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  • Open Access

    ARTICLE

    Intelligent Sound-Based Early Fault Detection System for Vehicles

    Fawad Nasim1,2,*, Sohail Masood1,2, Arfan Jaffar1,2, Usman Ahmad1, Muhammad Rashid3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3175-3190, 2023, DOI:10.32604/csse.2023.034550 - 03 April 2023

    Abstract An intelligent sound-based early fault detection system has been proposed for vehicles using machine learning. The system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the car. Early detection and correction of defects can improve the efficiency and life of the engine and other mechanical parts. The system uses a microphone to capture the sound emitted by the vehicle and a machine-learning algorithm to analyze the sound and detect faults. A possible fault is determined in the vehicle based on this processed sound. Binary classification is… More >

  • Open Access

    ARTICLE

    A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

    Omar Almomani*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113 - 22 March 2021

    Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has… More >

  • Open Access

    ARTICLE

    IWD-Miner: A Novel Metaheuristic Algorithm for Medical Data Classification

    Sarab AlMuhaideb*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576 - 26 November 2020

    Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can… More >

  • Open Access

    ARTICLE

    Vibration Based Tool Insert Health Monitoring Using Decision Tree and Fuzzy Logic

    Kundur Shantisagar, R. Jegadeeshwaran*, G. Sakthivel, T. M. Alamelu Manghai

    Structural Durability & Health Monitoring, Vol.13, No.3, pp. 303-316, 2019, DOI:10.32604/sdhm.2019.00355

    Abstract The productivity and quality in the turning process can be improved by utilizing the predicted performance of the cutting tools. This research incorporates condition monitoring of a non-carbide tool insert using vibration analysis along with machine learning and fuzzy logic approach. A non-carbide tool insert is considered for the process of cutting operation in a semi-automatic lathe, where the condition of tool is monitored using vibration characteristics. The vibration signals for conditions such as heathy, damaged, thermal and flank were acquired with the help of piezoelectric transducer and data acquisition system. The descriptive statistical features… More >

  • Open Access

    ARTICLE

    Condition Monitoring of Roller Bearing by K-Star Classifier and K-Nearest Neighborhood Classifier Using Sound Signal.

    Rahul Kumar Sharma*1, V. Sugumaran1, Hemantha Kumar2, Amarnath M3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

    Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone)… More >

  • Open Access

    ARTICLE

    Fault Diagnosis of Helical Gear Box using Variational Mode Decomposition and Random Forest Algorithm

    Akhil Muralidharan1,2, V. Sugumaran1, K.P Soman3, M. Amarnath4

    Structural Durability & Health Monitoring, Vol.10, No.1, pp. 55-80, 2014, DOI:10.3970/sdhm.2014.010.055

    Abstract Gears are machine elements that transmit motion by means of successively engaging teeth. In purely scientific terms, gears are used to transmit motion. A faulty gear is a matter of serious concern as it affects the functionality of a machine to a great extent. Thus it is essential to diagnose the faults at an initial stage so as to reduce the losses that might be incurred. This necessitates the need for continuous monitoring of the gears. The vibrations produced by gears from good and simulated faulty conditions can be effectively used to detect the faults… More >

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