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.

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 Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System

2016 ◽  
Vol 28 (2) ◽  
pp. 133-142 ◽  
Author(s):  
Lie Guo ◽  
Mingheng Zhang ◽  
Linhui Li ◽  
Yibing Zhao ◽  
Yingzi Lin
Keyword(s):  
Detection Rate ◽  
Detection Method ◽  
Detection System ◽  
Pedestrian Detection ◽  
Urban Traffic ◽  
Body Parts ◽  
Detection Time ◽  
Pedestrian Protection ◽  
Adaboost Algorithm ◽  
Threshold Adjustment

A novel pedestrian detection system based on vision in urban traffic situations is presented to help the driver perceive the pedestrian ahead of the vehicle. To enhance the accuracy and to decrease the time spent on pedestrian detection in such complicated situations, the pedestrian is detected by dividing their body into several parts according to their corresponding features in the image. The candidate pedestrian leg is segmented based on the gentle AdaBoost algorithm by training the optimized histogram of gradient features. The candidate pedestrian head is located by matching the pedestrian head and shoulder model above the region of the candidate leg. Then the candidate leg, head and shoulder are combined by parts constraint and threshold adjustment to verify the existence of the pedestrian. Finally, the experiments in real urban traffic circumstances were conducted. The results show that the proposed pedestrian detection method can achieve pedestrian detection rate of 92.1% with the average detection time of 0.2257 s.

Research on Real-Time Vision Detection Method for Sanitary Labels

2013 ◽  
Vol 300-301 ◽  
pp. 484-489
Author(s):  
Chao Luo ◽  
Le Song ◽  
Mei Rong Zhao ◽  
Yu Chi Lin ◽  
Jian Li
Keyword(s):  
Real Time ◽  
Template Matching ◽  
Detection Method ◽  
Detection System ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Inspection System ◽  
Matching Method ◽  
Accurate Identification ◽  
Vision Detection

Taking diaper which is a representative production of sanitary supplies as an example, a real-time detection method for diaper label based on machine vision is developed. To identify the location of diaper surface label position rapidly, a visual inspection system platform applies to production line is built. Images are captured with high-resolution colorful CCD industrial camera and NC template matching method is adopted as the surface label detection algorithm. Meanwhile, the comparative experiments results among NC, ABS method and Moment Matching method are presented. Experimental results show that this label detection system can realize accurate identification on the condition of different light, whose recognition rate can reach up to 97% and detection algorithm is of preferable instantaneity and stability.

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.

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