scholarly journals A Review of Non-Destructive Damage Detection Methods for Steel Wire Ropes

2019 ◽  
Vol 9 (13) ◽  
pp. 2771 ◽  
Author(s):  
Ping Zhou ◽  
Gongbo Zhou ◽  
Zhencai Zhu ◽  
Zhenzhi He ◽  
Xin Ding ◽  
...  
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Steel Wire ◽  
Guided Wave ◽  
Detection Methods ◽  
Wire Ropes ◽  
Intelligent Sensors ◽  
Detection Technology ◽  
Damage States ◽  
Non Destructive

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.

Elimination of outlier measurements for damage detection of structures under changing environmental conditions

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia
Keyword(s):  
Damage Detection ◽  
Multiple Regression ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Methods ◽  
Structure Model ◽  
Bridge Structure ◽  
Beam Structure ◽  
Dependent Variables ◽  
The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

scholarly journals A Test Device for Optimize PMU-Based Islanding Detection Technology

2015 ◽  
Vol 10 (2) ◽  
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Detection Method ◽  
Detection Methods ◽  
Islanding Detection ◽  
Algorithm Optimization ◽  
Test Device ◽  
Photovoltaic Power ◽  
Detection Technology ◽  
Bulk Power

Islanding detection is a necessary function for grid connected distributed generators. Usually, islanding detection methods can be classified as two catalogues: remote detecting methods and local detecting methods. Most of them have limitation and defects when they are applied in photovoltaic power stations. Recently synchronous phasor measuring units (PMU) is proposed to be applied for islanding detecting. Although the islanding detection method is supposed to be applied for traditional bulk power systems, it is also suitable for renewable generation power plants. To do this islanding detection will be implemented on central management unit of photovoltaic power station instead of on grid-tied inverters as traditionally. In implementing, the criteria of this method and the threshold of algorithm are needed to be optimized. This paper develops a test device which can optimize PMU-based islanding detection technology to validate the proposed islanding detection method applying in PV station. Then using simulation to discuss how to set a reasonable threshold for the researched islanding detection method applied in PV stations. Finally the paper provides a platform for the algorithm optimization.

scholarly journals 2511 Damage detection method in non-destructive inspection using topology optimization

2013 ◽  
Vol 2013.23 (0) ◽  
pp. _2511-1_-_2511-6_
Author(s):  
Takafumi NISHIZU ◽  
Akihiro TAKEZAWS ◽  
Mitsuru KITAMURA
Keyword(s):  
Topology Optimization ◽  
Damage Detection ◽  
Detection Method ◽  
Non Destructive

Structural damage detection via combining weighted strategy with trace Lasso

2018 ◽  
Vol 22 (3) ◽  
pp. 597-612 ◽  
Author(s):  
Chengbin Chen ◽  
Chudong Pan ◽  
Zepeng Chen ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Swarm Intelligence ◽  
Structural Damage ◽  
Optimization Problem ◽  
Detection Method ◽  
Rapid Development ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Structural Damage Detection ◽  
Selection Operator

With the rapid development of computation technologies, swarm intelligence–based algorithms become an innovative technique used for addressing structural damage detection issues, but traditional swarm intelligence–based structural damage detection methods often face with insufficient detection accuracy and lower robustness to noise. As an exploring attempt, a novel structural damage detection method is proposed to tackle the above deficiency via combining weighted strategy with trace least absolute shrinkage and selection operator (Lasso). First, an objective function is defined for the structural damage detection optimization problem by using structural modal parameters; a weighted strategy and the trace Lasso are also involved into the objection function. A novel antlion optimizer algorithm is then employed as a solution solver to the structural damage detection optimization problem. To assess the capability of the proposed structural damage detection method, two numerical simulations and a series of laboratory experiments are performed, and a comparative study on effects of different parameters, such as weighted coefficients, regularization parameters and damage patterns, on the proposed structural damage detection methods are also carried out. Illustrated results show that the proposed structural damage detection method via combining weighted strategy with trace Lasso is able to accurately locate structural damages and quantify damage severities of structures.

scholarly journals A comprehensive study of the magnetic concentrating sensor for the damage detection of steel wire ropes

2020 ◽  
Vol 7 (9) ◽  
pp. 096102
Author(s):  
Yiqing Zhang ◽  
Luyang Jing ◽  
Chengjun Chen ◽  
Xiaorui Bai ◽  
Jiwen Tan
Keyword(s):  
Damage Detection ◽  
Steel Wire ◽  
Wire Ropes ◽  
Comprehensive Study

scholarly journals Application of Lightweight Convolutional Neural Network for Damage Detection of Conveyor Belt

2021 ◽  
Vol 11 (16) ◽  
pp. 7282
Author(s):  
Mengchao Zhang ◽  
Yuan Zhang ◽  
Manshan Zhou ◽  
Kai Jiang ◽  
Hao Shi ◽  
...  
Keyword(s):  
Damage Detection ◽  
Working Conditions ◽  
Detection Method ◽  
Conveyor Belt ◽  
Detection Methods ◽  
Test Accuracy ◽  
Test Results ◽  
Test Speed ◽  
Conveyor Belts ◽  
Belt Conveyors

Aiming at the problem that mining conveyor belts are easily damaged under severe working conditions, the paper proposed a deep learning-based conveyor belt damage detection method. To further explore the possibility of the application of lightweight CNNs in the detection of conveyor belt damage, the paper deeply integrates the MobileNet and Yolov4 network to achieve the lightweight of Yolov4, and performs a test on the exiting conveyor belt damage dataset containing 3000 images. The test results show that the lightweight network can effectively detect the damage of the conveyor belt, with the fastest test speed 70.26 FPS, and the highest test accuracy 93.22%. Compared with the original Yolov4, the accuracy increased by 3.5% with the speed increased by 188%. By comparing other existing detection methods, the strong generalization ability of the model is verified, which provides technical support and empirical reference for the visual monitoring and intelligent development of belt conveyors.

A novel texture-based damage detection method for wire ropes

Measurement ◽  
2019 ◽  
Vol 148 ◽  
pp. 106954 ◽  
Author(s):  
Ping Zhou ◽  
Gongbo Zhou ◽  
Zhenzhi He ◽  
Chaoquan Tang ◽  
Zhencai Zhu ◽  
...  
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Wire Ropes

A Damage Detection Method: CMSE Combined with Niche GA

2007 ◽  
Vol 334-335 ◽  
pp. 929-932 ◽  
Author(s):  
Xu Ge ◽  
Yun Ju Yan ◽  
Huan Guo Chen
Keyword(s):  
Composite Material ◽  
Damage Detection ◽  
Composite Structures ◽  
Structural Damage ◽  
Strain Energy ◽  
Detection Method ◽  
Detection Methods ◽  
Damage Localization ◽  
Complex Structures ◽  
Modal Strain Energy

The paper presents an effective damage detection method of complex composite structures. It can be carried out through the experimental modal analysis of the damaged structure. The method using the improved Cross Modal Strain Energy (CMSE) technique and Niche GA has many advantages compared with other damage detection methods. The CMSE method can use any modes of the structure and the modes don’t need to be normalized or consistent in scale. The Niche GA improves the efficiency of the calculation and enhances the capacity of identifying structural damage localization. The model is the composite material airfoil case. The numerical results show that the method proposed in this paper is successful for damage detection of complex structures.

scholarly journals Experience of the Crane Steel Wire Ropes Non-Destructive Tests

2018 ◽  
Vol 12 (4) ◽  
pp. 157-163
Author(s):  
Pavel Peterka ◽  
Jozef Krešák ◽  
Marek Vojtko
Keyword(s):  
Steel Wire ◽  
Wire Ropes ◽  
Non Destructive
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