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Table 5 Feature vector samples for learning (rolling bearing)

From: An approach to performance assessment and fault diagnosis for rotating machinery equipment

Number

1

2

3

4

5

6

7

8

N_1

0.8111

0.5012

0.0524

0.2964

0.0002

0.0018

0.0053

0.0187

N_2

0.8259

0.4665

0.0544

0.3112

0.0002

0.0019

0.0054

0.02

N_3

0.7891

0.5274

0.0524

0.3097

0.0002

0.0018

0.0053

0.0204

N_4

0.8137

0.493

0.0553

0.3023

0.0002

0.0018

0.0056

0.0194

I_1

0.0795

0.2297

0.5852

0.1497

0.0014

0.0081

0.7446

0.1471

I_2

0.0823

0.2226

0.5831

0.1464

0.0015

0.0082

0.7467

0.157

I_3

0.081

0.2341

0.6031

0.1474

0.0014

0.0084

0.7306

0.1388

I_4

0.0723

0.2279

0.5922

0.1505

0.0014

0.0092

0.7412

0.1417

O_1

0.0069

0.0096

0.4907

0.0156

0.0082

0.0137

0.8681

0.0707

O_2

0.0065

0.0096

0.4945

0.0161

0.0081

0.0137

0.8655

0.0759

O_3

0.0069

0.0098

0.4831

0.0145

0.0076

0.0121

0.8725

0.0696

O_4

0.0065

0.01

0.5217

0.016

0.007

0.0124

0.8492

0.0777

B_1

0.045

0.0449

0.4876

0.0184

0.0005

0.0027

0.8703

0.0181

B_2

0.0443

0.0424

0.457

0.0189

0.0005

0.0025

0.887

0.0179

B_3

0.0426

0.0436

0.464

0.0187

0.0005

0.0025

0.8833

0.0186

B_4

0.0412

0.042

0.4584

0.0179

0.0004

0.0022

0.8865

0.0175