Noise Detection Technology Development for Car Cabin

2008 ◽  
Author(s):  
Junichi Kawano ◽  
Junichi Amakasu ◽  
Tsutomu Tanaka
Keyword(s):  
Technology Development ◽  
Noise Detection ◽  
Detection Technology

scholarly journals Development of Wireless Sensor Device for Machine English Oral Pronunciation Noise Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yaning Zhu
Keyword(s):  
Closed Loop ◽  
Detection Algorithm ◽  
Training System ◽  
Circuit Board ◽  
Wireless Sensor ◽  
Noise Detection ◽  
Traditional System ◽  
Spoken English ◽  
Loop Design ◽  
Detection Technology

There is often noise in spoken machine English, which affects the accuracy of pronunciation. Therefore, how to accurately detect the noise in machine English spoken language and give standard spoken pronunciation is very important and meaningful. The traditional machine-oriented spoken English speech noise detection technology is limited to the improvement of software algorithm, mainly including speech enhancement technology and speech endpoint detection technology. Based on this, this paper will develop a wireless sensor network based on machine English oral pronunciation noise based on air and nonair conduction, reasonably design and configure air sensors, and nonair conduction sensors to deal with machine English oral pronunciation noise, so as to improve the naturalness and intelligibility of machine English speech. At the hardware level, this paper mainly optimizes the AD sampling, sensor matching layout, and internal hardware circuit board layout of the two types of sensors, so as to solve the compatibility problem between them and further reduce the hardware power consumption. In order to further verify or evaluate the performance of the machine spoken English speech noise detection sensor designed in this paper, a machine spoken English training system based on Android platform is designed. Compared with the traditional system, the training system can improve the intelligence of machine oriented oral English noise detection algorithm, so as to continuously improve the accuracy of system detection. The machine English pronunciation is adjusted and corrected by combining the data sensed by the sensor, so as to form a closed-loop design. The experimental results show that the wireless sensor sample proposed in this paper has obvious advantages in detecting the accuracy of machine English oral pronunciation, and its good closed-loop system is helpful to further improve the accuracy of machine English oral pronunciation.

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.

Development of Bridge Concealment Engineering State Detection Technology

2014 ◽  
Vol 926-930 ◽  
pp. 541-544
Author(s):  
Yi Zheng ◽  
Ke Chao Zhang ◽  
Jian Zhang Chen
Keyword(s):  
Technology Development ◽  
Development Trend ◽  
Foreground Detection ◽  
Monitoring Technology ◽  
Development Status ◽  
Detection Technology ◽  
State Detection ◽  
Engineering State

Main detection and monitoring technology of bridges construction concealment engineering were carried out investigation and analysis. The use of concealed engineering inspection technology, monitoring technology were overviewed and analyzed. The development status of detection, monitoring technology at present reviewed and analyzed. Detection technology parameters on the internal prestress were compared. Technology development trend and foreground detection of concealed engineering were presented. Key words:bridge structure、concealed engineering、detection technology、monitoring technology、stress statement

scholarly journals OpenWeedLocator (OWL): an open-source, low-cost 1 device for fallow weed detection.

2021 ◽  
Author(s):  
Guy Coleman ◽  
William Salter ◽  
Michael Walsh
Keyword(s):  
Open Source ◽  
Weed Control ◽  
Technology Development ◽  
Low Cost ◽  
Yield Potential ◽  
Low Density ◽  
Weed Detection ◽  
Living Plant ◽  
Detection Technology ◽  
Assembly Instructions

Abstract The use of a fallow phase is an important tool for maximizing yield potential in moisture limited environments. There is a focus on ensuring these phases are maintained weed-free as even low weed densities can be detrimental to fallow efficiency. Repeated whole field herbicide treatment to control low-density weed populations is expensive and wasteful. Site-specific application of herbicide treatments to low density fallow weed populations is currently facilitated by sensor-based devices that detect chlorophyll fluorescence from living plant tissue. The use of image-based weed detection technology for fallow weed detection is an opportunity to develop an approach that can be translated for in-crop weed recognition. Here we present the OpenWeedLocator (OWL), an open-source, low-cost image-based approach for fallow weed detection that improves accessibility to this technology for the weed control community. A comprehensive repository, containing all code and assembly instructions, has been developed that will allow for community driven improvement over time. Four different colour-based weed detection algorithms were tested with the OWL system over seven fallow field scenarios under varying light, soil and stubble conditions. Across all scenarios, the four algorithms were similarly effective in detecting fallow weeds with average precision and recall of 79% and 52%, respectively. In individual transects, precision and recall values of up to 92% and 74%, respectively, suggest the potential fallow weed detection performance of the colour-based system. OWL represents an opportunity to redefine the approach to weed detection by enabling community-driven technology development and implementation in the weed control industry.

Image noise detection technology based on spatial domain

2013 ◽  
Vol 32 (6) ◽  
pp. 1552-1556 ◽  
Author(s):  
Yan-fei YU ◽  
Quan ZHENG ◽  
Song WANG ◽  
Wei LI ◽  
Jing YUAN ◽  
...  
Keyword(s):  
Spatial Domain ◽  
Image Noise ◽  
Noise Detection ◽  
Detection Technology

Some applications of electron beam microanalysis techniques in VLSI process evaluation

1983 ◽  
Vol 41 ◽  
pp. 160-161
Author(s):  
Simon Thomas
Keyword(s):  
Integrated Circuits ◽  
Process Evaluation ◽  
Large Scale ◽  
Technology Development ◽  
Analytical Techniques ◽  
Successful Implementation ◽  
Analysis Of Failures ◽  
Characterization Of Materials ◽  
Circuits Vlsi

Trends in the technology development of very large scale integrated circuits (VLSI) have been in the direction of higher density of components with smaller dimensions. The scaling down of device dimensions has been not only laterally but also in depth. Such efforts in miniaturization bring with them new developments in materials and processing. Successful implementation of these efforts is, to a large extent, dependent on the proper understanding of the material properties, process technologies and reliability issues, through adequate analytical studies. The analytical instrumentation technology has, fortunately, kept pace with the basic requirements of devices with lateral dimensions in the micron/ submicron range and depths of the order of nonometers. Often, newer analytical techniques have emerged or the more conventional techniques have been adapted to meet the more stringent requirements. As such, a variety of analytical techniques are available today to aid an analyst in the efforts of VLSI process evaluation. Generally such analytical efforts are divided into the characterization of materials, evaluation of processing steps and the analysis of failures.

On-line image readout in CTEM

1994 ◽  
Vol 52 ◽  
pp. 400-401
Author(s):  
K.-H. Herrmann ◽  
W. D. Rau ◽  
R. Sikeler
Keyword(s):  
Primary Electron ◽  
Digital Information ◽  
Electron Hole ◽  
Detection Technology ◽  
Long Time ◽  
On Line ◽  
Electron Image ◽  
Optical Transfer ◽  
Detection Quantum Efficiency ◽  
Technical Solutions

Quantitative recording of electron patterns and their rapid conversion into digital information is an outstanding goal which the photoplate fails to solve satisfactorily. For a long time, LLL-TV cameras have been used for EM adjustment but due to their inferior pixel number they were never a real alternative to the photoplate. This situation has changed with the availability of scientific grade slow-scan charged coupled devices (CCD) with pixel numbers exceeding 106, photometric accuracy and, by Peltier cooling, both excellent storage and noise figures previously inaccessible in image detection technology. Again the electron image is converted into a photon image fed to the CCD by some light optical transfer link. Subsequently, some technical solutions are discussed using the detection quantum efficiency (DQE), resolution, pixel number and exposure range as figures of merit.A key quantity is the number of electron-hole pairs released in the CCD sensor by a single primary electron (PE) which can be estimated from the energy deposit ΔE in the scintillator,

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