卷积神经网络与注意力机制和视觉振动信号分析用于轴承故障诊断
Qing Zhang1, Xiaohan Wei2, Ye Wang2
1School of Instrument Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了一种新的CBAM-CNN模型来诊断轴承故障,达到99.81%的准确性. 该方法通过可视化注意力权重来提高解释性,专注于频率而不是振幅,以改进故障识别.
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:
- 轴承故障在机械中很常见,导致故障.
- 传统的故障诊断依赖于专家的经验和时间频率分析.
- 现有的智能方法往往缺乏可解释性.
研究的目的:
- 开发一个可解释的深度学习模型来进行故障诊断.
- 为了提高轴承故障的特征提取和分类精度.
- 提高对诊断模型决策的理解.
主要方法:
- 开发了一个带有注意力机制的卷积神经网络 (CBAM-CNN).
- 整合了卷积块注意模块 (CBAM) 进行了增强的特征提取.
- 梯度加权类激活映射 (Grad-CAM) 用于模型的解释性.
主要成果:
- 在实验数据集上,CBAM-CNN的准确度达到99.81%.
- 与Base-CNN.相比,该模型显示了较好的融合速度.
- 注意重量分析显示,不同类型的故障有不同的焦点模式.
- 解释性实验显示,人们专注于频率分布与振幅.
结论:
- 该CBAM-CNN为轴承故障诊断提供了一个高度准确和可解释的解决方案.
- 注意力机制有效地增强了在时间频率领域的特征提取.
- 格拉德-CAM可视化为模型的决策过程提供了洞察力,突出了基于频率的分析.
更多相关视频
06:45Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
1.6K
06:37Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
3.7K
相关概念视频
Bearings: Problem Solving
282
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...
282
Node Analysis for AC Circuits
317
Consider an angioplasty system featuring a catheter equipped with a turbine, a critical tool for removing plaque deposits from coronary arteries. This intricate medical device operates using a circuit model reminiscent of a dual-node RLC circuit powered by a current-controlled voltage source.
To unravel the complexities of this system, nodal analysis is employed, a powerful technique founded on Kirchhoff's current law (KCL), which remains valid for phasors. AC circuits can effectively be...
To unravel the complexities of this system, nodal analysis is employed, a powerful technique founded on Kirchhoff's current law (KCL), which remains valid for phasors. AC circuits can effectively be...
317
Equilibrium and Balance
4.7K
The inner ear assumes dual functionalities of auditory perception and equilibrium maintenance. The vestibule is the organ responsible for balance. This organ contains mechanoreceptors, specifically hair cells, endowed with stereocilia, which aid in deciphering information regarding the position and motion of our heads. Two intrinsic components, the utricle and saccule, help perceive head position, while the semicircular canals track head movement. Neurological messages initiated in the...
4.7K
Discrete Fourier Transform
272
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
272
Visual System
580
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
Once through the pupil, the light passes through the lens, a...
580
Relative Motion Analysis using Rotating Axes
460
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
460
