An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor.However,traditional methods require a large number of filters,which leads to the deterioration of system stability and dynamic performance.In order to solve these problems,a new signal demodulation method is proposed in this paper.The proposed new method can directly obtain the amplitude of high-frequency current,thus eliminating the use of filters,improving system stability and dynamic performance and saving the work of adjusting filter parameters.In addition,a new magnetic polarity detection method is proposed,which is robust to current measurement noise.Finally,experiments verify the effectiveness of the method.

In-pit coal mine personnel uniqueness detection technology based on personnel positioning and face recognition

Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.

Analysis and Design of Surgical Instrument Localization Algorithm

With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.

A Method of Measuring Large Displacement and Deformation with High Precision *

A CCD position detecting system measuring the displacement and deformation of structure is presented. The measure method takes advantage of the position detecting technique based on digital image processing. A bright spot is pegged on the object to be measured and imaged to the target of CCD camera through a telescopic lens. The CCD target converts the optical signal to equivalent electric signal. The video frequency signal is digitized to an array of 512×512 pixels by the analog to digital converter (ADC), then transmitted to the computer. The computer controls the data acquisition, conducts image processing and detects the location of the target spot. Comparing the current position with the original position of the spot, the displacement of object is obtained. With the aid of analysis software, the system can achieve the resolution of 0 01 mm in the 6 m distance from the object to the point of observation. To meet the need of practice, the measuring distance can be extended to 100 m or even farther.

Visual positioning of rectangular lead components based on Harris corners and Zernike moments

With the increasing necessities for reliable printed circuit board(PCB) product, there has been a considerable demand for high speed and high precision vision positioning system. To locate a rectangular lead component with high accuracy and reliability, a new visual positioning method was introduced. Considering the limitations of Ghosal sub-pixel edge detection algorithm, an improved algorithm was proposed, in which Harris corner features were used to coarsely detect the edge points and Zernike moments were adopted to accurately detect the edge points. Besides, two formulas were developed to determine the edge intersections whose sub-pixel coordinates were calculated with bilinear interpolation and conjugate gradient method. The last experimental results show that the proposed method can detect the deflection and offset, and the detection errors are less than 0.04° and 0.02 pixels.

Detecting the Position of the Moving-iron Solenoid by Non-displacement Sensor Based on Parameter Identification of Flux Linkage Characteristics

Currently, most researches use signals, such as the coil current or voltage of solenoid, to identify parameters; typically, parameter identification method based on variation rate of coil current is applied for position estimation. The problem exists in these researches that the detected signals are prone to interference and difficult to obtain. This paper proposes a new method for detecting the core position by using flux characteristic quantity, which adds a new group of secondary winding to the coil of the ordinary switching electromagnet. On the basis of electromagnetic coupling theory analysis and simulation research of the magnetic field regarding the primary and secondary winding coils, and in accordance with the fact that under PWM control mode varying core position and operating current of windings produce different characteristic of flux increment of the secondary winding. The flux increment of the electromagnet winding can be obtained by conducting time domain integration for the induced voltage signal of the extracted secondary winding, and the core position from the two-dimensional fitting curve of the operating winding current and flux-linkage characteristic quantity of solenoid are calculated. The detecting and testing system of solenoid core position is developed based on the theoretical research. The testing results show that the flux characteristic quantity of switching electromagnet magnetic circuit is able to effectively show the core position and thus to accomplish the non-displacement transducer detection of the said core position of the switching electromagnet. This paper proposes a new method for detecting the core position by using flux characteristic quantity, which provides a new theory and method for switch solenoid to control the proportional valve.

An artificial neural network for detecting weld position in arc welding process

A kind of self organizing artificial neural network used for weld detection is presented in this paper, and its concepts and issues are discussed. The network can transform the weld visual information into typical patterns and match with the weld data collected on line, and so realize the accurate detection of the weld position in arc welding process.

FPC-BTB detection and positioning system based on optimized YOLOv5

With the aim of addressing the visual positioning problem of board-to-board(BTB)jacks during the automatic assembly of flexible printed circuit(FPC)in mobile phones,an FPC-BTB jack detection method based on the optimized You Only Look Once,version 5(YOLOv5)deep learning algorithm was proposed in this study.An FPC-BTB jack real-time detection and positioning system was developed for the real-time target detection and pose output synchronization of the BTB jack.On that basis,a visual positioning experimental platform that integrated a UR5e manipulator arm and Hikvision industrial camera was built for BTB jack detection and positioning experiments.As indicated by the experimental results,the developed FPC-BTB jack detection and positioning system for BTB target recognition and positioning achieved a success rate of 99.677%.Its average detection accuracy reached 99.341%,the average confidence of the detected target was 91%,the detection and positioning speed reached 31.25 frames per second,and the positioning deviation was less than 0.93 mm,which conforms to the practical application requirements of the FPC assembly process.

A real-time detection and positioning method for small and weak targets using a 1D morphology-based approach in 2D images

A small and weak target detection method is proposed in this work that outperforms all other methods in terms of real-time capability.It is the first time that two-dimensional(2D)images are processed using only one-dimensional1D structuring elements in a morphology-based approach,enabling the real-time hardware implementation of the whole image processing method.A parallel image readout and processing structure is introduced to achieve an ultra-low latency time on the order of nanoseconds,and a hyper-frame resolution in the time domain can be achieved by combining the row-by-row structure and the electrical rolling shutter technique.Experimental results suggest that the expected target can be successfully detected under various interferences with an accuracy of 0.1 pixels(1σ)under the worst sky night test condition and that a centroiding precision of better than 0.03 pixels(1σ)can be reached for static tests.The real-time detection method with high robustness and accuracy is attractive for application to all types of real-time small target detection systems,such as medical imaging,infrared surveillance,and target measurement and tracking,where an ultra-high processing speed is required.