Temperature prediction model training method and device, prediction method and device, equipment and medium
A prediction model and training method technology, which is applied in the fields of devices, equipment and media, prediction methods, and temperature prediction model training methods, can solve problems such as insufficient prediction accuracy and difficult data analysis, and achieve improved prediction accuracy and data analysis. The effect of high difficulty and improved accuracy
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Embodiment 1
[0079] Figure 1a It is a flow chart of a method for training a temperature prediction model provided in Embodiment 1 of the present invention. The temperature prediction model can be applied to different components, especially in the scenario of temperature prediction of traction motors. The method can be executed by a temperature prediction model training device, and the device can be realized by means of software and / or hardware. see Figure 1a , the method of this embodiment specifically includes:
[0080] 110. Collect temperature data of the electronic device, and electrical characteristic data of the electronic device at different temperatures.
[0081] Wherein, for an electronic device, various types of sensors may be used to collect electrical characteristic data and temperature data corresponding to the electronic device. For example, for the train traction system, the sensor coverage is very comprehensive. The current and voltage data of each branch in the system a...
Embodiment 2
[0106] figure 2 It is a flow chart of a method for predicting the temperature of an electronic device provided by Embodiment 2 of the present invention. This method can be applied to the application scenario of temperature prediction of electronic devices, and typically can be applied to the prediction process of traction converter chassis and motor temperature. The method can be executed by an electronic device temperature predicting device, and the device can be realized by means of software and / or hardware. Such as figure 2 As shown, the method includes:
[0107] 210. Use the collected temperature data, electrical characteristic data and electrical characteristic data within the second time period of the electronic device as basic data.
[0108] Among them, the electrical characteristic data is the electrical signal characteristic data representing the operating state of the electronic device, for example, network current, U-phase current instantaneous value, W-phase c...
Embodiment 3
[0121] image 3 A structural block diagram of a training device for a temperature prediction model provided in Embodiment 3 of the present invention, such as image 3 As shown, the device includes: data collection module 310, time segmentation module 320, feature matrix formation module 330, training sample determination module 340 and model training module 350; wherein,
[0122] The data collection module 310 is configured to collect temperature data of the electronic device, and electrical characteristic data of the electronic device at different temperatures;
[0123] The time segmentation module 320 is configured to segment the temperature data and corresponding electrical characteristic data according to a preset time interval;
[0124] The feature matrix forming module 330 is configured to perform data extraction according to the preset window sliding step size for the temperature data and electrical feature data of each time period after segmentation, and use all the e...
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