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A new wire rope tester based on principle of magnetic flux leakage is constructed. Two rings of NdFeB are cut in axial direction into 32 equal arc segments such that each arc segment subtends an angle of 22.5° at the centre. These arc segments are then parallely magnetized in magnetizer. A ferromagnetic cylinderical yoke is constructed by hinging t...
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Magnetic memory method (MMM) is widely used for diagnosing ferromagnetic material on early stage as a nondestructive technology, but no clear description exists for the influence of stress on MMM signals at the micro-defect position on the surface of steel wire yet. Hence, based on traditional magnetic charge model, a stress-dependent magnetic char...
Citations
... Kaur et al. designed a new type of magnetic flux leakage detection device for wire ropes. Cutting the long axis ring of the Nd-Fe-B permanent magnet into 32 equal arc segments and magnetizing it in parallel in a magnetizer can effectively detect wire rope breakage damage [20]. Yan et al. proposed an electromagnetic nondestructive testing method that simplifies the magnetic circuit, achieving the defect detection of wire ropes under the environment of electromagnetic interference [21]. ...
Wire rope breakage, as damage easily produced during the service period of wire rope, is an important factor affecting the safe operation of elevators. Especially in the high-speed elevator operation process, the problem of magnetization unsaturation caused by speed effects can easily lead to deformation of the magnetic flux leakage detection signal, thereby affecting the accuracy and reliability of wire breakage quantitative detection. Therefore, this article focuses on the problem that existing wire rope detection methods cannot perform non-destructive testing on high-speed elevator wire ropes and conducts design and experimental research on a high-speed running wire rope breakage detection device based on the principle of multi-stage excitation. The main research content includes simulation research on the multistage excitation, structural design, and simulation optimization of open–close copper sheet magnetizers and the building of a detection device for wire rope breakage detection experimental research. The simulation and experimental results show that the multistage magnetization method can effectively solve the problem of magnetization unsaturation caused by the velocity effect. The multistage excitation device has a good wire breakage recognition effect for speeds less than or equal to 3 m/s. It can detect magnetic leakage signals with a minimum of four broken wires and has good detection accuracy. It is a new and effective wire breakage detection device for high-speed elevator wire rope, providing important technical support for the safe and reliable operation of high-speed elevators.
... In the new technology, the polyurethane layer is used instead of the rope core to wrap around the steel rope strand, which has the effect of anti-rust and antiwear. Traction steel strip has the characteristics of light weight, small bending radius, low traction noise, no need for regular lubrication, environmental protection, etc., which is favored by the major elevator manufacturers.Otis first completed the theoretical demonstration of the steel strip traction system and the actual elevator manufacturing, and subsequently, Schindler, ThyssenKrupp, Hitachi and other brands also launched the elevator products with composite steel strip as the bearing parts [6] . ...
... kwaśniewski et al. [108] investigated the potential applications of magnetometric sensors based on amorphous materials for wire deformation and cracks in wire rope detection without external magnetic fields. Kaur et al. [109] proposed a new wire rope detector based on parallel magnetized NdFeB magnet segments, where two ring-shaped NdFeB were cut in axial direction into 32 equal arc segments, and the MFL signals verified the defect detection capability of the new detector. Zhang et al. [110] designed a shallow defect detector based on the magnetic probe structure, which was featured as cheap, light in weight and easy to manufacture. ...
Wire rope inspection by nondestructive testing methods, sensors and signal processing techniques are mainly reviewed in this paper. Owing to the difference of physical mechanism and testing principles, magnetic flux leakage, eddy current, acoustic emission and ultrasonic guide wave testing as well as other inspection methods for steel wire rope are summarized. Then, the commonly and frequently used testing sensors of inductive coil, hall element, magnetoresistive sensors and others are compared in the perspective of their corresponding operating principles, development situation, advantages and disadvantages. Furthermore, signal processing techniques including the signal filtering techniques such as the time and frequency analysis methods, quantitative data processing methods such as the machine learning and defect classification are studied. Finally, the challenges and future developing trends of wire rope inspection in practical applications are discussed.
... At present, the NDT methods of wire rope include electromagnetic [3,4], X-ray [5], acoustic [6][7][8][9], and optical [10] method [1]. X-ray apparatus has radioactive contamination; acoustic method detects wire rope by striking, which is simple but one-sided; CCD camera optical testing method can directly show the real defects through imaging, but it is susceptible to oil pollution; because of high sensitivity, high speed, and low cost, electromagnetic NDT method is widely used [11][12][13][14]. ...
The lifetime of wire rope is crucial in industry manufacturing, mining, and so on. The damage can be detected by using appropriate nondestructive testing techniques or destructive tests by cutting the part. For broken wires classification problems, this work is aimed at improving the recognition accuracy. Facing the defects at the exterior of the rope, a novel method for recognition of broken wires is firstly developed based on magnetic and infrared information fusion. A denoising method, which is adopted for magnetic signal, is proposed for eliminating baseline signal and wave strand. An image segmentation method is employed for parting the defects of infrared images. Characteristic vectors are extracted from magnetic images and infrared images, then kernel extreme learning machine network is applied to implement recognition of broken wires. Experimental results show that the denoising method and image segmentation are effective and the information fusion can improve the classification accuracy, which can provide useful information for estimating the residual lifetime of wire rope.
... In this method, a simplified magnetic circuit was proposed to excite WR, and the defect detection of thin WR in electromagnetic interference environment was realized. A new WR tester was established based on MLF principle in [28], and each arc segment subtends an angle of 22.5 degrees at the center by cutting two rings of NdFeB along axial direction into 32 equal arc segments, which were then parallelly magnetized in magnetizer. To detect WR damage in coal mine, Sun et al. [29] proposed an opening electric magnetizer through the magnetic control for a C-like electric loop-coil, which has an opening structure capable of directly encompassing and centering the endless object in it. ...
As an important load-bearing component, steel wire ropes (WRs) are widely used in complex systems such as mine hoists, cranes, ropeways, elevators, oil rigs, and cable-stayed bridges. Non-destructive damage detection for WRs is an important way to assess damage states to guarantee WR’s reliability and safety. With intelligent sensors, signal processing, and pattern recognition technology developing rapidly, this field has made great progress. However, there is a lack of a systematic review on technologies or methods introduced and employed, as well as research summaries and prospects in recent years. In order to bridge this gap, and to promote the development of non-destructive detection technology for WRs, we present an overview of non-destructive damage detection research of WRs and discuss the core issues on this topic in this paper. First, the WRs’ damage type is introduced, and its causes are explained. Then, we summarize several main non-destructive detection methods for WRs, including electromagnetic detection method, optical detection method, ultrasonic guided wave detection method, and acoustic emission detection method. Finally, a prospect is put forward. Based on the review of papers, we provide insight about the future of the non-destructive damage detection methods for steel WRs to a certain extent.
... They also require high magnetizing currents (30 kA) and pose logistic challenges (Riley et al. 2000). Kaur et al. (2018a) reported parallel magnetized NdFeB magnet segments used along with Hall sensors to detect local faults and damage like loss in the metallic area and broken strands. The Hall sensor had a sensitivity of 90 mV/mT and a range of 0-10 mT. ...
... Signal from a Hall sensor when a steel wire rope with a broken strand passes through the wire rope tester incorporating parallel NdFeB permanent magnet segments. (Reproduced fromKaur et al. (2018a) with permission from Springer) ...
Handbook of Advanced Non-Destructive Evaluation. Springer, Cham
The quantitative defect detection of wire rope is crucial to guarantee safety in various application scenes, and sophisticated inspection conditions usually lead to the accurate testing of difficulties and challenges. Thus, a magnetic flux leakage (MFL) signal analysis and convolutional neural networks (CNNs)-based wire rope defect recognition method was proposed to solve this challenge. Typical wire rope defect inspection data obtained from one-dimensional (1D) MFL testing were first analyzed both in time and frequency domains. After the signal denoising through a new combination of Haar wavelet transform and differentiated operation and signal preprocessing by normalization, ten main features were used in the datasets, and then the principles of the proposed MFL and 1D-CNNs-based wire rope defect classifications were presented. Finally, the performance of the novel method was evaluated and compared with six machine learning methods and related algorithms, which demonstrated that the proposed method featured the highest testing accuracy (>98%) and was valid and feasible for the quantitative and accurate detection of broken wire defects. Additionally, the considerable application potential as well as the limitations of the proposed methods, and future work, were discussed.
In-haul cables must be examined and maintained regularly to ensure the smooth operation of cable-stayed bridges. The magnetic flux leakage (MFL) detection method is being applied increasingly commonly to inspect defects. For the quantitative identification of the broken wire, the authors designed an MFL inspection equipment and investigated the performance. A trapezoidal magnetic dipole model is constructed to simulate the leakage distribution, and the axial and circumferential excitation schemes are used to obtain the intensity of magnetic induction. Then, based on the simulation of model parameters, an MFL detection system is configured for detecting the damage in the broken wire. To investigate the adaptability of the developed system, a rectangular defect is inspected in the vertical and spiral climbing modes, respectively. The signal acquired under different paths is processed by the median filtering and wavelet transform methods and analyzed. A random forest algorithm is used to quantitatively identify the number of broken wires, defect dimensions, and cross-sectional area loss to verify the proposed method. The results show that the axial excitation generates a single peak signal, which offers better detection of the wire defects. In the vertical climbing mode, the maximum detection errors in the width and cross-sectional area loss are 0.64 mm and 0.46%, respectively, while the values are 0.21 mm and 0.1% in spiral climbing mode, indicating that the latter mode offers higher identification accuracy. Furthermore, in future work, the detection capability of irregular defects should be studied, expanding its application in health monitoring.
