scholarly journals Review of Dissolved Oxygen Detection Technology: From Laboratory Analysis to Online Intelligent Detection

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3995 ◽  
Author(s):  
Yaoguang Wei ◽  
Yisha Jiao ◽  
Dong An ◽  
Daoliang Li ◽  
Wenshu Li ◽  
...  
Keyword(s):  
Dissolved Oxygen ◽  
Real Time ◽  
Optical Detection ◽  
Oxygen Sensors ◽  
Detection Methods ◽  
Future Research ◽  
Advantages And Disadvantages ◽  
Oxygen Detection ◽  
Detection Technology ◽  
Intelligent Technology

Dissolved oxygen is an important index to evaluate water quality, and its concentration is of great significance in industrial production, environmental monitoring, aquaculture, food production, and other fields. As its change is a continuous dynamic process, the dissolved oxygen concentration needs to be accurately measured in real time. In this paper, the principles, main applications, advantages, and disadvantages of iodometric titration, electrochemical detection, and optical detection, which are commonly used dissolved oxygen detection methods, are systematically analyzed and summarized. The detection mechanisms and materials of electrochemical and optical detection methods are examined and reviewed. Because external environmental factors readily cause interferences in dissolved oxygen detection, the traditional detection methods cannot adequately meet the accuracy, real-time, stability, and other measurement requirements; thus, it is urgent to use intelligent methods to make up for these deficiencies. This paper studies the application of intelligent technology in intelligent signal transfer processing, digital signal processing, and the real-time dynamic adaptive compensation and correction of dissolved oxygen sensors. The combined application of optical detection technology, new fluorescence-sensitive materials, and intelligent technology is the focus of future research on dissolved oxygen sensors.

Partial Discharge Detection Using Acoustic and Optical Methods in High Voltage Power Equipments: A Review

2013 ◽  
Vol 845 ◽  
pp. 283-286 ◽  
Author(s):  
Malik Abdul Razzaq Al Saedi ◽  
Mohd Muhridza Yaacob
Keyword(s):  
Acoustic Emission ◽  
High Voltage ◽  
Power Transformer ◽  
Partial Discharge ◽  
Optical Detection ◽  
Detection Threshold ◽  
Optical Methods ◽  
Detection Methods ◽  
Detection Techniques ◽  
Advantages And Disadvantages

There is a high risk of insulation system dielectric instability when partial discharge (PD) occurs. Therefore, measurement and monitoring of PD is an important preventive tool to safeguard high-voltage equipment from wanton damage. PD can be detected using optical method to increase the detection threshold and to improve the performance of on-line measurement of PD in noise environment. The PD emitted energy as acoustic emission. We can use this emitted energy to detect PD signal. The best method to detect PD in power transformer is by using acoustic emission. Optical sensor has some advantages such as; high sensitivity, more accuracy small size. Furthermore, in on-site measurements and laboratory experiments, it isoptical methodthat gives very moderate signal attenuations. This paper reviews the available PD detection methods (involving high voltage equipment) such as; acoustic detection and optical detection. The advantages and disadvantages of each method have been explored and compared. The review suggests that optical detection techniques provide many advantages from the consideration of accuracy and suitability for the applications when compared to other techniques.

Development of Detection Research on Fatigue Driving

2014 ◽  
Vol 641-642 ◽  
pp. 813-817
Author(s):  
Xiao Jun He ◽  
Jing Liu ◽  
Zhen Di Yi ◽  
Yuan Quan Yang
Keyword(s):  
Fatigue Testing ◽  
Detection Methods ◽  
Advantages And Disadvantages ◽  
Efficient Detection ◽  
Detection Technology ◽  
Driving Fatigue ◽  
Cost Efficient ◽  
Fatigue Driving ◽  
The Cost ◽  
Fatigue Detection

This paper presents the current most common fatigue-driving detection methods. The advantages and disadvantages of these detection methods are compared with. Moreover, several major products of the current fatigue detection are listed briefly. Furthermore, the development trends of driving-fatigue detection technology are prospected. The author believes that driver fatigue testing standards need to be further clarified and the non-contact detection method of driving-fatigue needs to be developed deeply. Information fusion is an important orientation for driving fatigue and we should design the cost-efficient detection products for fatigue-driving.

scholarly journals Islanding Fault Detection in Microgrids—A Survey

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3479 ◽  
Author(s):  
Mehdi Hosseinzadeh ◽  
Farzad Rajaei Salmasi
Keyword(s):  
Fault Detection ◽  
Detection Methods ◽  
Future Research ◽  
Extensive Literature ◽  
Detection Techniques ◽  
Comprehensive List ◽  
Advantages And Disadvantages ◽  
Utility Grid

This paper provides an overview of islanding fault detection in microgrids. Islanding fault is a condition in which the microgrid gets disconnected from the microgrid unintentionally due to any fault in the utility grid. This paper surveys the extensive literature concerning the development of islanding fault detection techniques which can be classified into remote and local techniques, where the local techniques can be further classified as passive, active, and hybrid. Various detection methods in each class are studied, and advantages and disadvantages of each method are discussed. A comprehensive list of references is used to conduct this survey, and opportunities and directions for future research are highlighted.

Isothermal Target and Probe Amplification Assay for the Real-Time Rapid Detection of Staphylococcus aureus

2015 ◽  
Vol 78 (4) ◽  
pp. 723-727 ◽  
Author(s):  
HYEWON SHIN ◽  
MINHWAN KIM ◽  
EUNJU YOON ◽  
GYOUNGWON KANG ◽  
SEUNGYU KIM ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Real Time ◽  
Rapid Detection ◽  
Food Poisoning ◽  
Detection Methods ◽  
Economic Losses ◽  
Fluorescence Detector ◽  
The Real ◽  
Robust Detection ◽  
Advantages And Disadvantages

Staphylococcus aureus, the species most commonly associated with staphylococcal food poisoning, is one of the most prevalent causes of foodborne disease in Korea and other parts of the world, with much damage inflicted to the health of individuals and economic losses estimated at $120 million. To reduce food poisoning outbreaks by implementing prevention methods, rapid detection of S. aureus in foods is essential. Various types of detection methods for S. aureus are available. Although each method has advantages and disadvantages, high levels of sensitivity and specificity are key aspects of a robust detection method. Here, we describe a novel real-time isothermal target and probe amplification (iTPA) method that allows the rapid and simultaneous amplification of target DNA (the S. aureus nuc gene) and a fluorescence resonance energy transfer–based signal probe under isothermal conditions at 61°C or detection of S. aureus in real time. The assay was able to specifically detect all 91 S. aureus strains tested without nonspecific detection of 51 non–S. aureus strains. The real-time iTPA assay detected S. aureus at an initial level of 101 CFU in overnight cultures of preenriched food samples (kiwi dressing, soybean milk, and custard cream). The advantage of this detection system is that it does not require a thermal cycler, reducing the cost of the real-time PCR and its footprint. Combined with a miniaturized fluorescence detector, this system can be developed into a simplified quantitative hand-held real-time device, which is often required. The iTPA assay was highly reliable and therefore may be used as a rapid and sensitive means of identifying S. aureus in foods.

scholarly journals Review of the Newly Developed, Mobile Optical Sensors for Real-Time Measurement of the Atmospheric Particulate Matter Concentration

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 416
Author(s):  
Sama Molaie ◽  
Paolo Lino
Keyword(s):  
Particulate Matter ◽  
Human Health ◽  
Real Time ◽  
Optical Sensors ◽  
Optical Devices ◽  
Detection Sensitivity ◽  
Detection Methods ◽  
Advantages And Disadvantages ◽  
Particulate Matter Concentration ◽  
Matter Concentration

Due to the adverse effects on human health and the environment, air quality monitoring, specifically particulate matter (PM), has received increased attention over the last decades. Most of the research and policy actions have been focused on decreasing PM pollution and the development of air monitoring technologies, resulting in a decline of total ambient PM concentrations. For these reasons, there is a continually increasing interest in mobile, low-cost, and real-time PM detection instruments in both indoor and outdoor environments. However, to the best of the authors’ knowledge, there is no recent literature review on the development of newly designed mobile and compact optical PM sensors. With this aim, this paper gives an overview of the most recent advances in mobile optical particle counters (OPCs) and camera-based optical devices to detect particulate matter concentration. Firstly, the paper summarizes the particulate matter effects on human health and the environment and introduces the major particulate matter classes, sources, and characteristics. Then, it illustrates the different theories, detection methods, and operating principles of the newly developed portable optical sensors based on light scattering (OPCs) and image processing (camera-based sensors), including their advantages and disadvantages. A discussion concludes the review by comparing different novel optical devices in terms of structures, parameters, and detection sensitivity.

scholarly journals Recent Advancement in Anomaly Detection in Surveillance Videos

2019 ◽  
Vol 8 (2) ◽  
pp. 964-970
Keyword(s):  
Computer Vision ◽  
Anomaly Detection ◽  
Video Data ◽  
Detection Methods ◽  
Future Research ◽  
Detection Techniques ◽  
Advantages And Disadvantages ◽  
Recent Computer ◽  
Banking Education ◽  
To Come

Detection of Anomaly is of a notable and emergent problem into many diverse fields like information theory, deep learning, computer vision, machine learning, and statistics that have been researched within the various application from diverse domains including agriculture, health care, banking, education, and transport anomaly detection. Newly, numbers of important anomaly detection techniques along with diverseness of sort have been watched. The main aim of this paper to come up with a broad summary of the present development on detection of an anomaly, exclusively for video data with mixed types and high dimensionalities, where identifying the anomalous behaviors and event or anomalous patterns is a significant task. The paper expresses the advantages and disadvantages of the detection methods the experiments tried on the publically available benchmark dataset to assess numerous popular and classical methods and models. The objective of this analysis is to furnish an understanding of recent computer vision and machine algorithms methods and also state-of-the-art deep learnings techniques to detect anomalies for researchers. At last, the paper delivered roughly directions for future research on an anomalies detection.

Image detection and basketball training performance simulation based on improved machine learning

2020 ◽  
pp. 1-12
Author(s):  
Wang Pengyu ◽  
Gao Wanna
Keyword(s):  
Machine Learning ◽  
Feature Recognition ◽  
Controlled Trial ◽  
Detection Methods ◽  
Basketball Player ◽  
Learning Technology ◽  
Advantages And Disadvantages ◽  
Detection Technology ◽  
Starting Point ◽  
Bounding Boxes

Basketball player detection technology is an important subject in the field of computer vision and the basis of related image processing research. This study uses machine learning technology to build a basketball sport feature recognition model. Moreover, this research mainly takes the characteristic information of basketball in the state of basketball goals as the starting point and compares and analyzes the detection methods by detecting the targets in the environment. By comprehensively considering the advantages and disadvantages of various methods, a method suitable for the subject is proposed, namely, a fast skeleton extraction and model segmentation method. The fitting effect of this method, whether in terms of compactness or quantity, has greater advantages than traditional bounding boxes, and realizes the construction of dynamic ellipsoidal bounding boxes in a moving state. In addition, this study designs a controlled trial to verify the analysis of this research model. The research results show that the model proposed in this paper has certain effects and can improve practical guidance for competitions and basketball players training.

scholarly journals Review of Weed Detection Methods Based on Computer Vision

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3647
Author(s):  
Zhangnan Wu ◽  
Yajun Chen ◽  
Bo Zhao ◽  
Xiaobing Kang ◽  
Yuanyuan Ding
Keyword(s):  
Computer Vision ◽  
Agricultural Production ◽  
Development Trend ◽  
Detection Methods ◽  
Future Research ◽  
Weed Detection ◽  
Factors Affecting ◽  
Advantages And Disadvantages ◽  
Related Plant ◽  
The Development Trend

Weeds are one of the most important factors affecting agricultural production. The waste and pollution of farmland ecological environment caused by full-coverage chemical herbicide spraying are becoming increasingly evident. With the continuous improvement in the agricultural production level, accurately distinguishing crops from weeds and achieving precise spraying only for weeds are important. However, precise spraying depends on accurately identifying and locating weeds and crops. In recent years, some scholars have used various computer vision methods to achieve this purpose. This review elaborates the two aspects of using traditional image-processing methods and deep learning-based methods to solve weed detection problems. It provides an overview of various methods for weed detection in recent years, analyzes the advantages and disadvantages of existing methods, and introduces several related plant leaves, weed datasets, and weeding machinery. Lastly, the problems and difficulties of the existing weed detection methods are analyzed, and the development trend of future research is prospected.

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