scholarly journals Insulator filth monitoring and situation awareness based on ultraviolet pulse and least square method

2021 ◽  
Vol 2108 (1) ◽  
pp. 012056
Author(s):  
Tao Liu ◽  
Bo Qu ◽  
Guolong Li
Keyword(s):  
Visible Light ◽  
Situation Awareness ◽  
Pulse Signal ◽  
Signal Amplitude ◽  
Pulse Method ◽  
Least Square ◽  
Electrical Pulse ◽  
Image Size ◽  
Observation Distance ◽  
Spot Area

Abstract To monitor the filth state of insulators in time, a method based on ultraviolet pulse method is proposed to monitor the filth status of insulators, which can detect the early corona discharge of insulators by detecting UV signals and determine the degree of insulator filth. On this basis, the response characteristics of spot area to electrical pulse signal are studied and theoretical analysis is carried out, the relationship between spot area and electrical pulse signal amplitude is studied, and the correlation curve is obtained. By observing the change law of image size with the observation distance in ultraviolet image. the experiment found that the image size of UV channel and the image size of visible light channel increased or decreased in approximate proportion with the observation distance and proposed a new method to estimate the “discharge imaging area ” of discharge on the surface of the insulator by using the image information of the visible light channel. According to the discharge “relative spot area mean”, one minute time “number of large spot area image frames” two ultraviolet imaging parameters used to characterize the filth discharge characteristics, combined with the ambient humidity to establish a fuzzy logic reasoning model of the filth state, to achieve the assessment of the filth state of the insulator. By using the proposed UV image processing method, the accuracy of insulator filth detection is improved.

scholarly journals An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 920
Author(s):  
Neha Chaudhary ◽  
Othman Isam Younus ◽  
Luis Nero Alves ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
...  
Keyword(s):  
Visible Light ◽  
Polynomial Regression ◽  
Power Level ◽  
Least Square ◽  
Line Of Sight ◽  
Received Power ◽  
Strength Based ◽  
Complex Linear ◽  
Linear Least Square ◽  
First Time

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.

scholarly journals Research on Mud Pulse MWD Device for Mines

2021 ◽  
Vol 248 ◽  
pp. 03050
Author(s):  
Gao Jun
Keyword(s):  
Signal Transmission ◽  
Drill Pipe ◽  
Pulse Signal ◽  
Pulse Method ◽  
Directional Drilling ◽  
Transmission Distance ◽  
Signal Encoding ◽  
Measurement While Drilling ◽  
Working Principle ◽  
Encoding Method

As the core accoutrement of directional drilling construction, the measurement while drilling (MWD) device can be divided into three types due to the different data transmission methods: wired, mud pulse and electromagnetic wave. This paper used the mud pulse method to develop a mud pulse MWD device for mines, and the working principle of the mud pulse signal transmission, the signal encoding method and the structure of the device were described. Experimental research showed that the mud pulse wireless MWD device had the advantages of long transmission distance and strong working stability. At the same time, the device was not restricted by the drill pipe during operation, which could be combined with sliding orientation and rotary feed, and had great promotion and application value.

scholarly journals Accurate Ultrasound Indoor Localization Using Spring-Relaxation Technique

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1290
Author(s):  
Moi Tin Chew ◽  
Fakhrul Alam ◽  
Mathew Legg ◽  
Gourab Sen Sen Gupta
Keyword(s):  
Visible Light ◽  
Indoor Localization ◽  
Least Square ◽  
Relaxation Technique ◽  
Positioning System ◽  
Ultrasonic Sensing ◽  
Chirp Signals ◽  
Flight Measurement ◽  
Active Localization ◽  
Linear Least Square

This paper reports on the development of an ultrasonic sensing-based active localization system. The system employs an ultrasonic array to transmit chirp signals and time-of-flight measurement for ranging. The position of the receiver is estimated iteratively using the spring-relaxation technique. A median and 90-percentile error of 12.4 and 21.7 mm, respectively, were obtained for measurements at 625 positions within a 1.2 × 1.2 m area testbed. The spring-relaxation technique outperforms the widely adopted linear least square-based lateration technique while using the same ranging data. The performance of the system is benchmarked against that of visible light positioning using the same platform setup. The reported results show the ultrasonic system to be more accurate when compared with the visible light positioning system, which achieved median and 90-percentile errors of 33.7 and 58.6 mm, respectively.

scholarly journals Determinants of stakeholders’ attitudes and intentions toward supporting the use of Wolbachia-infected Aedes mosquitoes for dengue control

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmad Firdhaus Arham ◽  
Latifah Amin ◽  
Muhammad Adzran Che Mustapa ◽  
Zurina Mahadi ◽  
Mashitoh Yaacob ◽  
...  
Keyword(s):  
Hot Spot ◽  
Sampling Technique ◽  
Partial Least Square ◽  
Least Square ◽  
High Rate ◽  
Perceived Benefits ◽  
Perceived Risks ◽  
Stakeholder Groups ◽  
Spot Area ◽  
Key Players

Abstract Background A recent approach in controlling dengue is by using the Wolbachia-infected Aedes mosquito (WiAM). The approach has been reported to be more effective than traditional methods, such as fogging. Therefore, it is imperative to assess the factors predicting its acceptance among stakeholders before implementing this technology more widely in Malaysia. Methods The survey data were collected from two primary stakeholder groups using a stratified random sampling technique. The two primary stakeholder groups were scientists (n = 202) and the public (n = 197) in the Klang Valley region of Malaysia, a hot spot area known for the high rate of dengue cases. The respondents answered questions on a seven-point Likert scale survey regarding trust in key players, attitudes toward nature versus materialism, religiosity, perceived benefits, perceived risks, attitudes, and intentions. The data were analyzed using Smart Partial Least Square (SmartPLS) software (version 3.2.6) to determine the predictors influencing attitudes and intentions to support the use of WiAM technology. Results The results indicated a strong positive relationship between attitudes and intentions to support the use of WiAM (β = 0.676, p < 0.001). The most important significant predictor for attitudes was perceived benefits (β = 0.493, p < 0.001), followed by perceived risks (β = − 0.080, p = 0.048). Trust in key players, attitudes toward nature versus material, and religiosity had indirect relationships with attitudes through the perceived benefits and risks. Conclusions The identified predictors can serve as indicators for the decision-making process regarding WiAM implementation in Malaysia and other developing countries with similar demographics and cultures.

scholarly journals Adaptive Residual Weighted K-Nearest Neighbor Fingerprint Positioning Algorithm Based on Visible Light Communication

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4432 ◽  
Author(s):  
Shiwu Xu ◽  
Chih-Cheng Chen ◽  
Yi Wu ◽  
Xufang Wang ◽  
Fen Wei
Keyword(s):  
Visible Light ◽  
Nearest Neighbor ◽  
Signal To Noise Ratio ◽  
Visible Light Communication ◽  
Least Square ◽  
Manhattan Distance ◽  
Positioning Error ◽  
K Nearest Neighbor ◽  
Positioning Algorithm ◽  
Self Adaptive

The weighted K-nearest neighbor (WKNN) algorithm is a commonly used fingerprint positioning, the difficulty of which lies in how to optimize the value of K to obtain the minimum positioning error. In this paper, we propose an adaptive residual weighted K-nearest neighbor (ARWKNN) fingerprint positioning algorithm based on visible light communication. Firstly, the target matches the fingerprints according to the received signal strength indication (RSSI) vector. Secondly, K is a dynamic value according to the matched RSSI residual. Simulation results show the ARWKNN algorithm presents a reduced average positioning error when compared with random forest (81.82%), extreme learning machine (83.93%), artificial neural network (86.06%), grid-independent least square (60.15%), self-adaptive WKNN (43.84%), WKNN (47.81%), and KNN (73.36%). These results were obtained when the signal-to-noise ratio was set to 20 dB, and Manhattan distance was used in a two-dimensional (2-D) space. The ARWKNN algorithm based on Clark distance and minimum maximum distance metrics produces the minimum average positioning error in 2-D and 3-D, respectively. Compared with self-adaptive WKNN (SAWKNN), WKNN and KNN algorithms, the ARWKNN algorithm achieves a significant reduction in the average positioning error while maintaining similar algorithm complexity.

scholarly journals Estimating Weak Pulse Signal in Chaotic Background with Jordan Neural Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Liyun Su ◽  
Xiu Ling
Keyword(s):  
Neural Network ◽  
Pulse Signal ◽  
Least Square ◽  
Data Matrix ◽  
Support Vector ◽  
Model Parameters ◽  
Elman Neural Network ◽  
Useful Signal ◽  
Weak Pulse ◽  
Space Data

In target estimating sea clutter or actual mechanical fault diagnosis, useful signal is often submerged in strong chaotic noise, and the targeted signal data are difficult to recover. Traditional schemes, such as Elman neural network (ENN), backpropagation neural network (BPNN), support vector machine (SVM), and multilayer perceptron- (MLP-) based model, are insufficient to extract the weak signal embedded in a chaotic background. To improve the estimating accuracy, a novel estimating method for aiming at extracting problem of weak pulse signal buried in a strong chaotic background is presented. Firstly, the proposed method obtains the vector sequence signal by reconstructing higher-dimensional phase space data matrix according to the Takens theorem. Then, a Jordan neural network- (JNN-) based model is designed, which can minimize the error squared sum by mixing the single-point jump model for targeting signal. Finally, based on short-term predictability of chaotic background, estimation of weak pulse signal from the chaotic background is achieved by a profile least square method for optimizing the proposed model parameters. The data generated by the Lorenz system are used as chaotic background noise for the simulation experiment. The simulation results show that Jordan neural network and profile least square algorithm are effective in estimating weak pulse signal from chaotic background. Compared with the traditional method, (1) the presented method can estimate the weak pulse signal in strong chaotic noise under lower error than ENN-based, BPNN-based, SVM-based, and -ased models and (2) the proposed method can extract the weak pulse signal under a higher output SNR than BPNN-based model.

scholarly journals Visible Light Communication with Input-Dependent Noise: Channel Estimation, Optimal Receiver Design and Performance Analysis

2021 ◽  
Author(s):  
MAYSA YASEEN ◽  
Malek Alsmadi ◽  
Ayse E. Canbilen ◽  
salama Ikki
Keyword(s):  
Channel Estimation ◽  
Visible Light ◽  
Data Transmission ◽  
Estimation Error ◽  
Visible Light Communication ◽  
Least Square ◽  
Channel Estimation Error ◽  
Closed Form Expression ◽  
Optimal Receiver ◽  
Ber Performance

<div>In this paper, single-input single-output (SISO) visible light communication (VLC) subject to signal-dependent shot noise (SDSN) is investigated. We discuss both channel estimation and data transmission. In the former, we introduce least square (LS) and maximum likelihood (ML) estimators. Moreover, we derive the Cram´er–Rao lower bound (CRLB) of the channel estimation error. With regard to data transmission, we present optimal and sub-optimal receiver designs and discuss their bit error rate (BER) performance. In particular, a closed-form expression of the BER is derived for a sub-optimal receiver using the on-off-keying (OOK) modulation technique. An approximated expression is then derived for the optimal receiver. Our analysis shows that the CRLB performance does not have a linear relation with the SDSN, thermal noise, or the fading channel. On the other hand, the SDSN has a dramatic effect on the channel estimation error bound, and it can degrade the BER performance. Increased performance degradation can also be noticed due to the joint effects of the channel estimation error and SDSN.</div>

scholarly journals Optimal hog cell to image ratio for robust multi-sensor face recognition systems

2019 ◽  
Vol 16 (3) ◽  
pp. 387-403
Author(s):  
Milos Pavlovic ◽  
Branka Stojanovic ◽  
Ranko Petrovic ◽  
Snezana Puzovic ◽  
Srdjan Stankovic
Keyword(s):  
Face Recognition ◽  
Visible Light ◽  
Environmental Conditions ◽  
Recognition Accuracy ◽  
Thermal Infrared ◽  
Feature Descriptor ◽  
Image Size ◽  
Accurate Identification ◽  
Recognition Systems ◽  
Facial Images

The main problem for modern visible light face recognition has been accurate identification under variable environmental conditions. Thermal infrared facial images utilization in face recognition systems can provide a solution for problems related to uncontrolled environmental conditions, especially to those caused by illumination limitations. This paper compares the results of the use of visible light and thermal infrared imagery for face recognition based on the HOG feature descriptor. In particular, the paper suggests an optimal HOG cell to image size ratio in order to improve recognition accuracy and reduce computational complexity. Performance statistics are presented on facial images with different facial expressions. The obtained results support the conclusion that recognition with thermal infrared images is more robust and that fusion of sensors should be included for improving recognition accuracy.

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