Detecting and Locating Local Flaws Based on Magnetic Flux Leakage Imaging for Wire Ropes

Because of their flexibility, high strength and durability, steel wire ropes are widely used in irrigation works, bridges, harbors, tourism and other industrial fields as vital components. Thus, it can cause accidents and economic losses if local flaws of wire ropes in service are not detected in time. This paper presents a design and a signal processing method of magnetic flux leakage imaging-based online nondestructive testing (NDT) for local flaw detection of wire ropes. In this design, the magnetic flux leakage sensor was fabricated by permanent magnets, low-carbon steel and a set of Hall sensors. The parameters of the sensor were optimized according to the simulations by COMSOL Multiphysics. And the Hall sensors formed an array which would scan the whole wire rope during its movement. Meanwhile, the 20-channel signal from the sensor array was sampled in equal interval of displacement by the analogto-digital converters (ADC). To test the sensor and our algorithm, a wire rope with five different-size defects was used in the experiments. With the signal obtained from the sensor, which indicated the magnitude and direction of magnetic flux leakage (MFL) along the rope, several signal processing methods were applied to reconstruct the image of the surface of the wire rope. These methods can effectively improve the quality of the signal and increase the signal to noise ratio. Moreover, by enveloping, the abnormal MFL signal in radius direction can be imaged as a single spot indicating the local flaw. The experimental results showed that the system can detect the local flaws accurately.