Research on Several Key Techniques of Power Tool Rest Noise Detection System

2012 ◽  
Vol 630 ◽  
pp. 271-275
Author(s):  
Xiao Hong Lu ◽  
Yong Yan Shang ◽  
Peng Zhuo Han ◽  
Guang Jun Li ◽  
Wen Yi Wu
Keyword(s):  
Spectrum Analysis ◽  
Detection Method ◽  
Detection System ◽  
Sampled Data ◽  
Noise Detection ◽  
Machining Center ◽  
Cnc Lathe ◽  
Spectrum Transformation ◽  
Key Techniques

The scarcity and imperfection of power tool rest noise detection method have seriously limited the development of the industry of CNC lathe, lathe and milling composite machining center. A noise detection system based on LabVIEW is developed. The developed system adopts a noise sensor as noise detection component to test the noise information of the power tool rest. To enhance the anti-interference ability of this system, the sampled signals are amplified and adjusted by the signal disposal instrument. Through the spectrum transformation and spectrum analysis of the sampled noise signals, the noise causes of the power tool rest can be inquired and the concerned measurements can be taken to reduce the noise effectively. Finally, the sampled data is stored by the data saving function.

scholarly journals An in-Process Inspection System to Detect Noise Originating from within the Interior Trim Panels of Car Doors

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 630
Author(s):  
Woonsang Baek ◽  
Duck Young Kim
Keyword(s):  
Source Localization ◽  
Detection Method ◽  
Noise Source ◽  
Detection System ◽  
Inspection System ◽  
Body Parts ◽  
Noise Detection ◽  
Process Noise ◽  
Time Difference Of Arrival ◽  
Trim Panel

Car body parts are sometimes responsible for irritating noise caused by assembly defects. Typically, various types of noise are known to originate from within the interior trim panels of car doors. This noise is considered to be an important factor that degrades the emotional satisfaction of the driver of the car. This research suggests an in-process inspection system consisting of an inspection workstation and a noise detection method. The inspection workstation presses down the car door trim panel by using a pneumatic pusher while microphones record the acoustic signals directly above the door trim panel and on the four sides of the workstation. The collected signals are analyzed by the proposed noise detection method after applying noise reduction. The noise detection method determines the presence of irritating noise by using noise source localization in combination with the time difference of arrival method and the relative signal strengths. The performance of the in-process noise detection system was evaluated by conducting experiments on faulty and healthy car door trim panels.

Image detection and parameterization for different components in cross-sections of radial tires

2021 ◽  
pp. 095440702110236
Author(s):  
Chen Liu ◽  
Yude Dong ◽  
Yanli Wei ◽  
Jiangtao Wang ◽  
Hongling Li
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Cross Sections ◽  
Digital Image ◽  
Detection Method ◽  
Detection System ◽  
Practical Significance ◽  
Vehicle Safety ◽  
Wire Steel ◽  
Good Detection

The internal structure analysis of radial tires is of great significance to improve vehicle safety and during tire research. In order to perform the digital analysis and detection of the internal composition in radial tire cross-sections, a detection method based on digital image processing was proposed. The research was carried out as follows: (a) the distribution detection and parametric analysis of the bead wire, steel belt, and carcass in the tire section were performed by means of digital image processing, connected domain extraction, and Hough transform; (b) using the angle of location distribution and area relationship, the detection data were optimized through coordinate and quantity relationship constraints; (c) a detection system for tire cross-section components was designed using the MATLAB platform. Our experimental results showed that this method displayed a good detection performance, and important practical significance for the research and manufacture of tires.

scholarly journals An Automata Based Intrusion Detection Method for Internet of Things

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yulong Fu ◽  
Zheng Yan ◽  
Jin Cao ◽  
Ousmane Koné ◽  
Xuefei Cao
Keyword(s):  
Open Access ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection Method ◽  
Detection System ◽  
Network Communication ◽  
5G Networks ◽  
Machine To Machine ◽  
Security Of Iot

Internet of Things (IoT) transforms network communication to Machine-to-Machine (M2M) basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS) is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

scholarly journals A Development Perspective of Point-Based Computer Graphics

2021 ◽  
Vol 39 (2) ◽  
pp. 343-352
Author(s):  
Ajahati Mukti
Keyword(s):  
Computer Graphics ◽  
Rapid Development ◽  
Three Dimensional ◽  
Sampled Data ◽  
Geometry Processing ◽  
Digital Geometry Processing ◽  
Physical Interactions ◽  
Key Techniques ◽  
Future Work ◽  
Development Perspective

Every object has its characteristic shape, appearance and responses to physical interactions. Computer graphics center on those three components of an object to bring them onto the computer display. With the rapid development of three dimensional (3D) printing technology, the accuracy of the focused object’s geometry was put forward. Point-based graphing is a way to taking the role in rendering the huge 3D sampled data. Based on the digital geometry processing of point-sampled model, various algorithms were reviewed, and some related key techniques were compared with the potential perspective of the future work in this area was also presented．

Semi supervised inspection algorithm of automatic packaging curve based on deep learning

2021 ◽  
pp. 1-10
Author(s):  
Yong He
Keyword(s):  
Deep Learning ◽  
Supervised Learning ◽  
Optimization Algorithm ◽  
Posterior Probability ◽  
Detection Method ◽  
Detection System ◽  
Experimental Results ◽  
Detection Accuracy ◽  
Data Set ◽  
Packaging Process

The current automatic packaging process is complex, requires high professional knowledge, poor universality, and difficult to apply in multi-objective and complex background. In view of this problem, automatic packaging optimization algorithm has been widely paid attention to. However, the traditional automatic packaging detection accuracy is low, the practicability is poor. Therefore, a semi-supervised detection method of automatic packaging curve based on deep learning and semi-supervised learning is proposed. Deep learning is used to extract features and posterior probability to classify unlabeled data. KDD CUP99 data set was used to verify the accuracy of the algorithm. Experimental results show that this method can effectively improve the performance of automatic packaging curve semi-supervised detection system.

scholarly journals Research on the Weld Position Detection Method for Sandwich Structures from Face-Panel Side Based on Backscattered X-ray

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3198 ◽  
Author(s):  
Angang Wei ◽  
Baohua Chang ◽  
Boce Xue ◽  
Guodong Peng ◽  
Dong Du ◽  
...  
Keyword(s):  
Detection Method ◽  
Sandwich Structures ◽  
Detection System ◽  
High Reliability ◽  
Sandwich Panels ◽  
Experimental System ◽  
Maximum Absolute Error ◽  
X Ray ◽  
Position Detection ◽  
The Face

Web-core sandwich panels are a typical lightweight structure utilized in a variety of fields, such as naval, aviation, aerospace, etc. Welding is considered as an effective process to join the face panel to the core panel from the face panel side. However, it is difficult to locate the joint position (i.e., the position of core panel) due to the shielding of the face panel. This paper studies a weld position detection method based on X-ray from the face panel side for aluminum web-core sandwich panels used in aviation and naval structures. First, an experimental system was designed for weld position detection, able to quickly acquire the X-ray intensity signal backscattered by the specimen. An effective signal processing method was developed to accurately extract the characteristic value of X-ray intensity signals representing the center of the joint. Secondly, an analytical model was established to calculate and optimize the detection parameters required for detection of the weld position of a given specimen by analyzing the relationship between the backscattered X-ray intensity signal detected by the detector and the parameters of the detection system and specimen during the detection process. Finally, several experiments were carried out on a 6061 aluminum alloy specimen with a thickness of 3 mm. The experimental results demonstrate that the maximum absolute error of the detection was 0.340 mm, which is sufficiently accurate for locating the position of the joint. This paper aims to provide the technical basis for the automatic tracking of weld joints from the face panel side, required for the high-reliability manufacturing of curved sandwich structures.

Exploration on Applying Non-Contact Photoelectric Detection Method for Double-Enveloping Hourglass Worm

2010 ◽  
Vol 97-101 ◽  
pp. 4287-4292
Author(s):  
Shu Yuan Zhang ◽  
Xiao Jing Chen ◽  
Song Kun Yu ◽  
Ting Chen Chen
Keyword(s):  
Light Source ◽  
Detection Method ◽  
Detection System ◽  
Image Sensor ◽  
Tooth Surface ◽  
Rotary Table ◽  
Ccd Imaging ◽  
Photoelectric Detection ◽  
Manufacturing Accuracy ◽  
Work Table

According to the principle of processing, a non-contact photoelectric detection method for double-enveloping hourglass worm is investigated. The structure of the detection system is designed. It consists of solid-state image sensor CCD and light source. The parallel light source is installed on a sliding-board which is fixed on the rotary table. There is an inclination angular β between the parallel light source and the plane of the work table. The industrial CCD lens is mounted on the other side of the worm through a frame. The plane of the CCD is vertical to the parallel light source. Therefore CCD imaging is along with the direction of the generating process surface. By comparing the measured spiral tooth surface with the standard spiral tooth surface, the manufacturing error of worm can be calculated. Manufacturing accuracy of the worm can be obtained. Based on the four-axis CNC grinder, Non-contact photoelectric detection method is studied through preliminary experimental study. The experimental results indicate that this method is feasible in the precise detection of the double-enveloping hourglass worm.

Sign in / Sign up

Export Citation Format

Share Document