The testing technique with high dynamic range is required to meet the measurement of refractive wavefront with large distortion from test refractive surface. A general deflectometric method based on reverse Hartmann test is proposed to test refractive surfaces. Ray tracing of the modeled testing system is performed to reconstruct the refractive wavefront from test surface, in which computer-aided optimization of system geometry is performed to calibrate the geometrical error. For the refractive wavefront error with RMS 255 μm, the testing precision better than 0.5 μm is achieved.
In the fringe-illumination deflectometry based on reverse-Hartmann-test configuration, ray tracing of the modeled testing system is performed to reconstruct the test surface error. Careful calibration of system geometry is required to achieve high testing accuracy. To realize the high-precision surface testing with reverse Hartmann test, a computer-aided geometrical error calibration method is proposed. The aberrations corresponding to various geometrical errors are studied. With the aberration weights for various geometrical errors, the computer-aided optimization of system geometry with iterative ray tracing is carried out to calibration the geometrical error, and the accuracy in the order of subnanometer is achieved.
The submicron-aperture fiber point-diffraction interferometer (SFPDI) can be applied to realize the measurement of
three-dimensional absolute displacement within large range, in which the performance of point-diffraction wavefront and
numerical iterative algorithm for displacement reconstruction determines the achievable measurement accuracy,
reliability and efficiency of the system. A method based on fast searching particle swarm optimization (FS-PSO)
algorithm is proposed to realize the rapid measurement of three-dimensional absolute displacement. Based on the SFPDI
with two submicron-aperture fiber pairs, FS-PSO method and the corresponding model of the SFPDI, the measurement
accuracy, reliability and efficiency of the SFPDI system are significantly improved, making it more feasible for practical
application. The effect of point-diffraction wavefront error on the measurement is analyzed. The error of pointdiffraction
wavefront obtained in the experiment is in the order of 1×10-4λ (the wavelength λ is 532 nm), and the
corresponding displacement measurement error is smaller than 0.03 μm. Both the numerical simulation and comparison
experiments have been carried out to demonstrate the accuracy and feasibility of the proposed SFPDI system, high
measurement accuracy in the order of 0.1 μm, convergence rate (~90.0%) and efficiency have been realized with the
proposed method, providing a feasible way to measure three-dimensional absolute displacement in the case of no guide
The posture and size of workpiece in pixel level can be determined through optimization of the internal parameters of the camera, utilizing the enclosing rectangle method based on rotation axis to position the workpiece. After selecting ROI of the object, the sub-pixel edge of workpiece is extracted using the bilinear interpolation algorithm and Hessian paradigm line fitting is utilized to find the object edge accurately. The industrial camera with 5 million pixels is used, and the sizes from 80mm to 150mm of the workpiece are measured under the condition of panorama shooting, with measurement repeatability reaching 0.015mm.
A measurement method with calotte cube was proposed to realize the high-precision calibration of size error in industrial computer tomography (CT) system. Using the traceability of calotte cube, the measurement of the repeatability error, probing error and length measurement error of industrial CT system was carried out to increase the acceptance of CT as a metrological method. The main error factors, including the material absorption, projection number and integration time and so on, had been studied in detail. Experimental results show that the proposed measurement method provides a feasible way to measure the size error of industrial CT system. Compared with the measurement results with invar 27- sphere gauge, a high accuracy in the order of microns is realized with the proposed method based on calotte cube. Differing from the invar 27-sphere gauge method, the material particularity of calotte cube (material of metallic titanium) could introduce beam hardening effect, the study on the influence of material absorption and structural specificity on the measurement, which provides significant reference for the measurement of metallic samples, is necessary.
Local mean decomposition (LMD) is a time-frequency analysis approach to deal with complex multi-frequency signal. However, as the decomposition process is sensitive to noise, there is a distinct limit when it is applied to analysis of the vibration signals of machinery with serious background noise. An improved LMD algorithm based on extracting the extrema of envelope curve is put forward to reduce the influence of high-frequency noise effectively. To verify its effect, three different de-noising methods, i.e., band-pass filter method, wavelet method and lift wavelet method are used, respectively. And the comparison result of the 4 methods shows that the proposed method has satisfactory reproducibility. Then the new algorithm is applied to real bearing signal, and experimental results show that it is effective and reliable. The method also has certain significance for the subsequent eigenvector research in intelligent fault diagnosis.
To solve the problem of feature extraction of weak gear fault under strong noise background, an early feature extraction method based on cascaded monostable stochastic resonance (CMSR) system and empirical mode decomposition (EMD) with teager energy operator demodulation was proposed. The model of monostable stochastic resonance expanded the processing range of characteristic frequency of the measured signal, and had a good effect on denoising performance by cascading. Firstly CMSR was employed as the preprocessor to remove noise, then the denoised signal was decomposed into a series of intrinsic mode functions (IMFs) of different scales by EMD, and finally teager energy operator demodulation was applied to obtain amplitudes and frequencies of each effective IMF to extract the weak gear fault feature. Simulation and application results showed that the proposed method could effectively detect the characteristic frequency of gear fault of local damage after the noise reduction by CMSR.
Against the image characteristics of dial gauges, an automatic detection system of dial gauges is designed and
implemented by using the technology of computer vision technology and digital image processing methods. Improved
image subtraction method and adaptive threshold segmentation method is used for previous processing; a new method
named as region-segmentation is proposed to partition the dial image, only the useful blocks of the dial image is
processed no the other area, this method reduces the computation amount greatly, and improves the processing speed
effectively. This method has been applied in the automatic detection system of dial gauges, which makes it possible for
the detection of dial gauges to be finished intelligent, automatically and rapidly.
A replacement algorithm used in the calculation of roundness errors by a least regional fitting method has been proposed
in this paper. Using the high fitting precision initial-value, which is calculated by the relative algebraic distance method,
the replacement algorithm needs less iterations and has a higher calculation speed. Simulation tests show the higher
fitting accuracy. The replacement algorithm by using computer programming is applied to measurement software of a
universal tools microscope.