A Novel Two-Stage Approach to On-Site Condition Monitoring for the Avoidance of Unscheduled Down-Time, Critical Equipment Failure and Costly False Alarms

2017 ◽  
Author(s):  
V. Leavers
Keyword(s):  
Condition Monitoring ◽  
False Alarms ◽  
Equipment Failure ◽  
Site Condition ◽  
Two Stage ◽  
Time Critical

scholarly journals Two Current-Based Methods for the Detection of Bearing and Impeller Faults in Variable Speed Pumps

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4514
Author(s):  
Vincent Becker ◽  
Thilo Schwamm ◽  
Sven Urschel ◽  
Jose Alfonso Antonino-Daviu
Keyword(s):  
Condition Monitoring ◽  
False Alarms ◽  
Signature Analysis ◽  
Variable Speed ◽  
Monitoring Methods ◽  
Time Frequency ◽  
Motor Current ◽  
Load Point ◽  
Bearing Defects ◽  
Current Signature

The growing number of variable speed drives (VSDs) in industry has an impact on the future development of condition monitoring methods. In research, more and more attention is being paid to condition monitoring based on motor current evaluation. However, there are currently only a few contributions to current-based pump diagnosis. In this paper, two current-based methods for the detection of bearing defects, impeller clogging, and cracked impellers are presented. The first approach, load point-dependent fault indicator analysis (LoPoFIA), is an approach that was derived from motor current signature analysis (MCSA). Compared to MCSA, the novelty of LoPoFIA is that only amplitudes at typical fault frequencies in the current spectrum are considered as a function of the hydraulic load point. The second approach is advanced transient current signature analysis (ATCSA), which represents a time-frequency analysis of a current signal during start-up. According to the literature, ATCSA is mainly used for motor diagnosis. As a test item, a VSD-driven circulation pump was measured in a pump test bench. Compared to MCSA, both LoPoFIA and ATCSA showed improvements in terms of minimizing false alarms. However, LoPoFIA simplifies the separation of bearing defects and impeller defects, as impeller defects especially influence higher flow ranges. Compared to LoPoFIA, ATCSA represents a more efficient method in terms of minimizing measurement effort. In summary, both LoPoFIA and ATCSA provide important insights into the behavior of faulty pumps and can be advantageous compared to MCSA in terms of false alarms and fault separation.

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.

scholarly journals Response Times to Visual and Auditory Alarms during Anaesthesia

1996 ◽  
Vol 24 (6) ◽  
pp. 682-684 ◽  
Author(s):  
R. W. Morris ◽  
S. R. Montano
Keyword(s):  
Response Times ◽  
Red Light ◽  
Anaesthetic Machine ◽  
Heart Beat ◽  
Visual Signal ◽  
False Alarms ◽  
Laptop Computer ◽  
Audible Alarm ◽  
High Level ◽  
Time Critical

Objective To measure and compare the response times to audibly or visually presented alarms in the operating theatre. Methods The time taken by anaesthetists to cancel randomly generated visual and audible false alarms was measured during maintenance of routine anaesthesia. Alarms were generated and times recorded by a laptop computer on the anaesthetic machine. The visual signal was a 15mm diameter red light positioned next to the physiological monitor mounted on top of the machine. The audible alarm was a Sonalert® buzzer of the type incorporated into many medical devices. Results Nineteen anaesthetists provided a total of seventy-two hours of data (887 alarm events). The response times to visual alarms was significantly longer than to audible alarms (P=0.001 Mann Whitney U test). Conclusions The ability of anaesthetists to appreciate changes in patient physiology may be limited by delays in noticing information presented by monitors. The rapid response to the vast majority of alarms indicates a high level of vigilance among the anaesthetists studied. However, this study suggests that it is safer to rely on audible rather than visual alarms when time-critical information such as oxygenation, heart beat and ventilator disconnection is concerned. Visual alarms would appear to be more appropriate for conveying less urgent information.

Dedicated On-Site Condition Monitoring of High Voltage Power Cables up to 150kV

ENERGYO ◽  
2018 ◽  
Author(s):  
Edward Gulski ◽  
Paul P. Seitz ◽  
Ben Quak ◽  
Frank Petzold ◽  
Frank De Vries
Keyword(s):  
Condition Monitoring ◽  
High Voltage ◽  
Power Cables ◽  
Site Condition

Research on Condition Monitoring and Fault Diagnosis of Metallurgical Machinery and Equipment

2011 ◽  
Vol 52-54 ◽  
pp. 504-510
Author(s):  
Zheng Rong Guan ◽  
Jun Ping Li ◽  
Xin Wu Wang
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Historical Data ◽  
Signal Amplitude ◽  
Production Equipment ◽  
Rotating Machinery ◽  
Equipment Failure ◽  
Shock Pulse ◽  
Maintenance Work ◽  
Vibration Parameters

Using the signal amplitude domain, frequency domain, bearing shock pulse measurement of bearings, gear boxes, motors and other rotating machinery vibration parameters for key components, through the accumulation of historical data and diagnosis, to predict in advance of equipment failure, for maintenance work to help provide a reliable and assurance purposes. The results show that the system does for the routine maintenance of production equipment has played a guiding role.

Identification of a Malicious Optical Edge Device in the SDN-Based Optical Fog/Cloud Computing Network

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Sandeep K. Sood ◽  
Kiran Deep Singh
Keyword(s):  
Cloud Computing ◽  
Detection System ◽  
Optical Network ◽  
Network Virtualization ◽  
Cost Effective ◽  
Passive Optical Network ◽  
Optical Channel ◽  
False Alarms ◽  
Successful Implementation ◽  
Two Stage

AbstractSoftware-defined networking (SDN) and optical transmission are the most cost-effective technologies for implementing high-bandwidth-based communication in the fog/cloud computing environment. The passive optical network uses optical line terminals and optical network units as optical edge devices (OEDs) to deliver fog/cloud-based services effectively. The security of such OEDs is one of the key issues for successful implementation of fog/cloud computing over the SDN-based optical network. The main security challenge is to detect and prevent the malicious OED that transmitting abusing data-frames in the SDN-based optical fog/cloud computing network. An OED can be easily hacked by the attacker to launch intrusive attacks those affect the quality of service of the optical channel. In this paper, a secure framework is proposed for identifying malicious OED in the fog/cloud computing over the SDN-based optical network. It identifies the malicious OED and shifts it to the honeypot to mitigate and analyze the attack. It uses two-stage hidden Markov model (HMM), intrusion detection system (IDS)-based fog manager and an optical virtual honeypot device (OVHD). A two-stage HMM is effectively used to reduce the false alarms of IDS in the identification of malicious OED and shifting it onto the OVHD. The OVHD is created in the SDN-based optical network by using the concept of free-available-resource and optical network virtualization. The proposed OVHD logs all malicious activities as well as attacker’s path for preventing future attacks. In order to validate the proposed framework, the simulation of two-stage HMM is implemented in MATLAB and mitigation impacts of the internal attacks are studied by using iFogSim toolkit. The results show the effectiveness of the proposed framework.

Dedicated On-Site Condition Monitoring of High Voltage Power Cables up to 150kV

2008 ◽  
Vol 9 (3) ◽  
Author(s):  
Edward Gulski ◽  
Paul P Seitz ◽  
Ben Quak ◽  
Frank Petzold ◽  
Frank de Vries
Keyword(s):  
Signal Processing ◽  
Condition Monitoring ◽  
High Voltage ◽  
Partial Discharge ◽  
Dielectric Losses ◽  
Power Cables ◽  
Site Condition ◽  
Cable System ◽  
Production Methods ◽  
Non Destructive

For advanced, non-destructive on-site condition monitoring of HV power cables up to 150kV by partial discharge detection and dielectric losses measurement it is necessary to energize the disconnected cable system. One of the methods available for this purpose is based on applying damped AC voltages up to 150kV. In this paper, the use of modern technological solutions in power electronics and signal processing as well as in technical design and production methods will be discussed on the basis of the ultra light system (300kg) which is able to test cables up to 20km lengths.

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