TY - JOUR
T1 - Novel method of data compression for the online detection signal of coal mine wire rope
AU - Jie, Tian
AU - Hongyao, Wang
AU - Guoying, Meng
AU - Bilen, Sven
AU - Xinli, Wu
N1 - Funding Information:
The authors would like to thank the National Natural Science Foundation of China (grant number 51774293), the Yue Qi Young Scholar Project, the Yue Qi Distinguished Scholar Project from China University of Mining & Technology, Beijing, China, and the Central Business Funds of Colleges (grant numbers 2014QJ01 and 2015QJ04) for providing the financial support to conduct this research. The authors would like to thank Professors Gang Hua, Zhao Xu, Hongsheng Yin and Yonggang Xu and postgraduate students Zhou Junying, Zhu Pufan, Li Xiaowei, Lv Xin and others for their help during the study. The authors also thank the reviewers for their useful comments and suggestions, which have helped to improve the manuscript.
PY - 2020/10
Y1 - 2020/10
N2 - Coal mine wire rope detection is related to personnel and production safety. With the Chinese coal mining trend tending towards deep mining, a considerable amount of data is critical for the online detection of deep well lifting wire rope. To improve the sampling rate, decrease the analysis processing time and realise real-time online detection, this paper proposes an online detection data compression processing method. The study focuses on the distortion compression method for the online detection signal of deep well hoisting wire rope. The set partitioning in hierarchical trees (SPIHT) algorithm is one of the most advanced methods in the field of image transformation coding. Compared with other coding algorithms, the SPIHT algorithm demonstrates desired characteristics such as a high signal-to-noise ratio, lower complexity and decreased computational load, among others. This paper discusses how, in combination with the image processing method, a compression coding method for the one-dimensional signal of the magnetic leakage detection of the mining wire rope is developed. Furthermore, the set partitioning sorting algorithm is investigated and analysed, the temporal orientation tree structure of the one-dimensional signal of the wavelet coefficient is defined for wire rope magnetic leakage detection and the SPIHT algorithm is presented, in addition to an example of the one-dimensional signal from the magnetic leakage detection of the wire rope. The results reveal that under the condition of the normalised mean square error (NMSE; NMSE < 0.01) of distortion, the compression ratio improved by 30%. The online detection signal lossy compression method proposed in this study has a considerable influence on the recovery of the original signal, in addition to a higher compression ratio and a reduced computation time, compared to the existing method.
AB - Coal mine wire rope detection is related to personnel and production safety. With the Chinese coal mining trend tending towards deep mining, a considerable amount of data is critical for the online detection of deep well lifting wire rope. To improve the sampling rate, decrease the analysis processing time and realise real-time online detection, this paper proposes an online detection data compression processing method. The study focuses on the distortion compression method for the online detection signal of deep well hoisting wire rope. The set partitioning in hierarchical trees (SPIHT) algorithm is one of the most advanced methods in the field of image transformation coding. Compared with other coding algorithms, the SPIHT algorithm demonstrates desired characteristics such as a high signal-to-noise ratio, lower complexity and decreased computational load, among others. This paper discusses how, in combination with the image processing method, a compression coding method for the one-dimensional signal of the magnetic leakage detection of the mining wire rope is developed. Furthermore, the set partitioning sorting algorithm is investigated and analysed, the temporal orientation tree structure of the one-dimensional signal of the wavelet coefficient is defined for wire rope magnetic leakage detection and the SPIHT algorithm is presented, in addition to an example of the one-dimensional signal from the magnetic leakage detection of the wire rope. The results reveal that under the condition of the normalised mean square error (NMSE; NMSE < 0.01) of distortion, the compression ratio improved by 30%. The online detection signal lossy compression method proposed in this study has a considerable influence on the recovery of the original signal, in addition to a higher compression ratio and a reduced computation time, compared to the existing method.
UR - https://www.scopus.com/pages/publications/85092322543
UR - https://www.scopus.com/inward/citedby.url?scp=85092322543&partnerID=8YFLogxK
U2 - 10.1784/insi.2020.62.10.600
DO - 10.1784/insi.2020.62.10.600
M3 - Article
AN - SCOPUS:85092322543
SN - 1354-2575
VL - 62
SP - 600
EP - 608
JO - Insight: Non-Destructive Testing and Condition Monitoring
JF - Insight: Non-Destructive Testing and Condition Monitoring
IS - 10
ER -