Motor axle vibration anomaly detection and prediction system and method

Abstract

The invention discloses a motor axle vibration anomaly detection and prediction system and method, and relates to the field of image processing, and the system comprises a visual collection system, a server, a motor element segmentation system, a multi-modal data construction system, and a machine vision system. The visual collection system acquires motor images from different directions; the motor element segmentation system executes a segmentation algorithm to generate a wheel shaft vibration sequence, a motor vibration sequence and a shell vibration sequence. The multi-modal data construction system performs data preprocessing and normalization to generate a dual-modal data set; and the machine vision system constructs a three-dimensional residual convolutional neural network by using the bimodal data set, and the machine vision system performs feature extraction and fusion on the bimodal data set to obtain detection and prediction results of external defects and vibration defects of the motor. According to the invention, a time sequence anomaly detection algorithm is integrated, detection can be carried out in the production process of a motor production line, and short-life products which may have problems in the future can be predicted.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a system and method for detecting and predicting abnormal vibration of a motor wheel shaft. Background technique [0002] At present, with the increasing dependence of various industries on motors, the production quality requirements of motors are getting higher and higher. On the one hand, while increasing the complexity of production processes to meet more specific needs, the requirements for product quality testing are also increasing. higher. Traditional detection mainly relies on manual detection, which has high labor costs and low detection efficiency. With the continuous development of motor technology, the cost and difficulty of detection technology are also increasing. [0003] The existing implementation scheme is mainly based on the rule setting, and the image of each angle of the motor is captured by the visual acquisition system, supplemented by manual mea...

AI Technical Summary

Problems solved by technology

[0004]1. The cost of manual quality screening is high, the speed is slow, and the accuracy is low

[0005]2. With the continuous development of motor production technology, there are more and more potential defects that may exist. There are too many parameters to be measured and checked by manual inspection, and some defects are often only It is reflected in the subtle mechanical vibration abnormalities of various parts of the motor, and this abnormality is difficult to be captured manually, further reducing the detection speed and accuracy

[0006]3. The manual quality screening method has poor transferability, and the assembly line of new products needs to reorganize the training of relevant personnel, and the scalability is poor

[0007]4. Manual screening cannot predict potential high-risk products, resulting in uneven service life of ex-factory products

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