Walking speed reducer fault model generation method and device and computer equipment
A technology of a travel reducer and a fault model, which is applied in the field of computer equipment and readable storage media, the generation of a fault model of a travel reducer, and the fault diagnosis method of a travel reducer, and can solve the problems of low diagnosis efficiency and high cost
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Embodiment 1
[0049] figure 1 It is a flow chart of a method for generating a walking speed reducer fault model provided in Embodiment 1 of the present invention, and the method includes the following steps:
[0050] Step S11: Obtain the vibration signals of the traveling reducer under various fault states.
[0051]In the embodiment of the present invention, the travel reducer can be used for excavator crawler drive, airport vehicle wheel drive, garbage compactor vehicle wheel drive, harvester wheel drive, road roller travel drive and drilling equipment crawler drive. A vibration acceleration sensor can be installed on the travel reducer, and the vibration acceleration sensor can be used to obtain the vibration signals of the travel reducer under various fault conditions, including at least normal vibration signals, vibration signals in the state of gear wear, broken teeth, and tooth root cracks vibration signal. Moreover, the acquired vibration signals can be transmitted to computer equi...
Embodiment 2
[0059] figure 2 It is a flow chart of decomposing vibration signals provided by Embodiment 2 of the present invention, including the following steps:
[0060] Step S21: performing wavelet packet decomposition on the vibration signal to obtain energy signals of each frequency band of the vibration signal.
[0061] Step S22: Calculating the energy sum of the signals in each frequency band of the vibration signal according to the energy signals of each frequency band.
[0062] Step S23: Perform normalization processing on the energy sum of signals in each frequency band of the vibration signal to obtain corresponding fault characteristic parameters of the vibration signal.
[0063] In the embodiment of the present invention, before the wavelet packet decomposition is performed on the vibration signal, the vibration signal may also be preprocessed, that is, the vibration signal may be subjected to smoothing and denoising, filtering and denoising, and other processing. The prepr...
Embodiment 3
[0069] image 3 It is a flowchart of fault diagnosis model modeling provided by Embodiment 3 of the present invention, including the following steps:
[0070] Step S31: Perform discretization processing on the fault characteristic parameters of the vibration signal to obtain observed input values of the fault model.
[0071] In the embodiment of the present invention, when performing hidden Markov model modeling, the observation value is required to be a limited number of discrete values, so it is necessary to discretize the energy feature quantity extracted by the wavelet packet, for example, the MATLAB toolbox can be used. The Lloyd algorithm realizes the scalar quantization of the feature vector, which can be used as the observation value of the hidden Markov model for training after scalar quantization.
[0072] In the embodiment of the present invention, the specific principle of the scalar quantization technology is as follows: the scalar quantization technology is ba...
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