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Simultaneous Fault Diagnosis for sensor and Railway Point Machine for Autonomous Rail System 27

Simultaneous Fault Diagnosis for Sensor and Railway Point Ma...

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27th IEEE International conference on Intelligent Transportation systems, ITSC 2024

作者： Hu, xiaoxi Zhang, xiaohan Chen, Fei Liu, Zongyang Liu, Jin Tan, Lei Tang, Tao Polytechnic Institute Zhejiang University Hangzhou310015 China Wuhan University State Key Laboratory of Water Resources Engineering and Management Wuhan430072 China Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China Institute for Transport Studies University of Leeds LeedsLS2 9JT United Kingdom Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Municipal Engineering Research Institute Beijing100037 China

ISBN: (纸本)9798331505929

Since the safe and reliable behavior of a Railway Point Machine (RPM) is definitely pivotal for rail transportation, scholars and engineers have studied a considerable number of algorithms for RPM fault diagnosis via many kinds of sensor. However, few scholars have considered the possibility that sensors can also experience faults, which cannot be ignored in practical railway applications. To fill the gap, we propose an end-to-end deep learning network named Simultaneous Fault Diagnosis Network (SFDNet) for the simultaneous fault diagnosis for sensor and RPM. Our approach includes Information Aggregate and Update Module (IAUM) and Fault Diagnosis Module (FDM). The IAUM module leverages the concept of Spatial Attention Mechanism (SAM) and Channel Attention Mechanism (CAM) to effectively filter and aggregate information from diverse sensors. It enhances the salience of normal sensor observations while attenuating the influence of anomalous signals, thereby enabling the resultant features to more accurately capture the operational state of the RPMs. The features yielded by SAM are directly employed for sensor fault diagnosis. The FDM integrates Bidirectional Gated Recurrent Units (BiGRUs) and Time-series Feature Pyramid Network (TFPN) to respectively extract and integrate long-term dependencies and multi-scale features, enhancing fault diagnosis in RPM by capturing comprehensive temporal patterns and correlations. Lastly, ablation experiments and comparison studies shows the superiority of our SFDNet. © 2024 IEEE.

关键词： Railroads

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A inertial navigation/laser Doppler velocimeter/geomagnetic sensor integrated navigation method 14

A inertial navigation/laser Doppler velocimeter/geomagnetic ...

引用

14th International conference on Information Optics and Photonics, CIOP 2023

作者： Yajie, Zhang Qi, Wang Jian, Zhou College of Advanced Interdisciplinary Studies National University of Defense Technology Hunan Changsha410073 China Nanhu Laser Laboratory National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781510671744

In solving the problem of random launch of long-distance and high-precision strategic missile trains, the passive autonomous navigation mode dominated by inertial navigation (INS) shows its unique advantages, but the Inertial navigation system has the problem that the accumulated error cannot be eliminated, which cannot meet the practical application requirements, and needs to be assisted by other navigation means. As a passive and fully autonomous navigation system, geomagnetic navigation has the advantages of low cost, anti-interference, all region, small size, and no accumulated error, which can effectively compensate for the shortcomings of other current navigation systems. In this paper, we introduce high-precision laser Doppler velocimeter (LDV) and geomagnetic sensor into the integrated system, and propose a geomagnetic sensor assisted INS/LDV integrated positioning scheme. On the basis of INS/LDV integration, we design INS/LDV/geomagnetic sensor integrated navigation system and algorithm, correct the error of NS/LDV integrated navigation system, and further improve the integrated navigation positioning accuracy. © 2023 SPIE.

关键词： Doppler effect

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sensor and Microcontroller based 360 Degree Car Assistance System 4

Sensor and Microcontroller based 360 Degree Car Assistance S...

引用

4th International conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Jenit Elavarasi, J. Franklin, Abilash Nagarajan, Srideivanai Hindustan Institute of Technology and Science Department of Computer Applications Tamil Nadu Chennai India

ISBN: (纸本)9798350300093

The 360 Degree Car Assistance System automatically applies emergency brakes when necessary and regulates a vehicle's speed based on the proximity of an object. Damages that may be made while driving will be avoided by this approach. The car's undercarriage is vulnerable to hit from the ground and vice versa, and the region is also hidden from the driver's view. Thus, in order to avoid this, a survey was conducted, and this project was built in such a manner that it would identify the item and alert the driver if there were any impediments beneath the car that are close to the Chassis and the Wheels. A prototype of the car is created and used in this project. The system uses an Ultrasonic sensor and AT Mega to detect obstructions, and it allows the execution of emergency braking in accordance with pre-burnt code in the AT Mega. Consequently, a cost-effective automatic collision avoidance system is suggested. In order to avoid and prevent accidents all automobile models can use the 360 Degree Car Assistance System that has been designed. © 2023 IEEE.

关键词： advanced driver assistance systems

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Fluid depth sensor using surface acoustic wave resonator 18

Fluid depth sensor using surface acoustic wave resonator

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conference on Active and Passive Smart Structures and Integrated systems XVIII

作者： Sreejith, V. S. Naghdi, M. Aslam, M. Z. Desai, M. H. Ju, S. Chinka, S. K. Zhang, H. Univ North Texas Dept Mech Engn Denton TX 76207 USA Univ North Texas Dept Elect Engn Denton TX 76207 USA

ISBN: (数字)9781510671997

ISBN: (纸本)9781510671997;9781510671980

Fluid depth measurement finds practical applications across various industries, including petroleum, water treatment processes, nuclear technology, and household appliances. Traditional methods include magnetic, radiation, linear variable differential transformers, LASER, pressure, capacitive, float, conductivity probe, fiber optics, ultrasonic, and triple bubbler sensors. Despite its promising attributes, such as suitability for low to very high-temperature environments, wireless interrogation, battery-less operation, and compact size, the application of piezoelectric Surface Acoustic Wave (SAW) sensors in fluid depth measurement has been comparatively unexplored in the current body of literature. This research presents a depth gauge engineered for fluid depth assessment employing a Surface Acoustic Wave (SAW) resonator. The apparatus comprises a 20 mu m thick aluminum diaphragm, with a quartz SAW resonator affixed to it. Employing an 868 MHz quartz SAW resonator enables the precise measurement of minute depth variations, with a remarkable sensitivity of 532 Hz/mm (equivalent to 0.61 ppm/mm), allowing for accurate detection of changes as small as 1 mm.

关键词： Depth gauge pressure sensor SAW strain measurement

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Miniature Modular sensor for Chemical Species Tomography with Enhanced Spatial Resolution

Miniature Modular Sensor for Chemical Species Tomography wit...

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2023 IEEE International conference on Imaging systems and Techniques, IST 2023

作者： Zhang, Rui xia, Jiangnan McCann, Hugh Liu, Chang Ahmed, Ihab Pourkashanian, Mohamed Gough, Andrew Armstrong, Ian Lengden, Michael Johnstone, Walter University of Edinbutgh School of Engineering Edinburgh United Kingdom University of Sheffield Department of Mechanical Engineering Sheffield United Kingdom University of Strathclyde Department of Electronic and Electrical Engineering Glasgow United Kingdom

ISBN: (纸本)9798350330830

The introduction of low/zero-carbon fuels in gas turbine engines poses challenges to the stability and efficiency of combustion processes. As a result, there is a growing demand for advanced imaging techniques that can provide enhanced spatial resolution to monitor and analyze the physiochemical parameters involved. Chemical Species Tomography (CST), utilizing multiple line-of-sight Laser Absorption Spectroscopy (LAS) measurements, has gained popularity in industrial applications due to its non-intrusive nature, robustness, and high sensitivity. Typically, existing CST sensors have few centimeters beam spacing and are highly customized for specific applications. Therefore, the limited beam spacing, and lack of generality pose challenges in terms of providing sufficient sampling and adaptability for wider application scenarios. To enhance the spatial resolution as well as improve the reconfiguration of the CST sensors, this paper proposes a miniature modular CST sensor with a 1cm beam spacing. The use of off-The-shelf components significantly reduces the cost of the system, making it more practical for industrial implementation. Experimental evaluation of the prototype sensor has been conducted for measurements of temperature and water vapor concentration. The results show consistent and accurate measurements, indicating good reliability of the sensor. The proposed miniature modular sensor offers increased flexibility and adaptability to the various CST systems, paving the way for its commercialization in industrial settings. © 2023 IEEE.

关键词： Tomography

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A Deep Dive into Existing Lip Reading Technologies

A Deep Dive into Existing Lip Reading Technologies

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2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Khekare, Ganesh Majumder, Goutam Shelke, Nilesh Sakarkar, Gopal Buchade, Siddhant School of Computer Science and Engineering Vellore Institute of Technology Vellore India Symbiosis Institute of Technology Nagpur Campus Symbiosis International Deemed University Pune India Dr. Vishwanath Karad MIT World Peace University Department of Computer Science and Applications Pune India

ISBN: (纸本)9798331517953

Lip reading, or Visual Speech Recognition (VSR), can revolutionize communication for those with hearing loss and in noisy environments. The researchers are trying to create advanced VSR systems using Deep learning models to overcome challenges. But still, several difficulties are there such as different shapes of lips during the video and different lightning conditions that can make deciphering or visualization difficult. Deep learning with the help of Convolutional Neural Networks (CNNs) helps to identify the exact shape and movement of a lip from a video frame. The continuous flow of lip movements in the video is handled by Recurrent Neural Networks (RNNs) which help in identifying words. However, RNNs are not good enough to remember the historical data. This issue is resolved by using Long Short Term Memory (LSTM) in the proposed research work. LSTMs have an additional internal memory that helps to store the history information for a longer period which helps to predict lip movement accurately even in rapid speech. The GRID and LRW datasets are used to generate the results. Additionally, VSR could improve video conferencing, allowing for natural communication even with compromised microphone quality. The impact of VSR extends beyond human-to-human and human-computer interaction. Frameworks like Streamlit offer a glimpse into the future, enabling the development of user-friendly lip reading applications. Deep learning unlocks the power of lip reading, paving the way for a future where communication go beyond the limitations of sound. © 2024 IEEE.

关键词： Video conferencing

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Research on multi-node gait information acquisition system and time synchronization based on BLE 6

Research on multi-node gait information acquisition system a...

引用

6th International conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2024

作者： Gao, Yuqi Yu, Chao Zhou, Xu Liu, Junjie Yao, Zhiming Lin, Ning Institute of intelligent Machines Hefei Institutes of Physical Science Chinese Academy of Sciences University of Science and Technology of China Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Department of Neurosurgery The Affliated Chuzhou Hospital of Anhui Medical University The First People's Hospital of Chuzhou Chuzhou China

ISBN: (纸本)9798331541699

Gait information is critical in various domains. However, achieving accurate time synchronization across multiple sensor nodes in wireless systems remains a challenge, particularly in gait information acquisition, where precise data alignment is essential. Current solutions are limited by high power consumption, system complexity, and transmission instability. This study proposes a multi-node gait information acquisition system incorporating a six-axis inertial sensor and a plantar pressure sensor, with the ESP32 serving as the core processing unit. The system utilizes the low-power Bluetooth protocol for real-time data transmission. To address the issue of time desynchronization, we introduce an average error-based time synchronization algorithm. The algorithm was tested in an experimental setup using a signal generator, two gait systems, and a mobile device. The results demonstrate that the average error method effectively estimates and corrects frequency drift, significantly reducing time synchronization errors. The system offers a low-power, high-precision solution for multi-node gait information acquisition, advancing the accuracy of gait data fusion and analysis. © 2024 IEEE.

关键词： sensor nodes

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Raman Distributed Temperature sensor Based on Pulse Compression Technique Using Hybrid Modulation Method 12

Raman Distributed Temperature Sensor Based on Pulse Compress...

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conference on advanced sensor systems and applications xiI

作者： Zeng, Sida Fan, xinyu He, Zuyuan Shanghai Jiao Tong Univ Dept Elect Engn State Key Lab Adv Opt Syst & Networks 800 Dongchuan Rd Shanghai 200240 Peoples R China Peng Cheng Lab Shenzhen 518055 Guangdong Peoples R China

ISBN: (纸本)9781510657090;9781510657083

In this paper, a novel distributed Raman distributed temperature sensing system based on pulse compression technique using hybrid modulation method is proposed. The structure of the new system and the corresponding modulation and demodulation methods are described. The system performance is verified by experiments. This scheme solves the inherent problem of mutual restrictions between spatial resolution and temperature resolution existed in conventional Raman distributed temperature sensing systems. Compared with other modulation schemes that do not use coding, the hybrid modulation method using in-pulse sweeping and inter-pulse coding can alleviate the transient effect, and reduce the peak power to avoid the influence of nonlinear effect, which improve the signal-to-noise ratio, and obtain a better performance.

关键词： Raman distributed temperature sensor pulse compression technique hybrid modulation method

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Predicting Carbon Dioxide Emissions from Energy Consumption in China with Long Short-Term Memory and Support Vector Regression Models 11th

Predicting Carbon Dioxide Emissions from Energy Consumption ...

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11th International conference on Robot Intelligence Technology and applications, RiTA 2023

作者： Tang, Lisirui Zhao, Peng Majeed, Anwar P. P. Abdul School of Artificial Intelligence and Advanced Computing Xi’an Jiaotong-Liverpool University Taicang Suzhou215400 China Department of Health and Environmental Sciences School of Science Xi’an Jiaotong-Liverpool University Suzhou Industrial Park Suzhou215123 China School of Engineering and Technology Sunway University Bandar Sunway Malaysia

ISBN: (纸本)9783031706868

Climate change is a pressing global issue that needs immediate attention. The primary cause of climate change is global warming resulting from the anthropogenic emissions of greenhouse gases (GHGs). The combustion of fuels required to meet the energy demand accelerates carbon emissions, contributing to the increase of ambient GHGs. In this study, we investigated the prediction of carbon dioxide (CO2, the most important GHG) emissions resulting from energy consumption in China using Long Short-Term Memory (LSTM) and Support Vector Regression (SVR), based on the energy consumption data and annual CO2 emissions per unit of energy data from 1965 to 2022. The results indicate that the LSTM model outperforms the others. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Greenhouse gas emissions

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Elevating Security in Wireless sensor Networks using ECC and AES Cryptographic Techniques

Elevating Security in Wireless Sensor Networks using ECC and...

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2023 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Dayana, D.S. Pandian, R. Babu, A. Ramesh Nirmalraj, S. Jebaseelan, S. D. Sundarsingh Mohan, V. SRM Institute of Science and Technology Dept. of Networking and Communications India Sathyabama Institute of Science and Technology Dept. of Electronics and Communication Engineering India Sathyabama Institute of Science and Technology Dept. of Electrical and Electronics Engineering India

ISBN: (纸本)9798350319200

This research article stands as a formidable response to the security vulnerabilities that loom over wireless sensor networks (WSNs). In a pioneering stride, the study introduces an advanced cryptographic framework designed to tackle these vulnerabilities head-on. The heart of this framework lies in the seamless integration of two potent cryptographic forces: Elliptic Curve Cryptography (ECC) and the advanced Encryption Standard (AES). The result is the ECC and AES cryptographic amalgamation, positioned as a robust solution to fortify the security of data transmission within WSNs. Engineered with a keen understanding of the challenges posed by resource-constrained environments - a hallmark of WSNs - the ECC and AES cryptographic system emerges as a beacon of security. This fusion optimizes security protocols while meticulously curtailing memory and energy consumption. The research outcomes hold promise for a transformative impact on WSNs, elevating the data protection landscape to unprecedented heights. This article transcends the boundaries of conventional security measures by presenting a cutting-edge framework that redefines security paradigms within WSNs. As modern applications continue to rely on the seamless and secure flow of data, the ECC and AES cryptographic solution emerges as an emblem of innovation, poised to elevate the potency of security protocols within the WSN domain. © 2023 IEEE.

关键词： advanced Encryption Standard (AES) data protection Elliptic Curve Cryptography (ECC) security vulnerabilities Wireless sensor Networks (WSNs)

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