Quantitative infrared thermography resolved leakage current problem in cathodic protection system

Leakage current problem can happen in Cathodic Protection (CP) system installation. It could affect the performance of underground facilities such as piping, building structure, and earthing system. Worse can happen is rapid corrosion where disturbance to plant operation plus expensive maintenance cost. Occasionally, if it seems, tracing its root cause could be tedious. The traditional method called line current measurement is still valid effective. It involves isolating one by one of the affected underground structures. The recent methods are Close Interval Potential Survey and Pipeline Current Mapper were better and faster. On top of the mentioned method, there is a need to enhance further by synthesizing with the latest visual methods. Therefore, this paper describes research works on Infrared Thermography Quantitative (IRTQ) method as resolution of leakage current problem in CP system. The scope of study merely focuses on tracing the root cause of leakage current occurring at the CP system lube base oil plant. The results of experiment adherence to the hypothesis drawn. Consequently, res

Single phase inverter system using proportional resonant current control

This paper presents the harmonic reduction performance of proportional resonant (PR) current controller in single phase inverter system connected to nonlinear load. In the study, proportional resonant current controller and low pass filter is discussed to eliminate low order harmonics injection in single phase inverter system. The potential of nonlinear load in producing harmonics is showed and identified by developing a nonlinear load model using a full bridge rectifier circuit. The modelling and simulation is done in MATLAB Simulink while harmonic spectrum results are obtained using Fast Fourier Transfor. End result show PR current controller capability to overcome the injection of current harmonic problems thus improved the overall total harmonic distortion (THD)

Multivariate Statistical Process Control Charts: An Overview

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.quality control, process control, multivariate statistical process control, Hotelling's T-square, CUSUM, EWMA, PCA, PLS

Method of lines and runge-kutta method in solving partial differential equation for heat equation

Solving the differential equation for Newton’s cooling law mostly consists of several fragments formed during a long time to solve the equation. However, the stiff type problems seem cannot be solved efficiently via some of these methods. This research will try to overcome such problems and compare results from two classes of numerical methods for heat equation problems. The heat or diffusion equation, an example of parabolic equations, is classified into Partial Differential Equations. Two classes of numerical methods which are Method of Lines and Runge-Kutta will be performed and discussed. The development, analysis and implementation have been made using the Matlab language, which the graphs exhibited to highlight the accuracy and efficiency of the numerical methods. From the solution of the equations, it showed that better accuracy is achieved through the new combined method by Method of Lines and Runge-Kutta method

The blockage ratio effect to the spray performances

Nozzle sprays are used in wide range of application. The used of nozzle application is depend on the spray characteristics, by which to suit the particular application. This project studies the effect of the air blockage ratio to the spray characteristics. This research conducted into two part which are experimental and simulation section. The experimental was conducted by using particle image velocimetry (PIV) method, and ANSYS software was used as tools for simulation section. There are two nozzles were tested at 1 bar pressure of water and air. Nozzle A (with blockage ratio 0.316) and nozzle B (blockage ratio 1.000). Both of the sprays performances generated by the nozzles was examined at 9 cm vertical line from 8 cm of the nozzle orifice. The validation result provided in the detailed analysis shows that the trend of graph velocity versus distance gives the good agreement within simulation and experiment. From result, nozzle A generated a wider spray angle and higher water droplet velocity which are 31.41 degree and 37.317 m/s compared to nozzle B which has produced 27.13 degree of spray penetration angle and 16.49 m/s water droplet velocity. As a conclusion, blockage ratio has affected the spray system by increasing the velocity of air inside the spray system. This is happened at a condition of 1 bar air pressure

Life jacket

Anyone who cannot swim well should wear life jacket whether they are in the water or around the water. Even those who are can swim well should wear the life jacket when they are doing activity such as swimming, fishing, boating or while doing any water-related activity. Life jacket is a kind of safety jacket that keeping the wearer float the in the water. The wearer may be in the conscious or unconscious condition but by wearing the life jacket we can minimize the risk of drowning because life jacket assist the wearer to keep floating in the water

Anomaly Detection in Multivariate Non-stationary Time Series for Automatic DBMS Diagnosis

Anomaly detection in database management systems (DBMSs) is difficult because of increasing number of statistics (stat) and event metrics in big data system. In this paper, I propose an automatic DBMS diagnosis system that detects anomaly periods with abnormal DB stat metrics and finds causal events in the periods. Reconstruction error from deep autoencoder and statistical process control approach are applied to detect time period with anomalies. Related events are found using time series similarity measures between events and abnormal stat metrics. After training deep autoencoder with DBMS metric data, efficacy of anomaly detection is investigated from other DBMSs containing anomalies. Experiment results show effectiveness of proposed model, especially, batch temporal normalization layer. Proposed model is used for publishing automatic DBMS diagnosis reports in order to determine DBMS configuration and SQL tuning.Comment: 8 page

Performance Analysis of ANN on Dataset Allocations for Pattern Recognition of Bivariate Process

Several approaches to identifying the out-of-control variables after the detection of abnormal pattern has been most intensively studied and used in practice. One of the several approaches is the Artificial Neural Network (ANN) based model for diagnosis of out-of-control signal of multivariate process mean shift. In spite of the number of years of research in neural network, limited research (if any) have been done on the effect of dataset allocations in percentages for training and testing on the performance of ANN. In this paper, we investigate the use of different percentages of dataset allocation into training, validation and testing on the performance of ANN in pattern recognition of bivariate process using six selected training algorithms. The result of study showed that large allocation of dataset for training was found suitable, having higher recognition accuracy for ANN learning and perform better for pattern recognition of bivariate process. Keywords: Bivariate Process; Pattern Recognition; Recognition accuracy; Multivariate quality control charts, training algorith