This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.

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Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

This paper provides an overview of methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage identification has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is presented. The methods are categorized according to various criteria such as the level of damage detection provided, model-based versus non-model-based methods, and linear versus nonlinear methods. The methods are also described in general terms including difficulties associated with their implementation and their fidelity. Past, current, and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of vibration-based damage identification.

A summary review of vibration-based damage identification methods

A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...

Vibration-based Damage Identification Methods: A Review and Comparative Study:

Vibration of cracked structures: A state of the art review

This book focuses on structural health monitoring in the context of machine learning. The authors review the technical literature and include case studies. Chapters include: operational evaluation, sensing and data acquisition, introduction to probability and statistics, machine learning and statistical pattern recognition, and data prognosis.

Structural Health Monitoring: A Machine Learning Perspective

A 90-nm dual-band high gain CMOS LNA has been proposed. The first stage consists of twin band pass filter which is used to achieve dual bands at 2.4 and 5.2 GHz. High gain is achieved using current starving technique. A buffer stage is used to isolate input-output signals. The two stage LNA delivers a power gain of 20.577 dB and 20.360 dB at 2.4 and 5.2 GHz respectively with a gain deviation of 0.217 dB. The noise figure is observed to be 2.129 dB and 3.177 dB by using a parallel LC input matching network. The proposed LNA operates at a supply voltage of 1.2 V with a power dissipation of 7.32 mW.

90-nm Dual-Band CMOS LNA with Gain Enhancement for Wireless LAN Applications

This book is designed to introduce the basics of different aspects of the biology of reproduction in a concise and coherent manner. The book aims to equip students with the fundamentals of the biology of reproduction and also update them with the most recent advances in the field of reproduction. The book has been organized into 16 chapters that introduce and explain different aspects in a stimulating manner. Each chapter is supplemented with a summary and relevant illustrations. A glossary has been added to help the students to understand some important scientific terms. The book offers comprehensive coverage of the important topics including: Flower structure and development Development and structure of male and female gametophytes Pollination biology, fertilization and self-incompatibility Endosperm, embryo and polyembryony Apomixis and seed biology A separate topic on experimental plant reproductive biology (experimental embryology) has been provided, which includes basics of cell, tissue and organ culture, anther culture, pollen culture, flower, ovary, ovule culture, embryo culture, somatic embryogenesis, synthetic seeds, protoplast culture and other aspects of plant biotechnology. The book aims to cater to the needs of the advanced undergraduate and post-graduate students in Botany, Forestry, Agriculture and related fields. 

Reproductive Biology of Angiosperms

Phylogenetic relationships of Indian Memecylon L. (Melastomataceae) based on nrDNA ITS and cpDNA rbcL sequence data

Phylogenetic relationships in Indian Daphne (Thymelaeaceae) based on nuclear ITS and cpDNAdata

Pea is an important grain and vegetable crop with a large genome of ~4.45 Gb. The softness of pod is key to the quality of pea, yet the genes controlling softness remain unknown. Here, the pod softness phenotype was visually scored at the fully mature stage, which suggested that this trait was a composite trait governed by two genes. Bulked segregant analysis sequencing (BSA-Seq) using the soft- and hard-podded pools from the F2 detected a strong peak of Δ (SNP-index) on chromosome 1 and a weaker peak on chromosome 5. The former was designated as PsPS1. Fine mapping using the F2 delimited PsPS1 to a ~6 Mb genomic region. A set of interesting candidate genes including those encoding cell wall components were identified. Sequence variants analysis from a panel of pea accessions and qRT-PCR in immature pods of the parents suggested Psat1g150000 encoding a pectate lyase superfamily protein as a candidate gene. The results solidify the basis for cloning of the gene determining pod softness and marker-assisted selection for the trait improvement. 

A.K. Pandey

Papers

90-nm Dual-Band CMOS LNA with Gain Enhancement for Wireless LAN Applications

Reproductive Biology of Angiosperms

Phylogenetic relationships of Indian Memecylon L. (Melastomataceae) based on nrDNA ITS and cpDNA rbcL sequence data

Phylogenetic relationships in Indian Daphne (Thymelaeaceae) based on nuclear ITS and cpDNAdata

Fine mapping PsPS1 , a gene controlling pod softness that defines market type in pea ( Pisum sativum )