Fault detection method and device, storage medium and electronic device
A detection method and detection device technology, applied in the computer field, can solve problems such as lack of integrity in fault detection, and achieve the effect of improving efficiency and diversity
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Embodiment 1
[0017] The method embodiment provided in Embodiment 1 of the present application may be executed in a terminal, a computer terminal, or a similar computing device. Take running on the terminal as an example, figure 1 It is a hardware structural block diagram of a terminal of a fault detection method in an embodiment of the present invention. Such as figure 1 As shown, the terminal 10 may include one or more ( figure 1 Only one is shown in the figure) processor 102 (processor 102 may include but not limited to processing devices such as microprocessor MCU or programmable logic device FPGA) and memory 104 for storing data. Optionally, the above-mentioned terminal can also be A transmission device 106 for communication functions and an input and output device 108 are included. Those of ordinary skill in the art can understand that, figure 1 The shown structure is only for illustration, and does not limit the structure of the above-mentioned terminal. For example, terminal 10...
Embodiment 2
[0046] In this embodiment, a fault detection device is also provided, which is used to implement the above embodiments and preferred implementation modes, and what has been described will not be repeated. As used below, the term "module" may be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
[0047] image 3 is a structural block diagram of a fault detection device according to an embodiment of the present invention, such as image 3 As shown, the device packs:
[0048] (1) acquisition module 32, used to acquire the first sample data for training the regression model, wherein the duration of the first sample data is a preset duration;
[0049] (2) processing module 34, for using the last second of the preset time length as the label of ...
Embodiment 3
[0057] An embodiment of the present invention also provides a storage medium, in which a computer program is stored, wherein the computer program is set to execute the steps in any one of the above method embodiments when running.
[0058] Optionally, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for performing the following steps:
[0059] S1. Obtain first sample data for training the regression model, where the duration of the first sample data is a preset duration;
[0060] S2, using the last second of the preset time as the label of the regression model, and extracting from the first sample data before the label within the preset time for training the regression model;
[0061] S3. Output the data to be verified to the trained regression model, and determine that the data to be verified is fault data when the mean square error output by the trained regression model is greater than a preset threshold.
[0062] Optional...
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