Optimized Fault Detection Algorithm Aided by BDS Baseband Signal for Train Positioning

Wang, Ershen; Yang, Di; Wang, Chuanyun; Huang, Yufeng; Qu, Pingping; Pang, Tao

doi:10.1049/cje.2019.09.004

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…After global average pooling, the final output size is 5. After softmax activation layer, the final output of bridge health state prediction is realized, that is, multiclassification prediction of bridge health state [19].…”

Section: Bridge Health Status Identificationmentioning

confidence: 99%

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Song¹

2022

Advances in Multimedia

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In order to alleviate the impact of the old bridge by the environment and its own life and the problem of increasing maintenance cost, the intelligent building integrated evaluation system based on BIM technology is proposed. Firstly, based on BIM technology, an all-weather hardware monitoring system is constructed by using multiple sensors laid on the bridge. The software communicates with the monitoring system through 5G public network and applies the unique advantages of deep neural network in classification to the assessment of the health status of old bridges with the help of the multiclassification convolutional neural network embedded in the software. The test results show that the preprocessed data is imported into the health diagnosis module for training, and the training accuracy reaches about 70%, and the loss curve is stable at about 0.5. Conclusion. The system meets the design requirements and solves the problem of difficult health diagnosis caused by long monitoring period and low efficiency of old bridges. The system has advantages of low difficulty in obtaining parameters, high precision, and accurate health assessment.

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Section: Bridge Health Status Identificationmentioning

confidence: 99%

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Song¹

2022

Advances in Multimedia

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“…In formula (1), is n t the first n feature item in w of the text, and is the feature weight corresponding to the i d feature item n t . The weighted algorithm TF-IDF (Term Frequency -Inverse Document Frequency) algorithm is often used in data mining, and its core idea is to evaluate the importance of a word to a certain document in the corpus, its calculation formula is shown in the formula.…”

Section: A Application Of Improved Fp-growth Algorithm In Signal Faul...mentioning

confidence: 99%

“…With the rapid development of China's railways in recent years, the safety requirements for railway transportation are becoming increasingly strict. With the in-depth development and application of information technology, the era of big data has come [1]. In the aspect of railway, the important premise to ensure traffic safety is to ensure the normal operation of railway signal equipment.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis Technology of Railway Signal Equipment based on Improved FP-Growth Algorithm

Yang¹

2022

IJACSA

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The rapid development of computer information technology has made various fault diagnosis and detection technologies emerge in an endless stream. As one of the main transportation vehicles, the detection efficiency of fault diagnosis of railway signal equipment has important practical significance for maintaining the overall safe operation of railways. On the basis of the traditional FP-Growth algorithm, improve the TF-IDF algorithm to realize the weight discretization of text features, and realize the improvement of the FP-Growth algorithm by adjusting the adaptive confidence and support. The FP-Growth algorithm will be improved. FP-Growth algorithm is used for performance tests and applications. The results show that the minimum running time-saving of the proposed algorithm is 1500ms, and the average accuracy of P@N exceeds 85%, which is higher than that of the FP-Growth algorithm (81.4%) and VSM algorithm (82.1%). The PR curve of the improved algorithm is closer to the upper right, which effectively ensures the processing of correlated data, and the overall average precision performance under the influence of positive and negative signal-to-noise ratio values exceeds 95%. And the signal curve generated by the algorithm. The error range of the data under the four fault types of track circuit, turnout, signal, and connecting line floats between 1% and 5%. The improved FP-Growth algorithm can effectively analyze railway fault types and data. Perform analysis and data processing to minimize diagnostic errors.

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“…Thus, all satellites in the constellation can be connected without global stations, and the satellites can continue to provide services even if they are disconnected from the ground. Because of these advantages, BDS begins to be widely used to measure height [29], vehicle position [30], anomaly detection [31], and train position [32], etc. Some scholars propose to combine BDS with other positioning technologies to produce higher cost performance [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

A Monitoring System Based on NB-IoT and BDS/GPS Dual-Mode Positioning

et al. 2022

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Monitoring system is widely used to detect the environment parameters such as temperature, humidity and position information in cold chain logistic, modern agriculture, hospital and so on. Poor position precision, high communication cost, high packet loss rate are the main problems in current monitoring system. To solve these problems, the paper presents a new monitoring system based on Narrow Band Internet of Things (NB-IoT) and BeiDou system/Global System Position (BDS/GPS) dual-mode positioning. Considering the position precision, a dual-mode positioning circuit based on at6558 is designed, and the calculation formula of the positioning information of the monitored target has been derived. Subsequently, a communication network based on wh-nb75-ba NB-IoT module is designed after compared with the LoRa technology. According to the characteristics of high time correlation of sensor data, an adaptive optimal zero suppression (AOZS) compression algorithm is proposed to improve the efficiency of data transmission. Experiments prove the feasibility and effectiveness of the system from the aspects of measurement accuracy, positioning accuracy and communication performance. The temperature and humidity error are less than 1 °C and 5% RH respectively with the selected sensor chips. The position error is decided by several factors, including the number of satellites used for positioning, the monitored target moving speed and NB-IoT module lifetime period. When the monitored target is stationary, the positioning error is about 2 m, which is less than that of the single GPS or BDS mode. When the monitored target moves, the position error will increase. But the error is still less than that of the single GPS or BDS mode. Then the AOZS compression algorithm is used in actually experiment. The compression ratio (CR) of it is about 10% when the data amount increasing. In addition, the packet loss rate test experiment proves the high reliability of the proposed system.

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Optimized Fault Detection Algorithm Aided by BDS Baseband Signal for Train Positioning

Cited by 8 publications

References 11 publications

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Fault Diagnosis Technology of Railway Signal Equipment based on Improved FP-Growth Algorithm

A Monitoring System Based on NB-IoT and BDS/GPS Dual-Mode Positioning

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