Crown block online detection and diagnosis system and method based on artificial intelligence technology

Abstract

The invention provides a crown block online detection and diagnosis system and method based on an artificial intelligence technology. The system comprises a crown block operation state monitoring system, a crown block state data analysis module and a man-machine interaction module, wherein the crown block operation state monitoring system and the man-machine interaction module are both electrically connected with the crown block state data analysis module, the crown block operation state monitoring system is used for collecting operation state data of all parts of a crown block, the crown block state data analysis module is used for analyzing the operation state data collected by the crown block operation state monitoring system, and the man-machine interaction module is used for displaying operation state data acquired by the crown block operation state monitoring system and an analysis result of the crown block state data analysis module. According to the crown block online detection and diagnosis system and method based on the artificial intelligence technology, acquisition and processing of crown block operation data can be achieved, and then automatic fault detection and analysis of the crown block are achieved.

Description

technical field [0001] The invention relates to the technical field of crane fault diagnosis, in particular to an artificial intelligence technology-based online crane detection and diagnosis system and method. Background technique [0002] The traditional multifunctional crane mechanism is complex and huge, with many failure points and complicated causes, and the maintenance personnel have heavy tasks, making it difficult to carry out efficient crane maintenance work. With the development of detection technology and automation equipment, maintenance personnel can use sensors to collect crane operation status data, and through data analysis to identify the crane operation status and fault information, some sensor data has a large amount of data, rapid changes, Due to the complex features, a lot of time will be wasted and some important information will be missed if manual analysis is performed after the data collection is completed. As an artificial intelligence method, dee...

AI Technical Summary

Problems solved by technology

[0002] The traditional multifunctional crane mechanism is complex and huge, with many fault points and complex causes, and the maintenance personnel have heavy tasks, making it difficult to carry out efficient crane maintenance work

With the development of detection technology and automation equipment, maintenance personnel can use sensors to collect crane operation status data, and through data analysis to identify the crane operation status and fault information, some sensor data has a large amount of data, rapid changes, Due to the complex characteristics, a lot of time will be wasted and some important information will be missed if manual analysis is performed after the data collection is completed.

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