Development of DMPS-EMAT for Long-Distance Monitoring of Broken Rail

Guo, Weijun; Yu, Zhiyang; Chui, Hsiang‐Chen; Chen, Xiaoming

doi:10.3390/s23125583

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…A literature review revealed many publications of research results aimed at increasing the sensitivity and information content of the electromagnetic-acoustic monitoring method [12][13][14][15]. Of particular interest are research and development on non-contact testing of extended and large-sized metal structures by scanning them with acoustic waves generated by electromagnetic-acoustic transducers [16]. But these studies are mainly aimed at improving the design of electromagnetic-acoustic converters and developing new methods for isolating and processing information contained in the parameters of acoustic waves.…”

Section: Introductionmentioning

confidence: 99%

Study of the relationship between the parameters of electromagnetic-acoustic transformation and the stress-strain state of the metal to solve the problem of remote monitoring of power equipment

Bashirov,

Bashirova,

Yusupova

et al. 2024

E3S Web Conf.

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The implementation of Russia’s energy strategy provides for the creation of an intelligent control system for active-adaptive electrical networks of the electric power complex, which contains a system for remote diagnostic monitoring of energy equipment, including metal load-bearing structures of electrical energy generation, transmission and consumption facilities. Promising in this regard is the use of a high-performance electromagnetic-acoustic method, which allows non-contact detection of metal defects and monitoring of their stress-strain state. But existing electromagnetic-acoustic diagnostic tools do not have sufficient sensitivity and information content to solve this problem. The article presents the results of experimental studies aimed at identifying and processing informative parameters of electromagnetic-acoustic transformation for the implementation of remote diagnostic monitoring of the stress-strain state and metal damage of power equipment. Based on the research results, it was proposed to use a frequency model formed as a result of spectral analysis of the electromagnetic-acoustic transducer signal as an integral parameter characterizing the state of the metal.

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Section: Introductionmentioning

confidence: 99%

Study of the relationship between the parameters of electromagnetic-acoustic transformation and the stress-strain state of the metal to solve the problem of remote monitoring of power equipment

Bashirov,

Bashirova,

Yusupova

et al. 2024

E3S Web Conf.

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“…EMAT equipment, transducers [19], and measurement methods have reached relative maturity. Current thickness measurement schemes mainly include the following:…”

Section: Introductionmentioning

confidence: 99%

Thickness Measurements with EMAT Based on Fuzzy Logic

Shi,

Tian,

Jiang

et al. 2024

Sensors

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Metal thickness measurements are essential in various industrial applications, yet current non-contact ultrasonic methods face limitations in range and accuracy, hindering the widespread adoption of electromagnetic ultrasonics. This study introduces a novel combined thickness measurement method employing fuzzy logic, with the aim of broadening the applicational scope of the EMAT. Leveraging minimal hardware, this method utilizes the short pulse time-of-flight (TOF) technique for initial thickness estimation, followed by secondary measurements guided by fuzzy logic principles. The integration of measurements from the resonance, short pulse echo, and linear frequency modulation echo extends the measurement range while enhancing accuracy. Rigorous experimental validation validates the method’s effectiveness, demonstrating a measurement range of 0.3–1000.0 mm with a median error within ±0.5 mm. Outperforming traditional methods like short pulse echoes, this approach holds significant industrial potential.

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Research on a Joint Extraction Method of Track Circuit Entities and Relations Integrating Global Pointer and Tensor Learning

Chen,

2024

Sensors

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To address the issue of efficiently reusing the massive amount of unstructured knowledge generated during the handling of track circuit equipment faults and to automate the construction of knowledge graphs in the railway maintenance domain, it is crucial to leverage knowledge extraction techniques to efficiently extract relational triplets from fault maintenance text data. Given the current lag in joint extraction technology within the railway domain and the inefficiency in resource utilization, this paper proposes a joint extraction model for track circuit entities and relations, integrating Global Pointer and tensor learning. Taking into account the associative characteristics of semantic relations, the nesting of domain-specific terms in the railway sector, and semantic diversity, this research views the relation extraction task as a tensor learning process and the entity recognition task as a span-based Global Pointer search process. First, a multi-layer dilate gated convolutional neural network with residual connections is used to extract key features and fuse the weighted information from the 12 different semantic layers of the RoBERTa-wwm-ext model, fully exploiting the performance of each encoding layer. Next, the Tucker decomposition method is utilized to capture the semantic correlations between relations, and an Efficient Global Pointer is employed to globally predict the start and end positions of subject and object entities, incorporating relative position information through rotary position embedding (RoPE). Finally, comparative experiments with existing mainstream joint extraction models were conducted, and the proposed model’s excellent performance was validated on the English public datasets NYT and WebNLG, the Chinese public dataset DuIE, and a private track circuit dataset. The F1 scores on the NYT, WebNLG, and DuIE public datasets reached 92.1%, 92.7%, and 78.2%, respectively.

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Development of DMPS-EMAT for Long-Distance Monitoring of Broken Rail

Cited by 3 publications

References 32 publications

Study of the relationship between the parameters of electromagnetic-acoustic transformation and the stress-strain state of the metal to solve the problem of remote monitoring of power equipment

Study of the relationship between the parameters of electromagnetic-acoustic transformation and the stress-strain state of the metal to solve the problem of remote monitoring of power equipment

Thickness Measurements with EMAT Based on Fuzzy Logic

Research on a Joint Extraction Method of Track Circuit Entities and Relations Integrating Global Pointer and Tensor Learning

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