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Application of the threshold and best tree based on wavelet analysis in the intelligent diagnosis on anchor poles

机译:基于小波分析的阈值和最优树在锚杆智能诊断中的应用

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With the wide application of anchor technology in geotechnical engineering, quality problems of anchor frequently occur. Quality inspection of anchor poles becomes more and more important. Wavelet analysis can finely distinct the normal and abnormal signals, and detect the weak signals by its characteristic analysis of local expansion and compression, which makes the intelligent diagnosis of defective anchor poles possible. Taking the project of “commercial buildings and museum in Marine Sports School of the State General Administration of Sports” in Qingdao as an example, this paper compares the thresholds and best trees between the good anchor and defective anchor pole by using wavelet analysis toolbox of MATLAB. The paper shows that intelligent diagnosis of anchor poles based on the thresholds and best trees is not only desirable and accurate, but also provides important basis for the site construction guidance and check acceptance work.
机译:随着锚固技术在岩土工程中的广泛应用,锚固的质量问题经常发生。锚杆的质量检查变得越来越重要。小波分析可以很好地区分正常信号和异常信号,并通过其局部扩展和压缩特征分析来检测微弱信号,从而可以智能诊断有缺陷的锚杆。以青岛市“国家体育总局海洋体育学院商业建筑与博物馆”项目为例,利用MATLAB的小波分析工具箱对良锚与不良锚之间的阈值和最佳树进行比较。 。结果表明,基于阈值和最佳树的智能诊断锚杆不仅是理想和准确的,而且为现场施工指导和验收工作提供了重要依据。

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