Research Article

Health State Assessment of Industrial Equipment Driven by the Fusion of Digital Twin Model and Intelligent Algorithm

Table 4

Part of the preprocessed data.

Parameter 1Parameter 2Parameter 3Parameter 4Parameter 5Parameter 6Grade identification

0.280.800.170.510.910.3201000
0.300.040.250.250.340.0510000
0.790.330.140.180.690.2010000
0.530.210.270.850.880.5700100
0.280.840.240.210.110.9010000
0.220.610.170.380.520.9701000
0.800.570.590.600.420.4500100
0.780.690.170.790.830.3200100
0.030.540.870.070.040.7901000
0.760.420.500.490.780.6101000
0.100.670.060.030.540.4810000
0.570.620.920.530.480.8200010
0.960.820.440.160.450.2510000
0.960.960.100.270.370.4210000
0.450.150.180.420.660.7210000
0.900.740.060.110.000.7401000
0.040.620.580.650.040.5100100
0.800.160.580.430.880.3401000
0.830.570.190.510.670.6700010
0.140.650.650.020.160.1010000
0.830.830.650.440.210.4801000
0.080.440.560.560.320.9201000
0.380.880.160.740.210.0510000
0.310.750.980.330.180.8801000
0.500.360.720.120.770.1010000