Vijanth Sagayan Asirvadam

A method for computation of surface roughness of digital elevation model terrains via multiscale analysis

In this paper, an algorithm to compute surface roughness of digital elevation model (DEM) terrains via multiscale analysis is proposed. The algorithm employs the lifting scheme to generate multiscale DEMs. At each scale, the areas of pixels that are modified are computed. Granulometric analysis is employed to compute the average area of curvature regions in the terrain, and the average roughness of the terrain due the distribution of curvature regions. The selected case studies of the algorithm implementation demonstrated that the proposed algorithm provides a surface roughness parameter that is realistic with respect to the amplitudes and frequencies of the terrain, invariant with respect to rotation and translation, and has intuitive meaning. The algorithm allows for a good quantification of a regions convexity/concavity over varying scales, distinguishing between shallow and deep incisions of valleys and ridges of the terrain, and hence, provides an accurate surface roughness parameter.

Adopting EWMA Filter on a Fast Sampling Wired Link Contention in WirelessHART Control System

The performance of a wireless industrial process plant is affected by wired and wireless links reliability. While recent related works focus mainly on wireless links reliability, this paper focuses on wired links reliability between the controller and the wireless highway addressable remote transducer (WirelessHART) node. In control application for a process plant with fast sampling, when the wired link delay is too short, message transmissions to the node could occur concurrently resulting in packet collision and packet dropout, thus leading to local contention. This can cause process plant with critical control application to be unstable. Therefore, this paper proposes an effective design of exponentially weighted moving average filter to mitigate the contentions effect and improve the process plants performance. In order to make evident and validate the existence of local contention, an experiment is carried out using a WirelessHART device. From the experiment, the controller delay is 0.1475 s and the estimated packet dropout is 12.29%. Simulation results with the designed filter show a significant improvement in process performance in terms of percentage of overshoot compared with performance of the process plant using traditionally optimized PID controller.

Simulation of WirelessHART networked control system with packet dropout

Industrial communication standard like WirelessHART enables wireless control in process plants. This paper presents a study on wired and wireless networked control system. It emphasizes on using packet dropout array for Markov chain simulation of packet dropout process, a key parameter affecting plants performance, in a closed-loop WirelessHART networked control system. Additionally, Bernoulli simulation of the process is covered for comparison purpose. Overshoot was found to be 633.3 % for Bernoulli model, 33.9 % for Markov model and even through it is the major drawback of the system, WirelessHART networked control system is still suitable for control applications when non-time-critical plant has response time longer than sampling period thousands times even with 50 %, 40 % dropout probabilities for Bernoulli, Markov models.

Condition monitoring of induction motors via instantaneous power analysis

Condition monitoring is an important factor in assuring the well-being of motors. Existing approaches of condition monitoring require access to the motor for sensor installation. This paper reviews various forms of existing condition monitoring methods and highlights the need for an economical intelligent fault diagnosis system. In this study, the methodology taken in developing a condition monitoring system for motor bearing fault identification, utilizing the commonly available motor stator current and voltage is demonstrated. This unique diagnostic condition monitoring system provides continuous real time tracking of the various bearing defects and determines the fault severity which can be adopted for fast decision making. The study on different bearing faults under no-load and full-load conditions was carried out experimentally and then analyzed. The results on the real hardware implementation have confirmed the effectiveness of the proposed approach.

Setpoint weighted wirelesshart networked control of process plant

The use of conventional PID controllers has proven to be inadequate in delayed and uncertain networks such as WirelessHART network. This is because the PIDs produce oscillatory and unstable response when large gains are used. Furthermore, the response become sluggish when very small gains are used. Because of complexity, the use of deadtime compensators and other model based controllers in the industries is also difficult. In this work, the application of setpoint weighting control strategy for WirelessHART environment is presented. The method permits the use of high stable gain and provides for good load disturbance regulation. Comparison of the performance of the proposed method to both PID and Smith predictor structures showed that it is better in terms of response speed and overshoot. It is also robust to load disturbance. Hence it provides a two degree of freedom control.

Pressure point analysis for early detection system

Pressure point analysis detection method is based upon the statistical properties of a series of pressure or velocity pipeline measurements at one point being different before and after a leak occurs. Usually the data is collected from various types of sensors over certain period of time and analysis is carried. However, this method required a lot of time for the researcher in order to collect and sampling the data. This paper presents a mathematical derivation for calculating the pressure before the leak as well as the pressure at the point of leakage. The pressure at the leakage point has a strong relationship with the mass flow rate of the substance, hence the derivation for the accidental leakage is also presented in this paper. The results show that, it is possible that the result from the simulation works can be used as the input for the pressure point analysis method. By doing this, a lot of time can be saved for collecting and sampling the data for the reason of leak detection system and more time can be used to improve the system itself.

Analysis of Bearing Surface Roughness Defects in Induction Motors

In this paper, a Park’s transformation method for the analysis of various bearing surface roughness defects is presented. The existing instantaneous power analysis and stator current analysis techniques are unable to diagnose bearing surface roughness defects, due to the fact that characteristics defect frequency model is not available for these types of defects. Thus, this paper proposes a Park’s transformation method which can detect surface roughness defects without requiring information of the characteristic defect frequencies. The theoretical and experimental work conducted shows that the proposed method can detect bearing outer and inner race surface roughness faults without use of any extra hardware. The results on the real hardware implementation confirm the effectiveness of the proposed approach.

Development of private cloud storage for medical image research data

Medical imaging research deals with large, heterogeneous and fragmented amounts of medical images. Such challenges lead to the need for secure, federated and functional medical image storage within this research community. With limited IT professional and research fund, the community is better provided with an outsourcing arrangement. Cloud computing promises lower cost, high scalability and availability which can be a natural solution such problems in long-term medical image archive. This paper presents a private cloud storage design and prototype development within an organization to solve such issues. Leveraging on the ability of cloud computing is shown meet to the system requirements. The prototype is implemented on OwnCloud cloud storage framework. The complete functionality of OwnCloud made it an ideal platform to develop and deploy this kind of cloud-based system. OwnCloud can keep images in different file formats and share such images to other researchers in simple way.

A non invasive fault diagnosis system for induction motors in noisy environment

In this paper a phase detection method for fault diagnosis of the induction motors has been presented. The proposed method has a powerful environmental noise suppression capability. It has been shown in literature that the performance of the previously used fault detection method (instantaneous power analysis) was affected by the environmental noise, switching disturbances and other low order harmonics. The instantaneous power analysis yields erroneous results under low load conditions of the motor where fault signature was buried in the noise. It has been theoretically and experimentally shown that the proposed phase detection method can detect fault signatures in the noisy environment without use of any extra hardware. The accuracy of the proposed phase detection method was compared with the instantaneous power analysis method for bearing ball defects and the results on the real hardware implementation confirm the effectiveness of the proposed approach.

Vision-based flame analysis using motion and Edge Detection

Fire can lead to major financial losses to industries. Consequently, it is very crucial to develop a reliable method to detect an occurrence of fire. In this research, the algorithms for flame detection using video processing will be proposed. System identification will be used to obtain a process model of the flame. This paper stresses on the flame detection algorithm. The results show that detection of flame using motion & shape features can be achieved by using Background Subtraction and Edge Detection approach.