Wind energy is one of the most important renewable energy sources and many countries are predicted to increase wind energy portion of their whole national energy supply to about twenty percent in the next decade. One potential obstacle in the use of wind turbines to harvest wind energy is the maintenance of the wind turbine blades. The blades are a crucial and costly part of a wind turbine and over their service life can suffer from factors such as material degradation and fatigue, which can limit their effectiveness and safety. Thus, the ability to detect damage in wind turbine blades is of great significance for planning maintenance and continued operation of the wind turbine. This paper presents a review of recent research and development in the field of damage detection for wind turbine blades. Specifically, this paper reviews frequently employed sensors including fiber optic and piezoelectric sensors, and four promising damage detection methods, namely, transmittance function, wave propagation, impedance and vibration based methods. As a note towards the future development trend for wind turbine sensing systems, the necessity for wireless sensing and energy harvesting is briefly presented. Finally, existing problems and promising research efforts for online damage detection of turbine blades are discussed.

https://iopscience.iop.org/article/10.1088/0964-1726/24/3/033001/pdf

A review of damage detection methods for wind turbine blades

The effect of prediction error correlation on optimal sensor placement in structural dynamics

Optimal sensor placement (OSP) technique plays a key role in the structural health monitoring (SHM) of large-scale civil infrastructures. This paper outlines an overview of current research and development in the field of OSP problems in a perspective of both researchers and engineers. The paper begins with a definition of the model of sensor placement and provides the basic issues covering relevant methodologies. The primary evaluation criteria and main sensor placement methods are then discussed in details. Following that, the linkage between several influential sensor placement methods is described. Finally, existing problems and promising research efforts in the OSP problem of civil SHM are discussed.

https://journals.sagepub.com/doi/pdf/10.1155/2012/612726

Methodology Developments in Sensor Placement for Health Monitoring of Civil Infrastructures

Sensor placement for modal identification

The developments and implementations of the structural health monitoring (SHM) system for large infrastructures have been gradually recognized by researchers, engineers and administrative authorities in the last decades. This paper summarizes an updated review on innovations and applications in SHM for infrastructures carried out by researchers at Dalian University of Technology. Invented sensors and data acquisition system are firstly briefly described. And then, some proposed theories and methods including the sensing technology, sensor placement method, signal processing and data fusion, system identification and damage detection are discussed in details. Following those, the activities on the standardization of SHM and several case applications on specific types of structure are reviewed. Finally, existing problems and promising research efforts in the field of SHM are given.

Reviews on innovations and applications in structural health monitoring for infrastructures

Load dependent sensor placement method: Theory and experimental validation

A note on fast computation of effective independence through QR downdating for sensor placement

A novel sensor placement criterion is proposed for structural health monitoring after five influencing criteria are critically reviewed. The objective of the proposed criterion is to achieve best identification of modal frequencies and mode shapes through almost unbiased estimation of modal coordinates. The proposed criterion derived by the Representative Least Squares method depends on both the characteristics and the actual loading situations of a structure. It selects sensor positions with the best subspace approximation of the vibration responses from the linear space spanned by the mode shapes. Furthermore, the connection between the Effective Independence and the approximate Representative Least Squares estimator is obtained through matrix perturbation analysis. It is found that the Effective Independence is a step-by-step approximation to that of the Representative Least Squares criterion.

Dong-Sheng Li

Papers

Load dependent sensor placement method: Theory and experimental validation

A note on fast computation of effective independence through QR downdating for sensor placement

On Optimal Sensor Placement Criterion for Structural Health Monitoring with Representative Least Squares Method

Comments on “Clustering of Sensor Locations Using the Effective Independence Method”

Comments on placement of sensors in operational modal analysis for truss bridges in Mechanical Systems and Signal Processing 31 (2012) 196–216