scholarly journals An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 370
Author(s):  
Lingling Wu ◽  
Guojun Wen ◽  
Yudan Wang ◽  
Xinjian Xu
Keyword(s):  
Detection Method ◽  
Detection System ◽  
Least Square Method ◽  
Least Square ◽  
Two Dimensional ◽  
Optical Inspection ◽  
Section Shape ◽  
Mechanical Bending ◽  
Low Efficiency ◽  
Displacement Based

Drill rod straightness has to be strictly controlled and the maximum bending degree detection needs to be used in the straightening process. The mechanical bending degree measurement depends on machinery instruments and workers’ experience, often with low efficiency and precision. While the optical inspection, as a non-contact detection method, with higher precision and lower installation accuracy requirements, is frequently applied in the online detection system. Based on this, an enhanced bending degree detection system for a drill rod is proposed in this paper. Compared to the existing detection system, the main progress is to use a two-dimensional laser to quickly obtain arc profile data and fit with ellipse. Segment inspection idea is also utilized is this system as the camera that could obtain the whole drill rod in one shot needs extremely high resolution and price. A specialized algorithm is designed to fit the cross-section shape and whole centerline displacement based on the least square method. Some laboratory tests are conducted to verify this detection system, findings of which are compared to manual measured results. The maximum bending degree error is 2.14 mm and the maximum position error is 8.21 mm, which are both within the tolerance of error. Those results show the feasibility and precision of this enhanced detection system.

Design of Rank Accuracy Detection System for Screw

2010 ◽  
Vol 37-38 ◽  
pp. 331-334
Author(s):  
Zhao Xin Meng ◽  
Zhi Wei Li ◽  
Jun Cao
Keyword(s):  
Laser Interferometer ◽  
Detection System ◽  
Least Square Method ◽  
Solution Procedure ◽  
Least Square ◽  
Error Evaluation ◽  
Evaluation Algorithm ◽  
Low Efficiency ◽  
Frequency Laser ◽  
Static Detection

In view of defects of static detection for screw, such as low efficiency, man made errors, this paper designed a dynamic detecting system, which employs two-frequency laser interferometer as the displacement benchmark and encoder as the angle benchmark. According to the lasting standards, the solution procedure of error evaluation algorithm is optimized by least square method to reduce computation. Experiment shows this system can dynamically detected screw, of which rank accuracy is more than two.

scholarly journals Research on Antennas Alignment of Dynamic Point-to-Point Communication

2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Qilin Zeng ◽  
Jiaxin Liu ◽  
Weiming Xiong
Keyword(s):  
Elevation Angle ◽  
Least Square Method ◽  
Optimal Level ◽  
Least Square ◽  
Two Dimensional ◽  
Scanning Strategy ◽  
One Dimensional ◽  
Communication Signal ◽  
Signal Value ◽  
Point To Point

In the dynamic point-to-point communication, to track and aim at antenna fast and accurately is the guarantee of high quality communication signal. In order to solve the problem of antenna alignment, we used the least square method (LSM) to fit the optimal level signal value (LSV) point which is based on coordinate coarse tracking alignment and matrix scanning strategy to find the LSV in this paper. Antenna is driven by two-dimensional turntable (azimuth and elevation angle (AE)): the two-dimensional turntable is decomposed into two independent one-dimensional turntables, and the LSV in AE direction are obtained by scanning, respectively. The optimal LSV point of two-dimensional turntable can be find by combing optimal LSV point of two independent one-dimensional turntables. The method has the advantages of high precision and easy implementation and can meet the requirement of fast and accurately alignment in dynamic point-to-point communication antenna engineering.

TWO-DIMENSIONAL DC RESISTIVITY MAPPING FOR SUBSURFACE INVESTIGATION USING SOFT COMPUTING APPROACHES

2015 ◽  
Vol 77 (17) ◽  
Author(s):  
Herman Wahid ◽  
Mohd. Hakimi Othman ◽  
Ruzairi Abdul Rahim
Keyword(s):  
Inverse Problem ◽  
Synthetic Data ◽  
Least Square Method ◽  
Least Square ◽  
Dc Resistivity ◽  
Two Dimensional ◽  
Actual Model ◽  
Subsurface Investigation ◽  
Artificial Neural Network Ann ◽  
Mlp Model

In geophysical subsurface surveys, difficulty to interpret measurement of data obtain from the equipment are risen. Data provided by the equipment did not indicate subsurface condition specifically and deviates from the expected standard due to numerous features. Generally, the data that obtained from the laws of physics computation is known as forward problem. And the process of obtaining the data from sets of measurements and reconstruct the model is known as inverse problem. Researchers have proposed multiple estimation techniques to cater the inverse problem and provide estimation that close to actual model. In this work, we investigate the feasibility of using artificial neural network (ANN) in solving two- dimensional (2-D) direct current (DC) resistivity mapping for subsurface investigation, in which the algorithms are based on the radial basis function (RBF) model and the multi-layer perceptron (MLP) model. Conventional approach of least square (LS) method is used as a benchmark and comparative study with the proposed algorithms. In order to train the proposed algorithms, several synthetic data are generated using RES2DMOD software based on hybrid Wenner-Schlumberger configurations. Results are compared between the proposed algorithms and least square method in term of its effectiveness and error variations to the actual values. It is discovered that the proposed algorithms have offered better performance in term minimum error difference to the actual model, as compared to least square method. Simulation results demonstrate that proposed algorithms can solve the inverse problem and it can be illustrated by means of the 2-D graphical mapping.

Indicial Function Predictions of Two Dimensional Unsteady Viscous Flows Around Bluff Bodies Based on Discrete Vortex Simulations

2012 ◽  
Author(s):  
H. Yadollahi Farsani ◽  
L. Ebrahimnejad ◽  
P. Marzocca ◽  
K. D. Janoyan ◽  
D. T. Valentine
Keyword(s):  
Lift Coefficient ◽  
Least Square Method ◽  
Least Square ◽  
Bluff Bodies ◽  
Two Dimensional ◽  
Discrete Vortex ◽  
Flow Solver ◽  
Aeroelastic Analysis ◽  
Unsteady Viscous Flow ◽  
Aerodynamic Moment

This paper provides aerodynamic indicial functions obtained through a discrete vortex computational fluid dynamics method for two-dimensional geometries, including two canonical sections, rectangular and elliptical shapes, and the Great Belt Bridge cross section. This methodology enables one to determine the unsteady lift and aerodynamic moment necessary in aeroelastic analysis of flexible bodies including flutter and vortex induced vibration. The predictions were obtained using an unsteady viscous flow solver, DVMFLOW, developed by COWI. The indicial functions developed have two exponential groups which parameters have been obtained using a nonlinear least square method. The numerical investigations show significant flow separation for the presented sections and an enhanced dynamic stall region at the initiation of a transient leading to higher values in the lift coefficient response. Vortex shedding frequency was also determined and the results are compared with other studies in the literature.

Quantitative Detection of C2H2 Gas Based on an Infrared Laser Gas Sensor

2015 ◽  
Vol 1092-1093 ◽  
pp. 400-406
Author(s):  
Jia Gui Tao ◽  
Jing Lei Shi ◽  
Xiao Xing Zhang
Keyword(s):  
Gas Sensor ◽  
Volume Fraction ◽  
Detection System ◽  
Least Square Method ◽  
Infrared Laser ◽  
State Assessment ◽  
Least Square ◽  
Transformer Oil ◽  
System Structure ◽  
Quantitative Detection

Detection of C2H2 gas in transformer oil is significant for diagnosing the operating state assessment of power equipment. The paper develops an infrared laser gas sensor to detect the C2H2 gas in transformer oil, and also introduces the system structure in detail. A gas-absorbed laser cell that contains a series of laser reflectors is designed and used in our detection system, which adds the optical path without changing the volume of the cell. 1529.16nm is chosen as the characteristic spectrum line of C2H2 gas, and concentration of C2H2 gas is quantitatively analyzed based on least square method. The experiment result shows that in certain volume fraction range of acetylene, the absorbance has a good linear relationship with the acetylene concentration, and the minimum detection limit for acetylene is 10μL/L. In general, the developed infrared laser gas sensor can detect C2H2 gas in transformer oil effectively.

scholarly journals Least Square Privacy Preserving Technique for Intrusion Detection System

2019 ◽  
Vol 9 (2) ◽  
pp. 2312-2319
Keyword(s):  
Intrusion Detection ◽  
Network Architecture ◽  
Privacy Preservation ◽  
Detection System ◽  
Least Square Method ◽  
Least Square ◽  
Ensemble Classification ◽  
Classification Model ◽  
User Privacy ◽  
Network Intrusion

Network intrusion is a foremost growing concern threat in the cyberspace, which can be damage the network architecture in a multiple ways by modifying the system configuration/parameters. Hackers/Intruders are familiar with signature based intrusion detection models and they are making successful attempts to crash the networks. Hence, it is necessary to preserve user privacy on intrusion data. PPDM techniques forms a necessary but existing techniques such as Encryption, Perturbation, Data Transformation, Normalization, L-Diversity, K-Anonymity methods forms excessive generalization and suppression problems. In this paper, LSPPM distortion technique using Least Square Method with ensemble classification model have been proposed for providing efficient privacy preservation on intrusion data. The proposed methodology is validated on benchmark NSL_KDD intrusion dataset. A comparative analysis of NSL_KDD class attributes is performed for better classification in terms of accuracy, FAR, F-Score and time taken to build LSPPM-NIDS. The experimental results of state-of-art PPDM methods are also analyzed before and after distortion, and privacy measures to ascertain the degree of privacy offered.

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