Bearing fault diagnosis device used in cooperation with wheel set bearing running-in machine and diagnosis method thereof

Abstract

The invention discloses a bearing fault diagnosis device used in cooperation with a wheel set bearing running-in machine and a diagnosis method thereof. The device comprises a wheel set bearing running-in machine assembly, a signal conditioning circuit, a bearing vibration diagnosis work station and vibration sensors. The vibration sensors acquire vibration signals of bearings and transmit the vibration signals to the signal conditioning circuit. The vibration signals are converted into electrical analog signals by the signal conditioning circuit to be inputted to the bearing vibration diagnosis work station to be processed and the fault type is judged. The diagnosis method comprises the following steps that 1. the wheel set bearing running-in machine assembly and the vibration sensors are installed; 2. the wheel set bearing running-in machine assembly drives vehicle wheels; 3. the vibration sensors acquire the signals and transmit the signals to the signal conditioning circuit and the bearing vibration diagnosis work station; and 4. comprehensive judgment is performed by the bearing vibration diagnosis work station via combination of a resonance envelope demodulation algorithm and a characteristic statistical parameter algorithm so that various faults of the bearings can be effectively judged and identified. Large number of bearings to be detected can be rapidly and accurately diagnosed by the method.

Description

technical field [0001] The invention belongs to the technical field of vehicle fault detection, and in particular relates to a bearing fault diagnosis device and a diagnosis method used in conjunction with a wheel set bearing running-in machine. Background technique [0002] As an important mechanical part of railway wagons, wheel set rolling bearings will directly affect the running safety of wagons if they fail. Therefore, the detection of the state of the rolling bearing has always been the key content of the safety detection of the depots of the railway bureaus. [0003] At present, the initial diagnosis of bearing faults in various domestic vehicle depots mainly relies on the experience of the operators. The workers rotate the bearings manually, use their ears to identify whether there is abnormal sound in the operation of the bearings, and feel whether there is jamming in the operation of the bearings. This detection method requires high operating experience and techn...

AI Technical Summary

Problems solved by technology

However, the resonance demodulation method also has insurmountable shortcomings. This method is only sensitive to local defects inside the bearing, and the defects such as size mismatch, raceway wear, pitting, and lack of oil in the bearing have no corresponding defect passing frequency. It is difficult to detect by the resonance demodulation method, so this kind of fault will be missed as a good bearing

According to the requirements of documents such as "Regulations for Repairing Railway Freight Car Sections" and "General Maintenance Regulations for Rolling Bearings without Axle Boxes for Railway Freight Cars", if these faults on the bearings reach the category C defects, they should be stopped and scrapped. Good bearings are likely to be scrapped; and acoustic signal acquisition is susceptible to environmental noise, especially in noisy repair shops

[0006] In summary, the existing bearing detection methods are difficult to quickly and accurately diagnose a large number of bearings to be tested

Images