Wear Detection Method for Flexible Polishing Bonnet Tools Based on Improved Iterative Closest Point Splicing Algorithm

Fig. 1. Schematic of data acquisition platform detection. (a) Three-axis motion platform; (b) schematic of bonnet polishing precession; (c) R40 bonnet tool; (d) KEYENCE LJ-X8200 large range line laser sensor;（e）SmartRay ECCO95.020 small range line laser sensor；（f）R160 bonnet tool

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Fig. 2. R40 bonnet tool dataset

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Fig. 3. Data preprocessing effect

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Fig. 4. Three frames of adjacent point clouds

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Fig. 5. Specific process of the algorithm

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Fig. 6. Flow chart of bonnet wear detection algorithm

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Fig. 7. Registration effect of R40 bonnet tool. (a) PFH-ICP registration algorithm; (b) FPFH-ICP registration algorithm; (c) 3DSC-ICP registration algorithm; (d) NDT-ICP registration algorithm; (e) proposed crude registration -ICP; (f) proposed algorithm

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Fig. 8. Registration effect of R160 bonnet tool. (a) PFH-ICP registration algorithm; (b) FPFH-ICP registration algorithm; (c) 3DSC-ICP registration algorithm; (d) NDT-ICP registration algorithm; (e) proposed crude registration-ICP; (f) proposed algorithm

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Fig. 9. Bonnet tool point cloud obtained by one-time full scanning

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Fig. 10. Contour plot in Y direction obtained by the large range line laser sensor

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Fig. 11. Contour plot in X direction obtained by the large range line laser sensor

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Fig. 12. Contour plot in Y direction obtained by the proposed algorithm

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Fig. 13. Contour plot in X direction obtained by the proposed algorithm

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Table 1. Motion parameters of three-axis platform

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Table 1. Motion parameters of three-axis platform

Platform motion axis	Parameter	Precision
X axis	Maximum stroke is 430 mm	Single-axis repeatable positioning accuracy is ±0.5 μm
Y axis	Maximum stroke is 430 mm	Single-axis repeatable positioning accuracy is ±0.5 μm
Z axis	Maximum stroke is 200 mm	Single-axis repeatable positioning accuracy is ±0.5 μm

Table 2. Parameters of KEYENCE LJ-X8200 large range line laser sensor

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Table 2. Parameters of KEYENCE LJ-X8200 large range line laser sensor

Base distance（best test distance）/mm	Z-axis measurement range（height）/mm	X-axis measurement range（width）/mm	X-axis repeatability（width）/μm	Z -axis repeatability（height）/μm
245	211-279	64-80	3	1

Table 3. Parameters of SmartRay ECCO95.020 small range line laser sensor

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Table 3. Parameters of SmartRay ECCO95.020 small range line laser sensor

Base distance（best test distance）/mm	Z-axis measurement range（height）/mm	X-axis measurement range（width）/mm	X-axis repeatability（width）/μm	Z -axis repeatability（height）/μm
60	50-70	22-28	0.2	0.2

Table 4. Data preprocessing result
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Table 4. Data preprocessing result
Point cloud data Number of original point clouds Number of point clouds after preprocessing Point cloud count reduction /%
1 1338814 5960 99.6
2 2393770 2850 99.9
3 2402175 2825 99.9
4 2349507 2833 99.8

Table 5. Average rotation error of two registrations for R40 bonnet tool

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Table 5. Average rotation error of two registrations for R40 bonnet tool

Algorithm	X	Y	Z
PFH-ICP	0.1292	0.0092	-0.7553
FPFH-ICP	0.0852	0.0174	-0.7694
3DSC-ICP	0.1145	0.0088	-0.7789
NDT-ICP	0.1851	0.2904	-0.7503
Proposed crude registration algorithm-ICP	0.00003	0.0005	-0.7485
Proposed algorithm	0.00002	0.0004	-0.7358

Table 6. Average rotation error of two registrations for R160 bonnet tool

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Table 6. Average rotation error of two registrations for R160 bonnet tool

Algorithm	X	Y	Z
PFH-ICP	0.0613	0.3383	-0.7677
FPFH-ICP	0.0413	0.3626	-0.7664
3DSC-ICP	0.1142	0.0498	-0.7735
NDT-ICP	0.3574	0.2896	-0.7803
Proposed crude registration algorithm-ICP	0.0007	0.0008	-0.7448
Proposed algorithm	0.0005	0.0004	-0.7248

Table 7. Average translation error of two registrations for R40 bonnet tool

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Table 7. Average translation error of two registrations for R40 bonnet tool

Algorithm	X	Y	Z
PFH-ICP	0.0016	-0.2978	-0.1985
FPFH-ICP	0.0015	-0.2985	-0.1998
3DSC-ICP	0.0018	-0.2997	-0.1993
NDT-ICP	0.0153	-0.2982	-0.1956
Proposed crude registration algorithm-ICP	0.0006	-0.2968	-0.1945
Proposed algorithm	0.0005	-0.2950	-0.1931

Table 8. Average translation error of two registrations for R160 bonnet tool

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Table 8. Average translation error of two registrations for R160 bonnet tool

Algorithm	X	Y	Z
PFH-ICP	0.0023	-0.2949	-0.1963
FPFH-ICP	0.0092	-0.2975	-0.1988
3DSC-ICP	0.0018	-0.2999	-0.1994
NDT-ICP	0.0065	-0.2942	-0.1985
Proposed crude registration algorithm-ICP	0.0006	-0.2935	-0.1931
Proposed algorithm	0.0004	-0.2915	-0.1911

Table 9. Average registration completion time of two registrations for R40 bonnet tool

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Table 9. Average registration completion time of two registrations for R40 bonnet tool

Algorithm	Coarse registration	Precise registration	Total time
PFH-ICP	18.137	1.044	19.181
FPFH-ICP	9.294	1.007	10.301
3DSC-ICP	2.187	10.663	12.849
NDT-ICP	1.379	21.539	22.918
Proposed crude registration algorithm-ICP	0.248	1.805	2.053
Proposed algorithm	0.248	0.931	1.179

Table 10. Average registration completion time of two registrations for R160 bonnet tool

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Table 10. Average registration completion time of two registrations for R160 bonnet tool

Algorithm	Coarse registration	Precise registration	Total time
PFH-ICP	327.330	6.804	334.134
FPFH-ICP	210.703	7.345	218.048
3DSC-ICP	46.185	461.184	507.369
NDT-ICP	6.345	44.387	50.732
Proposed crude registration algorithm-ICP	1.153	14.692	15.845
Proposed algorithm	1.153	7.845	8.998

Table 11. Wear depth of R40 bonnet tool
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Table 11. Wear depth of R40 bonnet tool
Method $\bar{Z_x}$ $\bar{Z_y}$ （ $\bar{Z_x}$ + $\bar{Z_y}$ ）/2
Wear depth error 0.0017 0.015 0.0067
One-time full scanning 0.2309 0.3372 0.2841
Proposed algorithm 0.2326 0.3222 0.2774

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Minhui Zheng, Zhenzhong Wang, Xuepeng Huang, Lucheng Li. Wear Detection Method for Flexible Polishing Bonnet Tools Based on Improved Iterative Closest Point Splicing Algorithm[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1612001

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