scholarly journals Aerial Locating Method Design for Civil Aviation RFI: UAV Monitoring Platform and Ground Terminal System

2021 ◽  
Vol 103 (2) ◽  
Author(s):  
Chao Zhou ◽  
Renhe Xiong ◽  
Hongzheng Zeng ◽  
Jun Xiao ◽  
Yao Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Safety Margin ◽  
Digital Transmission ◽  
Direction Finding ◽  
Civil Aviation ◽  
Angle Of Arrival ◽  
Monitoring Method ◽  
Location Method ◽  
Analysis System ◽  
Monitoring Platform

AbstractA key open question in the aerial locating method is ensure that parameters that identify the location of the radio frequency interference (RFI) are monitored, and to make sure that the locating algorithm is unbiased. Furthermore, the transmission of parameters to the ground for real-time analysis and display of the RFI location is important as it provides insight into the performance advantages of the aerial location method. The main contributions of the article are four points: the first is the introduction of the angle of arrival (AOA) algorithm to civil aviation RFI location, and the integration of algorithm characteristics with unmanned aerial vehicle (UAV) operations proposing an aerial monitoring method for civil aviation RFI. Simulation results show that the two-point cross-location method obtains effective information on the location parameters of the RFI. The second is to build a UAV monitoring platform, which is as light as possible to make sure the direction finding and digital transmission devices meet the airworthiness requirements, so that the UAV can complete the data acquisition task within a safety margin. Thirdly, a ground analysis system was designed to receive information on the UAV’s parameters, enabling software manipulation to ensure safe operation under non-visual conditions. In addition to this, the monitoring data is processed in real time and algorithms are used to resolve the location of interference sources and display them on a map. The fourth one is to verify the implementation of the aerial positioning method by setting up different test scenarios. Compared with portable direction-finding equipment and ground monitoring, the test results show that the UAV-based RFI monitoring method performances better in monitoring radius and positioning accuracy with a small direction-finding error, and the advantages of the ground analysis system are highly integrated and intuitive display.

PRESSURE MONITORING OF MICRO-PIPETTING BASED ON ABSOLUTE DEGREE OF GREY COEFFICIENTS AND DOUBLE EXTREMES METHOD

2015 ◽  
Vol 15 (06) ◽  
pp. 1540056
Author(s):  
LIANQING ZHU ◽  
MINGLI DONG ◽  
WENCHANG ZHANG ◽  
ZHEHAI ZHOU ◽  
XIAOPING LOU ◽  
...  
Keyword(s):  
Real Time ◽  
Single Point ◽  
Pressure Curve ◽  
Air Bubbles ◽  
Pressure Monitoring ◽  
Monitoring Method ◽  
The Real ◽  
Filtering Technique ◽  
Analysis System ◽  
The Stability

Toward improving the real-time property and stability of the micro-pipetting process of an automatic enzyme-linked immunoassay analysis system, the fault detection of the process was studied by monitoring the pressure. A new method that combines the absolute degree of grey coefficients (ADGC) with the double extremes method (DEM) for monitoring pressure is proposed. The ADGC is used to demonstrate the variation of the pressure signal. In particular, the sectioning used is more flexible and is not constrained by the key timings of the micro-pipetting process. The data for a single point can be calculated in real time to obtain the double extremes (the extremes of the pressure and the first derivative) using the DEM. The DEM can therefore be performed without the need to reduce the sampling frequency, thereby guarantying the information integrity. By comparing the double extremes with the preset threshold, the fault types such as tip blockage, presence of air bubbles, and sample shortage can be distinguished. Moreover, a grey filtering technique based on the GM (1, 1) model is used to improve the stability of the pressure sensor output and significantly reduce the real-time computation requirements. Experiments were performed to verify the feasibility of the combined pressure monitoring method, and it was confirmed that it could be used to ensure real-time integrity of the information of the pressure curve. It can thus be confidently concluded that the method can be used to improve the accuracy and stability of monitoring the pressure of micro-pipetting.

scholarly journals Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3635 ◽  
Author(s):  
Guoming Zhang ◽  
Xiaoyu Ji ◽  
Yanjie Li ◽  
Wenyuan Xu
Keyword(s):  
Smart Grid ◽  
Power Consumption ◽  
Real Time ◽  
Condition Monitoring ◽  
Resource Constraints ◽  
Detection System ◽  
Stable Operation ◽  
Detection Accuracy ◽  
Monitoring Method ◽  
Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

scholarly journals An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensor ◽  
Neurological Diseases ◽  
Principal Component ◽  
Sampling Frequency ◽  
Powerful Analytical Tool ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture ◽  
Gait Monitoring

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

Aircraft Cable Fault Location Based on Detection Model

2011 ◽  
Vol 55-57 ◽  
pp. 332-336 ◽  
Author(s):  
Xiao Lin Liu ◽  
Zhi Quan Li
Keyword(s):  
Fault Location ◽  
Reference Signal ◽  
Experimental Results ◽  
Civil Aviation ◽  
Location Method ◽  
Aviation Maintenance ◽  
Location System ◽  
Detection Model ◽  
Experimental Installation

An aircraft cable fault location method based on detection model is proposed to solve the problem of being difficult to inspect the fault for the civil aviation maintenance. In response to the condition of the experimental installation, the reference signal is designed. The fault of the cable can be located according to the reflected waveform. An aircraft cable fault location system is designed and the experimental results show that the method is rational and effective.

Processing Panorama Video in Real-time

2014 ◽  
Vol 08 (02) ◽  
pp. 209-227 ◽  
Author(s):  
Håkon Kvale Stensland ◽  
Vamsidhar Reddy Gaddam ◽  
Marius Tennøe ◽  
Espen Helgedagsrud ◽  
Mikkel Næss ◽  
...  
Keyword(s):  
Real Time ◽  
Graphics Processing Units ◽  
Low Cost ◽  
Video Camera ◽  
Wide Field ◽  
High Data ◽  
Data Rates ◽  
Camera Arrays ◽  
Analysis System ◽  
Performance Results

There are many scenarios where high resolution, wide field of view video is useful. Such panorama video may be generated using camera arrays where the feeds from multiple cameras pointing at different parts of the captured area are stitched together. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent timeliness requirements. In our research, we use panorama video in a sport analysis system called Bagadus. This system is deployed at Alfheim stadium in Tromsø, and due to live usage, the video events must be generated in real-time. In this paper, we describe our real-time panorama system built using a low-cost CCD HD video camera array. We describe how we have implemented different components and evaluated alternatives. The performance results from experiments ran on commodity hardware with and without co-processors like graphics processing units (GPUs) show that the entire pipeline is able to run in real-time.

scholarly journals A Real-Time Monitoring Platform for Distributed Energy Resources in a Microgrid—Pilot Study in Oman

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1803
Author(s):  
Nasser Hosseinzadeh ◽  
Ahmed Al Maashri ◽  
Naser Tarhuni ◽  
Abdelsalam Elhaffar ◽  
Amer Al-Hinai
Keyword(s):  
Real Time ◽  
Communication Channel ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Small Scale ◽  
Area Network ◽  
Distributed Energy ◽  
Real Time Monitoring ◽  
Holistic View ◽  
Monitoring Platform

This article presents the development of a platform for real-time monitoring of multi-microgrids. A small-scale platform has been developed and implemented as a prototype, which takes data from various types of devices located at a distance from each other. The monitoring platform is interoperable, as it allows several protocols to coexist. While the developed prototype is tested on small-scale distributed energy resources (DERs), it is done in a way to extend the concept for monitoring several microgrids in real scales. Monitoring strategies were developed for DERs by making a customized two-way communication channel between the microgrids and the monitoring center using a long-range bridged wireless local area network (WLAN). In addition, an informative and easy-to-use software dashboard was developed. The dashboard shows real-time information and measurements from the DERs—providing the user with a holistic view of the status of the DERs. The proposed system is scalable, modular, facilitates the interoperability of various types of inverters, and communicates data over a secure communication channel. All these features along with its relatively low cost make the developed real-time monitoring platform very useful for online monitoring of smart microgrids.

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