Temperature early warning system and method for rod control and rod position system cabinet

Abstract

The invention provides a temperature early warning system and method for a rod control and rod position system cabinet. The system comprises a sensor, a temperature prediction module, a dynamic threshold module and a judgment module. The temperature prediction module is internally provided with a rod-control rod-position system cabinet temperature prediction model, and is used for obtaining temperature and wind speed data from the sensor, and carrying out the real-time cabinet temperature prediction through the rod-control rod-position system cabinet temperature prediction model. And a POT model is arranged in the dynamic threshold module, and the dynamic threshold module is used for acquiring temperature and wind speed data and generating a real-time threshold by using the POT model. And the judgment module is used for comparing and judging the predicted temperature value and the alarm threshold temperature value and giving an alarm. According to the method and the device, the rod-control rod-position system cabinet temperature prediction model, the POT model algorithm and the cabinet temperature real-time monitoring technology are combined, so that the problem that the accuracy of abnormity judgment performed by manually setting a fixed alarm threshold value and the predicted temperature is very low when the rod-control rod-position system cabinet temperature early warning is performed in the prior art is solved.

Description

Technical Field

[0001] The present application belongs to the technical field of power plant maintenance and operation, and specifically relates to a temperature early warning system and method for a cabinet of a rod control rod position system. Background Art

[0002] The rod control and position system (RGL) includes the rod control system (RCS) and the rod position system. The rod control and position system is one of the core systems of the nuclear power plant, responsible for completing the reactor reactivity control function and measuring the position of the control rod in the core. The weak links in the reliability of the rod control and position system are mainly concentrated in the MDP board in the cabinet. According to the maintenance of the boards in Fuqing and other power plants, it is basically clear that the current sensor and the thyristor are the key components that restrict the normal operation of the MDP board, and the main failure factor is high temperature aging. At present, the cabinet temperature monitoring relies on regular inspections and manual recording, which cannot fully reflect the temperature status and change process of the rod control and position system cabinet (referred to as the RGL cabinet), nor can it warn in advance when the temperature of the rod control and position system cabinet is abnormal. Therefore, it is necessary to build a real-time temperature monitoring and early warning platform for the rod control and position system cabinet to improve the temperature abnormality early warning capability and improve system reliability.

[0003] In view of the characteristics of the cabinet structure and the temperature distribution inside the cabinet, the method of temperature monitoring through the combination of various thermal imaging devices and temperature sensors has been widely used in the field of real-time monitoring of cabinet temperature. Document CN210242989U discloses a temperature monitoring device for a substation cabinet. By evenly arranging multiple thermal imaging devices on the inner wall pillars of the cabinet, it can detect the inside of the cabinet from multiple angles and in a covering manner, and can timely alarm by setting an external alarm to prevent the alarm of self-ignition due to excessive temperature; Document CN109405982A discloses a cabinet temperature monitoring device, method and system. By installing temperature sensors at intervals along the length direction of the connecting parts, the temperature sensors are moved on the guide rails by using a driving device to collect real-time temperature, so that the server can more accurately draw the temperature field, thereby reflecting the temperature distribution on the air inlet side of the cabinet.

[0004] However, in the actual operation of the rod control and rod position system cabinet, the probability of abnormal temperature data is very small. During long-term operation, the data samples accumulate too much and the abnormal data is too little, which makes it difficult to locate the abnormality. In this context, the accuracy of abnormal judgment by manually setting fixed alarm thresholds and predicted temperatures is very low. Summary of the invention

[0005] In view of this, the present application is committed to providing a temperature warning system and method for a rod control and rod position system cabinet. By combining the temperature prediction model of the rod control and rod position system cabinet, the POT model algorithm and the real-time monitoring technology of the cabinet temperature, the problem of low accuracy of abnormal judgment by manually setting fixed alarm thresholds and predicted temperatures when using temperature warning for the rod control and rod position system cabinet is solved.

[0006] The first aspect of the present application provides a temperature warning system for a rod control and rod position system cabinet, which includes a sensor, a temperature prediction module, a dynamic threshold module and a judgment module. The sensor is connected to the temperature prediction module through a first serial port, and is connected to the dynamic threshold module through a second serial port. The temperature prediction module and the dynamic threshold module are connected to the judgment module through a third serial port. The sensor includes two types of sensors: temperature and wind speed. The temperature prediction module is provided with a temperature prediction model for the rod control and rod position system cabinet. The temperature prediction module is used to obtain temperature and wind speed data from the sensor, use the temperature prediction model for the rod control and rod position system cabinet to perform real-time cabinet temperature prediction, and output the predicted temperature data to the judgment module. The dynamic threshold module is provided with a POT model. The dynamic threshold module is used to obtain temperature and wind speed data from the sensor, use the POT model to generate real-time thresholds, and output the alarm threshold temperature value to the judgment module. The judgment module is used to compare and judge the predicted temperature value with the alarm threshold temperature value and issue an alarm.

[0007] In a specific implementation of the present application, the rod control and rod position system cabinet temperature prediction model is a feature fusion network model established based on the characteristics of characteristic factors related to the rod control and rod position system cabinet temperature.

[0008] In a specific embodiment of the present application, the cabinet temperature prediction model of the rod control rod position system is composed of three network layers, namely a recurrent network layer, a full convolution layer and a feature fusion layer.

[0009] The second aspect of the present application provides a temperature warning method for a rod control and rod position system cabinet, and the temperature warning method for a rod control and rod position system cabinet includes: using a temperature prediction module in a temperature warning system for a rod control and rod position system cabinet of the first aspect of the present application to obtain a data signal from a sensor, and inputting the data signal as an input module into a temperature prediction model of the rod control and rod position system cabinet to perform real-time cabinet temperature prediction, and after obtaining the predicted temperature data, output the predicted temperature data to the judgment module; using a dynamic threshold module in a temperature warning system for a rod control and rod position system cabinet of the first aspect of the present application to obtain a data signal from a sensor, using a POT model to generate a real-time threshold, and outputting an alarm threshold temperature value to the judgment module; using a judgment module in a temperature warning system for a rod control and rod position system cabinet of the first aspect of the present application to compare and judge the real-time predicted temperature value with the alarm threshold temperature value and issue an alarm.

[0010] In a specific embodiment of the present application, a temperature prediction module in a temperature early warning system of a rod control and rod position system cabinet of the first aspect of the present application is used to obtain a data signal from a sensor, and the data signal is input as an input module into a temperature prediction model of a rod control and rod position system cabinet to perform real-time cabinet temperature prediction, and after obtaining the predicted temperature data, the predicted temperature data is output to the decision module, including:

[0011] Using a temperature prediction module in a temperature early warning system of a rod control rod position system cabinet of the first aspect of the present application to obtain a data signal of a sensor in real time, and calibrate the data signal before the current moment as historical data, and calibrate the data signal at the current moment as real-time data;

[0012] Preprocessing the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data;

[0013] The pre-processed historical data is sent to the cabinet temperature prediction model of the rod control and rod position system as input for model training, and the cabinet temperature prediction model of the rod control and rod position system is updated regularly to obtain the data fitting network model of the cabinet temperature of the rod control and rod position system;

[0014] The preprocessed real-time data is used as the input of the data fitting network model of the cabinet temperature of the rod control rod position system, and then the predicted temperature data is output.

[0015] In a specific embodiment of the present application, a dynamic threshold module in a temperature warning system of a rod control rod position system cabinet of the first aspect of the present application is used to obtain a data signal from a sensor, generate a real-time threshold using a POT model, and output an alarm threshold temperature value to a decision module, including:

[0016] Using a dynamic threshold module in a temperature warning system of a rod control rod position system cabinet of the first aspect of the present application to obtain a data signal of a sensor in real time, and calibrate the data signal before the current moment as historical data, and calibrate the data signal at the current moment as real-time data;

[0017] Preprocessing the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data;

[0018] The preprocessed historical data is traversed to determine the maximum voltage value in the historical rod control rod position system cabinet temperature data, and the preprocessed real-time data is used as the input of the POT model. The POT model is used to calculate the threshold temperature value according to the maximum temperature value, and the alarm threshold temperature value is output to the judgment module.

[0019] In a specific embodiment of the present application, a judgment module in a temperature early warning system of a rod control and rod position system cabinet of the first aspect of the present application is used to compare and judge the real-time predicted temperature value with the alarm threshold temperature value and issue an alarm, including:

[0020] In a temperature early warning system of a rod control rod position system cabinet according to the first aspect of the present application, a judgment module reads predicted temperature data output by a temperature prediction module and an alarm threshold temperature value output by a dynamic threshold module, and checks whether the predicted temperature data and the alarm threshold temperature value are valid. If they are valid, subsequent steps are performed; otherwise, the data are invalid and this task ends.

[0021] The predicted temperature value is compared with the threshold value. When the predicted temperature value is greater than the threshold value, the temperature abnormality is confirmed and the alarm is triggered.

[0022] The beneficial effect of the technical solution of the present application is that: on the basis of the existing real-time cabinet temperature monitoring device, a dynamic alarm threshold temperature value output by the POT model is added as a reference point, and the predicted temperature data generated by the cabinet temperature prediction model of the rod control rod position system is used as a basis to determine whether the cabinet has a temperature abnormality, and can generate early warning information before the abnormal temperature causes substantial damage to the MDP card. At the same time, through the dynamic alarm threshold temperature value, the number of false alarms is effectively reduced and the credibility of the alarm is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Shown is a structural schematic diagram of a temperature warning system for a rod control and rod position system cabinet provided in one embodiment of the present application.

[0024] Figure 2 Shown is a specific structural schematic diagram of a cabinet temperature prediction model for a rod control rod position system provided in one embodiment of the present application.

[0025] Figure 3 The figure is a flow chart of a temperature warning method for a cabinet of a rod control rod position system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] At least one embodiment of the present application provides a temperature warning system for a cabinet of a rod control and rod position system. Figure 1The cabinet temperature early warning system includes a sensor 101, a temperature prediction module 102, a dynamic threshold module 103 and a judgment module 104. The sensor 101 is connected to the temperature prediction module 102 through the first serial port, and is connected to the dynamic threshold module 103 through the second serial port. The temperature prediction module 102 and the dynamic threshold module 103 are connected to the judgment module 104 through the third serial port. The sensor 101 includes two types of sensors: temperature and wind speed. The temperature prediction module 102 is provided with a cabinet temperature prediction model of a rod control and rod position system. The temperature prediction module 102 is used to obtain temperature and wind speed data from the sensor 101, use the cabinet temperature prediction model of the rod control and rod position system to predict the cabinet temperature in real time, and output the predicted temperature data to the judgment module 104. The dynamic threshold module 103 is provided with a POT model. The dynamic threshold module 103 is used to obtain temperature and wind speed data from the sensor 101, use the POT model to generate a real-time threshold, and output the alarm threshold temperature value to the judgment module 104. The decision module 104 is used to compare the real-time predicted temperature value with the alarm threshold temperature value and issue an alarm.

[0028] It should be noted that the rod control and rod position system cabinet may include any suitable combination of a logic cabinet, a power cabinet, a processing cabinet, a measurement cabinet and a test cabinet.

[0029] According to the technical solution provided in the embodiment of the present application, on the basis of the existing real-time cabinet temperature monitoring device, a dynamic alarm threshold temperature value output by the POT model is added as a reference point, and the predicted temperature data generated by the cabinet temperature prediction model of the rod control rod position system is used as a basis to determine whether a temperature abnormality has occurred in the cabinet, and to generate early warning information before the abnormal temperature causes substantial damage to the MDP card. At the same time, through the dynamic alarm threshold temperature value, the number of false alarms can be effectively reduced and the credibility of the alarm can be improved.

[0030] In at least one embodiment of the present application, the rod control and rod position system cabinet temperature prediction model is a feature fusion network model established based on the characteristics of characteristic factors related to the rod control and rod position system cabinet temperature.

[0031] In at least one embodiment of the present application, the cabinet temperature prediction model of the rod control rod position system is composed of three network layers, namely, a recurrent network layer, a full convolution layer, and a feature fusion layer. In this way, a feature fusion network structure based on PLSTM-FCN is established.

[0032] For example, the specific structure of the cabinet temperature prediction model of the rod control rod position system can be as follows: Figure 2 The three network layers have the following characteristics.

[0033] The recurrent network layer consists of LSTM (Long Short Term Memory Network) neurons and linear layers. It is the part of PLSTM-FCN responsible for learning the long-term dependency characteristics of time series data. The linear layer is also called the fully connected layer, where each neuron in the linear layer is connected to all neurons in the previous network layer, and the linear combination of the neurons in the previous layer is used to achieve linear transformation.

[0034] The Fully Convolutional Networks (FCN) layer is a functional module of the PLSTM-FCN network that extracts features from sliced ​​time series data. It consists of a convolutional layer, batch normalization, and an activation function. The Dropout layer stops training some neurons in the connected network layer during the network model training process, that is, temporarily hides them, and then hides other neurons during the next training. The Dropout layer can reduce overfitting during the model training process by generalizing the model;

[0035] The fusion network layer (Concatenate) is used to connect the data features extracted from the LSTM network layer and the FCN network layer. By splicing multiple features, the effect of data expansion is achieved, thereby reducing overfitting during the training process of the deep network model.

[0036] POT model: define the maximum value as x, the threshold as y, and the threshold y satisfies: y=c1*ln(c2*x+1)+b; wherein b is the lower limit of the preset value, c1 and c2 are preset fitting logarithmic function parameters, and the preset fitting logarithmic function parameters are calculated through N reference points on the fitting logarithmic function curve.

[0037] At least one embodiment of the present application further provides a temperature warning method for a cabinet of a rod control and rod position system, and the temperature warning method for a cabinet of a rod control and rod position system is implemented by using the cabinet temperature warning system provided by the above embodiment of the present application. Figure 3 The temperature warning method of the rod control rod position system cabinet includes the following steps.

[0038] S1: Using the temperature prediction module 102 in the temperature warning system of the rod control and rod position system cabinet provided in the embodiment of the present application to obtain a data signal from the sensor 101, and input the data signal as an input module into the temperature prediction model of the rod control and rod position system cabinet to perform real-time cabinet temperature prediction, and then output the predicted temperature data to the decision module 104.

[0039] S2: Using a temperature warning system of a rod control rod position system cabinet in an embodiment of the present application, the dynamic threshold module 103 obtains a data signal from the sensor 101, generates a real-time threshold using a POT model, and outputs an alarm threshold temperature value to the judgment module 104.

[0040] Specifically, after the dynamic threshold module 103 obtains the data signal from the sensor 101, it pre-processes the data and obtains the current alarm threshold temperature value according to the historical data. The alarm threshold temperature value may also be an abnormal temperature threshold.

[0041] S3: Using the judgment module 104 in the temperature warning system of the cabinet of the rod control and rod position system of the embodiment of the present application, the real-time predicted temperature value is compared with the alarm threshold temperature value to make a judgment and issue an alarm.

[0042] Specifically, the decision module 104 receives the predicted temperature data output from the temperature prediction module 102 and the alarm threshold temperature value output from the dynamic threshold module 103 and then performs alarm analysis.

[0043] According to the technical solution provided by the embodiment of the present application, based on the existing real-time monitoring device for cabinet temperature, a cabinet temperature early warning implementation method is proposed by combining the real-time prediction data of the cabinet temperature prediction model of the rod control rod position system and the dynamic alarm threshold temperature value generated by the POT model. By combining the cabinet temperature prediction model of the rod control rod position system, the POT model algorithm and the real-time monitoring technology of the cabinet temperature, that is, while monitoring the cabinet temperature in real time, a deep learning network can be used to predict the cabinet temperature in real time to achieve the early warning condition, and the dynamic threshold value can be set by applying the POT model to improve the accuracy of the alarm.

[0044] In at least one embodiment of the present application, S1.1 to S1.4 are a specific implementation of the above S1.

[0045] S1.1: Using the temperature prediction module 102 in the temperature warning system of the rod control rod position system cabinet of the embodiment of the present application, the data signal of the sensor 101 is acquired in real time, and the data signal before the current moment is calibrated as historical data, and the data signal at the current moment is calibrated as real-time data.

[0046] Specifically, the temperature prediction module 102 obtains temperature and wind speed data through sensors installed in the rod control and rod position system cabinet, stores the data in real time in the data module, and marks the previous data as historical data.

[0047] S1.2: Preprocess the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data.

[0048] Specifically, the temperature prediction module 102 sends the real-time data and historical data to the data processing module for data preprocessing.

[0049] S1.3: The preprocessed historical data is sent to the cabinet temperature prediction model of the rod control and rod position system as input for model training, and the cabinet temperature prediction model of the rod control and rod position system is updated regularly to obtain the data fitting network model of the cabinet temperature of the rod control and rod position system.

[0050] Specifically, the preprocessed historical data can be used as the input of the rod control and rod position system cabinet temperature prediction model to train the rod control and rod position system cabinet temperature prediction model and obtain the data fitting network model of the rod control and rod position system cabinet temperature.

[0051] It should be noted that the cabinet temperature prediction model of the rod control rod position system can be temporarily constructed or can be pre-constructed and directly called when used. The embodiment of the present application does not make specific limitations on this.

[0052] S1.4: The preprocessed real-time data is used as the input of the data fitting network model of the cabinet temperature of the rod control rod position system and the predicted temperature data is output.

[0053] In at least one embodiment of the present application, S2.1 to S2.3 are a specific implementation of the above S2.

[0054] S2.1: Utilize the dynamic threshold module 103 in the temperature warning system of the rod control rod position system cabinet of an embodiment of the present application to obtain the data signal of the sensor 101 in real time, and calibrate the data signal before the current moment as historical data, and calibrate the data signal at the current moment as real-time data.

[0055] Specifically, the temperature prediction module 102 obtains temperature and wind speed data through sensors installed in the rod control and rod position system cabinet, stores the data in real time in the data module, and marks the previous data as historical data.

[0056] S2.2: Preprocess the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data.

[0057] S2.3: Traverse the preprocessed historical data to determine the maximum voltage value in the historical rod control position system cabinet temperature data, and use the preprocessed real-time data as the input of the POT model. Use the POT model to calculate the threshold temperature value based on the maximum temperature value, and output the alarm threshold temperature value to the judgment module 104.

[0058] In at least one embodiment of the present application, S3.1 and S3.2 are a specific implementation of the above S3.

[0059] S3.1: In the temperature warning system of a rod control rod position system cabinet using an embodiment of the present application, the judgment module 104 reads the predicted temperature data output by the temperature prediction module 102 and the alarm threshold temperature value output by the dynamic threshold module 103, and checks whether the predicted temperature data and the alarm threshold temperature value are valid. If they are valid, proceed to subsequent steps; otherwise, the data is invalid and this task ends.

[0060] Specifically, the decision module 104 may determine whether the acquired predicted temperature data and the alarm threshold temperature value are complete and synchronized. If the above conditions are not met, the decision module 104 ends.

[0061] S3.2: The predicted temperature value is compared with the threshold value. When the predicted temperature value is greater than the threshold value, the temperature abnormality is confirmed and an alarm is triggered.

[0062] For example, if the predicted temperature data T1 is greater than the alarm threshold data T2, a temperature abnormality alarm is issued and the module operation is terminated; if the predicted temperature data T1 is less than the alarm threshold data T2, the module is terminated directly.

[0063] It should be noted that the combination of the various technical features in the embodiments of the present application is not limited to the combination described in the embodiments of the present application or the combination described in the specific embodiments, and all technical features described in the present application can be freely combined or combined in any way unless there is a contradiction between them.

[0064] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A temperature warning system for a rod control and rod position system cabinet, characterized in that: Including sensors, temperature prediction modules, dynamic threshold modules and judgment modules, The sensors are connected to the temperature prediction module through the first serial port and to the dynamic threshold module through the second serial port. The temperature prediction module and the dynamic threshold module are connected to the judgment module through the third serial port. The sensors include two types of sensors: temperature and wind speed. The temperature prediction module is provided with a temperature prediction model for the cabinet of the rod control and rod position system. The temperature prediction module is used to obtain temperature and wind speed data from the sensor, use the temperature prediction model for the cabinet of the rod control and rod position system to perform real-time cabinet temperature prediction, and output the predicted temperature data to the decision module; The dynamic threshold module is provided with a POT model, which is used to obtain temperature and wind speed data from the sensor, generate real-time thresholds using the POT model, and output alarm threshold temperature values ​​to the decision module; The judgment module is used to compare the predicted temperature value with the alarm threshold temperature value and issue an alarm.

2. A temperature warning system for a rod control and rod position system cabinet according to claim 1, characterized in that: The cabinet temperature prediction model of the rod control and rod position system is a feature fusion network model established based on the characteristics of characteristic factors related to the cabinet temperature of the rod control and rod position system.

3. A temperature warning system for a rod control and rod position system cabinet according to claim 1 or 2, characterized in that: The cabinet temperature prediction model of the rod control rod position system consists of three network layers, namely the recurrent network layer, the full convolution layer and the feature fusion layer.

4. A temperature warning method for a rod control rod position system cabinet, characterized in that: include: Utilize the temperature prediction module in the temperature early warning system of the cabinet of the rod control and rod position system according to any one of claims 1 to 3 to obtain a data signal from the sensor, and input the data signal as an input module into the temperature prediction model of the cabinet of the rod control and rod position system to perform real-time cabinet temperature prediction, and output the predicted temperature data to the decision module after obtaining the predicted temperature data; The dynamic threshold module in the temperature warning system of the rod control rod position system cabinet obtains data signals from the sensor, generates real-time thresholds using the POT model, and outputs the alarm threshold temperature value to the judgment module; The judgment module in the temperature warning system of the rod control rod position system cabinet is used to compare the real-time predicted temperature value with the alarm threshold temperature value and issue an alarm.

5. A temperature warning method for a rod control and rod position system cabinet according to claim 4, characterized in that: The temperature prediction module in the temperature early warning system of the cabinet of the rod control and rod position system according to any one of claims 1 to 3 is used to obtain a data signal from a sensor, and the data signal is input as an input module into the temperature prediction model of the cabinet of the rod control and rod position system to perform real-time cabinet temperature prediction, and the predicted temperature data is obtained and then output to the judgment module, including: Using a temperature prediction module in a temperature warning system of a rod control rod position system cabinet according to any one of claims 1 to 3 to obtain data signals of sensors in real time, and calibrate data signals before the current moment as historical data, and calibrate data signals at the current moment as real-time data; Preprocessing the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data; The pre-processed historical data is sent to the cabinet temperature prediction model of the rod control and rod position system as input for model training, and the cabinet temperature prediction model of the rod control and rod position system is updated regularly to obtain the data fitting network model of the cabinet temperature of the rod control and rod position system; The preprocessed real-time data is used as the input of the data fitting network model of the cabinet temperature of the rod control rod position system, and then the predicted temperature data is output.

6. A temperature warning method for a rod control and rod position system cabinet according to claim 4, characterized in that: The dynamic threshold module in the temperature warning system of the rod control rod position system cabinet obtains data signals from the sensor, generates real-time thresholds using the POT model, and outputs the alarm threshold temperature value to the judgment module, including: The dynamic threshold module in the temperature warning system of the rod control rod position system cabinet is used to obtain the data signal of the sensor in real time, and the data signal before the current moment is calibrated as historical data, and the data signal at the current moment is calibrated as real-time data; Preprocessing the historical data and the real-time data to obtain preprocessed historical data and preprocessed real-time data; The preprocessed historical data is traversed to determine the maximum voltage value in the historical rod control rod position system cabinet temperature data, and the preprocessed real-time data is used as the input of the POT model. The POT model is used to calculate the threshold temperature value according to the maximum temperature value, and the alarm threshold temperature value is output to the judgment module.

7. A temperature warning method for a rod control and rod position system cabinet according to claim 4, characterized in that: The judgment module in the temperature early warning system of the rod control rod position system cabinet is used to compare the real-time predicted temperature value with the alarm threshold temperature value and issue an alarm, including: Use the judgment module in the temperature early warning system of the rod control rod position system cabinet to read the predicted temperature data output by the temperature prediction module and the alarm threshold temperature value output by the dynamic threshold module, and check whether the predicted temperature data and the alarm threshold temperature value are valid. If they are valid, proceed to the subsequent steps, otherwise the data is invalid and this task ends; The predicted temperature value is compared with the threshold value. When the predicted temperature value is greater than the threshold value, the temperature abnormality is confirmed and the alarm is triggered.

Images