scholarly journals Analysis of fault diagnosis of DC motors by power consumption pattern recognition

2021 ◽  
Vol 5 (5 (113)) ◽  
pp. 14-20
Author(s):  
Hasan Shakir Majdi ◽  
Sameera Sadey Shijer ◽  
Abduljabbar Owaid Hanfesh ◽  
Laith Jaafer Habeeb ◽  
Ahmad H. Sabry
Keyword(s):  
Power Consumption ◽  
Profile Analysis ◽  
Control Circuit ◽  
Gear Train ◽  
Consumption Pattern ◽  
Motor Power ◽  
Dc Motors ◽  
Soft Computing Techniques ◽  
Power Pattern ◽  
The Mean

Early detection of faults in DC motors extends their life and lowers their power usage. There are a variety of traditional and soft computing techniques for detecting faults in DC motors. Many diagnostic techniques have been developed in the past to detect such fault-related patterns. These methods for detecting the aforementioned potential failures of motors can be utilized in a variety of scientific and technological domains. Motor Power Pattern Analysis (MPPA) is a technology that analyzes the current and voltage provided to an electric motor using particular patterns and protocols to assess the operational status of the motors without disrupting production. Engineers and researchers, particularly in industries, face a difficult challenge in monitoring spinning types of equipment. In this work, we are going to explain how to use the motor power pattern/signature analysis (MPPA) of a power signal driving a servo to find mechanical defects in a gear train. A hardware setup is used to simplify the demonstration of obtaining spectral metrics from the power consumption signals. A DC motor, a set of metal or nylon drive gears, and a control circuit are employed. The speed control circuit was eliminated to allow direct monitoring of the DC motor's current profiles. Infrared (IR) photo-interrupters with a 35 mm diameter, eight-holed, standard servo wheel were employed to gather the tachometer signal at the servo's output. The mean value of the measurements was 318 V for the healthy profile, while it was 330 V for the faulty gears power data. The proposed power consumption profile analysis approach succeeds to recognize the mechanical faults in the gear-box of a DC servomotor via examining the mean level of the power consumption pattern as well as the extraction of the Power Spectral Density (PSD) through comparing faulty and healthy profiles

scholarly journals Lipid profile in patients with alcohol dependence syndrome

2015 ◽  
Vol 1 (1) ◽  
pp. 29-32
Author(s):  
Mithileshwer Raut ◽  
Prashant Regmi ◽  
Saroj Prasad Ojha ◽  
Bharat Jha
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Lipid Metabolism ◽  
Alcohol Use ◽  
Alcohol Dependence ◽  
Lipid Profile ◽  
Consumption Pattern ◽  
Cholesterol Levels ◽  
Alcohol Dependence Syndrome ◽  
The Mean

BACKGROUND: Alcohol dependence syndrome (ADS) has become a global public health challenge because of its high prevalence and the concomitant increase in risk of liver disease, cardiovascular disease and premature death. Influence of alcohol use on lipid metabolism is well recognized. Investigations had been carried out in the earlier period on abnormal lipid profile as a risk factor for Coronary Heart disease (CHD). Patients of alcohol dependence usually have a consumption pattern of more heavy use. Therefore it is useful to study the lipid profile in patients of alcohol dependence, to understand the effects of increasing levels of consumption. METHODS: This cross-sectional study was conducted in TU Teaching Hospital. ADS patients were screened by the consultant psychiatrist using the Alcohol Use Disorder Identification Test (AUDIT) questionnaire. A total of 89 patients scored positive on the AUDIT as having alcohol-related problems and were included in the study. 89 ADS patients and 89 healthy controls both male and female were enrolled as participants. Blood Pressure and other anthropometric parameters were measured while fasting blood samples were analyzed for serum lipid profile. SPSS program was used to analyze data, t-test & Spearman's correlation coefficient was used to find correlation. RESULTS: Among the ADS cases 95% were current smokers. Mean age of cases and controls was 35.42±5.6 & 34.53±3.5 years respectively. The mean total cholesterol levels were found to be higher in cases (5.41±0.70) than controls (3.79±0.74) with a strong statistical significance (p<0.001). Also, Mean triglyceride (TG) levels (2.09±0.72), along with the mean HDL-cholesterol (1.66±0.40) and LDL-cholesterol levels (2.79±0.81) were also elevated in cases when compared to the control samples (p<0.001). CONCLUSION: This study has demonstrated definitive lipid profile changes in patients of alcohol dependence, with some correlation to the liver dysfunction. Alcohol causes alteration in various parameters of lipid metabolism including those which predispose to CHD. Low to moderate alcohol use over prolonged periods has been linked to have protective influence for development of coronary heart disease (CHD), through increase in high density lipoprotein cholesterol (HDL-C) levels. DOI: http://dx.doi.org/10.3126/acclm.v1i1.12312 Ann. Clin. Chem. & Lab. Med. 1(1) 2015: 29-32

scholarly journals Genetic Algorithms for Localization in WSN

2020 ◽  
Vol 9 (5) ◽  
pp. 2397-2401
Keyword(s):  
Wireless Sensor Networks ◽  
Genetic Algorithms ◽  
Bat Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Node Localization ◽  
Soft Computing Techniques ◽  
Anchor Nodes ◽  
The Mean

In wireless sensor networks, localization is a way to track the exact location of sensor nodes. Occasionally node localization may not be accurate due to the absence or limitation of anchor nodes. To reduce the mean localization error, soft computing techniques such as BAT and bacterial foraging driven bat algorithm (BDBA) are utilized in literature. For better localization with reduced error, in this paper, firefly driven bat algorithm (FDBA) is proposed, which combines the heuristic of firefly and BAT algorithms. Our proposed FDBA algorithm provides better localization in terms of error of 60% and 40 % less error as compared to BAT and BDBA algorithm, respectively.

A Demand Based Optimum Solar Panel Orientation

2010 ◽  
Author(s):  
Mohammad H. Naraghi
Keyword(s):  
New York ◽  
New York City ◽  
Power Consumption ◽  
York City ◽  
Energy Demand ◽  
Solar Panel ◽  
Consumption Pattern ◽  
Tilted Surface ◽  
Typical Summer ◽  
Building Cooling

The clear sky and monthly clearness index models are used to evaluate the hourly and monthly insolation on unit area of a tilted surface for the entire year. The hourly power consumption of a typical municipality (for this case New York City) for typical summer and winter days are used to determine the tilt and azimuth angles of a solar panel such that the solar energy reached the panel best match the energy consumption pattern. For the example case considered, in this work New York City, the electric power consumption peaks during summers at afternoon hours, due to increase in building cooling loads. It is found that orienting the solar panel at a westward azimuth angle with a tilt angle that results in maximum annual insolation is the best orientation of the solar panel for responding to both the peak energy demand and having reasonably high overall annual power generation. Although the model is used to optimize the solar panel orientation for New York City, it can however, be used for any building at any location as long as the needed solar data and power consumption pattern are known.

Exposure Assessment of Artificial Sweeteners among Type 2 Diabetic, Overweight and Obese Individuals

2016 ◽  
Vol 53 (3) ◽  
pp. 268
Author(s):  
A. Bhagyasri ◽  
R. Naveen Kumar ◽  
N. Balakrishna ◽  
V. Sudershan Rao
Keyword(s):  
Exposure Assessment ◽  
Daily Intake ◽  
Cross Sectional Study ◽  
Consumption Pattern ◽  
Cross Sectional ◽  
Significant Difference ◽  
Overweight Group ◽  
The Mean ◽  
Type 2 Diabetic

In recent years consumption of artificially sweetened foods and beverages became popular in India, with the regulatory formulations to use them in selected foods; their inclusion especially in sweets, biscuits and beverages has increased. There are many concerns rising regarding their safety and is becoming an area of controversy. So an exposure assessment has been carried out to evaluate intake levels among type II diabetic, overweight and obese individuals. A cross-sectional study design was applied and a food frequency questionnaire was used to obtain the information on consumption pattern. Range, standard deviation and mean daily intake levels were calculated and the values were compared with an appropriate Acceptable Daily Intake (ADI). Results indicated that, the mean daily intake levels of aspartame (0.85±0.75) were found to be high among type 2 diabetic individuals whereas sucralose (0.41±0.41) and acesulfame-k (0.07±0.02) were high among overweight group. There was a significant difference (p&lt;0.0001) observed in intake levels among both groups and all the sweeteners were found to be well within the ADI levels.

Soft Methods for Automatic Drug Infusion in Medical Care Environment

2015 ◽  
pp. 1384-1408
Author(s):  
Filipe Quinaz ◽  
Paulo Fazendeiro ◽  
Miguel Castelo-Branco ◽  
Pedro Araújo
Keyword(s):  
Medical Care ◽  
Modern Medicine ◽  
Future Research ◽  
Drug Infusion ◽  
Care Environment ◽  
Soft Computing Techniques ◽  
Infusion Systems ◽  
Future Research Directions ◽  
The Mean ◽  
Drug Infusion Systems

The automatic drug infusion in medical care environment remains an elusive goal due to the inherent specificities of the biological systems under control and to subtle shortcomings of the current models. The central aim of this chapter is to present an overview of soft computing techniques and systems that can be used to ameliorate those problems. The applications of control systems in modern medicine are discussed along with several enabling methodologies. The advantages and limitations of automatic drug infusion systems are analyzed. In order to comprehend the evolution of these systems and identify recent advances and research trends, a survey on the hypertension control problem is provided. For illustration, a state-of-the-art automatic drug infusion controller of Sodium Nitroprusside for the mean arterial pressure is described in detail. The chapter ends with final remarks on future research directions towards a fully automated drug infusion system.

scholarly journals Efficient Planning of Electrical Distribution System for Consumers in Sarawak, Malaysia

2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Ibrahim S.H. ◽  
Baharun A. ◽  
Nawi M.N.M ◽  
Chai C.J.
Keyword(s):  
Power Consumption ◽  
Distribution System ◽  
Load Distribution ◽  
Consumption Pattern ◽  
Load Factor ◽  
Cluster Sampling ◽  
Distribution Transformer ◽  
Consumption Data ◽  
Efficient Planning ◽  
Load Characteristics

This study presents a method to determine power consumption pattern for several types of consumers in Sarawak, Malaysia. The power consumption data for consumers has been recorded using EDMI Mk.6 Genius polyphase electronic (E3) meters installed at their premises. The multistage cluster sampling is used to design the sample size to determine the sufficient amount of meters required. The data obtained from the meters has been analysed to obtain the pattern of power consumption for different types of consumers. This power consumption pattern has been applied to determine load factor, diversity factor for the calculation of After Diversity Maximum Demand (ADMD). ADMD is also used to determine the optimal amount of load, distribution transformer size and 11kV cable size. Temperature sensitivity analysis related to the demand has been investigated as well. It is found that power consumption pattern model is beneficial in finding the total electrical load, distribution transformer size and 11kV cable size needed by the consumers. Thus through this study the load characteristics had been determined to support utility operation and planning efficiently.

scholarly journals Application of Predictive Control in Scheduling of Domestic Appliances

2020 ◽  
Vol 10 (5) ◽  
pp. 1627 ◽  
Author(s):  
Himanshu Nagpal ◽  
Andrea Staino ◽  
Biswajit Basu
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Predictive Control ◽  
Peak Power ◽  
Mixed Integer ◽  
Consumption Pattern ◽  
Problem Model ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Peak Power Consumption

In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.

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