Performance feature extraction is the primary problem in equipment performance degradation assessment. To handle the problem of high-dimensional performance characterization and complexity of calculating the performance indicators in flexible material roll-to-roll processing, this paper proposes a PCA method for extracting the degradation characteristic of roll shaft. Based on the analysis of the performance influencing factors of flexible material roll-to-roll processing roller, a principal component analysis extraction model was constructed. The original feature parameter matrix composed of 10-dimensional feature parameters such as time domain, frequency domain, and time-frequency domain vibration signal of the roll shaft was established; then, we obtained a new feature parameter matrix by normalizing the original feature parameter matrix. The correlation measure between every two parameters in the matrix was used as the eigenvalue to establish the covariance matrix of the performance degradation feature parameters. The Jacobi iteration method was introduced to derive the algorithm for solving eigenvalue and eigenvector of the covariance matrix. Finally, using the eigenvalue cumulative contribution rate as the screening rule, we linearly weighted and fused the eigenvectors and derived the feature principal component matrix of the processing roller vibration signal. Experiments showed that the initially obtained, 10-dimensional features of the processing rollers’ vibration signals, such as average, root mean square, kurtosis index, centroid frequency, root mean square of frequency, standard deviation of frequency, and energy of the intrinsic mode function component, can be expressed by 3-dimensional principal components , and . The vibration signal features reduction dimension was realized, and , and contain 98.9% of the original vibration signal data, further illustrating that the method has high precision in feature parameters’ extraction and the advantage of eliminating the correlation between feature parameters and reducing the workload selecting feature parameters.

国际旋转机制杂志

目录

目录

设备操作状态评估改进随机森林

空气润滑行为Kingsbury触发演示

振荡机轴动估计法验证

滑动组合底线框架振荡响应引擎

流体动力量对辨识旋转机故障的影响

特征提取弹性材料R2R处理机滚动器研究

开放源码OpenFOM测试线性喷射推送系统流体特征

高精度提取法与Eddy电流传感器

风洞测试空气轮廓垂直轴

包扣故障信号分析 基于适配多级合并语理滤波

阵风波片编译

网状硬度和振荡响应器研究

Axis轨道图像优化应用

JournalWhirl下热不可测振

不可凝聚气质分数和载波振荡性能数学模型

包扣故障信号分析基于适配多级合并语理滤波