Optical Sign Failure Warning Method

Abstract

The present application proposes a method for fault early warning of a light sign. Among them, the method includes: collecting the measured point data of multiple systems in a power plant and transmitting the measured point data to the light sign; the light sign identifies the source system of the measured point data according to the string information in the measured point data; in response to the transmission frequency of the measured point data being within the first target range, the light sign performs secondary early warning on the source system; in response to the transmission frequency of the measured point data being within the second target range, the light sign performs primary early warning on the source system. The present application collects the measured point data of multiple systems in a power plant and identifies the source system. According to the transmission frequency of the measured point signal, corresponding early warning is carried out on the target system, which can effectively monitor the transmission situation of the measured point data, give early warning in time for the poor transmission situation of the measured point data, remind the operation personnel to discover and handle it, and improve the quality of measured point data collection.

Description

Technical Field

[0001] This application relates to the technical field of intelligent monitoring in thermal power plants, and particularly to a method and device for fault warning of annunciator lights, and a method for generating a mathematical model of abnormal operation of a power plant system. Background Art

[0002] The annunciator light is an important component in the power plant monitoring system. The corresponding light on the central signal screen illuminates the annunciator light to monitor the operating status of each system device, timely warn of fault information, and remind the operating personnel to discover and handle it. In the power plant monitoring system, due to the switching of the computer system, it may cause poor transmission of the measuring point data of the power plant system, affect the quality of the measuring point data, and is not conducive to power plant monitoring and subsequent processing of the measuring point data. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] To this end, a first aspect of this application proposes a method for fault warning of annunciator lights to warn of the transmission status of the measuring point data. The method includes:

[0005] Collect the measuring point data of multiple systems in the power plant and transmit the measuring point data to the annunciator light;

[0006] The annunciator light identifies the source system of the measuring point data according to the string information in the measuring point data;

[0007] In response to the transmission frequency of the measuring point data being within the first target range, perform a secondary warning on the source system through the annunciator light;

[0008] In response to the transmission frequency of the measuring point data being within the second target range, perform a primary warning on the source system through the annunciator light.

[0009] In some embodiments of this application, the step of collecting the measuring point data of multiple systems in the power plant and transmitting the measuring point data to the annunciator light includes: collecting the measuring point data of multiple systems in the power plant to the DCS control cabinet; the DCS control cabinet transmits the measuring point data to the power plant big data platform database through OPC communication technology and stores the measuring point data; the power plant big data platform database transmits the measuring point data to the annunciator light.

[0010] In some embodiments of this application, the multiple systems include: turbine system, boiler system, electrical system, chemical system, and thermal control system.

[0011] In some embodiments of this application, the first target range is greater than 1 second and less than or equal to 10 seconds, and the second target range is greater than 10 seconds.

[0012] In some embodiments of the present application, the method further includes: storing the data transmission warning information of the measurement point data in the power plant big data platform database.

[0013] A second aspect of the present application provides a method for generating a mathematical model for abnormal operation of a power plant system, including:

[0014] Screening the measurement point data in the power plant big data platform database to obtain first target measurement point data, and putting the first target measurement point data into the data expert library; wherein, the first target measurement point data is the measurement point data without data transmission warning information in the power plant big data platform database;

[0015] Collecting second target measurement point data of the target system in the data expert library; wherein, the second target measurement point data of the target system is the normal operation measurement point data in the measurement point data of the target system;

[0016] Using the second target measurement point data of the target system to establish a first abnormal operation mathematical model of the target system;

[0017] Training the first abnormal operation mathematical model of the target system with the measurement point data of the target system in the data expert library to obtain a second abnormal operation mathematical model of the target system.

[0018] In some embodiments of the present application, the establishing the first abnormal operation mathematical model of the target system by using the second target measurement point data of the target system includes: using the second target measurement point data of the target system, and establishing the first abnormal operation mathematical model of the target system by any one of the random forest algorithm, the fully connected neural network algorithm, and the genetic algorithm.

[0019] In some embodiments of the present application, the target system is any one of a steam turbine system, a boiler system, an electrical system, a chemical system, and a thermal control system.

[0020] In some embodiments of the present application, the method further includes: verifying the second abnormal operation mathematical model of the target system by using the historical trend chart of the operation of each system in the power plant.

[0021] A third aspect of the present application provides a light annunciator fault warning device, including:

[0022] A collection module, configured to collect the measurement point data of multiple systems in the power plant and transmit the measurement point data to the light annunciator;

[0023] An identification module, configured to identify the source system of the measurement point data according to the string information in the measurement point data;

[0024] The first warning module, in response to the transmission frequency of the measured point data being within the first target range, is used to give a secondary warning to the source system through a pilot light board;

[0025] The second warning module, in response to the transmission frequency of the measured point data being within the second target range, is used to give a primary warning to the source system through the pilot light board.

[0026] According to the pilot light board fault warning method of the embodiment of the present application, the measured point data of multiple systems in a power plant is collected, and the source system is identified. Corresponding warnings are given to the target system according to the transmission frequency of the measured point signal, which can effectively monitor the transmission of the measured point data, give timely warnings for the poor transmission of the measured point data, remind the operators to discover and handle it, and improve the quality of the measured point data collection.

[0027] Some of the additional aspects and advantages of the present application will be given in the following description, some will become obvious from the following description, or will be understood through the practice of the present application. Description of the Drawings

[0028] The above-mentioned and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0029] Figure 1 is a schematic flowchart of a pilot light board fault warning method provided by an embodiment of the present application;

[0030] Figure 2 is a schematic flowchart of a method for generating a mathematical model of abnormal operation of a power plant system provided by an embodiment of the present application;

[0031] Figure 3 is a schematic diagram of a pilot light board fault warning device provided by an embodiment of the present application. Detailed Embodiments

[0032] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application, but should not be construed as limiting the present application.

[0033] The present application proposes a pilot light board fault warning method and device, and a method for generating a mathematical model of abnormal operation of a power plant system. Specifically, the pilot light board fault warning method and the method for generating a mathematical model of abnormal operation of a power plant system of the embodiments of the present application will be described below with reference to the drawings.

[0034] Figure 1The flowchart of a method for warning of the failure of a light signboard provided by an embodiment of the present application. As Figure 1 shown, the method for warning of the failure of a light signboard provided by an embodiment of the present application may include the following steps:

[0035] Step 101: Collect the measured point data of multiple systems in the power plant and transmit the measured point data to the light signboard.

[0036] It should be noted that there are multiple systems in the power plant, such as the steam turbine system, the boiler system, the electrical system, the chemical system, and the thermal control system. The status of each system can be monitored through the light signboard. As a possible implementation method, the measured point data of multiple systems in the power plant can be collected into the DCS control cabinet. The DCS control cabinet transmits the measured point data to the database of the power plant big data platform through the OPC communication technology and stores the measured point data. The database of the power plant big data platform transmits the measured point data to the light signboard.

[0037] Step 102: The light signboard identifies the source system of the measured point data according to the string information in the measured point data.

[0038] Step 103: In response to the transmission frequency of the measured point data being within the first target range, perform a secondary warning on the source system through the light signboard.

[0039] As a possible implementation method, the first target range can be set to be greater than 1 second and less than or equal to 10 seconds. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, perform a secondary warning on the source system through the light signboard.

[0040] Step 104: In response to the transmission frequency of the measured point data being within the second target range, perform a primary warning on the source system through the light signboard.

[0041] As a possible implementation method, the second target range can be set to be greater than 10 seconds. If the transmission frequency of the measured point data is greater than 10 seconds, perform a primary warning on the source system through the light signboard.

[0042] As an example, assume that the source system of the measured point data is the steam turbine system. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, the light signboard can display the text information of "Abnormal transmission of the measured point signal of the steam turbine system" and display the light signboard display color corresponding to the secondary warning. If the transmission frequency of the measured point data is greater than 10 seconds, the light signboard can display the text information of "Abnormal transmission of the measured point signal of the steam turbine system" and display the light signboard display color corresponding to the primary warning, so as to remind the operator of the abnormal transmission of the measured point signal in the steam turbine system and check and handle it in time.

[0043] As an example, assume that the source system of the measured point data is the boiler system. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, the text information of "Abnormal transmission of measured point signal in boiler system" can be displayed through the annunciator, and the annunciator display color corresponding to the secondary warning is also displayed; if the transmission frequency of the measured point data is greater than 10 seconds, the text information of "Abnormal transmission of measured point signal in boiler system" can be displayed through the annunciator, and the annunciator display color corresponding to the primary warning is also displayed, so as to remind the operator of the abnormal transmission of the measured point signal in the boiler system and check and handle it in time.

[0044] As an example, assume that the source system of the measured point data is the electrical system. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, the text information of "Abnormal transmission of measured point signal in electrical system" can be displayed through the annunciator, and the annunciator display color corresponding to the secondary warning is also displayed; if the transmission frequency of the measured point data is greater than 10 seconds, the text information of "Abnormal transmission of measured point signal in electrical system" can be displayed through the annunciator, and the annunciator display color corresponding to the primary warning is also displayed, so as to remind the operator of the abnormal transmission of the measured point signal in the electrical system and check and handle it in time.

[0045] As an example, assume that the source system of the measured point data is the chemical system. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, the text information of "Abnormal transmission of measured point signal in chemical system" can be displayed through the annunciator, and the annunciator display color corresponding to the secondary warning is also displayed; if the transmission frequency of the measured point data is greater than 10 seconds, the text information of "Abnormal transmission of measured point signal in chemical system" can be displayed through the annunciator, and the annunciator display color corresponding to the primary warning is also displayed, so as to remind the operator of the abnormal transmission of the measured point signal in the chemical system and check and handle it in time.

[0046] As an example, assume that the source system of the measured point data is the thermal control system. If the transmission frequency of the measured point data is within the range of greater than 1 second and less than or equal to 10 seconds, the text information of "Abnormal transmission of measured point signal in thermal control system" can be displayed through the annunciator, and the annunciator display color corresponding to the secondary warning is also displayed; if the transmission frequency of the measured point data is greater than 10 seconds, the text information of "Abnormal transmission of measured point signal in thermal control system" can be displayed through the annunciator, and the annunciator display color corresponding to the primary warning is also displayed, so as to remind the operator of the abnormal transmission of the measured point signal in the thermal control system and check and handle it in time.

[0047] It should be noted that when the transmission frequency of the measured point data is less than or equal to 1 second, it is regarded as normal transmission of the measured point data and no warning is required.

[0048] In some embodiments of the present application, in order to collect measurement point data more comprehensively, the data transmission warning information of the measurement point data (including primary warning information and secondary warning information) may also be stored in the power plant big data platform database.

[0049] According to the annunciator fault warning method of the embodiments of the present application, the measurement point data of multiple systems in the power plant are collected and the source systems are identified. Corresponding warnings are given to the target systems according to the transmission frequency of the measurement point signals, which can effectively monitor the transmission of the measurement point data, give timely warnings for the poor transmission of the measurement point data, remind the operators to discover and handle it, and improve the quality of the measurement point data collection.

[0050] Figure 2 It is a schematic flow chart of a method for generating a mathematical model of abnormal operation of a power plant system provided by an embodiment of the present application. As Figure 2 shown, the method for generating a mathematical model of abnormal operation of a power plant system provided by an embodiment of the present application may include the following steps:

[0051] Step 201: Screen the measurement point data in the power plant big data platform database to obtain the first target measurement point data, and put the first target measurement point data into the data expert library. Among them, the first target measurement point data is the measurement point data without data transmission warning information in the power plant big data platform database.

[0052] It should be noted that the data transmission warning information includes the primary warning information and secondary warning information in the above embodiments of the annunciator fault warning method. Therefore, the first target measurement point data is the measurement point data with normal transmission frequency, such as the measurement point data without warning with a transmission frequency less than or equal to 1 second.

[0053] Step 202: Collect the second target measurement point data of the target system in the data expert library. Among them, the second target measurement point data of the target system is the normal operation measurement point data in the target system measurement point data.

[0054] It should be noted that the target system may be any one of the turbine system, boiler system, electrical system, chemical system, and thermal control system in the power plant.

[0055] Among them, the measurement point data in the data expert library can be divided into three types: normal operation measurement point data, fault operation measurement point data, and non-operation measurement point data. Therefore, the measurement point data in the data expert library can be screened, the measurement point data of the target system can be selected, and the normal operation measurement point data in the target system measurement point data can be determined as the second target measurement point data of the target system. For example, if the target system is the chemical system, the measurement point data of the chemical system is screened in the data expert library, and the normal operation measurement point data in the chemical system is determined as the second target measurement point data of the target system.

[0056] As a possible implementation, it is possible to collect the normal operation measurement point data of some measurement points of the target system in the data expert database within one year as the second target measurement point data of the target system.

[0057] Step 203: Establish the first operation anomaly mathematical model of the target system by using the second target measurement point data of the target system.

[0058] Optionally, in some embodiments of the present application, the first operation anomaly mathematical model of the target system can be established by any one of the random forest algorithm, the fully connected neural network algorithm, and the genetic algorithm.

[0059] Step 204: Train the first operation anomaly mathematical model of the target system by using the measurement point data of the target system in the data expert database to obtain the second operation anomaly mathematical model of the target system.

[0060] Through the second operation anomaly mathematical model of the target system, the operation state of the target system can be judged based on the measurement point information of the target system, and the second operation anomaly mathematical model of the target system can be implemented in the power plant annunciator panel. If the second operation anomaly mathematical model of the target system judges that the target system is currently in an abnormal operation state, an early warning can be given through the power plant annunciator panel.

[0061] Optionally, in some embodiments of the present application, after obtaining the target operation anomaly mathematical model of the target system, the model effect of the second operation anomaly mathematical model of the target system can also be verified by using the historical trend chart of the operation of each system in the power plant.

[0062] According to the method for generating the operation anomaly mathematical model of the power plant system in the embodiments of the present application, the first operation anomaly mathematical model of the target system is established by using the normal operation measurement point data of the target system in the power plant big data platform database. The first operation anomaly mathematical model of the target system is trained by using the measurement point data of the target system in the data expert database to obtain the second operation anomaly mathematical model of the target system. The second operation anomaly mathematical model of the target system can judge the operation state of the target system according to the measurement point data of the target system, and combine with the power plant annunciator panel to give an early warning of the abnormal operation state of the target system, so as to effectively monitor the operation state of the power plant system.

[0063] Figure 3 It is a schematic diagram of an annunciator panel fault early warning device provided by an embodiment of the present application. As Figure 3 shown, the annunciator panel fault early warning device provided by the embodiment of the present application includes: a collection module 301, an identification module 302, a first early warning module 303, and a second early warning module 304.

[0064] Among them, the collection module 301 is used to collect the measurement point data of multiple systems in the power plant and transmit the measurement point data to the annunciator panel.

[0065] An identification module 302, configured to identify the source system of the measurement point data according to the string information in the measurement point data.

[0066] A first early warning module 303, in response to the transmission frequency of the measurement point data being within a first target range, is configured to perform a secondary early warning on the source system through a light annunciator.

[0067] A second early warning module 304, in response to the transmission frequency of the measurement point data being within a second target range, is configured to perform a primary early warning on the source system through a light annunciator.

[0068] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0069] According to the light annunciator fault early warning device of the embodiments of the present application, the measurement point data of multiple systems in a power plant is collected, and the source system is identified. Corresponding early warnings are performed on the target system according to the transmission frequency of the measurement point signals, which can effectively monitor the transmission situation of the measurement point data, give timely early warnings for the poor transmission situation of the measurement point data, remind the operation personnel to discover and handle it, and improve the quality of measurement point data collection.

[0070] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0071] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0072] Any process or method description, whether in a flowchart or otherwise described herein, can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed. This should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0073] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for early warning of optical character panel failures, characterized in that, It includes the following steps: Collect the measured point data of multiple systems in the power plant and transmit the measured point data to the annunciator panel; The annunciator panel identifies the source system of the measured point data according to the string information in the measured point data; In response to the transmission frequency of the measured point data being within the first target range, the annunciator panel gives a secondary warning to the source system; In response to the transmission frequency of the measured point data being within the second target range, the annunciator panel gives a primary warning to the source system; The first target range is greater than 1 second and less than or equal to 10 seconds, and the second target range is greater than 10 seconds; Screen the measured point data in the power plant big data platform database to obtain the first target measured point data, and put the first target measured point data into the data expert library; wherein, the first target measured point data is the measured point data without data transmission warning information in the power plant big data platform database, and the warning information includes: primary warning information and secondary warning information; Collect the second target measured point data of the target system in the data expert library; wherein, the second target measured point data of the target system is the normal operation measured point data in the measured point data of the target system; Use the second target measured point data of the target system to establish the first operation anomaly mathematical model of the target system; Use the measured point data of the target system in the data expert library to train the first operation anomaly mathematical model of the target system to obtain the second operation anomaly mathematical model of the target system; Based on the measured point information of the target system, judge the operation state of the target system through the second operation anomaly mathematical model of the target system, and implement the second operation anomaly mathematical model of the target system into the annunciator panel. If the second operation anomaly mathematical model of the target system judges that the target system is currently in an abnormal operation state, give a warning through the annunciator panel.

2. The method according to claim 1, characterized in that, The step of collecting the measured point data of multiple systems in the power plant and transmitting the measured point data to the annunciator panel includes: Collect the measured point data of multiple systems in the power plant to the DCS control cabinet; The DCS control cabinet transmits the measured point data to the power plant big data platform database through OPC communication technology and stores the measured point data; The power plant big data platform database transmits the measured point data to the annunciator panel.

3. The method according to claim 1, characterized in that, The multiple systems include: turbine system, boiler system, electrical system, chemical system, thermal control system.

4. The method according to claim 1, characterized in that, The method further includes: storing the data transmission warning information of the measured point data in the power plant big data platform database.

5. The method according to claim 1, characterized in that, The step of using the second target measured point data of the target system to establish the first operation anomaly mathematical model of the target system includes: Use the second target measured point data of the target system and establish the first operation anomaly mathematical model of the target system through any one of the random forest algorithm, fully connected neural network algorithm, and genetic algorithm.

6. The method according to claim 1, characterized in that, The target system is any one of the turbine system, boiler system, electrical system, chemical system, and thermal control system.

7. The method according to claim 1, characterized in that, The method further includes: Verify the second operation anomaly mathematical model of the target system by using the historical trend charts of the operations of each system in the power plant.

8. An optical character panel failure early warning device, characterized in that, It includes: An acquisition module, configured to acquire the measuring point data of multiple systems in the power plant and transmit the measuring point data to the annunciator panel. An identification module, configured to identify the source system of the measuring point data according to the string information in the measuring point data. A first early warning module, in response to the transmission frequency of the measuring point data being within a first target range, configured to give a secondary early warning to the source system through the annunciator panel, where the first target range is greater than 1 second and less than or equal to 10 seconds. A second early warning module, in response to the transmission frequency of the measuring point data being within a second target range, configured to give a primary early warning to the source system through the annunciator panel, where the second target range is greater than 10 seconds. An operation anomaly mathematical model training module, configured to screen the measuring point data in the database of the power plant big data platform to obtain first target measuring point data and put the first target measuring point data into the data expert database; where the first target measuring point data is the measuring point data without data transmission early warning information in the database of the power plant big data platform, and the early warning information includes: primary early warning information and secondary early warning information. Acquire second target measuring point data of the target system in the data expert database; where the second target measuring point data of the target system is the normal operation measuring point data in the measuring point data of the target system. Establish a first operation anomaly mathematical model of the target system by using the second target measuring point data of the target system. Train the first operation anomaly mathematical model of the target system by using the measuring point data of the target system in the data expert database to obtain a second operation anomaly mathematical model of the target system. Judge the operation state of the target system based on the measuring point information of the target system through the second operation anomaly mathematical model of the target system, and implement the second operation anomaly mathematical model of the target system into the annunciator panel. If the second operation anomaly mathematical model of the target system judges that the target system is currently in an abnormal operation state, give an early warning through the annunciator panel.

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