Latest Publications on Signal Processing
This is our latest selection of worldwide publications on Signal Processing, between many scientific online journals, classified and focused on signal processing, quantization, denoising, digital signal, analog signal and convolution.
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Prediction of Member Forces of Steel Tubes on the Basis of a Sensor System with the Use of AI
On 2025-02-03 by Haiyu Li, Heungjin Chung @MDPI
Keywords: prediction, member forces, sensor system, AI, structural health monitoring
AI summary: Development of AI-based sensor system for predicting forces on steel tubes in offshore wind turbine support systems. Improvement in predictive performance using machine learning algorithms. Optimization of input variables for cost-effective and accurate structural health monitoring. Creation of GUI-based system for real-time prediction of steel tube member forces.
Abstract: The rapid development of AI (artificial intelligence), sensor technology, high-speed Internet, and cloud computing has demonstrated the potential of data-driven approaches in structural health monitoring (SHM) within the field of structural engineering. Algorithms based on machine learning (ML) models are capable of discerning intricate structural behavioral patterns from real-time data gathered by sensors, thereby offering solutions to engineering quandaries in structural mechanics and SHM. Thi[...]
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Enhancing Driving Safety of Personal Mobility Vehicles Using On-Board Technologies
On 2025-02-03 by Eru Choi, Tuan Anh Dinh, Min Choi @MDPI
Keywords: safety technologies, driving assistance system, object detection, hardware acceleration, mobility devices
AI summary: Prevent accidents with driving assistance system using sensors and camera. Improve performance of object detection with hardware acceleration. YOLO model accelerated on specialized hardware for high accuracy in detecting obstacles. Future research will focus on enhancing system performance for electric wheelchair safety.
Abstract: Accidents involving electric wheelchairs are a growing concern, with users frequently encountering obstacles that lead to collisions, tipping, or loss of balance. These incidents underscore the need for advanced safety technologies tailored to electric wheelchair users. This research addresses this need by developing a driving assistance system to prevent accidents and enhance user safety. The system incorporates ultrasonic sensors and a front-facing camera to detect obstacles and provide real-t[...]
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Bearing Fault Diagnosis Grounded in the Multi-Modal Fusion and Attention Mechanism
On 2025-02-03 by Jianjian Yang, Haifeng Han, Xuan Dong, Guoyong Wang, Shaocong Zhang @MDPI
Keywords: fault diagnosis, multi-modal fusion, attention mechanism, convolutional neural networks, self-attention mechanism
AI summary: Novel method for bearing fault diagnosis using Fusion Attention Network (FAN-BD), validated with public dataset, achieves high accuracy and robustness, outperforming mainstream algorithms.
Abstract: This paper proposes a novel method called Fusion Attention Network for Bearing Diagnosis (FAN-BD) to address the challenges in effectively extracting and fusing key information from current and vibration signals in traditional methods. The research is validated using the public dataset Vibration, Acoustic, Temperature, and Motor Current Dataset of Rotating Machines under Varying Operating Conditions for Fault Diagnosis. The method first converts current and vibration signals into two-dimensional[...]
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Fault Diagnosis of Wire Disconnection in Heater Control System Using One-Dimensional Convolutional Neural Network
On 2025-02-03 by Jiawei Guo, Linfeng Sun, Takahiro Kawaguchi, Seiji Hashimoto @MDPI
Keywords: convolutional neural network, fault diagnosis, heater control system, disconnection, intelligent diagnostic model
AI summary: Fault diagnosis of wire disconnection in heater control system using CNN. Early and accurate diagnosis crucial to prevent system failures. Proposed model achieves 98% accuracy using experimental data. Feasible and high diagnostic accuracy demonstrated through analysis.
Abstract: Heaters are critical components in various heating control systems, and their faults are often a primary cause of system failure, drawing significant attention from engineers and researchers. Early and accurate fault diagnosis is crucial to prevent cascading failures. Many diagnostic methods target faults under generally stable and simple operating conditions, such as constant load or steady-state temperature. However, real-world scenarios are often complex and variable, involving dynamic loads,[...]
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Hypercomplex Numbers—A Tool for Enhanced Efficiency and Intelligence in Digital Signal Processing
On 2025-02-03 by Zlatka Valkova-Jarvis, Maria Nenova, Dimitriya Mihaylova @MDPI
Keywords: hypercomplex numbers, digital signal processing, engineering sciences, numerical systems, information and communication technologies
AI summary: Overview of numerical systems in engineering science, proposing approaches for hypercomplex numbers representation, importance of understanding hypercomplex numbers, potential of hypercomplex DSP.
Abstract: Mathematics is the wide-ranging solid foundation of the engineering sciences which ensures their progress by providing them with its unique toolkit of rules, methods, algorithms and numerical systems. In this paper, an overview of the numerical systems that have currently found an application in engineering science and practice is offered, while also mentioning those systems that still await full and comprehensive applicability, recognition, and acknowledgment. Two possible approaches for repres[...]
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Multi-Function Working Mode Recognition Based on Multi-Feature Joint Learning
On 2025-02-03 by Lei Liu, Minghua Wu, Dongyang Cheng, Wei Wang @MDPI
Keywords: recognition, multi-feature, joint learning, convolutional neural networks, Transformers
AI summary: Improved adaptability through joint learning framework using CNNs and Transformers for MFR working mode recognition, capturing dynamic patterns and semantic information for robust identification in complex environments.
Abstract: With advancements in phased array and cognitive technologies, the adaptability of modern multifunction radars (MFRs) has significantly improved, enabling greater flexibility in waveform parameters and beam scheduling. However, these enhancements have made it increasingly difficult to establish fixed relationships between working modes using traditional radar recognition methods. Furthermore, conventional approaches often exhibit limited robustness and computational efficiency in complex or noisy[...]
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