and a boiler data transmission method based on a distributed control system platform is provided. The method uses an improved adaptive cyclic redundancy (IACRC) algorithm in a DCS system to perform data verification, and performs data verification based on a CLIPS development framework in a control service platform. CLIPS supports diversified rule configuration, and can realize automatic generation of verification rules and dynamic update during runtime. Using CLIPS to verify data can quickly discover whether communication data is abnormal and issue an alarm in the first time.

[0005] The present invention solves the above problems through the following technical solutions:

[0006] The present application provides a communication data verification method based on industrial software and a distributed control system, characterized in that an improved adaptive cyclic redundancy (IACRC) algorithm is used to perform data verification on a distributed control system platform (DCS) side and data verification is performed on a control service platform side.

[0007] In a first aspect, the present application provides a communication data verification method based on industrial software and a distributed control system.

[0008] A boiler data transmission method based on a distributed control system platform comprises the following steps:

[0009] S1. Obtaining point data on boiler control in the distributed control system platform as boiler data;

[0010] S2. Using an improved adaptive cyclic redundancy algorithm in the distributed control system platform to calculate the boiler data to obtain a verification result. If the verification is successful, the boiler data is transmitted to the control service platform;

[0011] S3. The control service platform analyzes the boiler data, outputs an optimized boiler data, and transmits the optimized boiler data back to the distributed control system platform through the improved OPC communication protocol. The distributed control system platform uses the optimized boiler data to adjust the parameters of the boiler.

[0012] In step S1, the point data about boiler coal feeding control are instantaneous coal feeding amount, instantaneous coal feeding rate, furnace bed material temperature, furnace bed material pressure, current steam temperature and current steam pressure.

[0013] In step S2, an improved adaptive cyclic redundancy algorithm is used in the distributed control system platform to calculate the boiler data to obtain a verification result, which specifically includes:

[0014] S2.1. Adaptively select a parameter model of a cyclic redundancy algorithm according to the amount of boiler data;

[0015] S2.2, according to the parameters of the parameter model of the cyclic redundancy algorithm, the boiler data is shifted left to obtain the expanded data;

[0016] S2.3, use XOR operation to divide the expanded data to obtain the remainder;

[0017] S2.4, the remainder obtained in step S2.3 is added to the boiler data as a check code of the cyclic redundancy algorithm and sent to the receiving end;

[0018] S2.5. The receiving end verifies the received data using the generating polynomial to obtain a verification result.

[0019] In step S2.1, a parameter model of a cyclic redundancy algorithm is adaptively selected according to the amount of boiler data, specifically including:

[0020] S2.1.1) When the data measurement points of the boiler data contain five or more measurement points, it is determined to be large data volume data, and the parameter model of the cyclic redundancy algorithm selects the CRC-16 parameter model with high error detection capability and suitable for large data volume;

[0021] S2.1.2) When the data measurement points of the boiler data contain four or less measurement points, it is determined to be small data volume data, and the parameter model of the cyclic redundancy algorithm selects the CRC-8 parameter model with low error detection capability and suitable for small data volume.

[0022] In step S2.2, the boiler data is shifted left by 8 bits.

[0023] In step S3, the control service platform analyzes the boiler data and outputs optimized boiler data, which specifically includes:

[0024] S3.1. The control service platform analyzes the boiler data of coal feeding control through the proportional-integral-differential PID controller and outputs a coal feeding adjustment data;

[0025] S3.2. Generate facts in the expert system CLIPS format for the adjustment data and boiler data and store them in the fact database;

[0026] S3.3. The facts in the expert system CLIPS format and the rules in the knowledge base of the expert system CLIPS are periodically identified and matched through the RETE forward rule fast matching algorithm to determine whether the data is available. If available, the adjusted data is used as the optimized boiler data.

[0027] In step S3.3, some basic verification rules are stored in the knowledge base module of the expert system CLIPS, and the rules are set by boiler experts.

[0028] In step S3, the improved OPC communication protocol specifically includes:

[0029] 1. Authentication: The client and server in OPC are authenticated through OpenSSL certificates to ensure that only authorized applications and systems can connect to each other;

[0030] 2. Data encryption: Data is encrypted with 128-bit or 256-bit encryption using Basic128 or Basic256 encryption algorithms for secure transmission to ensure session security;

[0031] 3. Data signature: Data is digitally signed using the RSA algorithm and combined with a hash function such as SHA-256 to ensure that the received information is exactly the same as when it was sent, to prevent tampering;

[0032] 4. Sequencing packets: Prevent information replay attacks by sequencing packets;

[0033] 5 Audit: Record user and system activities and provide access audit trails for post-analysis and monitoring.

[0034] Furthermore, an improved adaptive cyclic redundancy (IACRC) algorithm is used on the distributed control system platform (DCS) side to perform data verification in order to determine whether there is a transmission interruption or excessive communication delay in the internal data transmission of the DCS system, which affects the correctness of data acquisition. Specifically, the following steps are included:

[0035] (D101) Acquire and identify data at each point in the DCS system;

[0036] (D102) Use the improved adaptive cyclic redundancy (IACRC) algorithm in the DCS system program page to establish multiple function block change parameter model parameters to verify the data;

[0037] (D103) Each data loop traverses the verification function block;

[0038] (D104) The function block point data is verified to obtain the verification result.

[0039] The step (D101) of obtaining data of each point in the DCS system specifically includes:

[0040] Various types of data are stored in each data point in the DCS (Distributed Control System) system. A connection with the point is established from the DCS system program page to obtain the corresponding data.

[0041] The improved adaptive cyclic redundancy (IACRC) algorithm specifically includes the following improvements:

[0042] According to the requirements for data error detection capability and the amount of data, select the parameter model of CRC-8, CRC-16 or CRC-32 according to the CRC parameter model table.

[0043] Use a more complex generator polynomial: Choose a generator polynomial that can detect more types of errors and provide better error detection performance;

[0044] Adaptive CRC: According to the characteristics of the data and application requirements, the custom function block in the DCS system is used to dynamically adjust the parameter model of the CRC algorithm, including WIDTH (CRC data bit width), POLY (generator polynomial), INIT (CRC initial value), REFIN (whether the original data is flipped), REFOUT (whether the CRC value is flipped), XOROUT (value of XOR operation), etc., to optimize the performance of error detection;

[0045] Byte expansion: Expand the CRC calculation from bit-based calculation to byte-based calculation. Due to the huge amount of data in the DCS system, this can reduce the number of data processing times and improve efficiency.

[0046] In step (D102), a check function block using an improved adaptive cyclic redundancy (IACRC) algorithm is established in the DCS system, and the check function block includes the following steps:

[0047] (D102-1) According to different error detection capability requirements of different data and the size of the data, a CRC parameter model is determined through a parameter model selection function block to match different requirements of different data;

[0048] (D102-2) The original data is shifted left by the number of bits of the corresponding parameter model;

[0049] (D102-3) Using an XOR operation to divide the expanded data, obtaining a remainder;

[0050] (D102-4) This remainder is attached to the original data as a CRC check code and then sent to the receiving end;

[0051] (D102-5) The receiving end verifies the received data using the same generating polynomial;

[0052] The step (D104) of verifying the function block point data to obtain a verification result specifically includes:

[0053] The receiving end uses the same generating polynomial to check the received data. If the output is correct, the remainder should be zero. After the check is passed, the point data is transmitted to the control service platform through the IOPC communication protocol; if the check fails, it indicates that the communication transmission in the DCS system is interrupted or the communication delay is too high, and an alarm is issued. Engineers are sent to check the DCS system communication network and re-check the data.

[0054] The IOPC protocol specifically includes:

[0055] The IOPC protocol adds a security authentication link based on the OPC protocol, which is achieved through the following aspects:

[0056] Session encryption: Information is encrypted with 128-bit or 256-bit encryption using Basic128 or Basic256 encryption algorithms for secure transmission to ensure session security;

[0057] Information signature: Information is digitally signed using the RSA algorithm and combined with a hash function such as SHA-256 to ensure that the received information is exactly the same as when it was sent, to prevent tampering;

[0058] Sequencing packets: prevent information replay attacks by sequencing packets;

[0059] Authentication: OPC UA clients and servers use OpenSSL certificates to authenticate their identities, ensuring that only authorized applications and systems can connect to each other.

[0060] Audit: Record user and system activities and provide access audit trails for post-analysis and monitoring;

[0061] OPC UA over MQTT: Combining the lightweight characteristics of MQTT and the data modeling capabilities of OPC UA, OPC UA over MQTT provides comprehensive security mechanisms, including authentication, authorization, encryption, and data integrity, to meet security challenges in industrial environments.

[0062] Through the above aspects, a strong security authentication link can be implemented in the IOPC protocol to ensure the communication security in industrial automation and IoT applications.

[0063] The data transmission via the IOPC communication protocol specifically includes the following steps:

[0064] The control service platform client authenticated by the OpenSSL certificate initiates a request to the local or remote OPC server authenticated by the OpenSSL certificate.

[0065] The local or remote OPC server processes the request and collects data from the points that have passed the IACRC check inside the DCS system.

[0066] The data is encrypted using Basic128 or Basic256 encryption algorithm.

[0067] The data is digitally signed using the RSA algorithm.

[0068] Sort packets.

[0069] Send data to the control service platform client.

[0070] The control service platform client verifies the signature and decrypts the data before using it.

[0071] In a second aspect, the present application provides a communication data verification method based on industrial software and a distributed control system, and performs data verification on the industrial control service platform side, including the following steps:

[0072] (S101) acquiring target communication data;

[0073] (S102) establishing an input and output parameter table of object attributes according to the business attributes of different object systems;

[0074] (S103) creating a CLIPS development framework based on C language;

[0075] (S104) CLIPS performs data verification on the data of different object systems and outputs the data verification results;

[0076] (S105) After the data verification is successful, it is sent to the DCS system through the improved IOPC protocol.

[0077] The step (S101) of acquiring target communication data specifically includes:

[0078] The control service platform obtains the data of each data point from the DCS (distributed control system) system through the IOPC communication protocol and performs further calculation and processing, and the data obtained from the calculation and processing is used for communication verification.

[0079] Step (S102) establishes an input and output parameter table of object attributes according to the business attributes of different object systems, specifically including:

[0080] Target system name, target system input parameters, target system output parameters.

[0081] The step (S103) of creating a CLIPS development framework based on C language specifically includes:

[0082] Fact base module; Knowledge base module; Reasoning engine module; Human-computer interaction module;

[0083] The fact base module specifically includes:

[0084] A fact represents known data information in CLIPS, represents a piece of information in the fact list, and is the basic unit of rule-calling data.

[0085] The knowledge base module specifically includes:

[0086] The main function of the CLIPS knowledge base module is to store some basic rules for data in different systems. The rules include the following:

[0087] Preset data objects;

[0088] Preset data types;

[0089] Default rule name;

[0090] Preset rule parameters;

[0091] Preset rule trigger conditions;

[0092] Preset rules to check error prompt words, etc.

[0093] The basic rule module includes the following rule modules: threshold detection module, update module, overspeed detection module, etc.

[0094] To meet different requirements for different data, you can select multiple basic rule modules and customize other modules.

[0095] The inference engine module specifically includes:

[0096] The CLIPS inference engine module, after setting up the data verification mechanism, matches the rules in the knowledge base module according to the current known data information in the fact base.

[0097] According to the established knowledge base and the adjustment data calculated by the PID controller, the data are preprocessed to generate relevant facts in CLIPS format.

[0098] The RETE fast matching algorithm is used to periodically identify and match the facts in the fact base and the rules in the defined knowledge base, and compare them with the facts in the current working memory.

[0099] With the preset conflict elimination mechanism, the normal operation of reasoning is ensured. When all the conditions of a rule are met, the rule is considered to be activated and can be triggered to generate the final verification result.

[0100] The human-computer interaction page at the front end of the feedback system is visualized.

[0101] Complete the system's reasoning work and be able to output reasoning results.

[0102] The inference engine keeps repeating the process of rule matching and execution. Newly added facts may trigger more rules, thus continuing the inference process until no more rules can be activated.

[0103] The human-computer interaction module specifically includes:

[0104] The function of the human-computer interaction module is to enable operators to better interact with the expert system, mainly to achieve the following functional requirements:

[0105] Operators can not only see the output results on the human-computer interaction interface, but also modify and improve the CLIPS system.

[0106] A friendly human-computer interaction interface determines the interactivity and usability of the software design, reducing the time cost for general operators to learn and use the expert system.

[0107] A more complete human-computer interaction interface can make people more familiar with the circulating fluidized bed boiler control system. When data verification fails, the cause and location of the data verification failure can be clearly understood and corresponding expert suggestions can be given. This not only gives operators time to react, but also indirectly ensures the security and stability of circulating fluidized bed boiler data transmission.

[0108] In the inference engine module, the selected data verification mechanism includes a failure rejection mechanism and a failure continuation mechanism, specifically including:

[0109] Set up the data validation mechanism in the inference engine:

[0110] When the failure rejection mechanism is used, if any data fails a certain rule check, the current check is terminated, the failed check result is returned, and the error parameters, description information and prompts are enumerated.

[0111] When the fail-continue mechanism is used, if there is data that fails a certain verification, the verification process will continue until all data has been verified, and the verification rule prompts corresponding to all data that failed the verification will be returned.

[0112] In the knowledge base module, the preset verification rules include rule verification error prompt words, which are specifically used for:

[0113] (1) the inference engine verifies the target verification data according to the knowledge base rules;

[0114] (2) When the verification result is a failed verification result, the error enumeration information is output on the human-computer interaction interface according to the verification mechanism to obtain abnormal information of the failed verification result, wherein the abnormal information includes error parameters, description information and prompts.

[0115] Step (S104) CLIPS performs data verification on the data of different object systems and outputs the data verification results, which specifically includes the following steps:

[0116] (1) The control service platform obtains legal and correct data from the DCS system.

[0117] (2) Use PID controller for further calculation and processing.

[0118] (3) The data obtained through computational processing is verified using CLIPS.

[0119] (4) After successful verification, the data can be sent to the DCS system through the IOPC protocol. The DCS system sends the data to the field controller, and the actuator adjusts the parameters.

[0120] (5) After the verification fails, the control service platform cuts off the automatic control of the upper computer, does not send the data of the verification failure, and sends out an alarm signal to remind the engineer to check whether the software code logic is incorrect or the on-site actuator has an abnormality, etc. for debugging, repair and maintenance.

[0121] According to still another aspect of the embodiments of the present invention, a computer readable medium is provided.

[0122] A computer readable medium stores a computer program, which, when executed by a processor, implements a data verification method provided by an embodiment of the present invention.

[0123] After the verification result of step (S105) is passed, the industrial software calculates the data and transmits it to the DCS system after completing security authentication through the IOPC communication protocol for control adjustment.

[0124] Compared with the prior art, the present invention has the following advantages:

[0125] In the present invention, the target verification data to be verified is obtained in the DCS system, and the improved adaptive cyclic redundancy (IACRC) algorithm is used in the DCS system to perform preliminary data verification to determine whether data transmission is interrupted, delayed, and has transmission errors. If not, it indicates that the data transmission communication is normal, and the data is transmitted to the industrial software through the IOPC protocol. The industrial software obtains the data transmitted by the DCS system, and uses the PID controller to calculate through these data to obtain the data that needs to be adjusted and modified for each control system of the DCS system at the next moment, and performs data verification on the control service platform side to verify the accuracy, consistency, and legality of these data. The industrial software obtains the business attributes of the target verification data, and creates a CLIPS development framework based on the C language according to the business attributes. CLIPS performs data verification on the data of different object systems and outputs the data verification results. After the data verification is successful, it is sent to the DCS system through the improved IOPC protocol. By setting up the knowledge base module in the CLIPS development framework based on C language and setting the verification rules under the corresponding business attributes, the technical problems of difficult dynamic maintenance of verification rules and low verification performance can be solved. The dynamic update of verification rules at runtime and the dynamic expansion of verification rules can be realized. It can also reduce the development of the same verification code, improve the reusability of the verification rules of the verifier, and enhance the adaptability of the verification rules. There is no need to introduce additional verification modules, which increases resource utilization, reduces resource waste, improves execution efficiency, and reduces maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0126] In order to more intuitively illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0127] Figure 1 A flowchart of all steps of a communication data verification method provided in an embodiment of the present application.

[0128] Figure 2 A flowchart of the steps of using an improved adaptive cyclic redundancy algorithm to perform verification on a DCS system side provided in an embodiment of the present application.

[0129] Figure 3A CRC parameter model table provided for an embodiment of the present application.

[0130] Figure 4 A specific implementation flow chart of an IOPC communication protocol provided in an embodiment of the present application.

[0131] Figure 5 An input and output parameter table of an object attribute provided in an embodiment of the present application.

[0132] Figure 6 An overall block diagram of a CLIPS development framework based on C language provided in an embodiment of the present application.

[0133] Figure 7 A flowchart of the specific steps of forward reasoning of the CLIPS inference engine provided in the embodiment of the present application.

[0134] Figure 8 A flowchart of the specific implementation of the method for verifying communication data on the control service platform side provided in an embodiment of the present application.

[0135] Fig. 9 A setting diagram of using custom function blocks to connect data points in a program page in a DCS system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0136] In order to enable those in the field of industrial technology who also use distributed control systems to better understand the scheme of the present invention, the implementation scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts should fall within the scope of protection of the present invention.

[0137] In the process of data transmission and interaction between function providers and function callers, it is often necessary to verify the consistency, correctness, and legality of the transmitted data, such as data cannot be empty, data cannot exceed a certain length, data has a range limit, and data cannot remain unchanged for a long time. For data verification problems, verification logic can be directly written through program code to solve them, but the various data verification methods and rules are mostly universal, and the use of program code to solve them will undoubtedly produce a lot of repetitive operations. Although this method can realize the function of data verification, it still has many limitations. When the number of data types and the amount of data increases, program vulnerabilities will inevitably appear. Modifying the verification code of different data types will be very complicated, the maintenance cost is extremely high, and it is easy to cause logical confusion; by creating a CLIPS development framework based on C language and setting verification rules in the knowledge base module to realize communication data verification, it only needs to set different verification rules for different data types and different scenarios to achieve dynamic maintenance, dynamic adjustment and expansion.

[0138] The method embodiment takes a circulating fluidized bed boiler coal feeding control system as an example.

[0139] Figure 1 is a flow chart of the overall steps of the communication data verification method of the embodiment of the present application, such as Figure 1 As shown, the method mainly includes steps D101 to D104 on the distributed control system side and steps S101 to S105 on the control service platform side:

[0140] The steps on the distributed control system side are as follows:

[0141] Step D101: Acquire and identify data of each point in the DCS system coal feeding control system, including instantaneous coal feeding amount, instantaneous coal feeding rate, furnace bed material temperature, furnace bed material pressure, current steam temperature and current steam pressure. Fig. 9 shown.

[0142] Various types of data are stored in each data point in the DCS system. A connection with the point is established from the DCS system program page to obtain the corresponding data.

[0143] Step D102: Use the improved adaptive cyclic redundancy (IACRC) algorithm in the DCS system program page to establish multiple function block change parameter model parameters to verify the data.

[0144] For data with medium data volume and low requirements on error detection capability, CRC8 is selected as the parameter model.

[0145] For data with large data volume and high requirements for error detection capabilities, CRC16 is selected as the parameter model.

[0146] The data volume is particularly large and the error detection capability is required to be extremely high. CRC32 is selected as the parameter model.

[0147] Since the data volume of instantaneous coal feeding amount and instantaneous coal feeding rate is relatively small, the demand for error detection capability is not high. Therefore, the CRC-8 parameter model with medium data volume and general error detection capability is selected. The specific parameters of the parameter model refer to the CRC parameter model table, such as Figure 3 as shown.

[0148] Parameters such as furnace temperature, furnace pressure, current steam temperature and current steam pressure play a key role in the subsequent PID controller's calculation of the coal feeding adjustment amount of the coal feeding control system. Therefore, high requirements are placed on the accuracy of transmission. In addition, parameters such as temperature and pressure require the transmission of data from multiple measuring points, and the amount of data is huge. Therefore, a CRC-16 parameter model with high error detection capability and applicability to large amounts of data is selected.

[0149] The verification of the function block includes the following steps:

[0150] (D102-1) According to different error detection capability requirements of different data and the size of the data, a CRC parameter model is determined through a parameter model selection function block to match different requirements of different data;

[0151] (D102-2) The original data is shifted left by the number of bits of the corresponding parameter model;

[0152] (D102-3) Using an XOR operation to divide the expanded data, obtaining a remainder;

[0153] (D102-4) This remainder is attached to the original data as a CRC check code and then sent to the receiving end;

[0154] (D102-5) The receiving end uses the same generating polynomial to verify the received data.

[0155] Step D103: loop through and check function blocks of each data;

[0156] Establish circular check stream check data.

[0157] Step D104: Verify the function block point data to obtain verification results.

[0158] The flow chart of the steps of using the improved adaptive cyclic redundancy algorithm to perform verification on the DCS system side is as follows: Figure 2As shown, taking the instantaneous coal feeding amount data as an example, after the function block obtains the instantaneous coal feeding amount data, since the instantaneous coal feeding amount data is a small data volume data, the CRC-8 parameter model is selected. Multiple function blocks change the parameters to the parameters of the CRC-8 model. The function block performs CRC verification on the instantaneous coal feeding amount data and transmits it to the receiving end. The receiving end uses the same generating polynomial to verify the received data. If the output is not wrong, the remainder should be zero. After the verification passes, the point data is transmitted to the control service platform through the IOPC communication protocol; if the verification fails, it prompts that the communication transmission in the DCS system is interrupted or the communication delay is too high, and an alarm is issued. An engineer is sent to check the DCS system communication network and re-verify the data.

[0159] The data transmission via the IOPC communication protocol specifically includes the following steps: Figure 4 As shown:

[0160] The control service platform client authenticated by the OpenSSL certificate initiates a request to the local or remote OPC server authenticated by the OpenSSL certificate.

[0161] The local or remote OPC server processes the request and collects the instantaneous coal feed data verified by IACRC into the DCS system.

[0162] The instantaneous coal feed quantity data is encrypted using Basic128 or Basic256 encryption algorithm.

[0163] The instantaneous coal feed data is digitally signed using the RSA algorithm.

[0164] Sort packets.

[0165] Send data to the control service platform client.

[0166] The control service platform client verifies the signature and decrypts the data before using it.

[0167] The steps for data verification on the control service platform are as follows:

[0168] Step S101: Obtain target communication data: coal feed quantity adjustment amount of the coal feed control system.

[0169] The industrial software obtains relevant data of the coal feeding control system from the DCS system, including instantaneous coal feeding amount, instantaneous coal feeding rate, furnace bed material temperature, furnace bed material pressure, current steam temperature and current steam pressure and other real-time data. Due to changes in the steam pressure or steam temperature required by the user, the coal feeding amount needs to be adjusted to meet the user's needs. Based on these real-time data of the boiler and the PID control algorithm, the industrial software calculates the coal feeding adjustment amount of the coal feeding control system to reach the target value at the next moment, and performs data verification on the control service platform side to verify the accuracy, consistency and legality of the coal feeding adjustment amount data.

[0170] Step S102: creating an input and output parameter table of object attributes according to the business attributes of different object systems.

[0171] According to the coal feeding control system, establish the input and output parameter table of the system, such as Figure 5 shown.

[0172] The table name is the coal feeding control system input and output parameter table.

[0173] The input parameters are: current coal feeding amount, current coal feeding rate, current furnace temperature, current furnace pressure, number of branches, etc.

[0174] The output parameters are: coal feed adjustment amount, weight value of each branch, upper and lower limits of coal feed of each branch, allowed unchanged time and other data.

[0175] Step S103: Create a CLIPS development framework based on C language, such as Figure 6 shown.

[0176] Setting up the fact base module of CLIPS specifically includes: obtaining the business attributes of the coal feeding control system according to the input and output parameter table of the coal feeding control system, including the coal feeding quantity adjustment amount, the weight value of each branch, the upper and lower limits of each branch and other data.

[0177] Set up the knowledge base module of CLIPS, which includes the following contents:

[0178] (1) Preset data object.

[0179] (2) Preset data type.

[0180] (3) Preset rule name.

[0181] (4) Preset rule parameters.

[0182] (5) Preset rule triggering conditions.

[0183] (6) Preset rule verification error prompt words.

[0184] The basic rule module includes the following rule modules: threshold detection module, update module, overspeed detection module, etc.

[0185] To meet different requirements for different data, you can select multiple basic rule modules and customize other modules.

[0186] Taking the coal feeding control system as an example, the main data include: coal feeding quantity output value, coal feeding quantity weight value, single branch execution deviation, coal feeding quantity feedback value, etc.

[0187] There are two types of data: REAL and BOOL.

[0188] Take the coal feed output value threshold detection module as an example: specify the range of the coal feed output value, set the maximum and minimum values ​​allowed, and the trigger condition is that the data exceeds the maximum value or is lower than the minimum value.

[0189] Coal feed output value update module: determines whether the value is updated normally, stipulates the maximum time that the coal feed output value is allowed to remain unchanged for a long time, records the data value at the previous moment, compares the data value at the current moment with the data value at the previous moment, if they are the same, the time of no data change is accumulated, if they are not the same, the time of no data change is reset and cleared to zero. When the time of no data change accumulates to a certain value, it reaches the maximum allowable time and triggers the module.

[0190] Coal feed overspeed detection module: It determines whether the change range of the coal feed output value is too large and exceeds the optimal adjustment frequency of the boiler coal feed system.

[0191] According to the selected rule module, the data is verified. The trigger prompt statements are: the coal feeding amount value exceeds the upper (lower) limit; the coal feeding amount data has not changed for a long time, and the coal feeding amount adjustment range is too large.

[0192] Set up the CLIPS inference engine module. The forward reasoning steps of the CLIPS inference engine are as follows: Figure 7 As shown, specifically including:

[0193] Select the data verification mechanism before the data is officially verified:

[0194] Select a data validation mechanism:

[0195] The data verification mechanism includes a failure rejection mechanism and a failure continuation mechanism;

[0196] When the failure rejection mechanism is used, if any data validator fails the verification, the current verification is terminated, the failed verification result is returned, and the error parameters, description information and prompts are enumerated.

[0197] When the fail-continue mechanism is used, if a data validator fails the verification, the verification process will continue until all data validators have completed the verification, and the verification rule prompts corresponding to all data validators that failed the verification are returned.

[0198] Obtain the business attributes of the target communication data from the input and output parameter table of the object attributes.

[0199] After acquiring the communication data, the business attributes of the communication data are identified, such as whether it is a coal supply quantity output value, a coal supply quantity weight value, or a coal supply quantity feedback value.

[0200] According to the established knowledge base and the adjustment data calculated by the PID controller, the data are preprocessed to generate relevant facts in CLIPS format.

[0201] Select different rule modules according to different business attributes.

[0202] The RETE fast matching algorithm is used to periodically identify and match the facts in the fact base and the rules in the defined knowledge base, and compare them with the facts in the current working memory.

[0203] According to the rule modules pre-set by the knowledge base module, the rule modules of all data under the business attribute are obtained, which contain at least one rule module.

[0204] If the business attribute of the acquired communication data is the coal feed output value, all rule modules under the coal feed output value business attribute are further matched: threshold detection module, update module, overspeed detection module, etc. The rule module defines the preset verification rules for the specific verification target verification data.

[0205] After obtaining all the rule modules of the data and obtaining the data value, a data verification flow is formed, such as Figure 8 As shown, in the verification flow, it is determined whether the data meets the trigger conditions of each rule module. If the trigger conditions are met, the verification of the current rule module fails. If the trigger conditions of the current rule module are not met, it is determined whether there is a next rule module. If there is, the verification of the next rule module continues. If not, the verification of the next communication data is performed. If all rule modules do not meet the trigger conditions, the verification passes; otherwise, the verification fails.

[0206] Relying on the preset conflict elimination mechanism to ensure the normal progress of reasoning work and generate the final verification results;

[0207] The human-computer interaction page at the front end of the feedback system is visualized.

[0208] Complete the system's reasoning work and output the reasoning results.

[0209] The inference engine keeps repeating the process of rule matching and execution. Newly added facts may trigger more rules, thus continuing the inference process until no more rules can be activated.

[0210] Set up the human-computer interaction module, including:

[0211] The function of the human-computer interaction module is to enable operators to better interact with the expert system, mainly to achieve the following functional requirements:

[0212] Operators can not only see the output results on the human-computer interaction interface, but also modify and improve the CLIPS system.

[0213] A friendly human-computer interaction interface determines the interactivity and usability of the software design, reducing the time cost for general operators to learn and use the expert system.

[0214] A more complete human-computer interaction interface can make people more familiar with the circulating fluidized bed boiler control system. When data verification fails, the cause and location of the data verification failure can be clearly understood and corresponding expert suggestions can be given. This not only gives operators time to react, but also indirectly ensures the security and stability of circulating fluidized bed boiler data transmission.

[0215] Step S104: CLIPS performs data verification on the data of different object systems and outputs the data verification results.

[0216] After the verification is successful, it can be sent to the DCS system through the IOPC protocol. The DCS system sends data to the field controller, and the coal feeder actuator adjusts the coal feeding parameters. After the verification fails, the control service platform does not send the failed data and cuts off the automatic control of the host computer. The error enumeration information is output on the human-computer interaction interface according to the verification mechanism, and the abnormal information of the failed verification result is obtained. The abnormal information includes error parameters and description information and prompts. An alarm signal is issued to remind engineers to check whether the software code logic is wrong or the field actuator is abnormal, etc. for debugging, repair and maintenance.

[0217] Step S105: After the data verification is successful, it is sent to the DCS system through the improved IOPC protocol.

[0218] The industrial software obtains the data sent by the DCS system, and uses the PID controller to perform further calculations based on these data to obtain the data that needs to be adjusted and modified for each control system of the DCS system at the next moment, and performs data verification on the control service platform side to verify the accuracy, consistency, and legality of these data. The industrial software obtains the business attributes of the target verification data, and obtains the rule module in the CLIPS rule library according to the business attributes, where the rule module contains the verification rules preset in advance. According to the target verification data and its corresponding rule module, a communication data verification loop is constructed. The communication data verification loop can automatically call each rule module corresponding to the data business attribute, verify the target communication data according to the preset verification rules of the rule module in the data verification loop, and finally obtain the verification result. Only after the verification is successful can the data be sent to the field controller, and the actuator can adjust the parameters. After the verification fails, the control service platform cuts off the automatic control of the upper computer, does not send the data that failed the verification, and sends an alarm signal to remind engineers to check whether the software code logic is wrong or the field actuator is abnormal, etc. for debugging, repair and maintenance.

Claims

1. A boiler data transmission method based on a distributed control system platform, characterized in that: The following steps are involved: S1. Obtaining point data on boiler control in the distributed control system platform as boiler data; S2. Using an improved adaptive cyclic redundancy algorithm in the distributed control system platform to calculate the boiler data to obtain a verification result. If the verification is successful, the boiler data is transmitted to the control service platform; S3. The control service platform analyzes the boiler data, outputs optimized boiler data, and transmits the optimized boiler data back to the distributed control system platform. The distributed control system platform uses the optimized boiler data to adjust the parameters of the boiler.

2. The boiler data transmission method based on a distributed control system platform according to claim 1 is characterized in that: In step S1, the point data about boiler coal feeding control are instantaneous coal feeding amount, instantaneous coal feeding rate, furnace bed material temperature, furnace bed material pressure, current steam temperature and current steam pressure.

3. The boiler data transmission method based on a distributed control system platform according to claim 1 is characterized in that: In step S2, an improved adaptive cyclic redundancy algorithm is used in the distributed control system platform to calculate the boiler data to obtain a verification result, which specifically includes: S2.

1. Adaptively select a parameter model of a cyclic redundancy algorithm according to the amount of boiler data; S2.2, according to the parameters of the parameter model of the cyclic redundancy algorithm, the boiler data is shifted left to obtain the expanded data; S2.3, use XOR operation to divide the expanded data to obtain the remainder; S2.4, the remainder obtained in step S2.3 is added to the boiler data as a check code of the cyclic redundancy algorithm and sent to the receiving end; S2.

5. The receiving end verifies the received data using the generating polynomial to obtain a verification result.

4. The boiler data transmission method based on a distributed control system platform according to claim 3 is characterized in that: In step S2.1, a parameter model of a cyclic redundancy algorithm is adaptively selected according to the amount of boiler data, specifically including: S2.1.1) When the data measurement points of the boiler data contain more than five measurement points, it is determined to be large data volume data, and the parameter model of the cyclic redundancy algorithm selects the CRC-16 parameter model; S2.1.2) When the data measurement points of the boiler data contain less than four measurement points, it is determined to be small data volume data, and the parameter model of the cyclic redundancy algorithm selects the CRC-8 parameter model.

5. The boiler data transmission method based on a distributed control system platform according to claim 3 is characterized in that: In step S2.2, the boiler data is shifted left by 8 bits.

6. The boiler data transmission method based on a distributed control system platform according to claim 1 is characterized in that: In step S3, the control service platform analyzes the boiler data and outputs optimized boiler data, which specifically includes: S3.

1. The control service platform analyzes the boiler data of coal feeding control through the PID controller and outputs a coal feeding adjustment data; S3.

2. Generate facts in the expert system CLIPS format for the coal quantity adjustment data and boiler data and store them in the fact database; S3.

3. The facts in the expert system CLIPS format and the rules in the knowledge base of the expert system CLIPS are periodically identified and matched through the RETE forward rule fast matching algorithm to determine whether the data is available. If available, the adjusted data is used as the optimized boiler data.

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