Showing 7 results for Monitoring
Moniri, Farshad,
Volume 2, Issue 1 (1-2006)
Abstract
Power transformers are key components in electrical power supplies and their failure could cause severe consequences on continuity of service and also generates substantial costs. Identifying problems at an early stage, before catastrophic failure occurs, is a great benefit for reliable operation of power transformers. Frequency Response Analysis (FRA) is a new, well-known and powerful diagnostic test technique for transformers which could find mechanical as well as electrical faults such as detection and positioning of winding short circuit, winding movement, loss of clamping pressure, aging of insulation, etc. Yet there are several practical limitations to affect the accuracy and ease using this test as a regular condition monitoring technique in the field that many of them originated from noise and measuring errors. This paper purposes a transformer automated self diagnosis system can be installed on every power supply as a part of SCADA to extract FRA graphs from transformers and offers high repeatability which is a great benefit for FRA test. This is the first time that KALMAN Filter will be use in order to eliminate narrow-band and wide-band noises from FRA graphs that ends up not only smoothed measurement but also rate of changes that is so valuable in decision making and scheduling for transformers maintenance. So we will have an intelligent system which is able to predict the future of transformer using experience of not only own self but also all the transformers in an integrated network.
Y Damchi, J Sadeh,
Volume 9, Issue 4 (12-2013)
Abstract
Appropriate operation of protection system is one of the effective factors to have a desirable reliability in power systems, which vitally needs routine test of protection system. Precise determination of optimum routine test time interval (ORTTI) plays a vital role in predicting the maintenance costs of protection system. In the most previous studies, ORTTI has been determined while remote back-up protection system was considered fully reliable. This assumption is not exactly correct since remote back-up protection system may operate incorrectly or fail to operate, the same as the primary protection system. Therefore, in order to determine the ORTTI, an extended Markov model is proposed in this paper considering failure probability for remote back-up protection system. In the proposed Markov model of the protection systems, monitoring facility is taken into account. Moreover, it is assumed that the primary and back-up protection systems are maintained simultaneously. Results show that the effect of remote back-up protection system failures on the reliability indices and optimum routine test intervals of protection system is considerable.
M Khodsuz, M Mirzaie,
Volume 11, Issue 4 (12-2015)
Abstract
This paper introduces the indicators for surge arrester condition assessment based on the leakage current analysis. Maximum amplitude of fundamental harmonic of the resistive leakage current, maximum amplitude of third harmonic of the resistive leakage current and maximum amplitude of fundamental harmonic of the capacitive leakage current were used as indicators for surge arrester condition monitoring. Also, the effects of operating voltage fluctuation, third harmonic of voltage, overvoltage and surge arrester aging on these indicators were studied. Then, obtained data are applied to the multi-layer support vector machine for recognizing of surge arrester conditions. Obtained results show that introduced indicators have the high ability for evaluation of surge arrester conditions.
A. Karimabadi, M. E. Hajiabadi, E. Kamyab, A. A. Shojaei,
Volume 16, Issue 2 (6-2020)
Abstract
The Circuit Breaker (CB) is one of the most important equipment in power systems. CB must operate reliably to protect power systems as well as to perform tasks such as load disconnection, normal interruption, and fault current interruption. Therefore, the reliable operation of CB can affect the security and stability of power network. In this paper, effects of Condition Monitoring (CM) of CB on the maintenance process and related costs are analyzed. For this, A mathematical formulation to categorize and model equipment failures based on their severity is developed. By CM, some of the high severity failures, named major failures, can be early detected and be corrected as a minor failure. This formulation quantifies the effect of CM on the outage rate and Predictive Maintenance (PDM) rate of equipment. Also, by combining the predictive maintenance to preventive maintenance, the Integrated Preventive and Predictive Maintenance Markov model is presented to analyze the effect of CM on the maintenance process. Finally, the optimal inspection rates of CBs based on the minimum maintenance cost in the traditional and the proposed Markov model are determined. To verify the effectiveness and applicability of the method, the proposed approach is applied to the CBs of KREC in Iran.
Pampa Debnath, Diptadip Barai, Rajorshi Mandal, Ayeshee Sinha, Jeet Saha, Arpan Deyasi,
Volume 20, Issue 2 (6-2024)
Abstract
A novel architecture is proposed in the present paper for detection and monitoring of air pollution at real-time condition following industrial standard, embedded with gas sensors which are able to identify both organic as well as inorganic hazardous contents. A vis-à-vis comparative analysis is carried out with existing literature highlighting cons of most referred circuits, both in component, system and power consumption levels, and a generalized drawback is reported citing their inefficacy for real-time data collection and accuracy level. Detailed review is reported based on qualitative assessments also, and henceforth, justifies the significance of the proposed design; where not only higher ranges of detection are possible, however is also associated with lower power consumption (26.41% and 10.71% respectively compared to the two latest circuits) and finer detection of dust particles even at extremely low concentration. The architecture will help to implicate precautionary steps at real-time condition for controlling the harmful effect in Society.
Shuvojit Kundu, Tuhel Ahmed, Jia Uddin,
Volume 21, Issue 1 (3-2025)
Abstract
This study aims to evaluate a cantilever beam type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. Harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress are calculated with greater precision using eigen frequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.
Julie Roslita Rusli, Muhamad Syahirin Danial Noor Shahrin, Nurul Izzati Binti Che Abdu Patah, Izanoordina Ahmad, Siti Marwangi Mohamad Maharum, Sairul Izwan Safie,
Volume 21, Issue 2 (6-2025)
Abstract
Digital stethoscopes represent a significant advancement in medical diagnostics, addressing the limitations of traditional auscultation methods, which often suffer from diagnostic delays and inefficient workflows. This digital stethoscope facilitates real-time diagnosis through machine learning and remote monitoring, utilizing the ESP32’s ADC and Wi-Fi capabilities to wirelessly send audio data to a remote server for comprehensive analysis. By integrating modern technologies such as the ESP32 microcontroller and the MAX9814 microphone module, these devices capture and transmit high-fidelity respiratory sounds, overcoming the challenges of imprecision and time lag in conventional methods. Initial tests have demonstrated the device's ability to capture clear respiratory sounds, underscoring its potential for effective remote health monitoring and telemedicine. These improvements aim to enhance diagnostic accuracy, facilitate early diagnosis, and ultimately improve patient outcomes, showcasing the significant potential of digital stethoscopes to transform respiratory diagnostics and patient care, particularly in remote and telemedicine settings. In this research, a prototype of a digital stethoscope for respiratory diagnostics was developed and evaluated. The obtained results from the prototype measurements demonstrated that the proposed system could be a solid starting point for the actual implementation of an advanced respiratory monitoring system.
