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Evaluating ultrasound signals of carbon steel fatigue testing using signal analysis approaches

机译:使用信号分析方法评估碳钢疲劳测试的超声信号

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摘要

The application of ultrasound techniques to monitor the condition of structures is becoming more prominent because these techniques can detect the early symptoms of defects such as cracks and other defects. The early detection of defects is of vital importance to avoid major failures with catastrophic consequences. An assessment of an ultrasound technique was used to investigate fatigue damage behaviour. Fatigue tests were performed according to the ASTM E466-96 standard with the attachment of an ultrasound sensor to the test specimen. AISI 1045 carbon steel was used due to its wide application in the automotive industry. A fatigue test was performed under constant loading stress at a sampling frequency of 8 Hz. Two sets of data acquisition systems were used to collect the fatigue strain signals and ultrasound signals. All of the signals were edited and analysed using a signal processing approach. Two methods were used to evaluate the signals, the integrated Kurtosis-based algorithm for z-filter technique (I-kaz) and the short-time Fourier transform (STFT). The fatigue damage behaviour was observed from the initial stage until the last stage of the fatigue test. The results of the I-kaz coefficient and the STFT spectrum were used to explain and describe the behaviour of the fatigue damage. I-kaz coefficients were ranged from 60 to 61 for strain signals and ranged from 5 to 76 for ultrasound signals. I-kaz values tend to be high at failure point due to high amplitude of respective signals. STFT spectrogram displays the colour intensity which represents the damage severity of the strain signals. I-kaz technique is found very useful and capable in assessing both stationary and non-stationary signals while STFT technique is suitable only for non-stationary signals by displaying its spectrogram.
机译:超声技术在监测结构条件下的应用变得越来越突出,因为这些技术可以检测诸如裂缝和其他缺陷的缺陷的早期症状。早期发现缺陷的重要性至关重要,以避免具有灾难性后果的主要失败。对超声技术的评估用于研究疲劳损伤行为。根据ASTM E466-96标准进行疲劳试验,并将超声波传感器连接到试样。由于其在汽车工业中的广泛应用,使用了AISI 1045碳钢。以8Hz的采样频率在恒定的负载应力下进行疲劳试验。两组数据采集系统用于收集疲劳应变信号和超声信号。使用信号处理方法编辑和分析所有信号。用于评估两种方法来评估信号,Z滤波技术(I-KAZ)和短时傅里叶变换(STFT)的综合峰基于峰基的算法。从初始阶段观察到疲劳损伤行为,直到疲劳试验的最后阶段。 I-KAZ系数和STFT光谱的结果用于解释和描述疲劳损伤的行为。 I-KAZ系数范围为60至61,用于应变信号,而超声信号的范围为5至76。由于相应信号的高幅度,I-KAZ值趋于高于故障点。 STFT频谱图显示了表示应变信号的损伤严重程度的颜色强度。 I-KAZ技术被发现非常有用,并且能够评估静止和非静止信号,而STFT技术仅适用于通过显示其谱图的非静止信号。

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  • 来源
    《中南大学学报(英文版)》 |2014年第1期|241-250|共10页
  • 作者单位

    Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;

    Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;

    Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;

    Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;

    Department of Mechanical and Materials Engineering, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;

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  • 入库时间 2022-08-18 01:07:03
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