Pantograph slider is a critical component of the electrical equipment to obtain power sources for the electric locomotive, whereas the interaction between the slider and the overhead contact line can cause persistent surface wear of the collector strip. The condition monitoring for the level of abrasion of the pantograph slider is significant to avoid major damage. An innovative approach based on multi-view analysis is proposed for monitoring the surface wear of the slider in a running train, accurately measuring the residual thickness of the slider and locating the wear defects appearing. Specially, the three-dimension (3D) reconstruction technology is used for detecting the wear quantity between the upper and lower edges of the slider. First, target edges of the slider are determined using the proposed subpixel edge detection algorithm. Second, mutual matching of the edge points between the multi-view images is finished using the epipolar geometric constraint. Moreover, the 3D reconstructions of the matching points are computed with the principle of triangulation. Finally, the wear volume of the slider can be determined. Experimental results show that the proposed method can successfully measure the abrasion of the pantograph slider under complex conditions, which demonstrate the applicability, effectiveness, and good performance of the proposed approach.

Pantograph slide is a vulnerable component because of the contact and friction between the pantograph and catenary while the train runs with a high speed. Condition monitoring of the slide is a necessary and meaningful work to improve the operation efficiency and reduce the occurrence of accident. It is a hard work to measure the slide abrasion due to the dynamic and complicated environment. In this article, an accurate edge extraction method based on image analysis is proposed, which aims at providing an image metric property based on vision measurement to detect the wear of slide. First, a subpixel edge detection method is proposed. The gradient in horizontal direction is first taken into account, which filters out the nonhorizontal edges. Then, the upper and lower edges of the slide are located using the geometric restriction. The subpixel edge feature are also extracted in the image process, which can be used to the vision measurement system for monitoring the wear condition of the slide. The experiment results shows that the proposed algorithm can precisely detect the subpixel edges of the slide. The measurement error of the slide is less than 2 mm, which demonstrates that the proposed algorithm has a high accuracy in the large field of view.

The pantograph is an essential component in modern electrified train. Due to the characters of contactless and high precision, the threedimensional (3D) stereo vision, which can effectively monitor the abrasion, is of great significance for ensuring train safety. However, illumination conditions such as over-brightness and insufficient light have a great impact on semi-global matching (SGM) stereo matching, inevitably affecting the integrity and accuracy of the abrasion measurement of the pantograph slipper. To this regard, a robust SGM stereo matching is proposed in this study for the 3D abrasion measurement. Firstly, the combination of the neighborhood information aware Census cost and multiscale fusion for cost aggregation is put forward. While insensitive to illumination condition changes, the improved Census cost can quantify texture information of the neighborhood. Moreover, multiscale cost aggregation further fuses the neighborhood information of different scales. As a result, the performance of SGM in weakly textured areas is greatly improved, especially in complex illumination conditions. EventnaIly, with the help of the sub-pixel disparity refinement and local points fitting, an accurate 3D abrasion calculation is achieved. Practical experiments show the robustness of stereo matching. The precision verification and computation time analysis confirm the measurement accuracy and applicabiIity.

The effect of antenna mutual coupling on signal correlation and bit error rate (BER) of a multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system has been modelled. A MIMO-OFDM model with correlated channels is presented. The correlation matrices are determined with the antenna mutual coupling taken into account. The effect of antenna mutual coupling is characterised using the receiving and transmitting mutual impedances. A rigorous expression for the BER of the system employing quadrature phase-shift keying digital modulation is derived. A 2×2 MIMO-OFDM system using the Alamouti space–time block code for OFDM symbol transmission over 64 sub-channels spanning a 20 MHz band centred at 5.2 GHz is simulated. The simulated results show that the antenna mutual coupling has a significant effect on the BER performance, especially when the spacing between the antenna elements is small.

With the development of semiconductor assembly technology, the continuous requirement for the improvement of chip quality caused an increasing pressure on the assembly manufacturing process. The defects of chip pin had been mostly verified by manual inspection, which has low efficiency, high cost, and low reliability. In this paper, we propose a vision measurement method to detect the chip pin defects, such as the pin warping and collapse that heavily influence the quality of chip assembly. This task is performed by extracting the corner feature of the chip pins, computing the corresponding point pairs in the binocular sequence images, and reconstructing the target features of the chip. In the corner feature step, the corner detection of the pins using the gradient correlation matrices (GCM), and the feature point extraction of the chip package body surface using the crossing points of the fitting lines are introduced, respectively. After obtaining the corresponding point pairs, the feature points are utilized to reconstruct the three dimensional (3D) coordinate information in the binocular vision measurement system, and the key geometry dimension of the pins is computed, which reflects whether the quality of the chip pins is up to the standard. The proposed method is evaluated on the chip data, and the effectiveness is also verified by the comparison experiments.

Focusing on the fields of industrial fault inspection and equipment simulation infrared simulation, this paper conducts research on 3D multimodal fusion reconstruction to address the decoupling problem between thermal distribution and geometric topology caused by the lack of dimensions in traditional 2D detection of infrared thermal imaging. Although Structure-from-Motion (SfM) technology has enabled low-cost 3D digitization, in hand-held uncontrolled scenarios, cross-modal registration failure, camera parameter drift caused by zooming, and texture mapping artifacts of complex structures remain core scientific issues restricting high-precision infrared 3D reconstruction. To address these problems, this paper proposes a low-cost framework named SOAR-3D (Semantic-initialized Optimization and Aware-mapping Reconstruction).This framework innovatively introduces a semantic prior-guided manual point selection robust registration strategy, addressing the challenge of feature matching in heterogeneous images, and realizes real-time correction of camera intrinsic parameter deviations caused by zooming through a joint optimization algorithm. Meanwhile, to tackle the self-occlusion problem of complex industrial parts, a geometry-aware texture mapping mechanism based on depth detection and normal constraint is constructed, and adaptive hole filling is achieved using KD-Tree. Experimental results demonstrate that the proposed method exhibits excellent performance in 3D structure recovery, with the relative dimensional deviation controlled within 0.4%, achieving geometric fidelity close to that of industrial-grade LiDAR; in terms of fusion quality, the reprojection error is as low as 1.9 pixels, and the texture coverage rate reaches 99.8%.Research has demonstrated that the SOAR-3D framework can achieve high-precision 3D thermal field reconstruction on consumer-grade terminals without the need for expensive hardware or cumbersome pre-calibration. It provides an efficient and low-cost technical means for the accurate positioning and defect diagnosis of complex electromechanical facilities, possessing significant engineering application value and academic research significance.