Recognition and Visualization of Working State of Quay Crane Based on K-means

Pengpeng Xu ； Dongliang Shi

《International Core Journal of Engineering》 6卷12期 (2020/12) Pp. 193-202

https://doi.org/10.6919/ICJE.202012_6(12).0029

摘要

The working efficiency of the port is affected by the working sustainability of the quay crane equipment, so it is necessary to ensure the healthy state of the quay crane. By analyzing the daily operation data of the quay crane, it can help to formulate a reasonable equipment maintenance and repair plan. In this paper, the operation data of a certain type of quay crane during continuous operation in a certain period of time are extracted. Each working day is taken as a cycle, and the integral of stress value with time at the section where the middle tie rod is 2 m away from the hinge is taken as the working strength of the quay crane. The distribution characteristics of the working conditions are observed by frequency statistics, and the number of working conditions is determined. This paper presents a method based on K-means and weighted PCA to obtain the visual state characteristics of the quay crane, and reasonably arrange the lifting capacity of the quay crane. The results show that this method can not only classify the load state of vibration signal reasonably, but also realize the diagnosis and recognition of each operation state of the quay crane.

關鍵字

Unsupervised clustering ； K-Means ； Quay crane ； Condition monitoring ； Predictive maintenance

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