Shafting fault diagnosis method and system based on ship motor howling identification

By using MEMS microphone arrays and beamforming technology to collect motor whistling sounds on new energy ships, and combining time-frequency characteristics and multi-source data fusion, real-time and intelligent diagnosis of shafting faults is achieved. This solves the problem of motor whistling sound recognition and shafting fault diagnosis in new energy ships, and has high anti-interference capability and low operation and maintenance cost.

CN121658993AActive Publication Date: 2026-03-13NANJING SMART WATER TRANSPORTATION TECH CO LTD
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Patent Information

Application Number
CN202511674094.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-14
Publication Date
2026-03-13
Estimated Expiration
2045-11-14

AI Technical Summary

Technical Problem

Existing technologies struggle to achieve real-time and accurate diagnosis of shafting faults under complex operating conditions in new energy ships, especially in complex noise environments where it is difficult to accurately identify motor whine and perform intelligent fault diagnosis.

Method used

The system uses a MEMS microphone array combined with beamforming technology to collect sound signals. It then uses time-frequency feature extraction and a pre-trained recognition model to identify motor whistling. In addition, it combines multi-source monitoring data for data fusion and probability smoothing to trigger shaft system fault diagnosis, enabling graded alarms and remote uploading.

Benefits of technology

It achieves intelligent identification of motor whistling sound and linkage diagnosis of shaft system faults in complex noise environments. It has strong real-time performance, high anti-interference ability, reliable diagnostic results, and low operation and maintenance costs, and is suitable for the intelligent monitoring and operation and maintenance needs of new energy ships.

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Abstract

The invention discloses a shafting fault diagnosis method based on ship motor howling identification, and the method comprises the following steps: collecting a sound signal of a ship motor and multi-source monitoring data; preprocessing the sound signals to extract time-frequency characteristics of the sound signals; inputting the time-frequency characteristics into a pre-trained recognition model to obtain a judgment result of motor squeal; probability smoothing and threshold judgment are carried out on the judgment result, and when a set condition is met, shafting diagnosis is triggered; after the shafting diagnosis is triggered, performing data fusion on the multi-source monitoring data and the time-frequency characteristics, and judging and positioning a shafting fault based on a fusion result to obtain a diagnosis result; and displaying the diagnosis result on an intelligent monitoring platform in real time, and triggering graded alarm and remote uploading. The method and the system provided by the invention have the advantages of strong real-time performance, high anti-interference capability, reliable diagnosis result, low operation and maintenance cost and the like.
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