Detection of motor rotor position based on image reversible phase-correlation algorithm

Ji-wen, 赵吉文 Zhao; Biao, 黄彪 Huang; Li-zhi, 王荔枝 Wang; Hong-biao, 吴红标 Wu

doi:10.3788/ope.20132106.1613

光学精密工程

2013

DOI: 10.3788/ope.20132106.1613

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Detection of motor rotor position based on image reversible phase-correlation algorithm

赵吉文 Zhao Ji-wen¹,

黄彪 Huang Biao²,

王荔枝 Wang Li-zhi³

et al.

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“…The extraction principle of point laser spot center based on the phase correlation is using Fourier transform to convert the template and detected spot image into frequency domain signal to get the phase correlation of the two images' correlation and take inverse transform [7,8,9,10,11,12].…”

mentioning

confidence: 99%

Research on the Recursive and Step-by-Step Algorithm for Extraction of Point Laser Spot Center

Yang

2014

AMR

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Whentesting the flatness of plate iron, if there is no disturbance in the spotdetection, the traditional centroid method and circle fitting method can bewell applied to extract the point laser spot center. However, the disturbanceof droplets, dusts, oil droplet and other factors are unavoidably in thepractical projects, and then the detection precision will falls sharply. In orderto solve the problem, the recursive and step-by-step method of extracting pointlaser spot center is proposed. There are two steps in this method.The thresholdcentroid method is used as the first step to extract the spots which containthe black blocks. The second step is to construct the template whose center hasa black block, then extract the black block center by running phase correlationalgorithm and the center is just the center of the point laser spot. Theresults of experiments verify that the precision of the spot center coordinateextracted by the proposed method is obviously higher than that extracted by thecentroid method and the circle fitting method with the disturbance of droplets.

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mentioning

confidence: 99%

Research on the Recursive and Step-by-Step Algorithm for Extraction of Point Laser Spot Center

Yang

2014

AMR

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Vision-based measurement for rotational speed by improving Lucas–Kanade template tracking algorithm

Guo

Zhu

et al. 2016

Appl. Opt.

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Rotational angle and speed are important parameters for condition monitoring and fault diagnosis of rotating machineries, and their measurement is useful in precision machining and early warning of faults. In this study, a novel vision-based measurement algorithm is proposed to complete this task. A high-speed camera is first used to capture the video of the rotational object. To extract the rotational angle, the template-based Lucas-Kanade algorithm is introduced to complete motion tracking by aligning the template image in the video sequence. Given the special case of nonplanar surface of the cylinder object, a nonlinear transformation is designed for modeling the rotation tracking. In spite of the unconventional and complex form, the transformation can realize angle extraction concisely with only one parameter. A simulation is then conducted to verify the tracking effect, and a practical tracking strategy is further proposed to track consecutively the video sequence. Based on the proposed algorithm, instantaneous rotational speed (IRS) can be measured accurately and efficiently. Finally, the effectiveness of the proposed algorithm is verified on a brushless direct current motor test rig through the comparison with results obtained by the microphone. Experimental results demonstrate that the proposed algorithm can extract accurately rotational angles and can measure IRS with the advantage of noncontact and effectiveness.

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Detection of motor rotor position based on image reversible phase-correlation algorithm

Cited by 2 publications

References 0 publications

Research on the Recursive and Step-by-Step Algorithm for Extraction of Point Laser Spot Center

Research on the Recursive and Step-by-Step Algorithm for Extraction of Point Laser Spot Center

Vision-based measurement for rotational speed by improving Lucas–Kanade template tracking algorithm

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