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 according to an embodiment of the present invention. like figure 1 As shown, the terminal 10 may include one or more ( figure 1 Only one is shown in the above) processor 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data, optionally, the above-mentioned terminal may also Transmission devices 106 and input and output devices 108 are included for communication functions. Those of ordinary skill in the art can understand that, figure 1 The shown structure is only for illustration, which does not limit the structure of the above-mentioned terminal. ...
Embodiment 2
[0046] In this embodiment, a fault detection device is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementations, and the descriptions that have been described will not be repeated. As used below, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is 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 package:
[0048] (1) an acquisition module 32, configured 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) The processing module 34 is used for taking...
Embodiment 3
[0057] An embodiment of the present invention further provides a storage medium, where a computer program is stored in the storage medium, wherein the computer program is configured to execute the steps in any 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 executing the following steps:
[0059] S1, acquiring first sample data for training the regression model, wherein the duration of the first sample data is a preset duration;
[0060] S2, using the last second of the preset duration as the label of the regression model, and extracting from the first sample data before the label within the preset duration 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...
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