Stochastic RUL calculation enhanced with TDNN-based IGBT failure modeling

Power electronics are widely used in the transport and energy sectors. Hence, the reliability of these power electronic components is critical to reducing the maintenance cost of these assets. It is vital that the health of these components is monitored for increasing the safety and availability of a system. The aim of this paper is to develop a prognostic technique for estimating the remaining useful life (RUL) of power electronic components. There is a need for an efficient prognostic algorithm that is embeddable and able to support on-board real-time decision-making. A time delay neural network (TDNN) is used in the development of failure modes for an insulated gate bipolar transistor (IGBT). Initially, the time delay neural network is constructed from training IGBTs' ageing samples. A stochastic process is performed for the estimation results to compute the probability of the health state during the degradation process. The proposed TDNN fusion with a statistical approach benefits the probability distribution function by improving the accuracy of the results of the TDDN in RUL prediction. The RUL (i.e., mean and confidence bounds) is then calculated from the simulation of the estimated degradation states. The prognostic results are evaluated using root mean square error (RMSE) and relative accuracy (RA) prognostic evaluation metrics

Wastewater Use in Cauliflower Production and Farmer’s Health: An Economic Analysis

The present study aims to estimate the economic values of negative externalities of wastewater use in cauliflower production. Cost-benefit analysis is employed to estimate the farmer’s health externalities in the production sector. The data are collected from 200 farmers (100 from each group, wastewater and freshwater) in the year 2006 from two peri-urban villages of Faisalabad city. Ignoring the value of negative externalities, wastewater use is profitable in vegetable production but when the economic value of negative externalities are factored in the analysis, the results strongly discourage its use. The cost of health externalities due to wastewater use in cauliflower production (only for a three-month crop) is Rs 3.2 million from the 741 acres planted. In Faisalabad, 5,283 acres of vegetables are cultivated using wastewater, and the value of total negative health externalities amounts to Rs 90.7 million in a year. A huge economic loss due to wastewater use may attract the attention of policy agents to intervene. Among different available options, installation of a water treatment plant appears to be most viable to minimise the external effect of wastewater use in peri-urban agriculture.Cauliflower, Wastewater, Freshwater, Externalities, Health Damages, Cost-benefit Analysis

A novel intermittent fault detection algorithm and health monitoring for electronic interconnections

There are various occurrences and root causes that result in no-fault-found (NFF) events but an intermittent fault (IF) is the most frustrating. This paper describes the challenging and most important area of an IF detection and health monitoring that focuses toward NFF situation in electronics interconnections. The experimental work focuses on mechanically-induced intermittent conditions in connectors. This paper illustrates a test regime, which can be used to repeatedly reproduce intermittence in electronic connectors, while subjected to vibration. A novel algorithm is used to detect an IF in interconnection. It sends a sine wave and decodes the received signal for intermittent information from the channel. This algorithm has been simulated to capture an IF signature using PSpice (electronic circuit simulation software). A simulated circuit is implemented for practical verification. However, measurements are presented using an oscilloscope. The results of this experiment provide an insight into the limitations of existing test equipment and requirements for future IF detection techniques. Aside from scheduled maintenance, this paper considers the possibility for in-service intermittent detection to be built into future systems, i.e., can IFs be captured without external test gear

A Carrier Signal Approach for Intermittent Fault Detection and Health Monitoring for Electronics Interconnections System

Abstract: Intermittent faults are completely missed out by traditional monitoring and detection techniques due to non-stationary nature of signals. These are the incipient events of a precursor of permanent faults to come. Intermittent faults in electrical interconnection are short duration transients which could be detected by some specific techniques but these do not provide enough information to understand the root cause of it. Due to random and non-predictable nature, the intermittent faults are the most frustrating, elusive, and expensive faults to detect in interconnection system. The novel approach of the author injects a fixed frequency sinusoidal signal into electronics interconnection system that modulates intermittent fault if persist. Intermittent faults and other channel effects are computed from received signal by demodulation and spectrum analysis. This paper describes technology for intermittent fault detection, and classification of intermittent fault, and channel characterization. The paper also reports the functionally tests of computational system of the proposed methods. This algorithm has been tested using experimental setup. It generate an intermittent signal by external vibration stress on connector and intermittency is detected by acquiring and processing propagating signal. The results demonstrate to detect and classify intermittent interconnection and noise variations due to intermittency. Monitoring the channel in-situ with low amplitude, and narrow band signal over electronics interconnection between a transmitter and a receiver provides the most effective tool for continuously watching the wire system for the random, unpredictable intermittent faults, the precursor of failure. - See more at: http://thesai.org/Publications/ViewPaper?Volume=6&Issue=12&Code=ijacsa&SerialNo=20#sthash.8RXsdW0t.dpu

The epidemiology of cryptosporidium at the wildlife-livestock and human interface on the western boundary of the Kruger National Park

Cryptosporidium has emerged as one of the most important zoonotic coccidian parasites affecting a wide range of wild and domestic animals and men. It causes severe life-threatening diarrhoea in neonates and immunocompromised individuals, especially in HIV/AIDS positive patients. Among rural communities surrounding the Kruger National Park (KNP) the prevalence of HIV/AIDS is high and contact between wildlife and livestock frequently occurs. Thus the risk of transmission of Cryptosporidium passing from the wildlife population in the KNP to the bordering communities and their livestock needs to be assessed. Currently, no data are available on the prevalence of Cryptosporidium in wildlife and cattle in South Africa. To identify the prevalence of Cryptosporidium in the wildlife and the livestock population, a total of 430 faecal samples were collected from wild animals (Buffalo, Impala and Elephant) in three different areas of the KNP (2 of them in proximity of the Western boundary and 1 within the KNP territory). In addition a total of 600 samples were collected from cattle in 10 different diptanks, located next to the KNP in the Bushbuckridge district (Mpumalanga). Simultaneously, a questionnaire to assess contacts between wildlife and cattle was implemented among cattle owners in the same locations. The fecal samples were then microscopically analysed using Ziehl Neelsen staining (ZN) and an Immunofluorescence (IF) kit test. Preliminary results of the ZN staining in wildlife samples, showed that the parasite was present in 7.7%of the samples. The highest prevalence was found in Elephants (18.8%), followed by Buffalo (3.3%) and Impala (2.2%). The results of the questionnaire highlighted the regular presence of wild animals on the communal farmland outside the KNP; Buffalo is frequently seen, followed by Elephants and Impala. At this stage of the study, the presence of Cryptosporidium in the wildlife population has been detected and therefore we can conclude that a potential transmission of this parasite to the bordering communities and their livestock is plausible. The Mpumalanga province has the highest prevalence of HIV in South Africa (23%) and the communities of our study area are regularly exposed to wild animals; therefore it is essential to address the importance of Cryptosporidium infection in this wildlife-livestock and human interface area. (Texte intégral

Assessing financial and flexibility incentives for integrating wind energy in the grid via agent-based modeling

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped to quantify the effect of feed-in tariffs and installed capacity of wind power on the consumption from renewable energy and market prices. The consumption from renewable sources, expressed as percentage of total system consumption, increased by 8.17% for every 10% increase in installed capacity of wind power. The sharpest increase in renewable energy consumption is observed when a feed-in tariff of 0.04 €/kWh is provided to the wind farm owners, resulting in an average increase of 9.1% and 5.1% in the consumption from renewable sources while the maximum installed capacity of wind power is 35% and 100%, respectively. The regression model for the annualized DAM prices showed an increase by 0.01 €cents/kWh in the DAM prices for every 10% increase in the installed wind power capacity. With every increase of 0.01 €/kWh in the value of feed-in tariffs, the mean DAM price is lowered as compared to the previous value of the feed-in tariff. DAM prices only decrease with increasing installed wind capacity when a feed-in tariff of 0.04 €/kWh is provided. This is observed because all wind power being traded on DAM at a very cheap price. Hence, no volume of electricity is being stored for availability on IM. The regression models for predicting IM prices show that, with every 10% increase in installed capacity of wind power, the annualized IM price decreases by 0.031 and 0.34 €cents/kWh, when installed capacity of wind power is between 0 and 25%, and between 25 and 100%, respectively. The models also showed that, until the maximum installed capacity of wind power is less than 25%, the IM prices increase when the value of feed-in tariff is 0.01 and 0.04 €/kWh, but decrease for a feed-in tariff of 0.02 and 0.03 €/kWh. When installed capacity of wind power is between 25 and 100%, increasing feed-in tariffs to the value of 0.03 €/kWh result in lowering the mean IM price. However, at 0.04 €/kWh, the mean IM price is higher, showing the effect of no storage reserves being available on IM and more expensive reserves being engaged on the IM. The study concludes that the effect of increasing installed capacity of wind power is more significant on increasing consumption of renewable energy and decreasing the DAM and IM prices than the effect of feed-in tariffs. However, the effect of increasing values of both factors on the profit of RES-E producers with storage facilities is not positive, pointing to the need for customized rules and incentives to encourage their market participation and investment in storage facilities