Research On Precision Vision Measurement Technology And Its Applications Under Strong Interference Conditions

The measurement technology based on computer vision has many significant advantages such as non-contact, flexibility and high integration, so it has a widespread application prospect in industrial testing. In extreme industrial environments, vibration, noise, mist, dust and other disturbances could have an adverse impact on vision measurement in the aspects of stability and accuracy. If a system always works under harsh conditions, the interference factors above will also cause the measurement device to deliver poor performance, to further reduce the detection accuracy and even to suffer system failure. System maintenance, as an important way to ensure system stability is to be minimized because it is difficult to implement in harsh industrial environment. It is difficult for existing vision measurement technology to guarantee accuracy and long-term reliability of detection under the condition of strong interference. Research of the vision measurement technology stable and accurate under strong interference conditions is a realistic and challenging work.Funded by the national science and technology major project,200MN Horizontal Extruder for Super Alloy (2009ZX04005-031), the technical transformation project of Southwest aluminum group, Technological Transformation of125mn Extruder, and the pre-research project of the state-operated Jiang-bei machinery factory under the No. Nine institute of aeronautics and astronautics, Computer Vision-based Swing Center Testing System for Flexible Joint, this paper present the systematical and intensive research of precision vision measurement technology under strong interference conditions from four aspects of feature extraction, image enhancement, precision calibration and data processing by combining theoretical analysis and experimental research. The hardware and software design and improved on the real industrial measuring system were achieved by integrating the above research results. The major work and innovations can be summarized as follows:1. The applicability scope, advantages and limitations of common image segmentation and circular feature extraction algorithm were systematically analyzed in light of the characteristics of industrial environment; and a fast precise circular feature extraction method based on regional and edge accurate positioning. This method based on Canny edge detector, Hough transform and curve fitting feature extraction technology gives excellent performance under noisy conditions and realizes high-precision feature extraction rapid under strong jamming. It can be used for multi-feature detection under complex background also.2. The advantages and limitations of common noise suppression and image enhancement method were discussed. For the most common problem in detection of very low quality images under the extreme conditions, a laser edge image inpainting method based on pixel adjacency analysis was presented combining distance transform and connected component analysis theory. This method can effectively repair larger edge gap and remove larger noises through the analysis of one single label image while the value of introduced error of centering measurement is steadily kept low. The method could also be applied to the measurement system whose detection feature is circle or ellipse.3. A linear imaging model and an introduced non-linear distortion imaging model by the principle of perspective were analyzed. To meet the requirement of industrial online measurement and in light of its characteristic, a method for accuracy calibration and maintenance of the industrial measurement system based on straight line distortion equation was presented. This method changes the parameter process of traditional optimized iterative solution system to data fitting, reducing the sensitivity to ambient noise; the calibration process consists of two steps:image distortion correction and position error correction, the layout of feature point, after optimization, become simple. An active vision implementation example by the new method was presented. The experimental results indicated that this method is high precise and easily applicable. It is an effective solution for accuracy calibration and maintenance of the industrial measurement system.4. In order to further improve the visual measuring system performance in the industrial test, some work was done to analyze a series of filter methods based on Bayesian theory, discuss the advantages and limitations of each method in light of the characteristics of industrial online detection. Sage-Husa adaptive Kalman filter and its improved algorithm werw chosen as the focus and the application of Sage-Husa adaptive filtering algorithm in system error suppression and feature extraction proposed.5. Part of research results in this paper was applied as system upgrade to the125MN extruder moving parts center online monitoring system. A real-time monitoring method for five-degrees-of-freedom of the large extruder's moving parts and a computer vision-based swing center testing method for flexible joint were proposed integrating the above research results and the latest progress of electronic measurement technology. A field test of the swing center testing method was conducted.