A Study of Automobile Four-Wheel Location Technology Based on Machine Vision

2011 ◽  
Vol 230-232 ◽  
pp. 235-240
Author(s):  
Chuan De Zhou ◽  
Li Lai
Keyword(s):  
Machine Vision ◽  
Model Space ◽  
High Accuracy ◽  
Attitude Measurement ◽  
Space Vector ◽  
Fast Speed ◽  
Imaging Model ◽  
Wide Range ◽  
Target Imaging ◽  
Measurement Algorithm

This paper researchs the space vector change and machine vision recognition based on plane target cooperation identification.Then establishes plane target imaging model, space attitude measurement algorithm and software flow, which are utilized in the measurement of automobile four-wheel location. The results indicate that this method is feasible in the automobile four-wheel location technology with the advantages of good anti-interference, fast speed, wide range and high accuracy.

scholarly journals A Novel Ultrasonic TOF Ranging System Using AlN Based PMUTs

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 284
Author(s):  
Yihsiang Chiu ◽  
Chen Wang ◽  
Dan Gong ◽  
Nan Li ◽  
Shenglin Ma ◽  
...  
Keyword(s):  
Clock Cycle ◽  
High Accuracy ◽  
Ultrasonic Waves ◽  
Oxide Semiconductor ◽  
Average Error ◽  
Cmos Process ◽  
Clock Frequency ◽  
Time Frequency ◽  
Range Finding ◽  
Wide Range

This paper presents a high-accuracy complementary metal oxide semiconductor (CMOS) driven ultrasonic ranging system based on air coupled aluminum nitride (AlN) based piezoelectric micromachined ultrasonic transducers (PMUTs) using time of flight (TOF). The mode shape and the time-frequency characteristics of PMUTs are simulated and analyzed. Two pieces of PMUTs with a frequency of 97 kHz and 96 kHz are applied. One is used to transmit and the other is used to receive ultrasonic waves. The Time to Digital Converter circuit (TDC), correlating the clock frequency with sound velocity, is utilized for range finding via TOF calculated from the system clock cycle. An application specific integrated circuit (ASIC) chip is designed and fabricated on a 0.18 μm CMOS process to acquire data from the PMUT. Compared to state of the art, the developed ranging system features a wide range and high accuracy, which allows to measure the range of 50 cm with an average error of 0.63 mm. AlN based PMUT is a promising candidate for an integrated portable ranging system.

scholarly journals A Machine Vision Approach for Bioreactor Foam Sensing

2021 ◽  
pp. 247263032110088
Author(s):  
Jonas Austerjost ◽  
Robert Söldner ◽  
Christoffer Edlund ◽  
Johan Trygg ◽  
David Pollard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Vision ◽  
State Of The Art ◽  
Low Cost ◽  
High Accuracy ◽  
Consumer Electronics ◽  
Learning System ◽  
Automotive Applications ◽  
Fine Grained

Machine vision is a powerful technology that has become increasingly popular and accurate during the last decade due to rapid advances in the field of machine learning. The majority of machine vision applications are currently found in consumer electronics, automotive applications, and quality control, yet the potential for bioprocessing applications is tremendous. For instance, detecting and controlling foam emergence is important for all upstream bioprocesses, but the lack of robust foam sensing often leads to batch failures from foam-outs or overaddition of antifoam agents. Here, we report a new low-cost, flexible, and reliable foam sensor concept for bioreactor applications. The concept applies convolutional neural networks (CNNs), a state-of-the-art machine learning system for image processing. The implemented method shows high accuracy for both binary foam detection (foam/no foam) and fine-grained classification of foam levels.

scholarly journals Integration of image segmentation and fuzzy theory to improve the accuracy of damage detection areas in traffic accidents

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Majid Amirfakhrian ◽  
Mahboub Parhizkar
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Machine Vision ◽  
Traffic Accidents ◽  
Fuzzy Theory ◽  
Machine Learning Techniques ◽  
Industrial Setting ◽  
Technological Advances ◽  
Learning Techniques ◽  
Wide Range

AbstractIn the next decade, machine vision technology will have an enormous impact on industrial works because of the latest technological advances in this field. These advances are so significant that the use of this technology is now essential. Machine vision is the process of using a wide range of technologies and methods in providing automated inspections in an industrial setting based on imaging, process control, and robot guidance. One of the applications of machine vision is to diagnose traffic accidents. Moreover, car vision is utilized for detecting the amount of damage to vehicles during traffic accidents. In this article, using image processing and machine learning techniques, a new method is presented to improve the accuracy of detecting damaged areas in traffic accidents. Evaluating the proposed method and comparing it with previous works showed that the proposed method is more accurate in identifying damaged areas and it has a shorter execution time.

Finding Gene Names

2006 ◽  
Author(s):  
Soumya Raychaudhuri
Keyword(s):  
Natural Language Processing ◽  
Language Processing ◽  
Critical Issue ◽  
High Accuracy ◽  
Scientific Text ◽  
Recognition Algorithms ◽  
Wide Range ◽  
Genomics Research ◽  
Processing Techniques ◽  
Mining Algorithms

Successful use of text mining algorithms to facilitate genomics research hinges on the ability to recognize the names of genes in scientific text. In this chapter we address the critical issue of gene name recognition. Once gene names can be recognized in the scientific text, we can begin to understand what the text says about those genes. This is a much more challenging issue than one might appreciate at first glance. Gene names can be inconsistent and confusing; automated gene name recognition efforts have therfore turned out to be quite challenging to implement with high accuracy. Gene name recognition algorithms have a wide range of useful applications. Until this chapter we have been avoiding this issue and have been using only gene-article indices. In practice these indices are manually assembled. Gene name recognition algorithms offer the possibility of automating and expediting the laborious task of building reference indices. Article indices can be built that associate articles to genes based on whether or not the article mentions the gene by name. In addition, gene name recognition is the first step in doing more detailed sentence-by-sentence text analysis. For example, in Chapter 10 we will talk about identifying relationships between genes from text. Frequently, this requires identifying sentences refering to two gene names, and understanding what sort of relationship the sentence is describing between these genes. Sophisticated natural language processing techniques to parse sentences and understand gene function cannot be done in a meaningful way without recognizing where the gene names are in the first place. The major concepts of this chapter are presented in the frame box. We begin by describing the commonly used strategies that can be used alone or in concert to identify gene names. At the end of the chapter we introduce one successful name finding algorithm that combines many of the different strategies. There are several commonly used approaches that can be exploited to recognize gene names in text (Chang, Shutze, et al. 2004). Often times these approaches can be combined into even more effective multifaceted algorithms.

Experiment and Simulation for Grid-Connected Photovoltaic Micro-Invereter

2013 ◽  
Vol 448-453 ◽  
pp. 1480-1485
Author(s):  
Li Jie Yin ◽  
Ya Zhen ◽  
Qi Li Fan
Keyword(s):  
Simulation Model ◽  
Control Algorithm ◽  
Single Phase ◽  
High Accuracy ◽  
Control Parameters ◽  
Working Process ◽  
Topology Structure ◽  
Matlab Software ◽  
Fast Speed ◽  
Micro Inverter

A modeling method of single-phase grid-connected photovoltaic micro-inverter is presented in this paper,which depends on the topology structure of fly-back converter. Simulation of the micro-inverter is performed using Matlab software, which has the virtues of high accuracy and fast speed. Prototype experiment results show that the simulation model can be a true reflection of the working process of a micro-inverter, and could be used to verify the control algorithm and select the control parameters.

A fractional order model for electrochemical impedance of IPMC actuators based on constant phase element

2020 ◽  
pp. 1045389X2097443
Author(s):  
Mohammad Javad Doregiraei ◽  
Hossein Moeinkhah ◽  
Jafar Sadeghi
Keyword(s):  
Fractional Order ◽  
Electrical Impedance ◽  
Constant Phase Element ◽  
Electrochemical Impedance ◽  
High Accuracy ◽  
Metal Composite ◽  
Order Model ◽  
Unknown Parameters ◽  
Fractional Order Model ◽  
Wide Range

The accurate modeling of electrical impedance over a wide range of frequency is essential for precise dynamic modeling and control problems of Electroactive Polymer (EAP) actuators. Recently, fractional order modeling has attracted more attention due to the high accuracy. This paper deals with a fractional order electrical impedance model and its identification procedure for a class of EAP actuator named Ionic Polymer Metal Composite (IPMC). To take IPMC’s fractional characteristic into account, constant phase element (CPE) is used to construct a model structure according to Electrochemical Impedance Spectroscopy (EIS). By employing the Levy’s method in combination with genetic optimization algorithm, the unknown parameters of the resulting fractional transfer function are identified. Finally the proposed model is verified, by comparing with experimental EIS data. The results show that the fractional order model has high accuracy for representing the electrical impedance of IPMC actuator. The proposed modeling procedure is general and can also be used for any type of EAPs.

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