A method and system for detecting and diagnosing cracks and missing teeth of online woodworking band saw blades

Abstract

The invention discloses a method and a system for performing online testing and diagnosing on crack and tooth falling failures of a woodworking band saw blade. The method comprises the steps of acquiring the main shaft rotating speed, the feeding speed, the saw blade tension force and the saw blade transverse vibration displacement of the to-be-tested woodworking band saw blade; obtaining an Lyapunov index based on a Duffing equation and an improved QR decomposition method according to the acquired main shaft rotating speed, the feeding speed, the saw blade tension force and the saw blade transverse vibration displacement; comparing the Lyapunov index with an Lyapunov index range comparison table, and determining the fault condition of the woodworking band saw blade. Through monitoring the number of the woodworking band saw blades, Lyapunov index testing is performed; according to the Lyapunov index, woodworking band saw blade damage determining is performed; and furthermore the Lyapunov index is based on a maximal Lyapunov index of the Duffing equation. Weak signal detection can be performed. The method and the system are applied to tooth falling fault testing of the woodworking band saw blade, thereby realizing real-time online broadcasting for the fault of the woodworking band saw blade, and preventing safety fault, woodworking quality reduction and severe wood wastage caused by incapability of finding out the fault of the woodworking band saw blade in time.

Description

technical field [0001] The invention relates to the technical field of fault detection, in particular to an online woodworking band saw blade crack and tooth loss fault detection and diagnosis method and system. Background technique [0002] Woodworking band saw machine is a machine tool widely used in wood processing enterprises. Its quality directly affects the economic benefits of the enterprise. As a rotary machine, woodworking band saw machine equipment monitoring and diagnosis has become an urgent need for the economic development of forestry enterprises. From the point of view of the current online fault diagnosis methods for woodworking machinery, one of the keys to solving the diagnosis problem is how to effectively analyze the non-stationary nonlinearity of the mechanical vibration dynamic signal obtained in the monitoring and diagnosis. [0003] Frequent failures of woodworking machinery and equipment during operation, such as peeling, friction, loosening, crawl...

AI Technical Summary

Problems solved by technology

[0004] Cracks and tooth loss defects of existing woodworking band saw blades can only be diagnosed afterwards. Because it uses closed cutting when processing wood, it is extremely difficult to see the state of the band saw blade. It can only be diagnosed based on sound, and it is difficult to be accurate due to experience problems , timely; thus causing the woodworking band saw blade to "fire"-break during sawing, thus affecting the safe work of the band saw machine and affecting the personal safety of the operator

Previous research methods used the numerical range of the lateral vibration displacement of the woodworking band saw blade and the lateral vibration frequency of the band saw blade to judge, which has the problem of range crossing, and it is difficult to make an accurate diagnosis

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