基于非轴对称超声波导向波和PSO-LSSVM算法90度肘部侵蚀预测的新方法
Zhaokun Wang1, Sizhu Zhou1, Ning Li1
1School of Mechanical Engineering, Yangtze University, Jingzhou 434023, China.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
这项研究使用引导波来检测肘部侵蚀. 一种新的粒子群优化-最小正方形支持向量机 (PSO-LSSVM) 算法准确预测侵蚀程度,有助于实时监测.
科学领域:
- 机械工程 机械工程
- 材料科学 材料科学 材料科学
- 非破坏性测试是指非破坏性测试.
背景情况:
- 肘部侵蚀在工业管道系统中构成了重大挑战.
- 精确检测侵蚀程度对于结构完整性和安全至关重要.
- 现有的方法难以高精度检测肘部侵蚀.
研究的目的:
- 开发一种高精度的方法来预测90度管道肘部的侵蚀程度.
- 为了建立引导波信号能量和剩余的墙壁厚度之间的关系.
- 通过对现有算法验证拟议的方法.
主要方法:
- 使用线性频率调制 (LFM) 信号激发非轴对称引导波.
- 引导波通过90度肘部传播,并通过四个PZT接收器获取信号.
- 应用分数福里埃过和粒子群优化-最小平方支向量机 (PSO-LSSVM) 算法用于侵蚀预测.
主要成果:
- 该PSO-LSSVM方法实现了各种侵蚀度的高预测精度 (平均高达98.1864%的样本和94.0039%的新度).
- 与非线性回归,LSSVM和BP神经网络算法相比,拟议的方法显示出更高的性能.
- 时间域能量价值的明显下降趋势与侵蚀过的部分的剩余厚度的减少有关.
结论:
- 使用PSO-LSSVM开发的基于引导波的方法对于准确预测肘部侵蚀程度是有效的.
- 这种技术为实时监测管道侵蚀提供了巨大的潜力.
- 这些发现为维护工业管道系统的完整性提供了宝贵的指导.
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