Shaking Noise Elimination for Detecting Local Flaw in Steel Wire Ropes Based on Magnetic Flux Leakage Detection

Abstract

Steel wire rope (SWR) is widely utilized in scenarios, such as goods transmission, elevators, and dams. However, SWR defects are unavoidable, so the surface health condition of SWRs should be tested to avoid accidents. After introducing the magnetic flux leakage (MFL) method to detect local flaws (LFs) in multiple channels, we find that shaking noise, like strand noise, is inevitable. Although shaking noise is pointed out, the representation of shaking noise and its phenomenological model are not studied. This article is focused on analyzing the influence of shaking noise on LF detection. The mathematical model of shaking noise is constructed based on its relation to lift-off distance, and shaking noise is simulated to test the performance of shaking noise elimination (SNE) methods. Then, a new SNE method, which retrieves the spatial information of multi-channel MFL signals, is proposed to filter out shaking noise. In comparison with the existing SNE methods, the proposed method improves LF detection in the presence of strong shaking noise. Furthermore, this article also raises awareness of the effects of lift-off distance on LF detection.