V. Prakash^*, S. Gopalakrishnan

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2575-2590, 2023, DOI:10.32604/iasc.2023.032122

Abstract Software test case optimization improves the efficiency of the software by proper structure and reduces the fault in the software. The existing research applies various optimization methods such as Genetic Algorithm, Crow Search Algorithm, Ant Colony Optimization, etc., for test case optimization. The existing methods have limitations of lower efficiency in fault diagnosis, higher computational time, and high memory requirement. The existing methods have lower efficiency in software test case optimization when the number of test cases is high. This research proposes the Tournament Winner Genetic Algorithm (TW-GA) method to improve the efficiency of software test case optimization. Hospital Information… More >

Zhijie Zhou¹, Zhichao Ming^1,*, Jie Wang¹, Shuaiwen Tang¹, You Cao¹, Xiaoxia Han¹, Gang Xiang^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1165-1185, 2023, DOI:10.32604/cmes.2023.025399

Abstract Fault diagnosis plays an irreplaceable role in the normal operation of equipment. A fault diagnosis model is often required to be interpretable for increasing the trust between humans and the model. Due to the understandable knowledge expression and transparent reasoning process, the belief rule base (BRB) has extensive applications as an interpretable expert system in fault diagnosis. Optimization is an effective means to weaken the subjectivity of experts in BRB, where the interpretability of BRB may be weakened. Hence, to obtain a credible result, the weakening factors of interpretability in the BRB-based fault diagnosis model are firstly analyzed, which are… More > Graphic Abstract

Qixin Lan, Binqiang Chen^*, Bin Yao

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2017-2037, 2023, DOI:10.32604/cmes.2023.025307

Abstract Many kinds of electrical equipment are used in civil and building engineering. The motor is one of the main power components of this electrical equipment, which can provide stable power output. During the long-term use of motors, various motor faults may occur, which affects the normal use of electrical equipment and even causes accidents. It is significant to apply fault diagnosis for the motors at the construction site. Aiming at the problem that signal data of faulty motor lack diversity, this research designs a multi-layer perceptron Wasserstein generative adversarial network, which is used to enhance training data through distribution fusion.… More >

Guo-Wen Sun¹, Gang Xiang^2,3, Wei He^1,4,*, Kai Tang¹, Zi-Yi Wang¹, Hai-Long Zhu¹

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1157-1177, 2023, DOI:10.32604/cmc.2023.035667

Abstract Wireless sensor networks (WSNs) operate in complex and harsh environments; thus, node faults are inevitable. Therefore, fault diagnosis of the WSNs node is essential. Affected by the harsh working environment of WSNs and wireless data transmission, the data collected by WSNs contain noisy data, leading to unreliable data among the data features extracted during fault diagnosis. To reduce the influence of unreliable data features on fault diagnosis accuracy, this paper proposes a belief rule base (BRB) with a self-adaptive quality factor (BRB-SAQF) fault diagnosis model. First, the data features required for WSN node fault diagnosis are extracted. Second, the quality… More >

Samah Alshathri¹, Ezz El-Din Hemdan², Walid El-Shafai^3,4,*, Amged Sayed^5,6

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 183-196, 2023, DOI:10.32604/cmc.2023.034048

Abstract In recent years, Digital Twin (DT) has gained significant interest from academia and industry due to the advanced in information technology, communication systems, Artificial Intelligence (AI), Cloud Computing (CC), and Industrial Internet of Things (IIoT). The main concept of the DT is to provide a comprehensive tangible, and operational explanation of any element, asset, or system. However, it is an extremely dynamic taxonomy developing in complexity during the life cycle that produces a massive amount of engendered data and information. Likewise, with the development of AI, digital twins can be redefined and could be a crucial approach to aid the… More >

Alamelu Manghai T Marimuthu¹, Jegadeeshwaran Rakkiyannan^2,*, Lakshmipathi Jakkamputi¹, Sugumaran Vaithiyanathan¹, Sakthivel Gnanasekaran²

Structural Durability & Health Monitoring, Vol.16, No.4, pp. 383-396, 2022, DOI:10.32604/sdhm.2022.011396

Abstract The requirement of fault diagnosis in the field of automobiles is growing higher day by day. The reliability of human resources for the fault diagnosis is uncertain. Brakes are one of the major critical components in automobiles that require closer and active observation. This research work demonstrates a fault diagnosis technique for monitoring the hydraulic brake system using vibration analysis. Vibration signals of a rotating element contain dynamic information about its health condition. Hence, the vibration signals were used for the brake fault diagnosis study. The study was carried out on a brake fault diagnosis experimental setup. The vibration signals… More >

Saqlain Abbas^1,2, Zulkarnain Abbas^3,4,*, Yanping Zhu², Waqas Tariq Toor⁵, Xiaotong Tu⁶

Structural Durability & Health Monitoring, Vol.16, No.4, pp. 307-321, 2022, DOI:10.32604/sdhm.2022.015266

Abstract In the previous couple of decades, techniques to reap energy and empower low voltage electronic devices have received outstanding attention. Most of the methods based on the piezoelectric effect to harvest the energy from ambient vibrations have been revolutionized. There’s an absence of experiment-based investigation which incorporates the microstructure analysis and crystal morphology of those energy harvest home materials. Moreover, the impact of variable mechanical and thermal load conditions has seldom been studied within the previous literature to utilize the effectiveness of those materials in several practical applications like structural health monitoring (SHM), etc. In the proposed research work, scanning… More >

Smarajit Ghosh^*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2391-2404, 2023, DOI:10.32604/csse.2023.028931

Abstract In the field of fault tolerance estimation, the increasing attention in electrical motors is the fault detection and diagnosis. The tasks performed by these machines are progressively complex and the enhancements are likewise looked for in the field of fault diagnosis. It has now turned out to be essential to diagnose faults at their very inception; as unscheduled machine downtime can upset deadlines and cause heavy financial burden. In this paper, fault diagnosis and speed control of permanent magnet synchronous motor (PMSM) is proposed. Elman Neural Network (ENN) is used to diagnose the fault of permanent magnet synchronous motor. Both… More >

Xiaoping Xie^*, Shijie Cheng, Xuyang Li

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2425-2448, 2023, DOI:10.32604/cmes.2023.023116

Abstract This paper proposed method that combined transmission path analysis (TPA) and empirical mode decomposition (EMD) envelope analysis to solve the vibration problem of an industrial robot. Firstly, the deconvolution filter time-domain TPA method is proposed to trace the source along with the time variation. Secondly, the TPA method positioned the main source of robotic vibration under typically different working conditions. Thirdly, independent vibration testing of the Rotate Vector (RV) reducer is conducted under different loads and speeds, which are key components of an industrial robot. The method of EMD and Hilbert envelope was used to extract the fault feature of… More >

Mrim M. Alnfiai^*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3763-3780, 2023, DOI:10.32604/cmc.2023.033448

Abstract Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems. Both structural and non-structural data of industrial systems are collected, which covers data formats of time-series, text, images, sound, etc. Several researchers discussed above were mostly qualitative, and ceratin techniques need expert guidance to conclude on the condition of gearboxes. But, in this study, an improved symbiotic organism search with deep learning enabled fault diagnosis (ISOSDL-FD) model for gearbox fault detection in industrial systems. The proposed ISOSDL-FD technique majorly concentrates on the identification and classification of faults in the gearbox… More >