An Analysis-by-Synthesis Approach to Rope Condition Monitoring

Wacker, Esther-Sabrina; Denzler, Joachim

doi:10.1007/978-3-642-17274-8_45

Cited by 6 publications

(7 citation statements)

References 11 publications

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“…For the defects of WR, the histogram of oriented gradient feature was the best, followed by the local binary patterns feature. In the work of [48,49], Wacker et al established a probabilistic appearance model as a representation of normal surface changes combined with the structure and appearance of the WR and realized the detection of WR abnormal surface. For surface defects of thin metallic wires, an automatic optical detection technique was presented by Sanchez-Brea et al in [50].…”

Section: Optical Detection Methodsmentioning

confidence: 99%

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

Zhou

Zhu

et al. 2019

Applied Sciences

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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.

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Section: Optical Detection Methodsmentioning

confidence: 99%

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

Zhou

Zhu

et al. 2019

Applied Sciences

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“…To estimate the rope geometry from 2d rope images, we use the framework described recently by Wacker and Denzler [10]. Their approach focuses on the image-based monitoring of important rope parameters and is not suitable for the automatic detection of surface defects.…”

Section: Geometric Rope Modelmentioning

confidence: 99%

“…In contrast to [10] we use this correspondence to form a parametric description of each surface point X in the rope. Fig.…”

Section: Geometric Rope Modelmentioning

confidence: 99%

“…By fusing a geometrical structure model with a statistical appearance model we achieve a much better discrimination between a real defect and normal appearance variations. In a first step the model geometry is estimated in an image-based manner with help of a perfectly regular 3d rope model introduced recently by Wacker and Denzler [10]. In contrast to our work, they used this model to monitor important rope parameters but they did not address the problem of rope surface defect detection.…”

Section: Introductionmentioning

confidence: 97%

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Combining Structure and Appearance for Anomaly Detection in Wire Ropes

Wacker

Denzler

2011

Computer Analysis of Images and Patterns

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Abstract. We present a new approach for anomaly detection in the context of visual surface inspection. In contrast to existing, purely appearancebased approaches, we explicitly integrate information about the object geometry. The method is tested using the example of wire rope inspection as this is a very challenging problem. A perfectly regular 3d model of the rope is aligned with a sequence of 2d rope images to establish a direct connection between object geometry and observed rope appearance. The surface appearance can be physically explained by the rendering equation. Without a need for knowledge about the illumination setting or the reflectance properties of the material we are able to sample the rendering equation. This results in a probabilistic appearance model. The density serves as description for normal surface variations and allows a robust localization of rope surface defects. We evaluate our approach on real-world data from real ropeways. The accuracy of our approach is comparable to that of a human expert and outperforms all other existing approaches. It has an accuracy of 95% and a low false-alarm-rate of 1.5%, whereupon no single defect is missed.

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“…Esther has established an image comprehensive analysis system based on the wire rope model, which can capture the actual 2-D projection of the wire rope using the camera, and construct a parametric 3-D model based on the structural parameters of the wire rope model. The accuracy of the lay length and strand space obtained by this method is 1 mm [4]. Sylvain has calculated the lay length according to the change of the scanning MFL signal with the uneven surface of the wire rope [5].…”

Section: Introductionmentioning

confidence: 99%

Research on Analysis of Eddy Current Response to Lay Length of Wire Ropes

Jiao

Jia

et al. 2020

Studies in Applied Electromagnetics and Mechanics

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The lay length is one of the important parameters for the wire rope and its detection can indirectly characterize its stress and surface damage state. The eddy current testing (ECT) method is advantageous because of its easy operation, single-side detection, low requirement of surface preparation, applicability in harsh environment, and other properties. Hence the lay length of the wire ropes is measured by ECT in this paper. The eddy current (EC) response to the wire rope is simulated. The EC on the surface of the strand below the pancake coil forms a vortex, and the distribution of the EC on the curved surfaces on both sides of the strand is symmetrical. The spacing between the adjacent peaks or troughs of the scanning signal is the distance between the adjacent strands, and the number of peaks or troughs of the scanning signal in a range of the lay length is related to the number of strands of the wire rope. Finally, the experimental validation is performed. The relative error of the lay length of the wire rope assessed by the EC method is less than 0.28%.

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An Analysis-by-Synthesis Approach to Rope Condition Monitoring

Cited by 6 publications

References 11 publications

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

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

Combining Structure and Appearance for Anomaly Detection in Wire Ropes

Research on Analysis of Eddy Current Response to Lay Length of Wire Ropes

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