Evolutionary programming techniques for economic load dispatch

Evolutionary programming has emerged as a useful optimization tool for handling nonlinear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness and these have been applied successfully on some benchmark mathematical problems. But few applications have been reported on real-world problems such as economic load dispatch (ELD). The performance of evolutionary programs on ELD problems is examined and presented in this paper in two parts. In Part I, modifications to the basic technique are proposed, where adaptation is based on scaled cost. In Part II, evolutionary programs are developed with adaptation based on an empirical learning rate. Absolute, as well as relative, performance of the algorithms are investigated on ELD problems of different size and complexity having nonconvex cost curves where conventional gradient-based methods are inapplicable.     

Computationally efficient algorithms for multiple fault diagnosis in large graph-based systems

Graph-based systems are models wherein the nodes represent the components and the edges represent the fault propagation between the components. For critical systems, some components are equipped with smart sensors for on-board system health management. When an abnormal situation occurs, alarms will be triggered from these sensors. This paper considers the problem of identifying the set of potential failure sources from the set of ringing alarms in graph-based systems. However, the computational complexity of solving the optimal multiple fault diagnosis (MFD) problem is exponential. Based on Lagrangian relaxation and subgradient optimization, we present a heuristic algorithm to find approximately the most likely candidate fault set. A computationally cheaper heuristic algorithm - primal heuristic - has also been applied to the problem so that real-time MFD in systems with several thousand failure sources becomes feasible in a fraction of a second. This paper also considers systems with asymmetric and multivalued alarms (tests).     

Surface integrity study of WEDM with various wire electrodes: experiments and analysis

Abstract

Wire electrical discharge machining (WEDM) is always significant for its high-precision machining. However, due to the generation of high discharge energy during machining, machined surfaces are often got distorted. These might be upgraded by choosing the correct tool with proper machining condition. The effects of the electrode materials and process parameters on different responses of WEDM like average surface roughness, recast layer thickness, and surface morphology are systematically examined here to enhance the knowledge of WEDM and its correlation with electrode property. The experiments have been carried out on one of the expensive steel namely Maraging steel 300 due to its applicability in tooling and aerospace industries. Plain brass wire, zinc-coated brass wire (ZCB), and silver-coated brass (SCB) wires are used as a tool electrode for analysis. Comparative experimental studies prove that among BW, ZCB, and SCB, the overall performance of SCB is commendable owing to the high-quality surface considering control parameters in low discharge energy level. However, the second-best performance is shown by ZCB.     

Note: Compact high voltage pulse transformer made using a capacitor bank assembled in the shape of primary

The experimental results of an air-core pulse transformer are presented, which is very compact (<10 Kg in weight) and is primed by a capacitor bank that is fabricated in such a way that the capacitor bank with its switch takes the shape of single-turn rectangular shaped primary of the transformer. A high voltage capacitor assembly (pulse-forming-line capacitor, PFL) of 5.1 nF is connected with the secondary of transformer. The transformer output voltage is 160 kV in its second peak appearing in less than 2 μS from the beginning of the capacitor discharge. The primary capacitor bank can be charged up to a maximum of 18 kV, with the voltage delivery of 360 kV in similar capacitive loads.     

ENVIRONMENTALLY CONSCIOUS MACHINING AND GRINDING WITH CRYOGENIC COOLING

High production machining and grinding is becoming essential to enhance productivity and profitability. But such machining technique inherently increases the machining and grinding zone temperature, which in turn enhances tool wear rate and impairs the product quality. Historically cutting compounds and grinding fluids are applied to control such high temperature. Not only are such cutting fluids not very effective, but most importantly they are being perceived as a major source of pollution from the machining and grinding industry. The drastic cooling action of liquid nitrogen jets does provide desirable temperature control along with other technological benefits. Several research groups and a few organisations in different parts of the world are investigating the effects of cryogenic cooling on the machinability and grindability of different work materials using different approaches.     

A New Link Failure Resilient Priority Based Fair Mutual Exclusion Algorithm for Distributed Systems

This paper aims towards designing a new token-based mutual exclusion algorithm for distributed systems. In some of the earlier work, token based algorithms for mutual exclusion are proposed for the distributed environment assuming inverted tree topology. In a wireless setup, such a stable, hierarchical topology is quite unrealistic due to frequent link failures. The proposed token-based algorithm works for processes with assigned priorities on any directed graph topology with or without cycles. The proposed algorithm, in spite of considering priorities of processes, ensures liveness in terms of token requests from low priority processes. Moreover, the algorithm keeps control message traffic reasonably low. The simulation results exhibit the performance of the proposed algorithm under varied contexts besides presenting a comparative performance with other recent algorithms for mutual exclusion like FAPP (Fairness Algorithm for Priority Process).     

Special issue: The International Conference on Soft Computing and Machine Intelligence

Neural Computing and Applications -     

Renormalized measure of regular languages

This paper modifies the signed real measure of regular languages, which has been reported in recent literature for analysis and synthesis of discrete event supervisory control laws. A new concept of renormalized measure is introduced to eliminate a user-selectable parameter in the present version of the language measure. The concept of measure renormalization is illustrated by an example.