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A platform for research: civil engineering, architecture and urbanism
Research on Tree Ring Micro-Destructive Detection Technology Based on Digital Micro-Drilling Resistance Method
Micro-drilling resistance method is a widely used tree ring micro-destructive detection technology. To solve the problem that the detection signal of the analog micro-drilling resistance method has excessive noise interference and cannot intuitively identify tree ring information, this research proposes a digital micro-drilling resistance method and provides a recommended hardware implementation. The digital micro-drilling resistance method adopts the photoelectric encoder instead of ADC as the signal sampling module. Through the theoretical analysis of the DC motor characteristic, the PWM closed-loop speed control, the detection principle of the digital method is given. Additionally, the experimental equipment that can complete the detection of the digital method and the analog method simultaneously is designed to carry out comparative experiments. The experimental results show that: (1) The detection results of the digital method have a better-quality signal which can intuitively identify the tree rings. (2) The average correlation coefficient reaches 0.9365 between the detection results of the digital method and the analog method. (3) The average Signal-to-Noise Ratio (SNR) of the digital method is 39.0145 dB, which is 19.2590 dB higher than that of the analog method. The average noise interference energy in the detection result of the digital method is only 1.27% of the analog method. In summary, hardware implementation of the digital micro-drilling resistance method can correctly reflect the tree ring information and significantly improve the signal quality of the micro-drilling resistance technology. This research is helping to improve the identification accuracy of micro-drilling resistance technology, and to develop the application of tree ring micro-destructive detection technology in the high-precision field.
Research on Tree Ring Micro-Destructive Detection Technology Based on Digital Micro-Drilling Resistance Method
Micro-drilling resistance method is a widely used tree ring micro-destructive detection technology. To solve the problem that the detection signal of the analog micro-drilling resistance method has excessive noise interference and cannot intuitively identify tree ring information, this research proposes a digital micro-drilling resistance method and provides a recommended hardware implementation. The digital micro-drilling resistance method adopts the photoelectric encoder instead of ADC as the signal sampling module. Through the theoretical analysis of the DC motor characteristic, the PWM closed-loop speed control, the detection principle of the digital method is given. Additionally, the experimental equipment that can complete the detection of the digital method and the analog method simultaneously is designed to carry out comparative experiments. The experimental results show that: (1) The detection results of the digital method have a better-quality signal which can intuitively identify the tree rings. (2) The average correlation coefficient reaches 0.9365 between the detection results of the digital method and the analog method. (3) The average Signal-to-Noise Ratio (SNR) of the digital method is 39.0145 dB, which is 19.2590 dB higher than that of the analog method. The average noise interference energy in the detection result of the digital method is only 1.27% of the analog method. In summary, hardware implementation of the digital micro-drilling resistance method can correctly reflect the tree ring information and significantly improve the signal quality of the micro-drilling resistance technology. This research is helping to improve the identification accuracy of micro-drilling resistance technology, and to develop the application of tree ring micro-destructive detection technology in the high-precision field.
Research on Tree Ring Micro-Destructive Detection Technology Based on Digital Micro-Drilling Resistance Method
Xueyang Hu (author) / Yili Zheng (author) / Da Xing (author) / Qingfeng Sun (author)
2022
Article (Journal)
Electronic Resource
Unknown
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