Vision-Based Damage Detection Method Using Multi-Scale Local Information Entropy and Data Fusion by Yiming Zhang, Zili Xu, Guang Li, Cun Xin

“…To tackle these challenges, we propose a novel vision-based damage detection method combining multi-scale signal analysis theory and data fusion algorithm. For high-spatial-resolution vibration measurements, phase-based optical flow estimation algorithm is adopted to deploy virtual sensors on the structure, yielding reliable mode shapes. …”
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Experimental Study on the Measurement of Water Bottom Vibration Induced by Underwater Drilling Blasting by Gu Wenbin, Chen Jianghai, Wang Zhenxiong, Wang Zhihua, Liu Jianqing, Lu Ming

“…It shows that the water bottom vibration monitor could collect vibration signals quite effectively in underwater environments. The followed signal analysis shows that the characteristics of water bottom vibration and land ground vibration induced by the same underwater drilling blasting are quite different due to the different geological environments. …”
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Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition by Jiaquan Yan, Haixin Sun, En Cheng, Xiaoyan Kuai, Xiaoliang Zhang

“…First, the observed signals are decomposed into high resonance component, low resonance component, and residual component by RSSD, which is a nonlinear signal analysis method based not on frequency or scale but on resonance. …”
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Interpretable DWT-1DCNN-LSTM Network for Power Quality Disturbance Classification by Shuangquan Yang, Tao Shan, Xiaomei Yang

“…Although deep learning methods have high accuracy, their lack of interpretability can limit their acceptance in engineering applications. Traditional signal analysis has a good physical foundation, but it is not integrated with deep learning to a sufficient degree. …”
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Multi-Band Torsional Vibration Amplitude Demodulation for Planetary Gearbox Fault Diagnosis Under Time-Varying Speed Conditions by Xiaowang Chen, Yubo Sun, Ying Zhang, Zhipeng Feng

“…Torsional vibration signal analysis is promising for diagnosing gear faults in planetary gearboxes. …”
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ECG heartbeat classification using progressive moving average transform by Rabah Mokhtari, Samir Brahim Belhouari, Khelil Kassoul, Abderraouf Hocini

“…The approach aims to enhance signal analysis and classification, particularly in the context of heartbeat classification. …”
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EEG-Based ADHD Classification Using Autoencoder Feature Extraction and ResNet with Double Augmented Attention Mechanism by Jayoti Bansal, Gaurav Gangwar, Mohammad Aljaidi, Ali Alkoradees, Gagandeep Singh

“…Method: This research endeavor sought to establish an objective diagnostic modality for ADHD through the utilization of electroencephalography (EEG) signal analysis. With the use of innovative deep learning techniques, this research seeks to improve the diagnosis of ADHD using EEG data. …”
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Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain by Juan Jose Saucedo-Dorantes, Miguel Delgado-Prieto, Juan Antonio Ortega-Redondo, Roque Alfredo Osornio-Rios, Rene de Jesus Romero-Troncoso

“…In this work, the influence of vibrations over the system is observed by performing motor current signal analysis to detect the presence of faults. The obtained results show the feasibility of detecting multiple faults in a kinematic chain, making the proposed methodology suitable to be used in the application of industrial machinery diagnosis.…”
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Hybrid Empirical and Variational Mode Decomposition of Vibratory Signals by Eduardo Esquivel-Cruz, Francisco Beltran-Carbajal, Ivan Rivas-Cambero, José Humberto Arroyo-Núñez, Ruben Tapia-Olvera, Daniel Guillen

“…Signal analysis is a fundamental field in engineering and data science, focused on the study of signal representation, transformation, and manipulation. …”
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Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning by Lixian Shi, Qiushi Cui, Yang Weng, Yigong Zhang, Shilong Chen, Jian Li, Wenyuan Li

“…However, traditional detection methods cannot achieve satisfactory performance when faced with limited data. Besides, some signal analysis methods based on waveform conversion to images cannot obtain understandable image data and cannot analyze both current and voltage signals simultaneously. …”
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Bidimensional Increment Entropy for Texture Analysis: Theoretical Validation and Application to Colon Cancer Images by Muqaddas Abid, Muhammad Suzuri Hitam, Rozniza Ali, Hamed Azami, Anne Humeau-Heurtier

“…Entropy algorithms are widely applied in signal analysis to quantify the irregularity of data. …”
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A novel denoising method for non‐linear and non‐stationary signals by Honglin Wu, Zhongbin Wang, Lei Si, Chao Tan, Xiaoyu Zou, Xinhua Liu, Futao Li

“…Abstract Signal denoising is a crucial step in signal analysis. Various procedures have been attempted by researchers to remove the noise while preserving the effective components of the signal. …”
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Spatial Cognitive EEG Feature Extraction and Classification Based on MSSECNN and PCMI by Xianglong Wan, Yue Sun, Yiduo Yao, Wan Zuha Wan Hasan, Dong Wen

“…Electroencephalogram (EEG) signal analysis presents substantial potential in spatial cognitive assessments. …”
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Piezoelectric biosensor with dissipation monitoring enables the analysis of bacterial lytic agent activity by Radka Obořilová, Eliška Kučerová, Tibor Botka, Hana Vaisocherová-Lísalová, Petr Skládal, Zdeněk Farka

“…Furthermore, the dissipation signal analysis facilitated the precise real-time monitoring of phage-mediated lysis. …”
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A 1.5D Spectral Kurtosis-Guided TQWT Method and Its Application in Bearing Fault Detection by Xiong Zhang, Ming Zhang, Shuting Wan, Rujiang Hao, Yuling He, Xiaolong Wang

“…Through experimental signal analysis, TQWT has good sparsity decomposition characteristics and can reasonably divide the signal frequency band, so as to separate the useful fault characteristic frequency band and interference frequency band. …”
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Population structure, selection signal and introgression of gamecocks revealed by whole genome sequencing by Naiyi Xu, Linyun Zhang, Feifan Chen, Zhengfu Feng, Jiangtao Zheng, DongHua Li, Yongju Zhao, Xiangtao Kang

“…Therefore, in this study, based on whole genome data of gamecocks, Chinese indigenous chickens, commercial chickens and wild jungle fowls, we performed population structure analysis, selection signal analysis, and genomic introgression analysis of gamecocks. …”
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An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst by Quanjie Zhu, Qingsong Li, Yu Feng, Xianwei Heng, Shaoquan Li, Tao Yang

“…The methodology presented in this paper for CGOB signal analysis provides a new method to obtain MS response precursor and predict CGOB disaster. …”
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Effect of EOG Signal Filtering on the Removal of Ocular Artifacts and EEG-Based Brain-Computer Interface: A Comprehensive Study by Malik M. Naeem Mannan, M. Ahmad Kamran, Shinil Kang, Myung Yung Jeong

“…Therefore, for BCI and clinical applications, it is very important to remove/reduce these artifacts before EEG signal analysis. Although, EOG-based methods are simple and fast for removing artifacts but their performance, meanwhile, is highly affected by the bidirectional contamination process. …”
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Comparative analysis of techno-economic and techno-environmental approach to optimal sizing and dispatch of hybrid solar–battery systems by Luka Smajila, Silvia Trevisan, Farzin Golzar, Ketan Vaidya, Rafael Guedez

“…Future research could further refine optimisation strategies for PV-BESS systems by delving deeper into specific aspects such as grid signal analysis and diverse end-of-life (EoL) pathways.…”
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Klasifikasi Sinyal Phonocardiogram Menggunakan Short Time Fourier Transform dan Convolutional Neural Network by Muhammad Alwi Adnan Amal, Dodi Zulherman, Rahmat Widadi

“…However, the use of PCG electronically requires complex signal analysis to classify heart conditions. This study aims to design a PCG signal classification system based on the extraction method using the Short Time Fourier Transform (STFT) and the classification method using the Convolutional Neural Network (CNN). …”
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