Self-healing treatment system and method for condensed water unit in thermal power plant

Abstract

The invention relates to a self-healing processing system and method for a condensation water unit in a thermal power plant, and the system comprises a DCS distributed control module and an intelligent calculation module. The DCS distributed control module is used for acquiring real-time operation data of a condensation water unit in a thermal power plant and transmitting the real-time operation data to the intelligent calculation module; the intelligent calculation module is used for obtaining a fault diagnosis result of the condensation water unit through a trained fault early warning model according to the real-time operation data and transmitting the fault diagnosis result to the DCS distributed control module; and the DCS distributed control module is used for carrying out self-healing treatment on the condensation water unit according to the fault diagnosis result. Through the application, the abnormal working condition of the condensation water unit is detected, and the repair operation can be automatically carried out after the fault is determined, so that the influence of the fault on production is reduced to the greatest extent, and the problem of how to reduce the influence of the fault of the condensation water unit on the production progress of a thermal power unit is solved.

Description

Technical Field

[0001] The present application relates to the field of industrial production technology, and in particular to a self-healing treatment system and method for a condensate unit in a thermal power plant. Background Art

[0002] In modern industrial production processes, stable operation of equipment is crucial to ensuring production efficiency and product quality. However, as the equipment is used for a longer time, various failures and abnormal conditions are difficult to avoid.

[0003] Traditional equipment maintenance methods mainly rely on regular inspections and passive maintenance, which often make it difficult to detect potential faults in a timely manner, leading to sudden equipment failures, affecting production progress, and even causing safety accidents. Therefore, how to effectively monitor equipment status and provide fault warnings has become the focus of the industry.

[0004] Currently, no effective solution has been proposed in the relevant technology on how to reduce the impact of condensate unit failure on the production progress of thermal power units. Summary of the invention

[0005] The embodiments of the present application provide a self-healing processing system and method for a condensate unit in a thermal power plant, so as to at least solve the problem in the related art of how to reduce the impact of condensate unit failure on the production progress of the thermal power unit.

[0006] In a first aspect, an embodiment of the present application provides a self-healing treatment system for a condensate unit in a thermal power plant, the system comprising a DCS distributed control module and an intelligent computing module;

[0007] The DCS distributed control module is used to obtain real-time operating data of the condensate units in the thermal power plant and transmit the real-time operating data to the intelligent computing module;

[0008] The intelligent computing module is used to obtain the fault diagnosis result of the condensate unit according to the real-time operation data through the trained fault warning model, and transmit the fault diagnosis result to the DCS distributed control module;

[0009] The DCS distributed control module is used to perform self-healing processing on the condensate unit according to the fault diagnosis result.

[0010] In some of the embodiments, the DCS distributed control module is used to perform self-healing processing on the condensate water unit according to the fault diagnosis result; if the fault diagnosis result is that the condensate water unit has a condensate pump variable frequency pump output failure, a one-key self-healing processing program is started.

[0011] In some of the embodiments, after the DCS distributed control module starts the one-key self-healing processing procedure:

[0012] The standby pump of the condensate unit is switched to the power frequency mode, and the related valves of the standby pump are adjusted to the automatic mode;

[0013] The main regulating valve of the deaerator of the condensate unit is switched to the three-impulse mode, and the condensate recirculation regulating valve automatically adjusts the valve opening based on the load change;

[0014] The frequency converter of the condensate unit stops running and switches to normal water replenishment mode.

[0015] In some of the embodiments, the condensate recirculation regulating valve of the condensate unit automatically adjusts the valve opening based on load changes, wherein the load change range is 660MW to 280MW, and the valve opening range is 75% to 100%.

[0016] In some of the embodiments, the intelligent computing module is used to obtain the predicted condensate flow rate of the condensate unit according to the real-time operation data through a trained fault warning model. If the deviation between the predicted condensate flow rate and the actual condensate flow rate exceeds the alarm threshold, and the outlet main pipe pressure of the condensate unit exceeds the lower limit, and the outlet pressure of the first condensate pump or the outlet pressure of the second condensate pump drops by more than a preset amplitude, the fault diagnosis result is that a condensate pump variable frequency pump output failure occurs in the condensate unit.

[0017] In some of the embodiments, the DCS distributed control module is also used to obtain historical operation data of condensate units in the thermal power plant and store the historical operation data.

[0018] In some of the embodiments, the intelligent computing module is used to mine and analyze the historical operating data according to the key operating parameters of the condensate unit to obtain training sample data for training the fault warning model.

[0019] In some of the embodiments, the intelligent computing module is used to mine the key operating data corresponding to the outlet main pipe pressure of the condensate unit, the feedback of the condensate minimum flow recirculation valve, the outlet pressure of the first condensate pump, and the outlet pressure of the second condensate pump from the historical operating data as input data in the training sample data for training the fault warning model;

[0020] The intelligent computing module is used to mine key operating data corresponding to the condensate flow rate of the condensate unit from the historical operating data as label data in the training sample data for training the fault warning model.

[0021] In some of the embodiments, the intelligent computing module is used to train the fault warning model according to the input data and label data in the training sample data to obtain a trained fault warning model.

[0022] In a second aspect, an embodiment of the present application provides a self-healing treatment method for a condensate unit in a thermal power plant, the method being executed based on the system described in any one of the first aspects above, and the method comprising:

[0023] Acquire real-time operation data of condensate units in a thermal power plant, and transmit the real-time operation data to an intelligent computing module;

[0024] According to the real-time operation data, a fault diagnosis result of the condensate unit is obtained through a trained fault warning model, and the fault diagnosis result is transmitted to the DCS distributed control module;

[0025] According to the fault diagnosis result, the condensate unit is self-healed.

[0026] Compared with the related art, the embodiment of the present application provides a self-healing processing system and method for a condensate unit in a thermal power plant, wherein the system includes a DCS distributed control module and an intelligent computing module; the DCS distributed control module is used to obtain real-time operating data of the condensate unit in the thermal power plant, and transmit the real-time operating data to the intelligent computing module; the intelligent computing module is used to obtain a fault diagnosis result of the condensate unit according to the real-time operating data and a trained fault warning model, and transmit the fault diagnosis result to the DCS distributed control module; the DCS distributed control module is used to perform self-healing processing on the condensate unit according to the fault diagnosis result. Through this system, the detection of abnormal operating conditions of the condensate unit is realized, and the repair operation can be automatically performed after determining that a fault has occurred, thereby minimizing the impact of the fault on production, and solving the problem of how to reduce the impact of the condensate unit fault on the production progress of the thermal power unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 It is a structural block diagram of a condensate unit self-healing treatment system in a thermal power plant according to an embodiment of the present application;

[0029] Figure 2 It is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0031] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0032] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0033] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0034] The embodiment of the present application provides a self-healing treatment system for a condensate unit in a thermal power plant, Figure 1 is a structural block diagram of a condensate unit self-healing treatment system in a thermal power plant according to an embodiment of the present application, such as Figure 1 As shown, the system includes a DCS distributed control module and an intelligent computing module;

[0035] DCS distributed control module is used to obtain the real-time operation data of the condensate units in the thermal power plant and transmit the real-time operation data to the intelligent computing module;

[0036] It should be noted that the DCS distributed control module is the original control module in the thermal power plant, and the intelligent computing module is an external module. The modbus485 communication protocol is used to achieve real-time communication between the original DCS and the intelligent computing module.

[0037] Intelligent computing module, which is used to obtain the fault diagnosis results of the condensate unit based on the real-time operation data and the trained fault warning model, and transmit the fault diagnosis results to the DCS distributed control module;

[0038] The DCS distributed control module is used to perform self-healing processing on the condensate unit according to the fault diagnosis results.

[0039] Through the DCS distributed control module and the intelligent computing module in the embodiments of the present application, the detection of abnormal conditions of the condensate unit is realized, and after a fault is determined, the repair operation can be automatically performed, thereby minimizing the impact of the fault on production and solving the problem of how to reduce the impact of the condensate unit fault on the production progress of the thermal power unit.

[0040] In some of the embodiments, the intelligent computing module is configured to obtain the predicted condensate flow rate of the condensate unit through a trained fault warning model based on real-time operation data. If the deviation between the predicted condensate flow rate and the actual condensate flow rate exceeds the alarm threshold, and the outlet header pressure of the condensate unit exceeds the lower limit value, and the outlet pressure of the first condensate pump or the second condensate pump shows a decrease exceeding the preset amplitude, the fault diagnosis result is that the condensate unit has a fault in the output of the condensate variable-frequency pump.

[0041] In some of the embodiments, if the fault diagnosis result is that the condensate unit has a fault in the output of the condensate variable-frequency pump, the DCS distributed control module starts a one-key self-healing processing program.

[0042] In some of the embodiments, after the DCS distributed control module starts the one-key self-healing processing program:

[0043] The standby pump of the condensate unit is switched to the industrial frequency mode, and the relevant valves of the standby pump are adjusted to the automatic mode;

[0044] It should be noted that for ①, the standby pump is started in the industrial frequency mode, the main regulating valve for deaerator water supply is automatic, the auxiliary regulating valve for deaerator water supply is automatic, the inverter adjustment is switched to manual, and the inverter frequency output is reduced to the rated value (such as 30Hz).

[0045] ② The main regulating valve for deaerator water supply of the condensate unit is switched to the three-element mode, and the condensate recycle regulating valve automatically adjusts the valve opening based on the load change;

[0046] It should be noted that for ②, the main regulating valve for deaerator water supply is switched to the three-element mode, the condensate recycle regulating valve is put into automatic, the opening of the condensate recycle regulating valve is overridden, and the valve opening (75%-100%) has a linear relationship with the load change (660MW - 280MW), that is, 660MW - 280MW corresponds to the valve opening of 75%-100%.

[0047] ③ The inverter of the condensate unit stops running and is switched to the normal water replenishment mode.

[0048] It should be noted that for ③, the input of the inverter is stopped, the normal water replenishment regulating valve for condensate is automatic, and the water level control set value is set to 700mm. The self-healing processing program for the abnormal conditions of the condensate system is completed.

[0049] In some of the embodiments, the DCS distributed control module is also used to obtain historical operation data of condensate units in the thermal power plant and store the historical operation data.

[0050] The intelligent computing module is used to mine and analyze historical operating data based on the key operating parameters of the condensate unit to obtain training sample data for training the fault warning model.

[0051] It should be noted that the historical operation data of the thermal power plant is mined and analyzed based on parameters such as load and main steam pressure. The historical operation data is first divided into several small data packets according to the operating conditions, and then the data in each operating condition is removed after the abnormal values ​​are removed to extract the central value (calculate the average value). Finally, a database is established to record the historical operating best values ​​under each operating condition.

[0052] In some of the embodiments, the intelligent computing module is used to mine the key operation data corresponding to the outlet main pipe pressure of the condensate unit, the feedback of the condensate minimum flow recirculation valve, the outlet pressure of the first condensate pump, and the outlet pressure of the second condensate pump from the historical operation data as input data in the training sample data for training the fault warning model;

[0053] It should be noted that the physical characteristics of the equipment are mainly considered when selecting the relevant parameters that affect the condensate flow rate. Before selecting the parameters, it is necessary to reasonably analyze the physical process of each parameter affecting the condensate flow rate during operation, and it needs to be consistent with the actual unit operating conditions. Finally, the outlet main pipe pressure of the condensate unit, the feedback of the condensate minimum flow recirculation valve, the outlet pressure of the first condensate pump, and the outlet pressure of the second condensate pump were selected as the key parameters affecting the condensate flow rate.

[0054] It should be further explained that the key operating data corresponding to the outlet main pipe pressure of the above-mentioned condensate unit, the condensate minimum flow recirculation valve feedback, the first condensate pump outlet pressure and the second condensate pump outlet pressure are the unit operating data under steady-state conditions where the load fluctuation range of the thermal power unit is less than 5% for at least 10 minutes and the main steam pressure fluctuation is less than 3%.

[0055] In some of the embodiments, the intelligent computing module is used to mine key operating data corresponding to the condensate flow rate of the condensate unit from historical operating data as label data in training sample data for training the fault warning model.

[0056] It should be noted that the historical operating optimal value corresponding to the condensate flow rate of the condensate unit is mined from the historical operating data and used as the input (label data) of the neural network early warning model. Compared with directly using the actual value of the system, this method can effectively reduce the impact of field noise on the data and make the output of the neural network early warning model more reliable.

[0057] In some of the embodiments, the intelligent computing module is used to train the fault warning model according to the input data and label data in the training sample data to obtain a trained fault warning model.

[0058] It should be noted that the fault warning model is pre-trained by inputting a large amount of historical data into the neural network model to obtain a fault warning model that can fully characterize the condensate unit, which can more accurately predict the condensate flow rate of the condensate unit, and the model is encapsulated into the intelligent computing module.

[0059] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0060] The present application provides a self-healing treatment method for a condensate unit in a thermal power plant, the method comprising the following steps:

[0061] Step 1: obtain the real-time operation data of the condensate unit in the thermal power plant, and transmit the real-time operation data to the intelligent computing module;

[0062] Step 2: According to the real-time operation data, the fault diagnosis result of the condensate unit is obtained through the trained fault warning model, and the fault diagnosis result is transmitted to the DCS distributed control module;

[0063] Step three: perform self-healing treatment on the condensate unit according to the fault diagnosis result.

[0064] Through the above steps in the embodiment of the present application, the detection of abnormal operating conditions of the condensate unit is realized, and the repair operation can be automatically performed after the fault is determined to have occurred, thereby minimizing the impact of the fault on production and solving the problem of how to reduce the impact of the condensate unit failure on the production progress of the thermal power unit.

[0065] It should be noted that the steps shown in the above process can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the above process, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0066] This embodiment further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0067] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0068] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0069] In addition, in combination with the self-healing treatment method of the condensate unit in the thermal power plant in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by the processor, any one of the self-healing treatment methods of the condensate unit in the thermal power plant in the above embodiment is implemented.

[0070] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a self-healing treatment method for a condensate unit in a thermal power plant is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball, or touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0071] In one embodiment, Figure 2 is a schematic diagram of the internal structure of an electronic device according to an embodiment of the present application, such as Figure 2 As shown, an electronic device is provided, which may be a server, and its internal structure diagram may be as shown in Figure 2 As shown. The electronic device includes a processor, a network interface, an internal memory and a non-volatile memory connected through an internal bus, wherein the non-volatile memory stores an operating system, a computer program and a database. The processor is used to provide computing and control capabilities, the network interface is used to communicate with an external terminal through a network connection, the internal memory is used to provide an environment for the operation of the operating system and the computer program, the computer program is executed by the processor to implement a self-healing treatment method for a condensate unit in a thermal power plant, and the database is used to store data.

[0072] Those skilled in the art will understand that Figure 2The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0073] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0074] Those skilled in the art should understand that the technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0075] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A self-healing treatment system for a condensate unit in a thermal power plant, characterized in that: The system includes a DCS distributed control module and an intelligent computing module; The DCS distributed control module is used to obtain real-time operating data of the condensate units in the thermal power plant and transmit the real-time operating data to the intelligent computing module; The intelligent computing module is used to obtain the fault diagnosis result of the condensate unit according to the real-time operation data through the trained fault warning model, and transmit the fault diagnosis result to the DCS distributed control module; The DCS distributed control module is used to perform self-healing processing on the condensate unit according to the fault diagnosis result.

2. The system according to claim 1, characterized in that The DCS distributed control module is used to perform self-healing processing on the condensate water unit according to the fault diagnosis result; if the fault diagnosis result is that the condensate water unit has a condensate pump variable frequency pump output failure, a one-key self-healing processing program is started.

3. The system according to claim 2, characterized in that After the DCS distributed control module starts the one-key self-healing processing program: The standby pump of the condensate unit is switched to the power frequency mode, and the related valves of the standby pump are adjusted to the automatic mode; The main regulating valve of the deaerator of the condensate unit is switched to the three-impulse mode, and the condensate recirculation regulating valve automatically adjusts the valve opening based on the load change; The frequency converter of the condensate unit stops running and switches to normal water replenishment mode.

4. The system according to claim 3, characterized in that The condensate recirculation regulating valve of the condensate unit automatically adjusts the valve opening based on load changes, wherein the load change range is 660MW to 280MW, and the valve opening range is 75% to 100%.

5. The system according to claim 1, characterized in that The intelligent computing module is used to obtain the predicted condensate flow rate of the condensate unit according to the real-time operation data through a trained fault warning model. If the deviation between the predicted condensate flow rate and the actual condensate flow rate exceeds the alarm threshold, and the outlet main pipe pressure of the condensate unit exceeds the lower limit, and the outlet pressure of the first condensate pump or the outlet pressure of the second condensate pump drops by more than a preset amplitude, the fault diagnosis result is that a condensate pump variable frequency pump output failure occurs in the condensate unit.

6. The system according to claim 1, characterized in that The DCS distributed control module is also used to obtain historical operation data of condensate units in the thermal power plant and store the historical operation data.

7. The system according to claim 6, characterized in that The intelligent computing module is used to mine and analyze the historical operating data according to the key operating parameters of the condensate unit to obtain training sample data for training the fault warning model.

8. The system according to claim 7, characterized in that The intelligent computing module is used to mine the key operating data corresponding to the outlet main pipe pressure of the condensate unit, the feedback of the condensate minimum flow recirculation valve, the outlet pressure of the first condensate pump and the outlet pressure of the second condensate pump from the historical operating data as input data in the training sample data for training the fault warning model; The intelligent computing module is used to mine key operating data corresponding to the condensate flow rate of the condensate unit from the historical operating data as label data in the training sample data for training the fault warning model.

9. The system according to claim 8, characterized in that The intelligent computing module is used to train the fault warning model according to the input data and label data in the training sample data to obtain a trained fault warning model.

10. A self-healing treatment method for a condensate unit in a thermal power plant, characterized in that: The method is performed based on the system according to any one of claims 1 to 9, and the method includes: Acquire real-time operation data of condensate units in a thermal power plant, and transmit the real-time operation data to an intelligent computing module; According to the real-time operation data, a fault diagnosis result of the condensate unit is obtained through a trained fault warning model, and the fault diagnosis result is transmitted to the DCS distributed control module; According to the fault diagnosis result, the condensate unit is self-healed.

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