# Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope
## 1 Introduction  
Steel wire rope is widely used in practical applications as loading and stretching with high strength and toughness in complex scenes such as the elevator, mine, and crane, which plays an important role in various engineering machinery [1; 2]. However, the failure of wire rope such as becoming broken [3], corrosion [4], and wear and fatigue [5] has caused huge losses to the economy and human lives. Therefore, many nondestructive testing methods [6; 7] have appeared in wire rope defect inspection, for instance, the widely used magnetic flux leakage testing method [8], metal magnetic memory, [9] and ultrasonic guided wave detection method [10]. The defect is tinny in most cases, while the detection signals are very weak and mixed with strand signals as a result of the spiral wire rope structures and environmental noises [11; 12], which makes the wire rope defect identification and signal processing full of difficulty and challenges. Generally, two main types of wire rope defects were investigated, namely, the local fault (LF) and loss of metallic sectional area (LMA). When the wire rope was scanned and the defect was sensed or captured by the sensor such as the inductive coil, the hall element and magnetic resistance sensor, and different inspection signal components could be acquired. As a consequence, a mass of signal denoising methods were proposed on account of the complex detection and interference environment. [PERSON] et al. [13]proposed a Hilbert transform-based enveloping and quantification magnetic flux leakage (MFL) signal processing method for wire rope damage detection. [PERSON] et al. [14] applied a morphological non-sampling and wavelet reconstruction-based wire rope signal processing method in a coal mine, which filtered the noises effectively by increasing the signal-to-noise ratio (SNR) and decreasing the elapsed time. [PERSON] et al. [15] proposed a multilevel wavelet and median filtering combined wire rope denoising algorithm, which not only increased the SNR, but also enhanced the signal quality. [PERSON] et al. [16] presented a new coil winding structure sensor with iron core inside, which improved the SNR almost six times compared with traditional inductive coil, and eliminated the influence of coil cross sectional area and liftoff effect to some extent. Other wire rope denoising methods such as the notch filtering [17], wavelet energy [18], tone-burst wavelet [19], adaptive filtering [20], and empirical mode decomposition-based [21] techniques were also reported, which were frequently applied and discussed in coal mines and elevators. According to the difference of wire rope inspection and defect sensing methods, other physical field characterizations as well as the wire rope structures were also utilized in wire rope signal processing. [PERSON] et al. [22] observed the fleet angle effect in the bird caging defect detection in a hoist winch system by indirectly analyzing the signals of stator current and load torque of a three-phase induction machine, which was experimentally demonstrated as a new noninvasive method in wire rope signal processing and defect inspection. [PERSON] et al. [23] obtained a surface anomaly detecting accuracy of 95% by making use of the wire rope structure and appearance, combining with image synthesis techniques and automatic visual inspection by the pattern recognition. [PERSON] et al. [24] proposed LF and LMA characterizations and an MFL image signal processing method by the axially and circumferentially hall testing signals processing using feature extraction of gray level co-occurrence matrix and back propagation (BP) network. [PERSON] et al. [25] solved the strand noise problems under a strong shaking detecting environment by using the principle of multi-channel signal fusion and median filtering techniques for MFL images of steel wire rope. [PERSON] et al. [26] applied a multi-criteria analysis method for wire rope inspection data by experiments of wire rope vibration in different range of frequencies.