Article
Computer Science, Information Systems
Zhiqiang Zeng, Rui Zhang, Wenan Cai, Yanfeng Li
Summary: This paper presents a time-frequency analysis method based on image enhancement using the local maximum synchrosqueezing transform, which improves the identification of bearing fault characteristics. The proposed method achieves clearer extraction of fault features and achieves a high accuracy rate.
Article
Engineering, Electrical & Electronic
Longbiao Cheng, Junfeng Li, Yonghong Yan
Summary: In this paper, a novel feature-specific convolutional neural network (FSCNet) is proposed for real-time speech enhancement. By dynamically parameterizing convolution kernels, leveraging long-term global contexts, and considering the importance of each feature channel, the network outperforms existing algorithms.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Automation & Control Systems
Xufeng He, Zhihua Chen, Lei Dai, Lei Liang, Jianfa Wu, Bin Sheng
Summary: In this study, a global-and-local aware network (GLAN) is proposed to address the complex and unpredictable degradation in nighttime or backlit photos. By projecting features into the frequency domain and incorporating them in a knowledge-sharing manner, GLAN effectively integrates global modeling capability and local sensitivity to represent structure and texture. The method achieves competitive results through feature extraction, multi-scale feature construction, adaptive multi-scale feature block, multi-scale channel attention module, pixel attention module, and frequency-aware interaction module.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Pingping Bing, Wei Liu, Yang Liu
Summary: The proposed seismic time-frequency analysis method TSST, which reassigns time-frequency coefficients in the time direction rather than in the frequency direction, is more effective in extracting seismic time-frequency features and identifying thin layers compared to the traditional method FSST.
Article
Automation & Control Systems
Li Wang, Sai Ma, Qinkai Han, Fulei Chu
Summary: A new unified sparse TA analysis (STFA) framework is proposed for TF analysis in industrial engineering applications, with superior properties for energy concentration, denoising, component separation, and reconstruction, especially for signals with fast-varying features.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Software Engineering
Sixiang Tan, Wenzhong Yang, JianZhuang Lin, Weijie Yu
Summary: This study proposes a feature extraction and enhancement network that achieves a balance between accuracy and computing speed in real-time semantic segmentation tasks.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Environmental Sciences
Yanyan Li, Linqiao Han, Xiaolei Liu
Summary: An improved method based on CEEMD and MPCA was proposed to enhance the accuracy of GNSS positioning and extract features. The results showed that the proposed method outperformed conventional Wavelet Decomposition-Principal Component Analysis (WD-PCA) and Empirical Mode Decomposition-Principal Component Analysis (EMD-PCA) in eliminating low- and high-frequency noise, making it suitable for denoising nonlinear and nonstationary GNSS position sequences.
Article
Engineering, Multidisciplinary
Zhiqiang Chen, Liang Guo, Hongli Gao, Yaoxiang Yu, Wenxin Wu, Zhichao You, Xun Dong
Summary: This paper proposes a fault pulse extraction and feature enhancement method for bearing fault diagnosis. By using the multi-scale alternating direction multiplier method for dictionary learning to extract fault impact signal and frequency spectrum averaging to enhance bearing fault characteristic frequency, the feasibility of this method in bearing fault diagnosis is verified through numerical simulation and rail transit transmission failure simulation experimental analysis.
Article
Automation & Control Systems
Shenghao Li, Shuang Liu, Qunfei Zhao, Qiaoyang Xia
Summary: This article proposes a quantized self-supervised local feature for indirect VSLAM, which shows outstanding localization accuracy and tracking stability. The proposed VSLAM utilizes a lightweight network to extract features in real time and establishes parallel indirect VSLAM using frame-wise matching and bundle adjustment.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Geochemistry & Geophysics
Jing Bai, Junjie Ren, Yujia Yang, Zhu Xiao, Wentao Yu, Vincent Havyarimana, Licheng Jiao
Summary: This study proposes a method for object detection in large-scale remote-sensing images with complex backgrounds, which combines time-frequency analysis and deep learning for feature optimization, effectively addressing the challenges of large-scale images and complex backgrounds.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Multidisciplinary
Zhu Yan, Yonggang Xu, Liang Wang, Aijun Hu
Summary: The time-frequency analysis method extends a one-dimensional signal to a two-dimensional time-frequency plane to reveal its time-varying characteristics. The time-frequency representation (TFR) obtained by the time-frequency postprocessing algorithm has characteristics of energy aggregation and high resolution. However, the generalized S-synchroextracting transform (GS-SET) method fails to extract effective information from multicomponent complex signals. To address this issue, we propose an enhanced time-frequency analysis method that decomposes the complex signal into mono-component signals using the Vold-Kalman time-varying filtering technique, processes them using the GS-SET method, and linearly superimposes the obtained TFRs for enhanced results. Simulation and experimental results confirm the effectiveness and practicality of this method.
Article
Geochemistry & Geophysics
Yang Yang, Yongqiang Cheng, Hao Wu, Zheng Yang, Hongqiang Wang
Summary: This letter proposes an effective time-frequency analysis algorithm based on adaptive short-time sparse representation (ASTSR) to enhance the TF feature of moving targets. The algorithm achieves accurate motion approximation by adaptively determining the width of the analysis window, resulting in high-resolution TF representations with high energy concentration. The algorithm performs well in weak component expressing and signal denoising without producing interference terms.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Guangyong Wei, Zhikui Duan, Shiren Li, Xinmei Yu, Guangguang Yang
Summary: A module called SWD is proposed to enhance local features by using sliding window with deformability. This module uses windows of variable size based on the depth of the embedded network layers. The SWD module is inserted into the Transformer network, named LFEformer, for automatic speech recognition, which is effective in capturing both local and global features. The experimental results on three widely used datasets, Aishell-1, HKUST, and WSJ (dev93/eval92), demonstrate significant improvements in CER and WER.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Duc-Hao Do, Thanh-Duc Chau, Thai-Son Tran
Summary: This study aims to extract the trends and changes inside the speech signal in the time-frequency plane by designing a new algorithm using time-frequency analysis technique. The proposed algorithm utilizes Poly-Linear Chirplet Transform to analyze the signal and returns a multichannel output which is then combined with MFCC feature for better recognition results in gender recognition, dialect recognition, and speaker recognition.
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
(2023)
Article
Mathematics
Lucero Veronica Lozano-Vazquez, Jun Miura, Alberto Jorge Rosales-Silva, Alberto Luviano-Juarez, Dante Mujica-Vargas
Summary: This paper describes an image enhancement method for reliable image feature matching. By applying an image enhancement method before feature extraction, the original characteristics of the scene can be preserved. Experimental results demonstrate that the combination of the Multi-Scale Retinex algorithm and SIFT method provides the best results in terms of the number of reliable feature matches.
Article
Energy & Fuels
Paulina Kujawa, Krzysztof Chudy, Aleksandra Banasiewicz, Kacper Lesny, Radoslaw Zimroz, Fabio Remondino
Summary: The porosity of rocks is a crucial parameter in rock mechanics and underground mining, affecting fluid movement and internal processes. Conventional testing methods are complex, while modern technologies are expensive. In this study, a core sample with karst and porous structures was used, and resin was poured to reinforce it. The core was then cut and 3D optical scanning was conducted for porosity assessment, achieving accurate results at a reasonable cost.
Review
Energy & Fuels
Adam Wroblewski, Pavlo Krot, Radoslaw Zimroz, Timo Mayer, Jyri Peltola
Summary: Electric hydraulic breaking hammers provide an energy-saving and eco-friendly solution for crushing oversized materials and demolishing concrete structures in industry. This paper reviews the global market analysis and potential applications of linear electric motor (LEM) hammers, discussing implementation aspects such as design optimization, dynamics simulation, machine control, and performance estimation. The preliminary measurements on an electric hammer demonstrate the need for online hammer control to achieve optimal parameters for different cases.
Article
Engineering, Mechanical
Wojciech Zulawinski, Katarzyna Maraj-Zygmat, Hamid Shiri, Agnieszka Wylomanska, Radoslaw Zimroz
Summary: The paper proposes a framework for modeling long-term non-homogeneous data with non-Gaussian properties and validates it using real data. The novelty of this research lies in the use of non-Gaussian data, which reveals new findings for the predictive maintenance community and opens up new research directions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Chemistry, Analytical
Pawel Trybala, Jaroslaw Szrek, Blazej Debogorski, Bartlomiej Zietek, Jan Blachowski, Jacek Wodecki, Radoslaw Zimroz
Summary: Mobile mapping technologies, such as SLAM and SfM, are crucial for 3D surveying and autonomous vehicles. However, the current multiline scanners used in mapping hardware have gaps between scanning lines and limited vertical field of view. To overcome these issues, researchers have added tilting or rotating motors to the lidar. This paper presents an adjustable mapping system that switches between stable, tilting, and fully rotating lidar positions, and evaluates the impact on 3D data quality using different metrics.
Article
Energy & Fuels
Aleksandra Banasiewicz, Pawel Sliwinski, Pavlo Krot, Jacek Wodecki, Radoslaw Zimroz
Summary: In this article, a statistical polynomial model for predicting nitrogen oxide (NOx) emissions from LHD vehicles with diesel engines was developed. The 4th order polynomial model achieved prediction accuracies of around 8% and 13% for 11 and 10 input variables, respectively. These accuracies are comparable to the accuracies of sensors during stable loading and transient operation periods. These findings allow for better planning of ventilation system capacity and power demand in deep underground mines with a large fleet of vehicles.
Article
Chemistry, Physical
Jacek Wodecki, Pavlo Krot, Adam Wroblewski, Krzysztof Chudy, Radoslaw Zimroz
Summary: Predictive maintenance is a popular approach in various industries, including mining, but it lacks notable examples of its efficiency in practice. The collaboration between Omya Group and Wroclaw University of Science and Technology examined the failure of an inertial vibrator's bearing. By employing advanced signal processing techniques, defects in the bearing were successfully identified and the amplitudes of vibration significantly reduced after repair. Further research directions are being considered.
Article
Chemistry, Multidisciplinary
Przemyslaw Dabek, Adam Wroblewski, Jacek Wodecki, Piotr Bortnowski, Maksymilian Ozdoba, Robert Krol, Radoslaw Zimroz
Summary: Belt mistracking is a dangerous and costly failure in belt conveyors. This article presents the main causes and detection methods for belt mistracking. Based on laboratory tests, the mechanical and operating parameters of a conveyor burdened with lateral running off were compared. Mistracking increases machine resistance, affecting forces in the drive system and energy consumption. Three non-contact methods for monitoring belt lateral run-off are discussed: vibration measurements, RGB images, and thermal imaging.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Govind Vashishtha, Sumika Chauhan, Surinder Kumar, Rajesh Kumar, Radoslaw Zimroz, Anil Kumar
Summary: This paper proposes a novel optimization method, Amended Gorilla Troop Optimization (AGTO), for the selection of hyperparameters in deep learning models for fault diagnosis. By converting vibration and acoustic signals into 2D images for feature extraction and optimizing the hyperparameters of the CNN model using the AGTO algorithm, stable performance is achieved. The results show that AGTO-CNN has the highest diagnostic accuracy.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Daniel Kuzio, Radoslaw Zimroz, Agnieszka Wylomanska
Summary: This paper discusses the problem of local damage diagnosis based on the detection of impulsive and periodic signals. Both features need to be checked, as fault frequency should be related to the true value calculated for a given machine and speed. Precisely estimating the fault frequency is challenging due to various factors. A broader perspective is proposed here, introducing an automatic statistical approach to analyze the distribution of estimated fault frequencies. The algorithm uses frequency estimation based on peak detection in the envelope spectrum and statistical testing. Simulation studies and industrial examples are presented, indicating that more advanced techniques, such as order analysis, should be used if the fault frequency is not constant and its distribution does not follow a Gaussian shape with minor variance.
Article
Engineering, Multidisciplinary
Katarzyna Maraj-Zygmat, Wojciech Zulawinski, Tomasz Barszcz, Radoslaw Zimroz, Agnieszka Wylomanska
Summary: This study proposes a method for identifying thresholds for health index (HI) data with time-varying characteristics and non-Gaussian behavior. The methodology includes data segmentation, data modeling, and Monte Carlo simulations for quantile lines identification based on fitted models. The proposed method provides more accurate results for non-Gaussian, time varying data.
Article
Engineering, Mechanical
Katarzyna Skowronek, Tomasz Barszcz, Jerome Antoni, Radoslaw Zimroz, Agnieszka Wylomanska
Summary: This paper introduces a novel approach to local damage detection in condition monitoring applications. It considers the acquired vector of observations as an additive mixture of signal of interest and noise with strongly non-Gaussian properties, which masks the signal. The distribution properties of the noise have a significant impact on the selection of signal analysis tools, and it is important to recognize and identify the non-Gaussian behavior of the noise. The paper also emphasizes the role of variance in signal analysis and proposes a procedure to check for the presence of infinite variance in the background noise.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Hamid Shiri, Pawel Zimroz, Jacek Wodecki, Agnieszka Wylomanska, Radoslaw Zimroz, Krzysztof Szabat
Summary: The number of timely diagnoses based on condition monitoring data is increasing, but the lack of specific limit values or thresholds poses challenges, especially in unique machine cases. Additionally, the non-Gaussian noise inherent in observed processes in many real applications makes diagnostics difficult. This paper introduces a robust methodology called switching maximum correntropy Kalman filter (SMCKF) that addresses the issues of threshold and online diagnostics in the presence of non-Gaussian noise using condition monitoring (CM) data. The proposed approach, based on dynamic behavior, eliminates the need for a diagnostic threshold and proves effective in both simulated and real data sets.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Chemistry, Physical
Pavlo Krot, Hamid Shiri, Przemyslaw Dabek, Radoslaw Zimroz
Summary: This research proposes a model-based diagnostic method for condition-based maintenance of vibrating screens, considering the interaction between the screen body and the upper deck under degraded bolted joints. It is found that the second natural mode of the upper deck can coincide with the excitation frequency or its harmonics, leading to accelerated bolt loosening. The proposed approach can reduce maintenance costs and energy consumption and prevent abrupt failures by detuning the system from resonance and anti-resonance.
Article
Remote Sensing
Pawel Trybala, Jaroslaw Szrek, Fabio Remondino, Paulina Kujawa, Jacek Wodecki, Jan Blachowski, Radoslaw Zimroz
Summary: The research potential in the field of mobile mapping technologies is often hindered by constraints such as expensive hardware, limited access to target sites, and the collection of ground truth data. To address these challenges, the research community often provides open datasets. However, datasets that encompass demanding conditions with synchronized sensors are currently limited. To alleviate this issue, the MIN3D dataset is proposed, which includes data gathered using a wheeled mobile robot in two distinct locations. By sharing this dataset, the aim is to support the development of robust methods for navigation and mapping in challenging underground conditions.
PFG-JOURNAL OF PHOTOGRAMMETRY REMOTE SENSING AND GEOINFORMATION SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Volodymyr Gurskyi, Vitaliy Korendiy, Pavlo Krot, Radoslaw Zimroz, Oleksandr Kachur, Nadiia Maherus
Summary: Theoretical investigations are conducted on the capabilities of a coaxial inertial drive for vibratory conveyors and screens with various operating modes. The drive is designed with one asynchronous electric motor and the rotation of two unbalanced masses. Different angular speed ratios are considered, resulting in circular, elliptical, and complex motion trajectories. The dynamics of the motor's shaft during running-up and running-out are considered, along with the influence of inertial parameters and phase shift angle on the motion trajectories. The forced kinematic synchronization ensures motion stability for all working regimes.
Article
Engineering, Mechanical
Xuanen Kan, Yanjun Lu, Fan Zhang, Weipeng Hu
Summary: A blade disk system is crucial for the energy conversion efficiency of turbomachinery, but differences between blades can result in localized vibration. This study develops an approximate symplectic method to simulate vibration localization in a mistuned bladed disk system and reveals the influences of initial positive pressure, contact angle, and surface roughness on the strength of vibration localization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zimeng Liu, Cheng Chang, Haodong Hu, Hui Ma, Kaigang Yuan, Xin Li, Xiaojian Zhao, Zhike Peng
Summary: Considering the calculation efficiency and accuracy of meshing characteristics of gear pair with tooth root crack fault, a parametric model of cracked spur gear is established by simplifying the crack propagation path. The LTCA method is used to calculate the time-varying meshing stiffness and transmission error, and the results are verified by finite element method. The study also proposes a crack area share index to measure the degree of crack fault and determines the application range of simplified crack propagation path.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Rongjian Sun, Conggan Ma, Nic Zhang, Chuyo Kaku, Yu Zhang, Qirui Hou
Summary: This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Zhang, Jiangcen Ke
Summary: This research introduces an intelligent scheduling system framework to optimize the ship lock schedule of the Three Gorges Hub. By analyzing navigational rules, operational characteristics, and existing problems, a mixed-integer nonlinear programming model is formulated with multiple objectives and constraints, and a hybrid intelligent algorithm is constructed for optimization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Jingjing He, Xizhong Wu, Xuefei Guan
Summary: A sensitivity and reliability enhanced ultrasonic method has been developed in this study to monitor and predict stress loss in pre-stressed multi-layer structures. The method leverages the potential breathing effect of porous cushion materials in the structures to increase the sensitivity of the signal feature to stress loss. Experimental investigations show that the proposed method offers improved accuracy, reliability, and sensitivity to stress change.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper presents a method for monitoring sub-second or sub-minute displacements using GBSAR signals, which employs spectral estimation to achieve multi-dimensional target detection. It improves the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xianze Li, Hao Su, Ling Xiang, Qingtao Yao, Aijun Hu
Summary: This paper proposes a novel method for bearing fault identification, which can accurately identify faults with few samples under complex working conditions. The method is based on a Transformer meta-learning model, and the final result is determined by the weighted voting of multiple models.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin
Summary: Inspired by chaos fractal theory and slowly varying damage dynamics theory, this paper proposes a new health monitoring indicator for vibration signals of rotating machinery, which can effectively monitor the mechanical condition under both cyclo-stationary and variable operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Wang, Songye Zhu
Summary: This paper extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed, and different latching control strategies are tested and evaluated. The latching control can optimize the phase lag between control force and structural response, and provide an innovative solution to improve damper effectiveness and develop adaptive semi-active dampers.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Menghao Ping, Xinyu Jia, Costas Papadimitriou, Xu Han, Chao Jiang, Wang-Ji Yan
Summary: Identification of non-Gaussian processes is a challenging task in engineering problems. This article presents an improved orthogonal series expansion method to convert the identification of non-Gaussian processes into a finite number of non-Gaussian coefficients. The uncertainty of these coefficients is quantified using polynomial chaos expansion. The proposed method is applicable to both stationary and nonstationary non-Gaussian processes and has been validated through simulated data and real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Lei Li, Wei Yang, Dongfa Li, Jianxin Han, Wenming Zhang
Summary: The frequency locking phenomenon induced by modal coupling can effectively overcome the dependence of peak frequency on driving strength in nonlinear resonant systems and improve the stability of peak frequency. This study proposes the double frequencies locking phenomenon in a three degrees of freedom (3-DOF) magnetic coupled resonant system driven by piezoelectricity. Experimental and theoretical investigations confirm the occurrence of first frequency locking and the subsequent switching to second frequency locking with the increase of driving force. Furthermore, a mass sensing scheme for double analytes is proposed based on the double frequencies locking phenomenon.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Kai Ma, Jingtao Du, Yang Liu, Ximing Chen
Summary: This study explores the feasibility of using nonlinear energy sinks (NES) as replacements for traditional linear tuned mass dampers (TMD) in practical engineering applications, specifically in diesel engine crankshafts. The results show that NES provides better vibration attenuation for the crankshaft compared to TMD under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Wentao Xu, Li Cheng, Shuaihao Lei, Lei Yu, Weixuan Jiao
Summary: In this study, a high-precision hydraulic mechanical stand and a vertical mixed-flow pumping station device were used to conduct research on cavitation signals of mixed-flow pumps. By analyzing the water pressure pulsation signal, it was found that the power spectrum density method is more sensitive and capable of extracting characteristics compared to traditional time-frequency domain analysis. This has significant implications for the identification and prevention of cavitation in mixed-flow pump machinery.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaodong Chen, Kang Tai, Huifeng Tan, Zhimin Xie
Summary: This paper addresses the issue of parasitic motion in microgripper jaws and its impact on clamping accuracy, and proposes a symmetrically stressed parallelogram mechanism as a solution. Through mechanical modeling and experimental validation, the effectiveness of this method is demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zhifeng Shi, Gang Zhang, Jing Liu, Xinbin Li, Yajun Xu, Changfeng Yan
Summary: This study provides useful guidance for early bearing fault detection and diagnosis by investigating the effects of crack inclination and propagation direction on the vibration characteristics of bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
