scholarly journals Review of Chloride Ion Detection Technology in Water

2021 ◽  
Vol 11 (23) ◽  
pp. 11137
Author(s):  
Dan Wu ◽  
Yinglu Hu ◽  
Ying Liu ◽  
Runyu Zhang
Keyword(s):  
Chloride Ion ◽  
Domestic Sewage ◽  
Volumetric Method ◽  
Molecular Probe ◽  
Detection Methods ◽  
Ecological Environment ◽  
Interference Detection ◽  
Research Focus ◽  
Detection Technology ◽  
Industrial Sewage

The chloride ion (Cl−) is a type of anion which is commonly found in the environment and has important physiological functions and industrial uses. However, a high content of Cl− in water will do harm to the ecological environment, human health and industrial production. It is of great significance to strictly monitor the Cl− content in water. Following the recent development of society and industry, large amounts of domestic sewage and industrial sewage are discharged into the environment, which results in the water becoming seriously polluted by Cl−. The detection of Cl− has gradually become a research focus. This paper introduces the harm of Cl− pollution in the environment and summarizes various Cl− detection methods, including the volumetric method, spectrophotometry method, electrochemical method, ion chromatography, paper-based microfluidic technology, fluorescent molecular probe, and flow injection. The principle and application of each technology are described; their advantages, disadvantages, and applicability are discussed. To goal of this research is to find a more simple, rapid, environmental protection and strong anti-interference detection technology of Cl−.

scholarly journals A Test Device for Optimize PMU-Based Islanding Detection Technology

2015 ◽  
Vol 10 (2) ◽  
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Detection Method ◽  
Detection Methods ◽  
Islanding Detection ◽  
Algorithm Optimization ◽  
Test Device ◽  
Photovoltaic Power ◽  
Detection Technology ◽  
Bulk Power

Islanding detection is a necessary function for grid connected distributed generators. Usually, islanding detection methods can be classified as two catalogues: remote detecting methods and local detecting methods. Most of them have limitation and defects when they are applied in photovoltaic power stations. Recently synchronous phasor measuring units (PMU) is proposed to be applied for islanding detecting. Although the islanding detection method is supposed to be applied for traditional bulk power systems, it is also suitable for renewable generation power plants. To do this islanding detection will be implemented on central management unit of photovoltaic power station instead of on grid-tied inverters as traditionally. In implementing, the criteria of this method and the threshold of algorithm are needed to be optimized. This paper develops a test device which can optimize PMU-based islanding detection technology to validate the proposed islanding detection method applying in PV station. Then using simulation to discuss how to set a reasonable threshold for the researched islanding detection method applied in PV stations. Finally the paper provides a platform for the algorithm optimization.

scholarly journals A Review of Non-Destructive Damage Detection Methods for Steel Wire Ropes

2019 ◽  
Vol 9 (13) ◽  
pp. 2771 ◽  
Author(s):  
Ping Zhou ◽  
Gongbo Zhou ◽  
Zhencai Zhu ◽  
Zhenzhi He ◽  
Xin Ding ◽  
...  
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Steel Wire ◽  
Guided Wave ◽  
Detection Methods ◽  
Wire Ropes ◽  
Intelligent Sensors ◽  
Detection Technology ◽  
Damage States ◽  
Non Destructive

As an important load-bearing component, steel wire ropes (WRs) are widely used in complex systems such as mine hoists, cranes, ropeways, elevators, oil rigs, and cable-stayed bridges. Non-destructive damage detection for WRs is an important way to assess damage states to guarantee WR’s reliability and safety. With intelligent sensors, signal processing, and pattern recognition technology developing rapidly, this field has made great progress. However, there is a lack of a systematic review on technologies or methods introduced and employed, as well as research summaries and prospects in recent years. In order to bridge this gap, and to promote the development of non-destructive detection technology for WRs, we present an overview of non-destructive damage detection research of WRs and discuss the core issues on this topic in this paper. First, the WRs’ damage type is introduced, and its causes are explained. Then, we summarize several main non-destructive detection methods for WRs, including electromagnetic detection method, optical detection method, ultrasonic guided wave detection method, and acoustic emission detection method. Finally, a prospect is put forward. Based on the review of papers, we provide insight about the future of the non-destructive damage detection methods for steel WRs to a certain extent.

scholarly journals An API Semantics-Aware Malware Detection Method Based on Deep Learning

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Xin Ma ◽  
Shize Guo ◽  
Wei Bai ◽  
Jun Chen ◽  
Shiming Xia ◽  
...  
Keyword(s):  
Machine Learning ◽  
Detection Method ◽  
Malware Detection ◽  
Poor Performance ◽  
Detection Methods ◽  
Interference Detection ◽  
Machine Learning Method ◽  
Accuracy Rate ◽  
Malware Classification ◽  
Self Protection

The explosive growth of malware variants poses a continuously and deeply evolving challenge to information security. Traditional malware detection methods require a lot of manpower. However, machine learning has played an important role on malware classification and detection, and it is easily spoofed by malware disguising to be benign software by employing self-protection techniques, which leads to poor performance for existing techniques based on the machine learning method. In this paper, we analyze the local maliciousness about malware and implement an anti-interference detection framework based on API fragments, which uses the LSTM model to classify API fragments and employs ensemble learning to determine the final result of the entire API sequence. We present our experimental results on Ali-Tianchi contest API databases. By comparing with the experiments of some common methods, it is proved that our method based on local maliciousness has better performance, which is a higher accuracy rate of 0.9734.

Ultrasonic TOFD Detection by Finite Element Simulation Method

2014 ◽  
Vol 602-605 ◽  
pp. 1594-1597
Author(s):  
Han Xin Chen ◽  
Shi Qi Yang
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Time Of Flight ◽  
Simulation Method ◽  
Industrial Applications ◽  
Detection Methods ◽  
Analysis Model ◽  
Element Analysis ◽  
Time Of Flight Diffraction ◽  
Detection Technology

This paper investigated the ultrasonic mechanism of Time of Flight Diffraction (TOFD) by finite element analysis for the better applications of ultrasonic TOFD (Time of Flight Diffraction) detection technology. The welding steel plate with the artificial defects is used in the finite element analysis model. The experimental A-scan signal with higher noise is filtered by the wavelet transform, which can clearly show defective diffracted wave. The software simulation of ultrasound is used to present the propagation process of ultrasonic signal inside the sample. Simulation results are compared with the experimental results, which shows valid basis for the practical TOFD ultrasonic detection methods in industrial applications.

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.

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.

Method of Harmonic Detection Based on the Wavelet Transform

2013 ◽  
Vol 748 ◽  
pp. 646-650
Author(s):  
Qing Yang Liang ◽  
Zhe Sun ◽  
Chen Fei Zhang
Keyword(s):  
Wavelet Transform ◽  
Active Power Filter ◽  
Active Power ◽  
Detection Methods ◽  
Harmonic Detection ◽  
Harmonic Current ◽  
Time Frequency ◽  
Power Filter ◽  
Detection Technology ◽  
Current Detection

The harmonic current detection technology is one of the key technologies of active power filter technologies. The development of the harmonic current detection technology directly determines the development of the active power filter technologies. Based on this, this paper introduces some basis concepts of wavelet transform and analyzes its time-frequency localization properties, then, describes the harmonic detection methods based on wavelet transform in terms of program building, algorithm selection and wavelet function selection. The results show that the harmonic current detection methods based on wavelet transform are able to compensate the inadequacy of Fourier transforms and can achieve the functions of detecting the steady-state and time-varying harmonic current of the grid in harmonic detection of active power filter.

Effect of Chlorine Concentration on Determining COD by Acid and Alkaline Potassium Permanganate

2013 ◽  
Vol 807-809 ◽  
pp. 232-235 ◽  
Author(s):  
Mo Di E ◽  
Tao Ding ◽  
Sheng Chao Zhan ◽  
Fu Wei Yao ◽  
Hong Ke Wan
Keyword(s):  
Potassium Permanganate ◽  
Water Body ◽  
Potassium Dichromate ◽  
Chloride Ion ◽  
Chlorine Concentration ◽  
Detection Methods ◽  
Tidal Period ◽  
Freshwater Sample ◽  
Standard Solution ◽  
The Difference

In water monitoring, effect of chloride ion in water body on determining COD can not be ignored. Potassium dichromate has a strong oxidizing, and it can oxidize most of the organic in matter. But it generally is used to determine the water body which COD is larger than 30mg/L, and easily influenced by Chloride ion. So we often use alkaline potassium permanganate method which has weak impact by Chloride ion in high chlorine concentration wastewater. For the tidal estuary, we often use acidic potassium permanganate method in upstream and alkaline potassium permanganate method in downstream. The different detection methods cause the disagreement of water quality evaluation. This paper describes the influence of chlorine level on the COD standard solution prepared by laboratory and river freshwater sample from Qiantang River upstream in detail, and analyses the difference between the acid potassium permanganate method and alkaline potassium permanganate by comparing the COD standard solution prepared by laboratory and the freshwater sample. Last, this paper discusses the variation of COD during a tidal period.

scholarly journals Diseases Detection of Occlusion and Overlapping Tomato Leaves Based on Deep Learning

2021 ◽  
Vol 12 ◽  
Author(s):  
Xuewei Wang ◽  
Jun Liu ◽  
Guoxu Liu
Keyword(s):  
Natural Environment ◽  
Network Architecture ◽  
Plant Diseases ◽  
Frame Rate ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Layer By Layer ◽  
Detection Technology ◽  
Tomato Diseases ◽  
Detection Speed

Background: In view of the existence of light shadow, branches occlusion, and leaves overlapping conditions in the real natural environment, problems such as slow detection speed, low detection accuracy, high missed detection rate, and poor robustness in plant diseases and pests detection technology arise.Results: Based on YOLOv3-tiny network architecture, to reduce layer-by-layer loss of information during network transmission, and to learn from the idea of inverse-residual block, this study proposes a YOLOv3-tiny-IRB algorithm to optimize its feature extraction network, improve the gradient disappearance phenomenon during network deepening, avoid feature information loss, and realize network multilayer feature multiplexing and fusion. The network is trained by the methods of expanding datasets and multiscale strategies to obtain the optimal weight model.Conclusion: The experimental results show that when the method is tested on the self-built tomato diseases and pests dataset, and while ensuring the detection speed (206 frame rate per second), the mean Average precision (mAP) under three conditions: (a) deep separation, (b) debris occlusion, and (c) leaves overlapping are 98.3, 92.1, and 90.2%, respectively. Compared with the current mainstream object detection methods, the proposed method improves the detection accuracy of tomato diseases and pests under conditions of occlusion and overlapping in real natural environment.

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