Abstract: A battery malfunction detection method includes: applying a preset number of vibration signals with different frequencies to a battery to be detected through a vibration generation device; collecting a response signal of the battery to be detected through a response collection device, where the response signal includes the preset number of vibration response amplitudes of the battery to be detected; determining whether the battery to be detected is malfunctioning according to the response signal.

Abstract: Relating to the technical field of batteries, and provided are a battery fault detection method, a battery fault detection system, a terminal, and a computer-readable storage medium. The method comprises: by means of a vibration generation device, sequentially applying a preset number of vibration signals of different frequencies to a battery to be tested (301); collecting response signals of the battery by means of a response collection device (302), the response signals comprising a preset number of vibration response amplitudes of the battery, wherein the preset number of vibration response amplitudes are separately generated by the battery under the action of vibration signals of different frequencies; and according to the response signals, determining whether the battery is faulty (303). By means of the described method, it is possible to quickly and non-destructively detect whether a battery is faulty.

Abstract: A method and a device for 3D shape matching based on a local reference frame are proposed. After acquiring a 3D point cloud and feature points in the method, the feature point set is projected to a plane, and feature transformation is performed on the projected points by using at least one factor from the distances between the 3D points and the feature points, the distances between the 3D points and the projected points, and the average distances between the 3D points and its 1-ring neighboring points to acquire a point distribution with a larger variance in a certain direction than the projected point set, and the local reference frame is determined based on the transformed point distribution. The 3D local feature descriptor established based on this local reference frame can encode the 3D local surface information more robustly, so as to obtain a better 3D shape matching effect.

Abstract: A 3D shape matching method and a 3D shape matching device based on 3D local feature description using SGHs are provided. In the method, the spherical neighborhood of the feature point is not only divided based on space but also divided based on geometry, the spherical neighborhood of the feature point is not only divided based on the radial direction and the azimuth respectively but also divided based on the elevation, and the spherical neighborhood of the feature point is not only divided based on the deviation angle deviating from the z axis but also divided based on the deviation angle deviating from the x axis. When the deviation angle deviating from the z axis of the spherical neighborhood is divided, the deviation angle is divided more densely where it is closer to the positive direction of the z axis.

Abstract: A method and a device for 3D shape matching based on a local reference frame are proposed. After acquiring a 3D point cloud and feature points in the method, the feature point set is projected to a plane, and feature transformation is performed on the projected points by using at least one factor from the distances between the 3D points and the feature points, the distances between the 3D points and the projected points, and the average distances between the 3D points and its 1-ring neighboring points to acquire a point distribution with a larger variance in a certain direction than the projected point set, and the local reference frame is determined based on the transformed point distribution. The 3D local feature descriptor established based on this local reference frame can encode the 3D local surface information more robustly, so as to obtain a better 3D shape matching effect.

Abstract: A calibration method is described for a telecentric imaging 3D shape measurement system, including step S1: establishing a telecentric 3D shape measurement system; S2: controlling a telecentric projection equipment to project a sinusoidal fringe pattern to a translation stage, and collecting the sinusoidal fringe pattern by a telecentric camera equipment; moving the translation stage to different depth, then obtaining absolute phase values of a pixel for calibration by a phase-shifting method; and conducting linear fitting on the series of absolute phase values of the pixel and the corresponding depths to obtain a phase-depth conversion of the measurement system; and S3: transforming pixel coordinates on the image plane of the telecentric camera equipment into world coordinates through calibrating parameters of the telecentric camera equipment. A relationship between phase and depth herein is linear, and only needs to calibrate the linearity of one pixel.

Abstract: A method and system for calculating laser beam spot size, comprising: collecting a spot image of a laser beam and a corresponding background noise image along an optical axis direction; conducting pretreatment using a background subtraction method and a threshold method according to the spot image and the background noise image collected to obtain a pretreated spot image; calculating the central position of a laser spot of the pretreated spot image; and storing the pixel gray values of the spot image at the central position of the laser spot on a horizontal direction and a vertical direction, then conducting Gaussian curve fitting, calculating variances of Gaussian fitted curves on the horizontal direction and the vertical direction, and obtaining the spot radiuses of the spot image on the horizontal direction and the vertical direction according to the variances calculated.

Abstract: A method and system for calculating laser beam spot size, comprising: collecting a spot image of a laser beam and a corresponding background noise image along an optical axis direction; conducting pretreatment using a background subtraction method and a threshold method according to the spot image and the background noise image collected to obtain a pretreated spot image; calculating the central position of a laser spot of the pretreated spot image; and storing the pixel gray values of the spot image at the central position of the laser spot on a horizontal direction and a vertical direction, then conducting Gaussian curve fitting, calculating variances of Gaussian fitted curves on the horizontal direction and the vertical direction, and obtaining the spot radiuses of the spot image on the horizontal direction and the vertical direction according to the variances calculated.

Abstract: A calibration method is described for a telecentric imaging 3D shape measurement system, including step S1: establishing a telecentric 3D shape measurement system; S2: controlling a telecentric projection equipment to project a sinusoidal fringe pattern to a translation stage, and collecting the sinusoidal fringe pattern by a telecentric camera equipment; moving the translation stage to different depth, then obtaining absolute phase values of a pixel for calibration by a phase-shifting method; and conducting linear fitting on the series of absolute phase values of the pixel and the corresponding depths to obtain a phase-depth conversion of the measurement system; and S3: transforming pixel coordinates on the image plane of the telecentric camera equipment into world coordinates through calibrating parameters of the telecentric camera equipment. A relationship between phase and depth herein is linear, and only needs to calibrate the linearity of one pixel.