On the identification of the early developmental stages of clupeiform fishes from Indian waters

Among about 65 species of clupeiform fishes present in the seas around India, most are distributed along both the east and west coasts and have similar spawning seasons and spawning grounds. The most difficult problem experienced with regard to the identification of their early developmental stages is the overlapping sets of diagnostic features among many species within the same genus as well as among species belonging to two or more genera. From studies carried out recently, the present paper sites a few instances wherein certain subtle characters have been used for distinguishing the early developmental stages of a few allied species.

Balanced parametrizations and canonical forms for system identification

This paper contains a review of recent results concerning the parametrization of asymptotically stable linear systems using balanced realizations. Particular emphasis is given on the application of these results to system identification. This work is part of a continuing programme aimed at elucidating the role of balanced realization in system identification.

Identification of support conditions of buried pipes using a vibrating pig

This paper describes a method for monitoring the variation in support condition of pipelines using a vibration technique. The method is useful for detecting poor support of buried pipelines and for detecting spanning and depth of cover in sub-sea lines. Variation in the pipe support condition leads to increased likelihood of pipe damage. Under roadways, poorly supported pipe may be damaged by vehicle loading. At sea, spanned sections of pipe are vulnerable to ocean current loading and also to snagging by stray anchors in shallow waters. A vibrating `pig' has been developed and tested on buried pipelines. Certain features of pipe support, such as voids and hard spots, display characteristic responses to vibration, and these are measured by the vibrating pig. Post-processing of the measured vibration data is used to produce a graphical representation of the pipeline support and certain `feature characteristics' are identified. In field tests on a pipeline with deliberately constructed support faults, features detected by the vibrating pig are in good agreement with the known construction.

Commodity and product identification for value chain analysis.

This commodity and product identification research was undertaken in the context of the CGIAR Research Program on Aquatic Agricultural Systems (AAS). AAS seeks to reduce poverty and improve food security for the millions of small-scale fishers and farmers who depend on the world’s floodplains, deltas and coasts. The objective of this research is to strengthen the capacity of AAS to undertake value chain studies with high potential impact on smallholders. The capacity-building aspect of this research was focused on the process of commodity and product identification for value chain analysis. Its scope was limited to fish and other aquatic animals and products in the Tonle Sap area identified for AAS intervention. The result of the identification process was the selection of a number of commodities and products that were deemed to involve a high number of smallholders along the value chain and that have high market development potential.

Algorithm for identification in the v-gap metric

This paper suggests a method for identification in the v-gap metric. For a finite number of frequency response samples, a problem for identification in the v-gap metric is formulated and an approximate solution is described. It uses an iterative technique for obtaining an L2-gap approximation. Each stage of the iteration involves solving an LMI optimisation. Given a known stabilising controller and the L2-gap approximation, it is shown how to derive a v-gap approximation.

Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Towards identification of a general model of damping

Characterization of damping forces in a vibrating structure has long been an active area of research in structural dynamics. In spite of a large amount of research, understanding of damping mechanisms is not well developed. A major reason for this is that unlike inertia and stiffness forces it is not in general clear what are the state variables that govern the damping forces. The most common approach is to use `viscous damping' where the instantaneous generalized velocities are the only relevant state variables. However, viscous damping by no means the only damping model within the scope of linear analysis. Any model which makes the energy dissipation functional non-negative is a possible candidate for a valid damping model. This paper is devoted to develop methodologies for identification of such general damping models responsible for energy dissipation in a vibrating structure. The method uses experimentally identified complex modes and complex natural frequencies and does not a-priori assume any fixed damping model (eg., viscous damping) but seeks to determine parameters of a general damping model described by the so called `relaxation function'. The proposed method and several related issues are discussed by considering a numerical example of a linear array of damped spring-mass oscillators.