scholarly journals False Alarms Analysis of Wind Turbine Bearing System

2020 ◽  
Vol 12 (19) ◽  
pp. 7867 ◽  
Author(s):  
Ana María Peco Chacón ◽  
Isaac Segovia Ramírez ◽  
Fausto Pedro García Márquez
Keyword(s):  
Wind Speed ◽  
Condition Monitoring ◽  
Wind Farms ◽  
Data Partitioning ◽  
False Alarms ◽  
Monitoring And Control ◽  
Condition Monitoring Systems ◽  
Mining Centers ◽  
Critical Components ◽  
And Control

Wind turbines are complex systems that use advanced condition monitoring systems for analyzing their health status. The gearbox is one of the most critical components due to its elevated downtime and failure rate. Supervisory Control and Data Acquisition systems are employed in wind farms for condition monitoring and control in real time. The volume and variety of the data require novel and robust techniques for data analysis. The main novelty of this work is the development of a new modelling of the temperature curve of the gearbox bearing versus wind speed to detect false alarms. An approach based on data partitioning and data mining centers is employed. The wind speed range is divided into intervals to increase the accuracy of the model, where the centers are considered representative samples in the modelling. A method based on the alarm detection is developed and studied together with the alarms report provided by a real case study. The results obtained allow the identification of critical alarm periods outside the confidence interval. It is validated that the study of alarm identification, pre-filtered data, state variable, and output power contribute to the detection of the false alarms.

A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

2021 ◽  
Author(s):  
Zhangyue Shi ◽  
Chenang Liu ◽  
Chen Kan ◽  
Wenmeng Tian ◽  
Yang Chen
Keyword(s):  
Information Technologies ◽  
Manufacturing Systems ◽  
Rapid Development ◽  
Data Access ◽  
Sensor Data ◽  
False Alarms ◽  
Monitoring And Control ◽  
Stream Data ◽  
Physical Security ◽  
And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

scholarly journals Investigation of the Superposition Effect of Oil Vapor Leakage and Diffusion from External Floating-Roof Tanks Using CFD Numerical Simulations and Wind-Tunnel Experiments

Processes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 299
Author(s):  
Jie Fang ◽  
Weiqiu Huang ◽  
Fengyu Huang ◽  
Lipei Fu ◽  
Gao Zhang
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Simulation Method ◽  
Vapor Concentration ◽  
Monitoring And Control ◽  
Wind Tunnel Experiments ◽  
Ambient Wind ◽  
Wind Speeds ◽  
High Concentrations ◽  
And Control

Based on computational fluid dynamics (CFD) and Realizable k-ε turbulence model, we established a numerical simulation method for wind and vapor-concentration fields of various external floating-roof tanks (EFRTs) (single, two, and four) and verified its feasibility using wind-tunnel experiments. Subsequently, we analysed superposition effects of wind speed and concentration fields for different types of EFRTs. The results show that high concentrations of vapor are found near the rim gap of the floating deck and above the floating deck surface. At different ambient wind speeds, interference between tanks is different. When the ambient wind speed is greater than 2 m/s, vapor concentration in leeward area of the rear tank is greater than that between two tanks, which makes it easy to reach explosion limit. It is suggested that more monitoring should be conducted near the bottom area of the rear tank and upper area on the left of the floating deck. Superposition in a downwind direction from the EFRTs becomes more obvious with an increase in the number of EFRTs; vapor superposition occurs behind two leeward tanks after leakage from four large EFRTs. Considering safety, environmental protection, and personnel health, appropriate measures should be taken at these positions for timely monitoring, and control.

Remote Condition Monitoring and Control of Standby Diesel Generators

1992 ◽  
Vol 25 (6) ◽  
pp. 164-168
Author(s):  
R Perryman ◽  
M Reynolds ◽  
S Strudwick
Keyword(s):  
Condition Monitoring ◽  
Monitoring And Control ◽  
Diesel Generators ◽  
And Control

Wireless Condition Monitoring and Control of Air Compressor Fleet System Based on the Internet of Things

2014 ◽  
Vol 1027 ◽  
pp. 294-297
Author(s):  
Ye Ming Zhang ◽  
Zhi Guo Li ◽  
Mao Li Cai
Keyword(s):  
Energy Efficiency ◽  
Condition Monitoring ◽  
Test System ◽  
Monitoring And Control ◽  
Health Maintenance ◽  
Air Compressor ◽  
Energy Saving Potential ◽  
Optimization Control ◽  
And Control ◽  
The Internet Of Things

The whole optimization control and health maintenance of air compressor fleet system in coal mine is the current key problems urgently to be solved in pneumatic system application. The test system of wireless condition monitoring and control for air Compressor fleet is setup and the hardware structure of test system is put forward. Overall energy efficiency and piecewise energy efficiency concept of air compressor fleet system is proposed in this paper. The overall efficiency and the energy-saving potential of compressed gas supplying system are quantified by the method of Capacity on Demand. Network optimization control algorithm for the air compressor fleet system is proposed for the better management of the compressed air system.

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