Table 6 ACC, F1-score, and Recall comparison of different models in UofO dataset under different SNRs (%).

From: Attention activation network for bearing fault diagnosis under various noise environments

SNR (dB)

− 9

− 6

− 3

Model

Noise type

ACC

F1-score

Recall

ACC

F1-score

Recall

ACC

F1-score

Recall

MLSCA-CW (two locations)

Gauss-noise

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

Laplace-noise

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

Violet-noise

99.744

99.744

99.744

100.000

100.000

100.000

100.000

100.000

100.000

Brownian-noise

95.819

95.828

95.819

96.160

96.084

96.087

96.331

96.349

96.355

Mixed-noise

73.976

73.987

73.976

81.655

81.630

81.607

86.263

86.059

85.990

MLSCA-CW (single location)

Gauss-noise

89.759

89.837

89.759

92.918

92.943

93.013

99.915

99.917

99.916

Laplace-noise

88.055

87.764

88.055

99.829

99.825

99.829

99.829

99.823

99.823

Violet-noise

67.491

66.903

67.491

67.662

66.959

66.957

68.515

68.431

68.515

Brownian-noise

69.966

70.422

69.966

71.331

71.388

71.177

78.157

77.906

77.771

Mixed-noise

63.140

62.380

63.450

64.505

56.557

64.944

66.212

59.645

66.212

LR

Gauss-noise

80.887

80.857

80.887

81.399

81.206

81.686

82.594

82.203

82.594

Laplace-noise

80.802

80.574

80.802

81.826

81.531

81.826

83.532

83.170

83.532

Violet-noise

62.201

60.689

62.201

65.785

62.516

64.547

68.345

67.076

68.345

Brownian-noise

32.594

18.560

32.594

33.703

20.273

33.481

35.410

23.759

35.410

Mixed-noise

37.500

37.080

37.500

38.225

34.837

38.225

43.345

39.934

43.078

MC-CNN

Gauss-noise

95.734

95.737

95.734

97.440

97.438

97.440

100.000

100.000

100.000

Laplace-noise

94.966

94.968

94.966

96.416

96.413

96.416

100.000

100.000

100.000

Violet-noise

81.911

81.878

81.911

85.448

85.391

85.448

92.217

92.126

92.217

Brownian-noise

41.076

40.546

41.076

46.200

45.463

46.200

95.601

95.588

95.601

Mixed-noise

68.174

68.443

68.174

70.734

70.804

70.734

74.147

74.209

74.147

WDCNN

Gauss-noise

73.294

73.266

73.294

74.915

74.944

74.915

99.915

99.916

99.916

Laplace-noise

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

Violet-noise

65.870

63.396

65.870

67.065

66.142

67.044

69.625

68.699

69.625

Brownian-noise

72.952

72.924

72.952

73.294

73.418

73.175

76.024

75.754

75.671

Mixed-noise

68.089

68.240

68.381

70.478

70.141

70.070

73.891

73.745

73.891

Multiscale inner product

Gauss-noise

92.491

92.495

92.491

95.648

95.671

95.648

97.355

97.367

97.355

Laplace-noise

89.505

89.501

89.505

92.065

92.064

92.065

94.625

94.619

94.625

Violet-noise

83.959

83.930

83.959

85.666

85.646

85.666

88.225

88.208

88.225

Brownian-noise

91.041

91.043

91.041

92.747

92.753

92.747

95.307

95.308

95.307

Mixed-noise

69.120

69.098

69.120

72.504

72.453

72.504

74.196

74.229

74.196

SANet

Gauss-noise

69.795

69.414

69.795

78.157

76.166

78.505

79.863

78.058

79.863

Laplace-noise

68.345

58.102

68.345

69.198

59.924

69.198

71.758

64.939

71.758

Violet-noise

66.638

64.001

66.638

67.065

67.083

67.199

68.601

68.450

68.601

Brownian-noise

52.986

52.579

52.986

55.205

51.545

55.219

56.911

53.621

56.911

Mixed-noise

53.840

53.528

54.046

55.034

54.700

54.862

58.106

57.489

58.106

QCNN

Gauss-noise

99.829

99.829

99.829

100.000

100.000

100.000

100.000

100.000

100.000

Laplace-noise

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

100.000

Violet-noise

67.235

66.850

67.235

69.113

67.640

68.070

70.819

70.205

70.819

Brownian-noise

52.218

52.018

52.218

54.181

49.979

54.194

56.485

56.316

56.485

Mixed-noise

72.696

72.369

72.696

74.061

73.675

73.680

75.341

75.333

75.341

  1. Best results is highlighted