scholarly journals A Novel Condition Monitoring Procedure for Early Detection of Copper Corrosion Problems in Oil-Filled Electrical Transformers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4266
Author(s):  
Ramsey Jadim ◽  
Mirka Kans ◽  
Mohammed Alhattab ◽  
May Alhendi
Keyword(s):  
Early Detection ◽  
Condition Monitoring ◽  
Copper Corrosion ◽  
Corrosion Reaction ◽  
Anticorrosion Additive ◽  
Monitoring Procedure ◽  
Electrical Transformers ◽  
Early Fault Detection ◽  
Negative Impacts ◽  
Explosion Accidents

The negative impacts of catastrophic fire and explosion accidents due to copper corrosion problems of oil-filled electrical transformers are still in the spotlight due to a lack of effective methods for early fault detection. To address this gap, a condition monitoring (CM) procedure that can detect such problems in the initial stage is proposed in this paper. The suggested CM procedure is based on identified measurable variables, which are the relevant by-products of the corrosion reaction, and utilizes an Early Fault Diagnosis (EFD) model to detect and solve the copper corrosion problems. The EFD model includes a fault trend chart that can track a fault progression during the useful life of transformers. The purpose of this paper is to verify and validate the effectiveness of the suggested CM procedure by an empirical study in a power plant. The result of applying this procedure was early detection of copper corrosion problems in two transformers with suspected copper corrosion propagation from a total of 84. The corrective action was adding an optimized amount of a passivator, an anticorrosion additive, to suppress the corrosion reaction at the correct time. The main conclusion of this study is the importance of early detection of transformer faults to avoid the negative impacts on societal, company, and individual levels.

scholarly journals On Approaching Relevant Cost-Effective Sustainable Maintenance of Mineral Oil-Filled Electrical Transformers

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3670
Author(s):  
Ramsey Jadim ◽  
Mirka Kans ◽  
Jesko Schulte ◽  
Mohammed Alhattab ◽  
May Alhendi ◽  
...  
Keyword(s):  
Power Plants ◽  
Sustainability Assessment ◽  
Health And Safety ◽  
Cost Effective ◽  
Maintenance Strategy ◽  
Failure Propagation ◽  
Electrical Transformers ◽  
Negative Impacts ◽  
Explosion Accidents ◽  
Relevant Cost

Fire and explosion accidents of oil-filled electrical transformers are leading to negative impacts, not only on the delivery of energy, but also on workplace health and safety as well as the surrounding environment. Such accidents are still being reported, regardless of applying the regular maintenance strategy in the power plants. The purpose of this paper is to integrate a sustainability perspective into the maintenance strategy. The problem addressed is: how can we approach the relevant cost-effective sustainable maintenance for oil-filled electrical transformers? For this purpose, an empirical study in a power plant in Kuwait was introduced. The first stage was to carry out a sustainability assessment using the ABCD procedure. In this procedure, gaps to approach sustainability were identified and actions prioritized to close these gaps were demonstrated. Applying this procedure yielded an early fault diagnosis (EFD) model for achieving cost-effective sustainable maintenance using a fault trend chart based on a novel numerical method. Implementing this model resulted in an extension of the lifetime of transformers with suspected failure propagation, leading to a deferral of the replacement investment costs. The principal conclusion of this paper is the importance of viewing the maintenance strategy of transformers from a strategic sustainability perspective, in order to approach relevant cost-effective sustainable maintenance.

scholarly journals Intelligent Fault Diagnosis of Synchromesh Gearbox Using Fusion of Vibration and Acoustic Emission Signals for Performance Enhancement

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
T Praveenkumar ◽  
M Saimurugan ◽  
K I Ramachandran
Keyword(s):  
Support Vector Machine ◽  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Support Vector ◽  
Feature Level Fusion ◽  
Sensor Signals ◽  
Early Fault Detection ◽  
Ae Signals ◽  
Level Fusion

Condition monitoring system monitors the system degradation and it identifies common failure modes. Several sensor signals are available for monitoring the changes in system components. Vibration signal is one of the most extensively used technique for monitoring rotating components as it identifies faults before the system fails. Early fault detection is the significant factor for condition monitoring, where Acoustic Emission ( AE ) sensor signals have been applied for early fault detection due to their high sensitivity and high frequency. In this paper, vibration and acoustic emission signals are acquired under various simulated gear and bearing fault conditions from the synchromesh gearbox. Then the statistical features are extracted from vibration and AE signals and then the prominent features are selected using J48 decision tree algorithm respectively. The best features from the vibration and AE signals are then fused using feature-level fusion strategy and it is classified using Support Vector Machine ( SVM ) and Proximal Support Vector Machine ( PSVM ) classifiers and it is compared with individual signals for fault diagnosis of the synchromesh gearbox. From the experiments, it is observed that the performance of the fault diagnosis system has been improved for the proposed feature level fusion technique compared to the performance of unfused vibration and AE feature sets.

scholarly journals Development of Early Detection Method for Drought and Flood on Rice Paddy

Agromet ◽  
2018 ◽  
Vol 32 (2) ◽  
pp. 81
Author(s):  
Elza Surmaini ◽  
Erni Susanti ◽  
Yeli Sarvina ◽  
M. Ridho Syahputra
Keyword(s):  
Early Detection ◽  
Standardized Precipitation Index ◽  
Rice Paddy ◽  
Detection Model ◽  
Extreme Climate ◽  
Drought And Flood ◽  
Climate Event ◽  
Droughts And Floods ◽  
Negative Impacts ◽  
North Sumatra

<p>Droughts and floods due to extreme climate events has caused yield loss in various regions of Indonesia, including the Provinces of Aceh and North Sumatra. An early detection model needs to be developed to anticipate the negative impacts of extreme climate event. The model may describe the association of surplus and rainfall deficits with paddy damage due to drought and flood. We used Standardized Precipitation Index (SPI) to explore drought and flood characteristics in period 1989-2016. The study aimed: (i) to analyze the relationship between SPI and paddy damage due to drought and flood events, (ii) to analyze the critical value of the duration and intensity of SPI which causes paddy damage, and (iii) to determine which districts were prone to drought and flood in the Provinces of Aceh and North Sumatra. The results concluded that SPI-3 and -6 months can better describe the frequency of drought and rice flooding. In addition, drought on paddy occured mostly if the SPI was smaller than -1 which took place within 4-5 months, whereas flood occured if the SPI was greater than 1. Short duration drought (2-3 months) were observed in five districts in Aceh (2) and North Sumatra (3). On other hand, more flood districts were identified (9 districts).</p>

Development of Prognostic Techniques for Surface Defect Growth in Railroad Bearing Rolling Elements

2017 ◽  
Author(s):  
Nancy De Los Santos ◽  
Robert Jones ◽  
Constantine M. Tarawneh ◽  
Arturo Fuentes ◽  
Anthony Villarreal
Keyword(s):  
Growth Rate ◽  
Early Detection ◽  
Condition Monitoring ◽  
Surface Defect ◽  
Full Load ◽  
Defect Growth ◽  
Bearing Condition Monitoring ◽  
Full Load Operation ◽  
Railroad Bearing ◽  
The University

Prevention of bearing failures which may lead to catastrophic derailment is a major safety concern for the railroad industry. Advances in bearing condition monitoring hold the promise of early detection of bearing defects, which will improve system reliability by permitting early replacement of failing components. However, to minimize disruption to operations while providing the maximum level of accident prevention that early detection affords, it will be necessary to understand the defect growth process and try to quantify the growth speed to permit economical, non-disruptive replacement of failing components rather than relying on immediate removal upon detection. The study presented here investigates the correlation between the rate of surface defect (i.e. spall) growth per mile of full-load operation and the size of the defects. The data used for this study was acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs operated by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement and documentation. Castings were made of spalls using low-melting, zero shrinkage Bismuth-based alloys so that a permanent record of the full spall geometry could be retained. Spalls were measured using optical techniques coupled with digital image analysis and also with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™ and Solidworks™. The spall growth rate in area per mile of full-load operation was determined and, when plotted versus spall area, clear trends emerge. Initial spall size is randomly distributed as it depends on originating defect depth, size, and location on the rolling raceway. The growth of surface spalls is characterized by two growth regimes with an initial slower growth rate which then accelerates when spalls reach a critical size. Scatter is significant but upper and lower bounds for spall growth rates are proposed and the critical dimension for transition to rapid spall growth is estimated. The main result of this study is a preliminary model for spall growth which can be coupled to bearing condition monitoring tools to permit economical scheduling of bearing replacement after the initial detection of spalls.

Early Detection of Tropical Forest Degradation: an IFRI Pilot Study in Uganda

1995 ◽  
Vol 22 (1) ◽  
pp. 31-38 ◽  
Author(s):  
C. Dustin Becker ◽  
Abwoli Y. Banana ◽  
William Gombya-Ssembajjwe
Keyword(s):  
Pilot Study ◽  
Early Detection ◽  
Tropical Forest ◽  
Time Lag ◽  
Forest Degradation ◽  
Policy Changes ◽  
Negative Impacts ◽  
Forestry Resources ◽  
International Forestry

Early detection of forest degradation may help to compensate for the time-lag that often exists between recognition of poor stewardship and the policy-changes required to mitigate such negative impacts. We report here on an International Forestry Resources and Institutions (IFRI) pilot study in Uganda.

Parameter Identification for a High-Performance Hydrostatic Actuation System Using the Variable Structure Filter Concept

2006 ◽  
Vol 129 (2) ◽  
pp. 229-235 ◽  
Author(s):  
S. R. Habibi ◽  
R. Burton
Keyword(s):  
Parameter Estimation ◽  
Early Detection ◽  
State Estimation ◽  
Condition Monitoring ◽  
High Performance ◽  
Variable Structure ◽  
Maintenance Costs ◽  
Estimation Strategy ◽  
Actuation System ◽  
Smooth Variable Structure Filter

Parameter estimation is an important concept that can be used for health and condition monitoring. Estimation or measurement of physically meaningful parameters and their evaluation against predetermined thresholds allows detection of gradual or abrupt deteriorations in the plant. This early detection of faults enables preventative unscheduled maintenance that is of benefit to industries concerned with reliability and safety. In this paper, a recently proposed state estimation strategy referred to as the smooth variable structure filter (SVSF) is reviewed and extended to parameter estimation. The SVSF is applied to a novel hydrostatic actuation system referred to as the electrohydraulic actuator (EHA). Condition monitoring of the EHA for preventative unscheduled maintenance would increase its safety in applications pertaining to aerospace and would reduce its operational and maintenance costs.

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