Research Article

Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning

Table 3

Correlation coefficient matrix at normal state.

SensorV1XV1YV2XV2yV3xV3yV4xV4yF1F2F3F4

V1x0.490.970.950.470.970.430.960.400.370.450.350.31
V1y0.390.380.650.890.610.960.580.980.610.640.590.50
V2x0.740.220.640.270.950.220.890.190.720.650.550.65
V2y0.530.630.150.310.491.000.611.000.280.100.070.32
V3x0.840.360.690.540.420.460.970.420.720.520.470.65
V3y0.680.530.440.810.710.490.571.000.140.350.260.08
V4x0.710.060.710.220.760.180.460.550.810.560.510.83
V4y0.340.510.440.660.350.830.250.260.100.300.190.06
F10.120.050.270.070.030.150.250.100.430.880.780.97
F20.200.020.470.040.090.130.510.300.880.550.950.79
F30.290.030.570.000.220.220.630.190.780.950.630.64
F40.370.160.580.110.420.350.610.060.970.790.640.57