Elevator fault recognition system based on open dataset construction

Changming Li; Jing Wang

doi:10.1117/12.3039598

4 September 2024 Elevator fault recognition system based on open dataset construction

Changming Li, Jing Wang

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132591W (2024) https://doi.org/10.1117/12.3039598
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

A system for elevator fault recognition based on open dataset construction is proposed in response to the frequent occurrence of elevator accidents and the inefficiency and timeliness of maintenance and inspection methods. The system involves elevator Internet of Things (IOT) and computer software technology, including the elevator fault recognition front end, server end, and client end. The data acquisition device of the elevator fault recognition front end collects video stream data and sends it to the edge computing device, and the fault algorithm model library of the edge computing device including fault algorithm models, and the fault recognition module will use the data to recognize faults in the video stream. When maintenance engineers detect the elevator operation fault from the video stream data, they input the fault characteristics into the model training server through the client’s model training app. The model training server, based on transfer learning, will apply the input fault characteristics to train new fault algorithm models and update them to the fault algorithm model library. This system provides maintenance engineers with open elevator fault model training services, continuously updating the model dataset to improve fault recognition accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Changming Li and Jing Wang "Elevator fault recognition system based on open dataset construction", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132591W (4 September 2024); https://doi.org/10.1117/12.3039598

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KEYWORDS

Data modeling

Detection and tracking algorithms

Education and training

Video

Instrument modeling

Data acquisition

Cameras

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