Vibration data processing method and system, model training method and system and detection method and system of lifting equipment
A technology for lifting equipment and vibration data, applied in elevators, character and pattern recognition, instruments, etc., can solve the problems of low fault judgment accuracy, single data, large deviation, etc., to improve fault judgment accuracy and comprehensive diagnosis range. , the effect of avoiding downtime failures
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Embodiment 1
[0081] This embodiment provides a method for processing real-time operation data of fixed lifting equipment. refer to figure 1 , the processing method of the real-time operation data of the fixed lifting equipment includes:
[0082] S11. Obtain vibration data generated by the fixed lifting equipment during operation through the vibration sensor. Wherein, the fixed lifting device may be an elevator car, and the vibration data includes the vibration acceleration data in the X-axis, Y-axis and Z-axis directions generated by the elevator car during operation.
[0083] S12. Obtain target data. The target data is the data of the constant speed section obtained by segmenting the vibration data according to the running state of the fixed lifting equipment, and the data of the constant speed section is the vibration data when the fixed lifting equipment is in a constant speed running state. Among them, the operating state of the fixed lifting equipment includes an upward running acce...
Embodiment 2
[0098] This embodiment provides a model training method. refer to figure 2 , the model training methods include:
[0099] S21. Obtain a feature data set. Each set of data in the feature data set is processed by using the real-time operation data processing method of the fixed lifting equipment in Embodiment 1. Wherein, the feature data set is preferably the data set formed in step S122 of Embodiment 1.
[0100] S221. Obtain the first device state corresponding to each group of data in the feature data set, and mark the data in the feature data set with the first device state to obtain the first marked data set, wherein the first device state is normal or abnormal ; Obtain a health status assessment model based on the first labeled data set training.
[0101]S222. Obtain the second device state corresponding to each group of data in the feature data set, and mark the data in the feature data set with the second device state to obtain the second marked data set, wherein the ...
Embodiment 3
[0125] This embodiment provides a detection method for fixed lifting equipment. refer to image 3 , the detection methods of fixed lifting equipment include:
[0126] S31. Obtain the data to be detected of the fixed lifting device to be detected, the data to be detected is the data obtained after processing the fixed lifting device to be detected by using the processing method of the real-time operation data of the fixed lifting device in Embodiment 1 .
[0127] S32. Input the data to be detected into the health status evaluation model trained based on the model training method in Embodiment 2 to obtain the health status evaluation result of the fixed lifting equipment to be detected. If the health status evaluation result is that the equipment is abnormal, the The data to be detected is input to the fault diagnosis model trained based on the model training method in Embodiment 2 to obtain the equipment fault type of the fixed lifting equipment to be detected. In this embod...
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