Positioning the actual interference fringe pattern on the tooth flank in measuring gear tooth flanks by laser interferometry

Abstract

In measuring form deviation of gear tooth flanks by laser interferometry, the collected interference fringe pattern (IFP) is badly distorted, in the case of shape, relative to the actual tooth flank. Meanwhile, a clear and definite mapping relationship between the collected IFP and the actual tooth flank is indispensable for both transforming phase differences into deviation values and positioning the measurement result on the actual tooth flank. In order to solve these problems, this paper proposes a method using the simulation tooth image as a bridge connecting the actual tooth flank and the collected IFP. The mapping relationship between the simulation tooth image and the actual tooth flank has been obtained by ray tracing methods [Fang et al., Appl. Opt. 49(33), 6409 -6415 (2010)]. This paper mainly discusses how to build the relationship between the simulation tooth image and the collected IFP by using a matching algorithm of two characteristic point sets. With the combination of the two above-mentioned assistant mapping relationships, the mapping relationship between the collected IFP and the actual tooth flank can be built; the collected IFP can be positioned on the actual tooth flank. Finally, the proposed method is employed in a measurement of the form deviation of a gear tooth flank and the result proves the feasibility of the proposed method. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

Object image and modulation-based method to segment gear tooth flank region from interference fringe patterns

“…Previous research has found that the boundary curves fitted by the least square method can fit the gear tooth flank region effectively, and these fitted boundary curves can be directly used to match with the simulated IFP. 10,11 So, based on the boundary points of the gear tooth flank region at the beam inside, the tip, and the beam outside, the three boundary curves of the gear tooth flank region for the matching step can be obtained by the least square method, as shown in Fig. 4(c).…”

“…9 The main objective of the matching step is to establish the correlation between the coordinate of the image and that of the tooth flanks. [10][11][12] In the end, the deviation information is calculated through the phase information, and it is positioned onto the actual gear tooth flank by the correlation established through the matching step. Obviously, the segmentation of the gear tooth flank region is the first step of the whole image processing process, and its result is critical to the entire measurement system.…”

“…In addition, all the current studies in this measurement system are to complete the segmentation of the gear tooth flank region first and then carry out the matching step. 10,11,22 However, it can be found from the previous introduction that the matching step is closely related to the segmentation of the gear tooth flank region. The final deviation information is also dependent on the unwrapped phase value corresponding to each pixel in the matched simulation IFP.…”

A method combining laser and vision detection for on-line measurement of small modules gears

“…Kang et al [10] used a line laser sensor on a coordinate measuring machine (CMM) to scan and measure 3D tooth surfaces and perform 3D tooth surface characterization and evaluation. Lu et al [11] proposed an optical method for gear flank measurement based on the phase-shifted optical triangulation principle, which uses a phase expansion algorithm to obtain surface topography with micron-level resolution; Fang et al [12,13] developed a laser interferometric gear measurement system and proposed a method to use simulated tooth surface images as a bridge between the actual tooth surface and the interferometric fringes for positioning the collected interferometric fringes; Hamid et al [14] investigated the use of a point self-focusing probe for tooth profile measurement and 3D full gear measurement, and the obtained point cloud data were compared with nominal CAD models; Katsuhiro et al developed a point autofocus probe gear measurement method with a high degree of angular tracking capability; Guo et al [15] proposed a 3D point cloud measurement system based on a line laser sensor and a high-precision air-bearing rotary table, which can acquire more than 1.5 million 3D data points on a single side of a gear tooth surface within 5 s. Zhou et al [16] proposed a production-site oriented gear rapid sorting and inspection system based on the visual measurement principle to collect defects such as missing teeth, black spots, and phi-fronts of gears for detection, and the inspection speed can reach 150 pcs min −1 .…”

Autofocusing algorithm of interferogram based on object image and registration technology

“…So the registration technology is employed to establish the corresponding relationship between the collected interferogram and the measured tooth flank [8].…”