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相关概念视频

Bearings: Problem Solving01:24

Bearings: Problem Solving

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Understanding the calculations and concepts related to double-collar bearings is essential for engineers and designers to optimize the performance of these components in various applications. By analyzing the bearing under different conditions, one can ensure that it can withstand the forces and moments experienced during operation. This knowledge enables better decision-making when designing and selecting bearings for specific purposes and configurations. Consider a double-collar bearing with...
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Wald-Wolfowitz Runs Test I01:17

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The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Rolling Resistance: Problem Solving01:17

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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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滚动轴承故障诊断基于支持向量机优化通过改进的灰狼算法.

Weijie Shen1, Maohua Xiao2, Zhenyu Wang2

  • 1Zhejiang Technical Institute of Economics, Hangzhou 310018, China.

Sensors (Basel, Switzerland)
|July 29, 2023
PubMed
概括

本研究引入了一种改进的灰狼优化器 (IGWO),以提高滚动轴承故障诊断的支向量机 (SVM) 精度. 与现有方法相比,IGWO-SVM模型实现了更高的性能.

关键词:
这就是IGWO算法.在SVM算法中,SVM算法是错误诊断 错误诊断 错误诊断 是一个问题.滚动轴承 滚动轴承 滚动轴承

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科学领域:

  • 机械工程 机械工程
  • 人工智能的人工智能
  • 信号处理 信号处理

背景情况:

  • 滚动轴承故障诊断对于机械健康至关重要.
  • 现有的支持矢量机 (SVM) 方法的准确性和效率都很低.
  • 需要优化算法来提高SVM在故障诊断中的性能.

研究的目的:

  • 为优化支持矢量机 (SVM) 参数提出一个改进的灰狼优化器 (IGWO) 算法.
  • 为了提高滚动轴承故障诊断的准确性和效率.
  • 引入非线性收缩因子和动态重量更新的新策略.

主要方法:

  • 开发了一个改进的灰狼优化器 (IGWO),集成深度学习和群集智能.
  • 实施了非线性收缩因子更新策略,以实现平衡的搜索能力.
  • 使用动态重量更新策略进行自适应位置更新.
  • 使用Case Western Reserve大学的数据集和定制的机械变速箱轴承测试平台验证了IGWO-SVM模型.

主要成果:

  • 在Case Western Reserve大学的数据集上,IGWO-SVM模型实现了98.75%的诊断准确率.
  • 对比分析显示,IGWO-SVM在故障诊断准确性和趋同方面表现优于PSO-SVM和GWO-SVM.
  • 拟议的模型在一个全生命周期的机械变速箱轴承测试平台上表现出卓越的性能.

结论:

  • IGWO-SVM 模型显著提高了滚动轴承故障诊断的准确性和效率.
  • 非线性收缩因子和动态重量更新策略增强了优化趋同.
  • 这种方法为机械系统的智能故障诊断提供了强大的解决方案.