1. School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China 2. Jiangsu Key Laboratory of Advanced Manufacturing for Marine Machinery and Equipment, Zhenjiang 212003, China
An orthogonal analysis method of fused deposition molding (FDM) 3D printing drawing defects based on vibration signals was proposed in order to solve the abnormal working conditions of wire drawing in the printing process in time. The single factor test was conducted, and the time domain analysis of the signal collected by the acceleration vibration sensor was conducted. The correlation kurtosis, peak factor and pulse factor eigenvalues were extracted to determine the relationship between the four printing parameters, namely, nozzle temperature, pullback distance, pullback rate, empty driving speed and drawing defects of the parts. The four-factor and three-level orthogonal test was conducted based on the single-factor test, and the extracted time-domain eigenvalues of vibration signals were taken as the evaluation index. The test data were analyzed by range and variance analysis. The test results show that the on-line monitoring method based on acceleration vibration sensor can identify the drawing defects very well. The drawing distance and nozzle temperature significantly affect the drawing defects when the used material is PLA, while the effects of empty driving speed and drawing speed are not significant. The wire drawing condition of the printing model is the best when the nozzle temperature is 190 ℃, the drawing speed is 50 mm/s, the drawing distance is 12 mm and the empty driving speed is 50 mm/s.
Fig.3Time domain diagram of sensor Ⅲ different factors and horizontal vibration signals
Fig.4Relationship between different factor levels and kurtosis indexes
Fig.5Relationship between different factor levels and peak factor indexes
Fig.6Relationship between different factor levels and impulse factor index
Fig.7Printed physical pictures of 9 groups of orthogonal tests
试验编号
传感器Ⅰ
传感器Ⅱ
传感器Ⅲ
K
C
I
K
C
I
K
C
I
S1
6.38
5.54
5.89
5.17
3.82
5.18
4.83
5.48
6.70
S2
4.88
4.64
5.73
4.94
4.32
5.05
5.71
4.37
5.71
S3
6.58
5.47
7.98
6.62
4.95
6.33
6.64
5.77
7.58
S5
7.24
7.98
8.26
7.01
6.07
6.96
6.86
6.03
6.45
S6
4.48
4.40
5.13
3.90
3.92
5.27
3.87
3.79
4.54
S7
6.05
5.20
6.58
5.30
5.32
6.12
5.07
5.32
7.02
S8
4.35
4.81
5.36
4.56
3.62
5.34
4.39
4.83
5.54
S9
3.65
4.32
5.02
3.73
3.29
5.08
4.14
3.83
4.96
Tab.3Characteristic indexes of vibration signals of three sensors
指标
因素
K1
K2
K3
$ \overline {{K_1}}$
$ \overline {{K_2}} $
$ \overline {{K_3}} $
R
水平主次
因素主次
峭度
A
17.85
17.40
14.04
5.95
5.80
4.68
1.27
1 2 3
C > A > B > D
B
18.09
16.47
14.70
6.03
5.49
4.90
1.13
1 2 3
C
15.21
14.19
19.86
5.07
4.73
6.62
1.89
3 1 2
D
17.28
15.42
16.59
5.76
5.14
5.53
0.62
1 3 2
峰值因子
A
15.66
18.75
14.34
5.22
6.25
4.78
1.47
2 1 3
A > C > D > B
B
17.10
17.43
14.19
5.70
5.81
4.73
1.08
2 1 3
C
14.76
15.33
18.66
4.92
5.11
6.22
1.30
3 2 1
D
17.85
14.25
16.65
5.95
4.75
5.55
1.20
1 3 2
脉冲因子
A
19.59
19.44
16.95
6.53
6.48
5.65
0.88
1 2 3
C > A > D > B
B
18.54
19.35
18.12
6.18
6.45
6.04
0.41
2 1 3
C
16.38
16.80
22.83
5.46
5.60
7.61
2.15
3 2 1
D
19.17
17.43
19.41
6.39
5.81
6.47
0.66
3 1 2
Tab.4Analysis of index range under sensor Ⅰ
Fig.8Horizontal trend diagram of various sensor indicators and factors
指标
方差来源
df
SS
MS
F
传感器Ⅰ峭度
A
2
8.53
4.27
5.47
B
2
5.00
2.50
3.21
C
2
17.34
8.67
11.13
D
2
1.85
0.93
1.19
传感器Ⅱ峭度
A
2
9.94
4.97
7.42
B
2
5.88
2.94
4.39
C
2
7.49
3.75
5.59
D
2
5.01
2.51
3.74
传感器Ⅲ峭度
A
2
5.56
2.78
4.09
B
2
1.03
0.52
0.76
C
2
26.59
13.29
19.59
D
2
2.05
1.02
1.51
Tab.5Analysis of variance of kurtosis index
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