Electronics and Instrumentation Engineering

This paper proposes a fully automated angular measurement method for various applications using hit or miss morphology technique. The morphological transformation is analyzed for the recognition of pattern and the hit-or-miss transform indicates the positions where a certain pattern occurs in the image. The extracted position in the image is mapped into a line graph for angular measurement. The efficiency of the proposed technique is justified by applying it in various applications such as instrument panel board interfacing, angular speed measurement and angular orientation of a robotic arm. From the results, it is evident that the proposed system provides a better performance and cost effectiveness.

This paper suggests an idea to design an adaptive PID controller for Non-linear liquid tank System and is implemented in PLC. Online estimation of linear parameters (Time constant and Gain) brings an exact model of the process to take perfect control action. Based on these estimated values, the controller parameters will be well tuned by internal model control. Internal model control is an unremarkably used technique and provides well tuned controller in order to have a good controlling process. PLC with its ability to have both continues control for PID Control and digital control for fault diagnosis which ascertains faults in the system and provides alerts about the status of the entire process.

This paper deals with design of various controllers such as Proportional Integral Derivative (PID) controller, Internal Model Controller(IMC) and transfer function controller by using Genetic Algorithm(GA) for a non-linear liquid conical tank system. Level control of a conical tank is a complex issue because of the nonlinear nature of the tank. For each stable operating point, a First Order Process with Time Delay model was identified using process reaction curve method. The need for improved performance of the process has led to the development of the optimal controllers. GA is an evolutionary algorithm that is proposed in this aspect. The performance of GA based controllers is compared with conventional controllers tuned using Ziegler Nicholas (Z-N) closed loop method and Z-N open loop method. The comparison is done based on rise time, settling time, overshoot and Integral Time Absolute Error(ITAE) and it was found that the GA based IMC controller is better suited for this process.

Level measurement was a vital parameter in process industries and it demands the need for cheap and non-contact measurement which was addressed in this paper. A fully automated computer based system of non-contact level measurement using image processing technique was proposed. The design consists of float allowed move freely in the vertical column when the liquid level changes. The image of the float is acquired and processed to extract its dimension and the extracted dimension is calibrated in terms of actual level. Various dimensions such as image pixel count, float area, side of a square float and radius of a circular float was considers for level measurement and their characteristics are analyzed. Finally, a GUI was developed to monitor and calibrated the instrument remotely.

This paper proposes a novel approach to estimate the true position of Planar cable driven robot using Kalman filter. Cable driven robot is designed which consists of multiple cables attached to the end effector. Since such robots have larger workspace, we cannot have a wide range of sensor to measure the position of the robot. So Computer Vision is employed for measurement which is basically subjected to noise. Finally, Kalman filter eliminates noise and estimate the true position which was justified by a minimal error covariance.

Material handling and Object classification systems are employed in many industries to increase the productivity and quality of the product they manufacture. Robotic arms are employed in order to increase the efficiency and to operate on hazardous conditions. The aim of the proposed work is to design and implement path planning algorithm for a robotic arm in real time. The efficiency and speed of operation of the robotic arm depends on the selection of optimal path for the arm to navigate in its work space. This demands a need for path planning algorithms for robotic arm in order to find a collision-free shortest route, avoiding obstacles and reaching the target place. The visual feedback system extracts multiple features such as information about the current position of the robotic arm as well as the obstacles present in the environment also. A Graphical User Interface (GUI) was also developed to interact and monitor the robotic arm. It also provides a platform to test various path planning algorithms Index Term-visual feedback, path planning, GUI

In this paper a robust modelling method of a interacting pressure tank process with structured parametric perturbations has been used which results in a model in Linear Fractional Transformation (LFT) form. The LFT form of the system can be generated from the model of the system, Based on these modelling paradigms robust stability and performance tests have been applied for three types of control namely the H-inf control, H-inf loop shaping and ,.-synthesis.

This paper proposes the simulation of photovoltaic (PV) cell operated in various conditions. A DC-DC Buck converter is used to produce the simulated voltage from a high input voltage. The mathematical model of photovoltaic (PV) cell is modelled and some of the parameters are refer to data sheet to make it accurate. The users have to enter the ambient temperature (Ta) and irradiance (G) to simulate the PV voltage. Here the fuzzy logic controller is designed as a feedback compensator for fast response and error reduction. Finally, the proposed model with fuzzy controller was implemented in MATLAB and its performance compared with a PID Controller shows a significant improvement.

In this paper we propose a method to count the cement bags moving on a conveyer belt using a video feed from a still camera. This paper is done overcome the drawbacks of the already existing technology using proximity sensor or known as bag counter. We are using the optical flow estimation technique to count the bags.

The human auditory system is divided into three main parts: outer, middle and inner auditory system. The auditory system is mainly responsible for hearing and balance. The Cochlea, which is present in the inner auditory system, consists of Basilar Membrane, Organ of Corti, OHC and IHC together execute the hearing mechanism. Otoacoustic Emissions are inaudible sounds which come out from the inner auditory system. These are produced due to Cochlear amplification wherein OHCs play an important role by providing electro-mechanical positive feedback. OAEs are mainly used for diagnosis of hearing sensitivity in new-born babies and adults. They are not produced for persons having hearing disabilities more than 25 -30 dB. The OAEs are classified into Spontaneous and Evoked types. The main objective of this project is to generate Transient-Evoked and Sustained-Frequency OAEs by simulating a human inner auditory system model. The basic underlying principle of modeling the human inner auditory system used in this project is Hydrodyamics. Hydrodynamics is the study of motion of incompressible and compressible fluids. The incompressible fluids present inside the cochlea, Endolymph and Perilymph, are responsible for the movement of the BM.. Keyword-OHC,IHC,Baislar Membrane,OAE,Hydrodynamic model V.S. Balaji et.al / International Journal of Engineering and Technology (IJET)

This paper proposes an idea for designing a continuously tuned adaptive PI controller for a non-linear process such as conical tank. In this paper, a simple tuning system is used to continuously tune the controller parameters in correspondence with the change in operating points. For each stable operating point, a FOPTD model was identified using process reaction curve method. The estimated model parameters are used to calculate the controller parameters for each operating points. Based on these calculated controller parameters and its operating points, a tuning system was created. The tuning system will able to interpolate and extrapolate the relation between control variable and the controller parameters over entire span of control variables. Finally, a detailed time-domain modeling of the conical tank was performed. Then the adaptive PI controller was implemented in Matlab and was simulated to verify its performance. Thus the adaptive controller was able to produce a consistent response regardless of parametric variations with minimum overshoots and minimum settling time.

Temperature of fluid stream through tube is a key variable in shell and tube heat exchanger. However, this variable is not easy to measure straightly. Therefore, a state observer is designed to estimate the tube temperature variable for direct control of shell and tube heat exchanger. A dynamical state space model is used to describe the heat exchanger process. Kalman filter based observer is designed to generate the estimates of states for desirable control system. Kalman filter given the good performance in trimming the noise in the process and congregating to the actual states from improper initial states. A SFC (State Feedback Controller) is designed to control the temperature of fluid stream flowing out through the heat exchanger. A PID (Proportional Integral and Derivative) controller is also designed for temperature control. The simulations of state feedback and PID controller are performed using MATLAB. Obtained transient results are compared and an analysis is conducted.

In process industries there is lot of uncertainties in the process especially in nonlinear process. This paper deals with the ANFIS controller which is designed for Quadruple tank. Though Neural Network captures the nonlinearity, it has drawback of not to know that how to take decisions with respect to the change in manipulated Variable. To overcome those errors Fuzzy Logic controller is implemented where membership functions of the fuzzy logic control has been classified by Neural Network Functions. To provide stringent control action, ANFIS controller has been implemented for quadruple tank.

Infrared (IR) radiation is emitted by all objects above zero Kelvin. Since humans are warm blooded they emit infrared radiation. Oxygen saturation is an indicator of disease in humans, based on this oxygen level infrared radiation varies. When oxygen to a body region increases the metabolism in that region is increased which leads to an increase in temperature along that region, due to this increased temperature profile infrared radiation in that region gets increased. Similarly decrease of oxygen to a region leads to reduced metabolism which gives a decrease in temperature profile and infrared radiation. So finding out the intensity variation in the image will leads to the oxygen variation in human body. In this paper an analysis is made by providing an user defined threshold values to the pixels in an image to represent the regions related to its intensity, three threshold values of 0.5, 0.75, 0.9 are used to classify less oxygenated regions in the arthritis patient and higher oxygenated regions in hypothyroidism patient. This allows finding out the disease severity and the regions with similar condition in the given infrared image taken from the patient. Diagnosis and prognosis is done from the infrared images by processing the images.

1 Abstract—Wheel slip compensation is vital for building accurate and reliable dead reckoning based robot localization and mapping algorithms. This investigation presents stochastic slip compensation scheme for robot localization and mapping. Main idea of the slip compensation technique is to use wheel-slip data obtained from experiments to model the variations in slip velocity as Gaussian distributions. This leads to a family of models that are switched depending on the input command. To obtain the wheel-slip measurements, experiments are conducted on a wheeled mobile robot and the measurements thus obtained are used to build the Gaussian models. Then the localization and mapping algorithm is tested on an experimental terrain and a new metric called the map spread factor is used to evaluate the ability of the slip compensation technique. Our results clearly indicate that the proposed methodology improves the accuracy by 72.55% for rotation and 66.67% for translation motion as against an uncompensated mapping system. The proposed compensation technique eliminates the need for extro receptive sensors for slip compensation, complex feature extraction and association algorithms. As a result, we obtain a simple slip compensation scheme for localization and mapping.

1 Abstract—Sensor fusion based localization techniques often need accurate estimate of the fast and uncertain scene change in environment. To determine the scene change from two consecutive LIDAR scans, this paper proposes a novel technique called 'keep zero as zero' polar correlation. As it name implies any zero in the scan data is kept isolated from scene change estimation as it do not carry any information about scene change. Unlike existing techniques, the proposed methodology employs minimization of selective horizontal and vertically shifted sum of difference between the scans to estimate scene change in terms of rotation and translation. Minimization of the proposed correlation function across the specified search space can guarantee an accurate estimate of scene change without any ambiguity. The performance of the proposed method is tested experimentally on a mobile robot in two modes depending on the scene change. In the first mode, scene change is detected using dynamic LIDAR, whereas static LIDAR is used in the second mode. The proposed methodology is found to be more robust to environmental uncertainties with a reliable level of localization accuracy.

Robustness of the controller is vital in many process industries. The robust controller will not only compensate for disturbance but also for the parametric variation in the process itself. This paper proposes the design of such a robust propositional-integral (PI) controller for a non-linear level control process, like hemi-spherical tank system, using volumetric observer. In a level control system, the volume has a linear relation to the differences in inflow and outflow, whereas the rate change in height is non-linearly related to the flow difference. The robustness of the proposed controller was enhanced by using volume error instead of level error. The volume error is derived by using a volumetric observer, which observes the tank volume and a volume estimator, which estimate the desired tank volume. This enables a linear controller like PI controller to be more robust over the entire span of tank height. The robustness of the proposed controller was compared with the conventional controller and its performance is validated by using the averaged performance indices like averaged-ISE, ITAE and IAE. Simulation results illustrates that the proposed controller has faster response and lesser oscillations.

Most senior citizens are often neglected and are helpless in times of medical emergencies, as they are alone in their twilight years. To tackle this, we have come up with a prospective Remote Health Monitoring and Alert System (RHMAS). In elderly people heart attacks are associated with symptoms like, body temperature fluctuations, high BP, profuse sweating, improper cardiac rhythm etc. Our solution is to integrate robust sensors capable of sensing and monitoring these symptoms with a microcontroller to alert the next of kin and health services during emergencies. Since most devices for this purpose are wired, a wireless device wouldn't interfere with the movement of the user The proposed system consists of a Photo-Plethysmography (PPG) based pulse sensor, to detect arrhythmia, a temperature sensor to constantly monitor their body temperature and a sweat sensor to monitor the Galvanic Skin Response (GSR). A GSM module will send an alert to the next of kin if the monitored data deviates from the nominal body condition. If the monitored data reaches emergency levels, health services would also be alerted.

Industrial control system (ICS) encompasses the several types of the control systems which is placed in the various applications like industrial production, distributed control systems, small control configuration system and so on. The ICS developing process the model predictive controller (MPC) is utilized because of the easy concepts and controller tuning package. At the time of ICS implementation process, it consists of computing power problem which leads to reduce the entire ICS power. To reduce the problem present in the MPC, it has been optimized by utilizing MPC and the quadratic problem is overcome by applying the several quadric methods such as, sequential quadratic programming, barrier function and iterative interior point quadratic optimization are used. From the optimized controller system, the pilot scale distillation control system is developed and the performance of the proposed system is developed using state space model which is analyzed in terms of the error metrics and mean cost metrics. Keywords Industrial control system · Model predictive controller · Sequential quadratic programming · Barrier function · Iterative interior point (IIP) · Quadratic optimization methods

Hydrophobicity of polymeric insulator plays a vital role in determining the insulation quality in outdoor overhead electrical transmission and distribution lines. Loss of hydrophobicity increases the leakage current and leads to flashover. Monitoring hydrophobicity becomes a fundamental requirement to ensure continuity of power line operations. Hydrophobicity of polymeric insulator is classified according to STRI (Swedish Transmission Research Institute) guidelines. This paper proposes an intelligent ANFIS (Adaptive Neuro-Fuzzy Inference System) based classifier to determine the hydrophobicity quality using the digital image of the insulator. Ten statistical features are extracted from the digital images. Two stages of feature reduction are employed to reduce the number of features. Pre-design stage uses PCA (Principal Component Analysis) and reduces the number of features to six from ten and the post-design stage analyzes the accumulation effect to reduce the number of features to four. Various ANFIS classifiers are trained using these reduced features extracted from the image. The performance of these ANFIS classifiers is evaluated in both field and laboratory specimens. Results indicate classification accuracy of 96.4% and 93.3% during the training and testing phase when triangular membership function with linear output function is employed in ANFIS. A GUI (Graphical User Interface) has also been designed to facilitate the use of the proposed system by field operators.