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  • Open Access

    ARTICLE

    Fault Identification for Shear-Type Structures Using Low-Frequency Vibration Modes

    Cuihong Li1, Qiuwei Yang2,3,*, Xi Peng2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2769-2791, 2024, DOI:10.32604/cmes.2023.030908

    Abstract Shear-type structures are common structural forms in industrial and civil buildings, such as concrete and steel frame structures. Fault diagnosis of shear-type structures is an important topic to ensure the normal use of structures. The main drawback of existing damage assessment methods is that they require accurate structural finite element models for damage assessment. However, for many shear-type structures, it is difficult to obtain accurate FEM. In order to avoid finite element modeling, a model-free method for diagnosing shear structure defects is developed in this paper. This method only needs to measure a few low-order vibration modes of the structure.… More >

  • Open Access

    ARTICLE

    Identification of Type of a Fault in Distribution System Using Shallow Neural Network with Distributed Generation

    Saurabh Awasthi*, Gagan Singh, Nafees Ahamad

    Energy Engineering, Vol.120, No.4, pp. 811-829, 2023, DOI:10.32604/ee.2023.026863

    Abstract A distributed generation system (DG) has several benefits over a traditional centralized power system. However, the protection area in the case of the distributed generator requires special attention as it encounters stability loss, failure re-closure, fluctuations in voltage, etc. And thereby, it demands immediate attention in identifying the location & type of a fault without delay especially when occurred in a small, distributed generation system, as it would adversely affect the overall system and its operation. In the past, several methods were proposed for classification and localisation of a fault in a distributed generation system. Many of those methods were… More >

  • Open Access

    ARTICLE

    Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

    Mudita Uppal1, Deepali Gupta1, Divya Anand2, Fahd S. Alharithi3, Jasem Almotiri3, Arturo Mansilla4,5, Dinesh Singh6, Nitin Goyal1,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1799-1814, 2022, DOI:10.32604/cmc.2022.025330

    Abstract The rapid expansion of Internet of Things (IoT) devices deploys various sensors in different applications like homes, cities and offices. IoT applications depend upon the accuracy of sensor data. So, it is necessary to predict faults in the sensor and isolate their cause. A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults. This technique identifies the faulty sensor and determines the correct working of the sensor. Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.… More >

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