scholarly journals An In-Process BSR-Noise Detection System for Car Door Trims

2018 ◽  
pp. 35-38 ◽  
Author(s):  
Woonsang Baek ◽  
Duck Young Kim
Keyword(s):  
Detection System ◽  
Noise Detection

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.

Implementation of a thrust reverse noise detection system for airports

2013 ◽  
Vol 19 ◽  
pp. 42-47 ◽  
Author(s):  
C. Asensio ◽  
G. Moschioni ◽  
M. Ruiz ◽  
M. Tarabini ◽  
M. Recuero
Keyword(s):  
Detection System ◽  
Noise Detection

The Research on the Low Clutch’s Noise Detection Technology which Based on the Wavelet Transform

2012 ◽  
Vol 433-440 ◽  
pp. 4082-4086
Author(s):  
Yue Dong Chen ◽  
Chang Zhong Yu
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Detection System ◽  
Rotating Machinery ◽  
Noise Detection ◽  
Machine Vibration ◽  
Bearing Defects ◽  
Detection Technology ◽  
On Line ◽  
Reasonable Choice

The essay introduce the hardware Design based on the Line detection system, and apply the wavelet analysis theory to the low clutch’s fault signal processing to fulfill the low clutch’s noise detection which based on the wavelet transform. Practice shows that the continuous wavelet signal has a strong ability of fault detection, if reasonable choice of wavelet function and various parameters among the fault detection, the local feature of the fault signal can be intuitively got, thus supply the products with a effective tool. The current washing machine clutch all have a washing deceleration function, so it is called as low clutch. As one of the most common parts of rotating machinery, low clutch is also one of the easily damaged parts among the rotating machinery. According to statistics, thirty percent of the rotating machinery’s operational problems caused by the bearing faults[1]. Bearing defects can cause severely machine vibration and generation noise, or even cause damage to the equipment[4]. This article is mainly detect the low clutch’s vibration noise in operation by accelerometer, and deal with the collected data through wavelet transform, thus realize the On-line condition monitoring to the low clutch.

Low Noise Detection System Using a Silicon Photodiode with a Charge Integrating Amplifier

1995 ◽  
Vol 115 (2) ◽  
pp. 333-334
Author(s):  
Iwao Mizumoto ◽  
Shinzo Yamakawa ◽  
Shinro Mashiko ◽  
Nobumi Hagiwara
Keyword(s):  
Detection System ◽  
Low Noise ◽  
Noise Detection ◽  
Silicon Photodiode ◽  
A Charge

Design of LabView-Based System of Noise Measurement on Gear Box

2011 ◽  
Vol 328-330 ◽  
pp. 2167-2171 ◽  
Author(s):  
Xie Ben Wei ◽  
Wen Zheng ◽  
Rong Lin
Keyword(s):  
Fault Diagnosis ◽  
Historical Data ◽  
Detection System ◽  
Noise Measurement ◽  
Signal Acquisition ◽  
Noise Detection ◽  
Teaching Laboratory ◽  
Multiple Data ◽  
On Line ◽  
Gear Box

The gear box is widely used in rotating machinery equipments, also it is a key component of the machinery equipment. Gear box, once it is failure, will cause serious machinery equipments failure, so the condition monitoring and fault diagnosis research of the gear box is very necessary. Its state of running and fault diagnosis can be acquired through measuring and analysis the noise of gear box. A feasible on-line LabView-based system of noise measurement on the gear box is designed by Using NI's hardware and other ordinary sound-tested equipments in teaching laboratory, as well as its applied effect is confirmed in practical test. This system realizes the signal acquisition and analysis in the online and offline conditions. It has the following functions: multiple data collection and preservation, historical data query, gearbox online monitoring and vibration quantity value alarming, etc. So, the noise detection system has very good application prospects in the actual noise detection and analysis of the gear box.

Low-Noise Detection System for the Counted Implantation of Single Ions in Silicon

2008 ◽  
Vol 55 (2) ◽  
pp. 812-816 ◽  
Author(s):  
T. Hopf ◽  
C. Yang ◽  
S. M. Hearne ◽  
D. N. Jamieson ◽  
E. Gauja ◽  
...  
Keyword(s):  
Detection System ◽  
Low Noise ◽  
Noise Detection

Abnormal drone noise detection system based on the microphone array and self-supervised learning

2021 ◽  
Vol 263 (1) ◽  
pp. 5754-5760
Author(s):  
Hao Wu ◽  
Huitian Jiang ◽  
Haifeng Wen ◽  
Chuang Shi
Keyword(s):  
Supervised Learning ◽  
Learning Strategy ◽  
Detection System ◽  
Microphone Array ◽  
Network Models ◽  
Low Complexity ◽  
Raspberry Pi ◽  
Channel Noise ◽  
Noise Detection ◽  
Neural Network Models

The drone noise mainly comes from its rotating blades, providing plentiful information of the status of the drone. In the production line, the abnormal sound detection system has the advantages of no contact and simple deployment and can help to locate the fault products at relatively low costs. Therefore, this paper develops an abnormal drone noise detection system based on the microphone array and self-supervised learning. The microphone array is a part of the data acquisition module to pick up the drone noise. There are eight microphones in the array, forming four differential microphone pairs. Each of them is pointing to a blade of the drone. A four-channel noise sample is recorded and then analyzed. It is worth noting that drone noise samples are extremely unbalanced, because abnormal samples are difficult to encounter. Hence, a self-supervised learning strategy is adopted by creating auxiliary classification tasks to fine tune representations of the normal drone noise samples. With the consideration of low-complexity, the trained neural network models can be finally deployed even on a Raspberry Pi system with no graphic cards.

Pulse System Based on Noise Detection System Research

2012 ◽  
Vol 268-270 ◽  
pp. 1606-1609
Author(s):  
Xin Zhang ◽  
Chun Xiu Wang
Keyword(s):  
Detection System ◽  
Sound Intensity ◽  
Load Test ◽  
Pulse System ◽  
Noise Detection ◽  
Test Analysis ◽  
Noise Test ◽  
Analysis System ◽  
A Company

In this paper, based on B & K pulse system, the noise test analysis had been implemented on the load test station of a company in Yinchuan. It is clear and concise that displayed noise distribution situation of the load test set by BK sound intensity probe, 3560B-type multi-analysis system and pc machine. Through the CPB analysis, it can quickly get the main segment of the noise and the real-time monitoring of the gearbox, so the quality of the product is guaranteed.

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