Research on Screw Thread Form Based on Non-Contact Measurement

2011 ◽  
Vol 101-102 ◽  
pp. 593-596
Author(s):  
Shao Feng Shen ◽  
Xian Cheng Wang ◽  
Jun Hua Chen
Keyword(s):  
Measurement Accuracy ◽  
Optical Axis ◽  
Optical Field ◽  
New Method ◽  
Detection Accuracy ◽  
Screw Thread ◽  
Characteristic Parameters ◽  
The Real ◽  
Contact Measurement ◽  
High Skill

There is a problem with non-contact measurement and detection, which reduces its measurement accuracy. Methods developed for measuring and inspecting screw thread characteristic parameters usually using a camera, which is controlled to scan the projection of thread in the parallel optical field to obtain thread images. However, with the block of screw line on the projection of the real thread form, it is impossible to acquire the real thread form from images. The traditional way is adjusting the optical axis to a suitable angle with the thread axis to acquire the real thread form projection, which has some problems, such as time consuming, high skill of operator, high-precision equipment for adjustment, inaccuracy, and so on. Hence, a new method through digital image calibration is presented. The results of relevant simulation indicated the feasibility of this new method, which improves thread measurement and detection accuracy.

Single-level anterior cervical fusion: a new method to evaluate the real need for plate augmentation

2019 ◽  
Vol 63 (4) ◽  
Author(s):  
Marco Ajello ◽  
Nicola Marengo ◽  
Paolo Pacca ◽  
Federico Pecoraro ◽  
Francesco Zenga ◽  
...  
Keyword(s):  
Anterior Cervical Fusion ◽  
New Method ◽  
Cervical Fusion ◽  
The Real ◽  
Single Level

scholarly journals A New Method to Verify the Measurement Speed and Accuracy of Frequency Modulated Interferometers

2021 ◽  
Vol 11 (13) ◽  
pp. 5787
Author(s):  
Toan-Thang Vu ◽  
Thanh-Tung Vu ◽  
Van-Doanh Tran ◽  
Thanh-Dong Nguyen ◽  
Ngoc-Tam Bui
Keyword(s):  
Phase Change ◽  
High Speed ◽  
Measurement Accuracy ◽  
Slow Motion ◽  
New Method ◽  
Virtual Displacement ◽  
Electro Optic ◽  
Lock In ◽  
Speed And Accuracy ◽  
Electro Optic Modulator

The measurement speed and measurement accuracy of a displacement measuring interferometer are key parameters. To verify these parameters, a fast and high-accuracy motion is required. However, the displacement induced by a mechanical actuator generates disadvantageous features, such as slow motion, hysteresis, distortion, and vibration. This paper proposes a new method for a nonmechanical high-speed motion using an electro-optic modulator (EOM). The method is based on the principle that all displacement measuring interferometers measure the phase change to calculate the displacement. This means that the EOM can be used to accurately generate phase change rather than a mechanical actuator. The proposed method is then validated by placing the EOM into an arm of a frequency modulation interferometer. By using two lock-in amplifiers, the phase change in an EOM and, hence, the corresponding virtual displacement could be measured by the interferometer. The measurement showed that the system could achieve a displacement at 20 kHz, a speed of 6.08 mm/s, and a displacement noise level < 100 pm//√Hz above 2 kHz. The proposed virtual displacement can be applied to determine both the measurement speed and accuracy of displacement measuring interferometers, such as homodyne interferometers, heterodyne interferometers, and frequency modulated interferometers.

scholarly journals A Research on Landslides Automatic Extraction Model Based on the Improved Mask R-CNN

2021 ◽  
Vol 10 (3) ◽  
pp. 168
Author(s):  
Peng Liu ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Jingjing Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Extraction Methods ◽  
New Method ◽  
Detection Accuracy ◽  
Sufficient Information ◽  
Automatic Extraction ◽  
Emergency Rescue ◽  
Feature Pyramid ◽  
High Level ◽  
Extraction Model

Landslides are the most common and destructive secondary geological hazards caused by earthquakes. It is difficult to extract landslides automatically based on remote sensing data, which is import for the scenario of disaster emergency rescue. The literature review showed that the current landslides extraction methods mostly depend on expert interpretation which was low automation and thus was unable to provide sufficient information for earthquake rescue in time. To solve the above problem, an end-to-end improved Mask R-CNN model was proposed. The main innovations of this paper were (1) replacing the feature extraction layer with an effective ResNeXt module to extract the landslides. (2) Increasing the bottom-up channel in the feature pyramid network to make full use of low-level positioning and high-level semantic information. (3) Adding edge losses to the loss function to improve the accuracy of the landslide boundary detection accuracy. At the end of this paper, Jiuzhaigou County, Sichuan Province, was used as the study area to evaluate the new model. Results showed that the new method had a precision of 95.8%, a recall of 93.1%, and an overall accuracy (OA) of 94.7%. Compared with the traditional Mask R-CNN model, they have been significantly improved by 13.9%, 13.4%, and 9.9%, respectively. It was proved that the new method was effective in the landslides automatic extraction.

A New Method for Detecting the Diameter and Spatial Location of Tiny Through-Hole

2011 ◽  
Vol 189-193 ◽  
pp. 4186-4190 ◽  
Author(s):  
Zhi Gen Fei ◽  
Jun Jie Guo ◽  
Chang Shi Li
Keyword(s):  
Image Processing ◽  
Function Method ◽  
Optical Axis ◽  
Spatial Location ◽  
Processing Technique ◽  
New Method ◽  
Image Processing Technique ◽  
Experimental Platform ◽  
Digital Image Processing Technique ◽  
Through Hole

Aiming at the problem that the traditional plunged-bar method is difficult to meet the measurement requirement of spatial location of thin and small through-hole, in this paper, the digital image processing technique combined with sub-pixel detection technique is employed, and a new method is proposed to detect the tiny through-holes. The evaluating function method based on the “roundness” of the image of hole is presented to find out the posture parameters of CCD where the optical axis of CCD is parallel to the centerline of hole. Therefore, the spatial location of hole can be easily obtained by these posture parameters. Meanwhile, the diameter of hole can be achieved by means of image measuring technology at calculated posture of CCD. Owing to the non-contact measurement, this method is particularly suitable for those small through-holes drilled on the soft and easy-deformed object. The experiment results on the experimental platform illustrate the feasibility and validity of this method.

The Yellow-Ring Measurement of White LED by the Reflective Lightspot Method (RLM)

2013 ◽  
Vol 284-287 ◽  
pp. 2805-2811
Author(s):  
Ching Ching Yang ◽  
Hsin Yi Tsai ◽  
Wen Tse Hsiao ◽  
Kuo Cheng Huang
Keyword(s):  
Beam Splitter ◽  
Optical Axis ◽  
Ccd Camera ◽  
White Led ◽  
Automatic Inspection ◽  
Phosphor Layer ◽  
The Real ◽  
Acrylic Plate ◽  
Working Distance ◽  
Plm System

The yellow-ring (YR) is a chromatism phenomenon which is caused by the inhomogeneous phosphor layer of the white-light LED (WLED). The characterized lightspot with YR is that the yellow light appears in the periphery of white lightspot zone. The lightspot image of WLED can be acquired from two approaches; projective lightspot method (PLM) and transmissive lightspot method (TLM). By the PLM system, the lightspot could be projected on the spot screen (wall or others) and its image is acquired by a CCD camera. However, the working distance between camera and sample WLED must be larger (~ 2 m) to obtain the lightspot image without tilt aberration. For the convenience of automatic inspection, the working distance in the TLM system can be modified to 0.3 m. Since the light travels through the spot screen, such as copier paper or acrylic plate, etc., the camera cannot obtain the real lightspot image in the TLM system. In practice, the material of spot screen will absorb and scatter the WLED light, and in the image color would be a bit different between the real lightspot and the acquired lightspot. In order to improve the above disadvantages, the study presents the reflective lightspot method (RLM) that the camera acquires the reflective lightspot image from the 50/50 beam splitter at the same optical axis. The RLM system is not only able to capture the tilt-less lightspot image, but also obtain readily the non-saturated image. The experiment results show the RLM system has the better evaluation of YR index (YRI), and is more suitable for the automatic inspection of WLEDs.

Front vehicle detection based on improved fusion method for lidar and visual image

2022 ◽  
pp. 095440702110685
Author(s):  
Aijuan Li ◽  
Zhenghong Chen ◽  
Donghong Ning ◽  
Xin Huang ◽  
Gang Liu
Keyword(s):  
Average Method ◽  
Weighted Average ◽  
Visual Image ◽  
Vehicle Detection ◽  
Detection Accuracy ◽  
The Real ◽  
Weighted Average Method ◽  
Weighted Fusion ◽  
Vehicle Test ◽  
Real Vehicle

In order to ensure the detection accuracy, an improved adaptive weighted (IAW) method is proposed in this paper to fuse the data of images and lidar sensors for the vehicle object’s detection. Firstly, the IAW method is proposed in this paper and the first simulation is conducted. The unification of two sensors’ time and space should be completed at first. The traditional adaptive weighted average method (AWA) will amplify the noise in the fusion process, so the data filtered with Kalman Filter (KF) algorithm instead of with the AWA method. The proposed IAW method is compared with the AWA method and the Distributed Weighted fusion KF algorithm in the data fusion simulation to verify the superiority of the proposed algorithm. Secondly, the second simulation is conducted to verify the robustness and accuracy of the IAW algorithm. In the two experimental scenarios of sparse and dense vehicles, the vehicle detection based on image and lidar is completed, respectively. The detection data is correlated and merged through the IAW method, and the results show that the IAW method can correctly associate and fuse the data of the two sensors. Finally, the real vehicle test of object vehicle detection in different environments is carried out. The IAW method, the KF algorithm, and the Distributed Weighted fusion KF algorithm are used to complete the target vehicle detection in the real vehicle, respectively. The advantages of the two sensors can give full play, and the misdetection of the target objects can be reduced with proposed method. It has great potential in the application of object acquisition.

scholarly journals A Research Paper on Traffic Sign Recognition with Machine Learning and IOT

2021 ◽  
Vol 9 (VI) ◽  
pp. 1774-1778
Author(s):  
Mahesh Singh
Keyword(s):  
Machine Learning ◽  
Object Detection ◽  
Real World ◽  
Research Paper ◽  
Raspberry Pi ◽  
Detection Accuracy ◽  
Great Success ◽  
The Real ◽  
Road Traffic Safety ◽  
Execution Speed

This paper will help to bring out some amazing findings about autonomous prediction and performing action by establishing a connection between the real world with machine learning and Internet Of thing. The purpose of this research paper is to perform our machine to analyze different signs in the real world and act accordingly. We have explored and found detection of several features in our model which helped us to establish a better interaction of our model with the surroundings. Our algorithms give very optimized predictions performing the right action .Nowadays, autonomous vehicles are a great area of research where we can make it more optimized and more multi - performing .This paper contributes to a huge survey of varied object detection and feature extraction techniques. At the moment, there are loads of object classification and recognition techniques and algorithms found and developed around the world. TSD research is of great significance for improving road traffic safety. In recent years, CNN (Convolutional Neural Networks) have achieved great success in object detection tasks. It shows better accuracy or faster execution speed than traditional methods. However, the execution speed and the detection accuracy of the existing CNN methods cannot be obtained at the same time. What's more, the hardware requirements are also higher than before, resulting in a larger detection cost. In order to solve these problems, this paper proposes an improved algorithm based on convolutional model A classic robot which uses this algorithm which is installed through raspberry pi and performs dedicated action.

scholarly journals Bounding Lagrangian widths via geodesic paths

2014 ◽  
Vol 150 (12) ◽  
pp. 2143-2183 ◽  
Author(s):  
Matthew Strom Borman ◽  
Mark McLean
Keyword(s):  
Sectional Curvature ◽  
New Method ◽  
Finite Width ◽  
Energy Capacity ◽  
Positive Sectional Curvature ◽  
Floer Cohomology ◽  
The Real ◽  
Ambient Manifold ◽  
Open Map ◽  
Geodesic Paths

AbstractThe width of a Lagrangian is the largest capacity of a ball that can be symplectically embedded into the ambient manifold such that the ball intersects the Lagrangian exactly along the real part of the ball. Due to Dimitroglou Rizell, finite width is an obstruction to a Lagrangian admitting an exact Lagrangian cap in the sense of Eliashberg–Murphy. In this paper we introduce a new method for bounding the width of a Lagrangian$Q$by considering the Lagrangian Floer cohomology of an auxiliary Lagrangian$L$with respect to a Hamiltonian whose chords correspond to geodesic paths in$Q$. This is formalized as a wrapped version of the Floer–Hofer–Wysocki capacity and we establish an associated energy–capacity inequality with the help of a closed–open map. For any orientable Lagrangian$Q$admitting a metric of non-positive sectional curvature in a Liouville manifold, we show the width of$Q$is bounded above by four times its displacement energy.

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