| 光谱学与光谱分析 |
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| Backscattering Characteristics of Machining Surfaces and Retrieval of Surface Multi-Parameters |
| TAO Hui-rong, ZHANG Fu-min*, QU Xing-hua |
| State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China |
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Abstract For no cooperation target laser ranging, the backscattering properties of the long-range and real machined surfaces are uncertain which seriously affect the ranging accuracy. It is an important bottleneck restricting the development of no cooperation ranging technology. In this paper, the backscattering characteristics of three typical machining surfaces (vertical milling processing method, horizontal milling processing method and plain grinding processing method) under the infrared laser irradiation with 1 550 nm were measured. The relation between the surface machining texture, incident azimuth, roughness and the backscattering distribution were analyzed and the reasons for different processing methods specific backscattering field formed were explored. The experimental results show that the distribution of backscattering spectra is greatly affected by the machined processing methods. Incident angle and roughness have regularity effect on the actual rough surface of each mode. To be able to get enough backscattering, knowing the surface texture direction and the roughness of machined metal is essential for the optimization of the non-contact measurement program in industry. On this basis, a method based on an artificial neural network (ANN) and genetic algorithm (GA), is proposed to retrieve the surface multi-parameters of the machined metal. The generalized regression neural network (GRNN) was investigated and used in this application for the backscattering modeling. A genetic algorithm was used to retrieve the multi-parameters of incident azimuth angle, roughness and processing methods of machined metal surface. Another processing method of sample (planer processing method) was used to validate data. The final results demonstrated that the method presented was efficient in parameters retrieval tasks. This model can accurately distinguish processing methods and the relative error of incident azimuth and roughness is 1.21% and 1.03%, respectively. The inversion accuracy is high. It can reduce the impact of surface texture, the incident azimuth and incidence angle to the ranging scope. The experiments proved that the inversion of the surface parameters greatly broadened the ranging scope in no cooperation target laser ranging. Taking the Vertical milling sample with roughness Ra=6.3 μm for example, the measuring range can be increased by about 22 m when the incidence angle is increased in the incidence plane which is vertical to the surface texture. The study results of this paper have a certain reference value to the research of the backscattering of machined surface and its application in other areas.
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Received: 2015-01-07
Accepted: 2015-04-22
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Corresponding Authors:
ZHANG Fu-min
E-mail: zhangfumin@tju.edu.cn
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