SDR: Sensor data recovery for system condition monitoring

2018 ◽  
Author(s):  
Liu Liansheng ◽  
Liu Datong ◽  
Guo Qing ◽  
Peng Yu ◽  
Liang Jun
Keyword(s):  
Condition Monitoring ◽  
Data Recovery ◽  
Sensor Data

A WBAN-Based Framework for Health Condition Monitoring and Faulty Sensor Node Detection Applying ANN

2021 ◽  
Vol 10 (2) ◽  
pp. 44-65
Author(s):  
Koushik Karmakar ◽  
Sohail Saif ◽  
Suparna Biswas ◽  
Sarmistha Neogy
Keyword(s):  
Condition Monitoring ◽  
Health Monitoring ◽  
Wearable Sensors ◽  
Wireless Body Area Network ◽  
Health Condition ◽  
Sensor Data ◽  
Area Network ◽  
Cardiac Condition ◽  
Artificial Neural Network Ann ◽  
Sensor Detection

Remote health monitoring framework using wireless body area network with ubiquitous support is gaining popularity. However, faulty sensor data may prove to be critical. Hence, faulty sensor detection is necessary in sensor-based health monitoring. In this paper, an artificial neural network (ANN)-based framework for learning about health condition of patients as well as fault detection in the sensors is proposed. This experiment is done based on human cardiac condition monitoring setup. Related physiological parameters have been collected using wearable sensors from different people. These data are then analyzed using ANN for health condition identification and faulty node detection. Libelium MySignals HW (eHealth Medical Development Shield for Arduino) v2 sensors such as ECG sensor, pulse oximeter sensor, and body temperature sensor have been used for data collection and ARDINO UNO R3 as microcontroller device. ANN method detects faulty sensor data with classification accuracy of 98%. Experimental results and analyses are given to prove the claim.

Design a degradation condition monitoring system scheme for rolling bearing using EMD and PCA

2017 ◽  
Vol 117 (4) ◽  
pp. 713-728 ◽  
Author(s):  
Jun Wu ◽  
Chaoyong Wu ◽  
Yaqiong Lv ◽  
Chao Deng ◽  
Xinyu Shao
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Rolling Bearing ◽  
Sensor Data ◽  
Health Index ◽  
Rolling Bearings ◽  
Content Type ◽  
Bearing Condition Monitoring ◽  
Condition Monitoring System ◽  
Monotonicity Analysis

Purpose Rolling bearings based on rotating machinery are one of the most widely used in industrial applications because of their low cost, high performance and robustness. The purpose of this paper is to describe how to identify degradation condition of rolling bearing and predict its fault time in big data environment in order to achieve zero downtime performance and preventive maintenance for the rolling bearing. Design/methodology/approach The degradation characteristic parameters of rolling bearings including intrinsic mode energy and failure frequency were, respectively, extracted from the pre-processed original vibration signals using EMD and Hilbert transform. Then, Spearman’s rank correlation coefficient and PCA were used to obtain the health index of the rolling bearing so as to detect the appearance of degradations. Furthermore, the degradation condition of the rolling bearings might be identified through implementing the monotonicity analysis, robustness analysis and degradation analysis of the health index. Findings The effectiveness of the proposed method is verified by a case study. The result shows that the proposed method can be applied to monitor the degradation condition of the rolling bearings in industrial application. Research limitations/implications Further experiment remains to be done so as to validate the effectiveness of the proposed method using Apache Hadoop when massive sensor data are available. Practical implications The paper proposes a methodology for rolling bearing condition monitoring representing the steps that need to be followed. Real-time sensor data are utilized to find the degradation characteristics. Originality/value The result of the work presented in this paper form the basis for the software development and implementation of condition monitoring system for rolling bearings based on Hadoop.

scholarly journals A Lost Data Recovery Scheme for Sensor Data Stream Multicasting

2018 ◽  
Vol 26 (0) ◽  
pp. 158-168 ◽  
Author(s):  
Ei Khaing Win ◽  
Tomoki Yoshihisa ◽  
Yoshimasa Ishi ◽  
Tomoya Kawakami ◽  
Yuuichi Teranishi ◽  
...  
Keyword(s):  
Data Stream ◽  
Data Recovery ◽  
Sensor Data ◽  
Recovery Scheme

scholarly journals Novel Data Compression Algorithm for Transmission Line Condition Monitoring

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8275
Author(s):  
Gang Liu ◽  
Lei Jia ◽  
Taishan Hu ◽  
Fangming Deng ◽  
Zheng Chen ◽  
...  
Keyword(s):  
Transmission Line ◽  
Sensor Network ◽  
Condition Monitoring ◽  
Compression Algorithm ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Compression Algorithms ◽  
High Compression ◽  
Index Sequence ◽  
Line Condition

For the problem of data accumulation caused by massive sensor data in transmission line condition monitoring system, this paper analyzes the type and amount of data in the transmission line sensor network, compares the compression algorithms of wireless sensor network data at home and abroad, and proposes an efficient lossless compression algorithm suitable for sensor data in transmission line linear heterogeneous networks. The algorithm combines the wavelet compression algorithm and the neighborhood index sequence algorithm. It displays a fast operation speed and requires a small amount of calculation. It is suitable for battery powered wireless sensor network nodes. By combining wavelet correlation analysis and neighborhood index sequence coding, the compression algorithm proposed in this paper can achieve a high compression rate, has strong robustness to packet loss, has high compression performance, and can help to reduce network load and the packet loss rate. Simulation results show that the proposed method achieves a high compression rate in the compression of the transmission line parameter dataset, is superior to the existing data compression algorithms, and is suitable for the compression and transmission of transmission line condition monitoring data.

scholarly journals Development of Platooning Technology with Road Condition Monitoring

2021 ◽  
Vol 9 (10) ◽  
pp. 515-518
Author(s):  
Srinivaas A
Keyword(s):  
Time Delay ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Sensor Data ◽  
Automated Driving ◽  
The Road ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Condition Monitoring System ◽  
Lead Vehicle

Abstract: In this paper, we present a complete platooning system using a time-delay algorithm. The platooning is achieved by measuring the driver inputs from the lead vehicle and sending these inputs to the trail vehicle with a time-delay so that the trail vehicle can exactly mimic the motion of the lead vehicle. This system also does a road condition monitor as an add-on benefit which will help in assisting the driver of the trail vehicle/vehicle which takes the same path. The function of this monitoring system is to analyse the road surface using a lead vehicle and acquire sensor data, this acquired sensor data helps in assisting drivers who take the same track. The combination of both this platooning method and road condition monitoring system could potentially reduce the current risk of utilising this semi-automated driving system. Index terms: Platooning, Semi-automated driving, Road condition monitoring, Time-delay algorithm.

Condition Monitoring of Next Generation Digitized Electric Subsea Actuators

2021 ◽  
Author(s):  
Tobias Winter ◽  
Markus Glaser
Keyword(s):  
Condition Monitoring ◽  
Health Management ◽  
High Reliability ◽  
Continuous Production ◽  
Water Concentration ◽  
Sensor Data ◽  
Mode Analysis ◽  
Detailed Knowledge ◽  
Electric Actuator ◽  
Digital Twin

Abstract A detailed knowledge about the health status of the installed assets is the key for continuous production without unexpected events and downtime, which causes production loss. A major aspect is the prediction of the occurrence of a failure before the affected function is demanded. This is one purpose of the Condition Monitoring (CM), Prognostics and Health Management (PHM) and the application of a Digital Twin. The paper presents the result of an ability analysis for a subsea actuator towards its possibilities to increase the availability through a novel and extensive grade of information. The paper presents the resulting architecture and solution to achieve an actuator design, which is capable to provide a high safety, high reliability and a predictive health management which is prepared for a digital twin application. For this purpose, an applied Condition Monitoring concept is described and shown based on the case study. The analysis and resulting solution is based on a detailed research towards the state of the art. Different available subsea actuators are analyzed towards the communication interfaces and the ability to allow CM. Therefore, the required status and information of the actuator are shown (e.g. Torque, position, temperature, acceleration, water concentration in oil, humidity, pressure, inclinometer). The required environment information about the actuator are evaluated with the help of a failure mode analysis. The different sensor principles provide the necessary information. The paper evaluates the significance of the sensor information towards the CM concept. The data can be provided on different communication interfaces and protocols. These are analyzed towards the satisfaction of the CM requirements. The result of the analysis is a detailed architecture of a CM capable subsea electric actuator including the CM concept. The possible interfaces are shown and the provided sensor data by the actuator. The sensors provide the input for the CM model and the remote accessibility and controllability of the actuator. The result is the novel design of a subsea actuator, which fits perfect in a digitalized subsea environment to increase the availability and controllability including a CM concept.

A Digital Twin concept for the prescriptive maintenance of protective coating systems on wind turbine structures

2021 ◽  
pp. 0309524X2110605
Author(s):  
Andreas W Momber ◽  
Torben Möller ◽  
Daniel Langenkämper ◽  
Tim W Nattkemper ◽  
Daniel Brün
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Wind Turbines ◽  
Protective Coating ◽  
Image Annotation ◽  
Initial Point ◽  
Sensor Data ◽  
Surface Protection ◽  
Digital Twin ◽  
Inspection Condition

The application of protective coating systems is the major measure against the corrosion of steel for tower sections of wind turbines. The inspection, condition monitoring and maintenance of protective coating system is a demanding and time-consuming procedure and requires high human effort. The paper introduces for the first time a Digital Twin concept for the condition monitoring and prescriptive maintenance planning for surface protection systems on wind turbine towers. The initial point of the concept is an in-situ Virtual Twin for the generation of reference areas for condition monitoring. The paper describes the integration of an online image annotation and processing tool, a maintenance model, corrosive resistance parameters, structural load parameters, and sensor data into the Digital Twin concept. The prospects of the concept and its practical relevance are shown for tower structures of large onshore wind turbines.

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