THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

American Society for Testing and Materials

This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Introduction to the Finite Element Method

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

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:

A fuzzy logic system (FLS) is developed for ground based health monitoring of a helicopter rotor blade. Structural damage is modeled as a loss of stiffness at the damaged location that can result from delamination. Composite materials, which are widely used for fabricating rotor blades, are susceptible to such delaminations from barely visible impact damage. The rotor blade is modeled as an elastic beam undergoing transverse (flap) and inplane (lag) bending, axial and torsion deformations. A finite element model of the rotor blade is used to calculate the change in blade frequencies (both rotating and nonrotating) because of structural damage. The measurements used for health monitoring are the first four flap (transverse bending) frequencies of the rotor blade. The measurement deviations due to damage are then fuzzified and mapped to a set of faults using a fuzzy logic system. The output faults of the fuzzy logic system are four levels of damage (undamaged, slight, moderate and severe) at five locations along the blade (root, inboard, center, outboard, tip). Numerical results with noisy data show that the FLS detects damage with an accuracy of 100% for noise levels below 15% when nonrotating frequencies are used. The FLS also correctly classifies the ‘‘undamaged’’ condition up to noise levels of 30% thereby reducing the possibility of false alarms, a key problem for diagnostics systems. The fuzzy logic approach is thus able to extract maximum information from very limited and uncertain data. Using rotating frequencies lowers the success rate for small damage because the centrifugal stiffening caused by rotation counters the stiffness reduction caused by structural damage. The fuzzy logic system in this study is proposed as an information-processing tool to help the maintenance engineer by locating the damage area roughly but accurately for further nondestructive inspections.

/pdf/a-fuzzy-logic-system-for-ground-based-structural-health-54fu7ek14n.pdf

A Fuzzy Logic System for Ground Based Structural Health Monitoring of a Helicopter Rotor Using Modal Data

A neural network approach is used for detection of structural damage in a helicopter rotor blade using rotating frequencies of the flap (transverse bending), lag (in-plane bending), elastic torsion and axial modes. A finite element method is used for modeling the helicopter blade. Radial basis function (RBF) neural networks are used and several combinations of modes are investigated for training and testing the neural network. Using the first 10 modes of the rotor blade for damage detection yields accurate results for the soft in-plane hingeless rotor considered in this study. Using a parametric study of the blade rotating frequency in conjunction with the neural network, it is found that a reduced measurement set consisting of five modes (the first two torsion modes, the second lag mode and the third and fourth flap modes) also gives good results for damage detection. Furthermore, taking only the first four flap modes also results in good damage detection accuracy. Three rotating frequency sets are therefore identified in this paper for structural damage detection in a helicopter rotor using RBF neural networks.

https://iopscience.iop.org/article/10.1088/0964-1726/12/2/311/pdf

Structural damage detection in a helicopter rotor blade using radial basis function neural networks

Genetic fuzzy system for online structural health monitoring of composite helicopter rotor blades

Hysteresis in piezoceramic materials causes considerable complications in the use of piezo actuators in applications, such as vibration control. In this study, the classical Preisach model is used to characterize the hysteresis in a piezostack actuator used to move a trailing-edge flap for helicopter vibration control. The hysteresis in the actuator is primarily due to material nonlinearity and to a lesser extent due to losses in the amplification mechanism. Most helicopter vibration control studies ignore the effect of the hysteresis on the actuator performance. The desired motion of the flap for maximum reduction in vibration is determined using an aeroelastic analysis of the helicopter. Numerical results indicate that complete compensation of actuator hysteresis can result in up to 90% reduction in helicopter vibrations. The performance of the vibration control system deteriorates considerably when the actuator is represented by a linear model or when the compensator is based only on the primary material hysteresis of the actuator. Complete compensation of both material and mechanical hysteresis in the actuator is therefore critical to the performance of the trailing-edge flap vibration control system in a helicopter.

Modeling and compensation of piezoceramic actuator hysteresis for helicopter vibration control

A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.

Ranjan Ganguli

Papers

A Fuzzy Logic System for Ground Based Structural Health Monitoring of a Helicopter Rotor Using Modal Data

Structural damage detection in a helicopter rotor blade using radial basis function neural networks

Genetic fuzzy system for online structural health monitoring of composite helicopter rotor blades

Modeling and compensation of piezoceramic actuator hysteresis for helicopter vibration control

Structural Damage Detection Using Modal Curvature and Fuzzy Logic