MKSSS's Cummins College of Engineering for Women

About: MKSSS's Cummins College of Engineering for Women is a based out in . It is known for research contribution in the topics: Support vector machine & Discrete wavelet transform. The organization has 432 authors who have published 424 publications receiving 1919 citations.

Design of PID controller based on reduced order model and Characteristic Ratio Assignment method

Abstract: This paper presents design of PID controller using Characteristic Ratio Assignment (CRA) method. The design methodology uses reduced first order plus delay time (FOPDT) model of system. Based on required overshoot and settling time the controller parameters are computed using CRA method. To demonstrate the performance and stability of controller simulation examples are presented. To indicate the robustness of the controller the 20% uncertainty is added to the system model and controller performance is evaluated. To show the real life applicability of the proposed controller a real life flow control system is used for the demonstration. The performance of the proposed controller is compared with a PID controller in the literature.

Testing of Silicon Rubber/Montmorillonite Nanocomposite for Mechanical and Tribological Performance.

Abstract: Nanocomposite made by blending nano-montmorillonite (MMT) and Silicon Rubber (SR) for mechanical and tribological performance is explored in this work. Different configurations of MMT/SR nanocomposite, with 0, 0.5, 2 and 5 wt % of MMT are manufactured by two roll mixing methods. Noticeable improvement in the mechanical and tribological performance is observed, which is also justified by a morphological study of fractured and wear surfaces through SEM. Two percent of MMT loading is found to be the optimum content that shows excellent performance compared to other compositions. The performance improvement can be linked to the good interfacial interaction between the MMT and SR. Statistical modeling through ANOVA is carried out for tribological performance, which reveals the influence of load on the coefficient of friction (COF) and the influence of sliding distance on the wear rate.

Energy Distribution and Coherence-Based Changes in Normal and Epileptic Electroencephalogram

Abstract: In endeavor toward better understanding of brain functions, the analysis of information transfer between the various brain lobes plays a crucial role. Electroencephalogram (EEG) is an electrical brain signal in microvolts, which provides unique and important information about the brain dynamics. Frequency of EEG signal lies between 0 and 100 Hz. In epileptic or seizure related studies, decomposition of EEG signal into various frequency sub-bands such as α, β, \( \delta \), \( \theta \), and γ is essential. EEG plays a key role in diagnosis of neurological disorders such as epilepsy. In this paper, we explore decomposition of EEG by db18 wavelet, power spectral density, coherence, energy distribution, and empirical cumulative distribution function of EEGs. This work was carried out to study the changes in the normal and epileptic EEGs with respect to PSD, coherence, energy, and ECDF to check the suitability of these parameters as an input to the classifiers. The methodology was applied mainly to three groups consisting of male and females between the age group of 01–107 years: (1) healthy subjects (normal), (2) subjects with focal seizures, (3) subjects with generalized seizures. The work was carried out on the signals obtained from real subjects to study the EEG-based brain connectivity analysis. It was observed that PSD and coherence study related to the sub-bands reveal more accurate information than the study of complete EEG with or without the seizures.

Availability Analysis of a Steam Boiler in Textile Process Industries Using Failure and Repair Data: A Case Study

Abstract: The demand of steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. Many of the process industries depend on...