Vehicle gear box abnormality determination method and device and vehicle

By collecting and analyzing gearbox operating noise and speed signals, performing time-frequency analysis and order tracking, the problem of relying on manual experience for troubleshooting vehicle gearbox anomalies in existing technologies has been solved, enabling more accurate fault type judgment and efficient maintenance processes.

CN122409181APending Publication Date: 2026-07-17WUXI INFIMOTION PROPULSION TECH CO LTD +1

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
WUXI INFIMOTION PROPULSION TECH CO LTD
Filing Date
2026-05-26
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In the existing technology, the investigation of abnormal noise in vehicle gearboxes mainly relies on manual experience, lacks unified and objective quantitative basis, makes it difficult to accurately locate specific abnormal parts, and traditional methods are labor-intensive and time-consuming, inefficient, and may introduce assembly deviations.

Method used

By collecting gearbox operating noise and speed signals, time-frequency and frequency spectrum analyses are performed. This is repeated, combining the collected gearbox operating noise signals with speed changes, to obtain a time-frequency spectrum diagram. Furthermore, based on the speed signal, order tracking is performed to extract the amplitude and energy trajectory characteristics of abnormal orders, thus determining the fault type.

Benefits of technology

It enables more detailed fault type identification of vehicle gearbox anomalies under varying speed conditions, improving location accuracy and troubleshooting efficiency while reducing manual intervention and time costs.

✦ Generated by Eureka AI based on patent content.

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Abstract

本申请涉及一种车辆齿轮箱异常判断方法、装置及车辆。所述车辆齿轮箱异常判断方法包括采集齿轮箱的运行噪声信号以及车辆的转速信号;对所述运行噪声信号进行时频分析以获得时频谱图,并基于所述转速信号对所述运行噪声信号进行阶次跟踪以获得运行阶次谱;提取所述运行阶次谱中各阶次分量的实际幅值并与预存的基准幅值比对,确定存在幅值异常的异常阶次;在所述时频谱图中分析与所述异常阶次对应的能量轨迹的时变特征,以判断所述异常阶次所对应的故障类型。
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