This is a book review of 'The Micro-Doppler Effect in Radar' by V. C. Chen. Artech House, 16 Sussex Street, London, SW1V 4RW, UK. 2011. 290pp + diskette. Illustrated. £90. ISBN 978-1-60807-057-2.

'The Micro-Doppler Effect in Radar' by V.C. Chen

Theory Of Wing Sections Including A Summary Of Airfoil Data

Damage detection techniques for wind turbine blades: A review

Applications of Machine Learning (ML) algorithms in Structural Health Monitoring (SHM) have become of great interest in recent years owing to their superior ability to detect damage and deficiencies in civil engineering structures. With the advent of the Internet of Things, big data and the colossal and complex backlog of aging civil infrastructure assets, such applications will increase very rapidly. ML can efficiently perform several analyses of clustering, regression and classification of damage in diverse structures, including bridges, buildings, dams, tunnels, wind turbines, etc. In this systematic review, the diverse ML algorithms used in this domain have been classified into two major subfields: vibration-based SHM and image-based SHM. The efficacy of deploying ML algorithms in SHM has been discussed and detailed critical analysis of ML applications in SHM has been provided. Accordingly, practical recommendations have been made and current knowledge gaps and future research needs have been outlined.

Machine Learning Algorithms in Civil Structural Health Monitoring: A Systematic Review

As wind energy is becoming a significant utility source, minimizing the operation and maintenance (O&M) expenses has raised a crucial issue to make wind energy competitive to fossil fuels. Wind turbines (WTs) are subject to unexpected failures due to operational and environmental conditions, aging, and so on. An accurate estimation of time to failures assures reliable power production and lower maintenance costs. In recent years, a notable amount of research has been undertaken to propose prognosis techniques that can be employed to forecast the remaining useful life (RUL) of wind farm assets. This article provides a recent literature review on modeling developments for the RUL prediction of critical WT components, including physics-based, artificial intelligence (AI)-based, stochastic-based, and hybrid prognostics. In particular, the pros and cons of the prognosis models are investigated to assist researchers in selecting proper models for certain applications of WT RUL forecast. Our comprehensive review has revealed that hybrid methods are now the leading and most accurate tools for WT failure predictions over individual hybrid components. Strong candidates for future research include the consideration of variable operating environments, component interaction, physics-based prognostics, and the Bayesian application in the development of WT prognosis methods.

Critical Wind Turbine Components Prognostics: A Comprehensive Review

Ground-based radar (GBR) are increasingly being used either as a vibration-based or as guided-wave-based structural health monitoring (SHM) sensors for monitoring of wind turbines blades. Despite various studies mentioning the use of radar as transducer for SHM, a singular exclusive review of GBR in blade monitoring may have been lacking. Various studies undertaken for SHM of blades using GBR have largely been laboratory-based or with actual wind turbines in parked positions or focussed on the extraction of only specific condition parameters like frequency or deflection with no validation with actual expected operating data. The present study provides quantitative data that relates in-field monitoring of wind turbines by GBR with actual design operating data. As such it helps the monitoring of blades during design, testing, and operation. Further, it supports the determination of fatigue damage for in-field wind turbine blades especially those made of composite materials by way of condition parameters residuals and deflection. A review of the two GBR-SHM approaches is thus undertaken. Additionally, a case study demonstrating its practical use as a vibration-based noncontact SHM sensors is also provided. The study contributes to the monitoring of blades during design, testing, and operation. Further, it supports the determination of damage detection for in-field wind turbine blades within a 3-tier SHM framework especially those made of composite materials by way of condition parameter residuals of extracted modal frequencies and deflection. © 2018 John Wiley & Sons, Ltd.

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A review of ground-based radar as a noncontact sensor for structural health monitoring of in-field wind turbines blades

This paper describes performance analysis of a direct drive Axial Flux Permanent Magnet (AFPM) generator developed for small scale wind energy applications. The design process approach began by a field survey intended to understand reasons behind low penetration of Small Wind Turbines (SWTs) in Kenya and failures of existing power transmission systems, before making a decision on the most suitable electrical generator system. The main objective of this study was to design a generator that is cost efficient to improve its adoption, easy to manufacture so that it can be made in small workshops using basic tools and with limited electrical engineering knowledge, to make it attractive as a source of employment for the youth. Starting by elimination among different possible generator structures, a decision was made for the configuration of a core-less (air-cored) double rotor AFPM generator oriented to SWT applications. The design process combines both analytic and Finite Element Analysis (FEA) of the generator. A simple analytic electromagnetic design model, including sizing equations, considering the fundamental laws governing this type of machine was used to achieve and implement a prototype. FEA model and performance equations were used to verify its performance. The generator assembly is reinforced using an innovative strong T-frame to improve generator stability since coreless AFPMs are known to have stability problems. This frame provides a strong reinforcement to the generator assembly and also offers a flexible mounting support to the turbine blades so that the generator can easily be mounted both on a Horizontal Axis Wind Turbine (HAWT) as well as a Vertical Axis Wind Turbine (VAWT). The AFPM generator will be fitted with suitable protective cover to shield the generator from effects of drought such as corrosion and keep debris from becoming lodged in the inner parts. This has the possibility of extending the life of the generator. The generator has also been designed with large number of poles to improve its performance at low wind speeds. The generator efficiency is high with typical efficiency values of between 75-89%.

Performance Analysis of a Direct Drive Permanent Magnet Generator for Small Wind Energy Applications

In the last two decades, an increase in large rotary machines/systems has been witnessed. To ensure safe operation of these systems especially due to extreme stress caused by centrifugal forces as well as the wind or water loadings, regular structural health monitoring (SHM) of the unbalanced parameters, particularly at the blade tips is necessary. For this, the use of non-contact sensors provides the most appropriate approach; however, millimetric out-of-plane deflection monitoring using non-contact sensors at distances >1 m has not been comprehensively addressed for rotary systems, like wind turbines. This study presents a modelling environment to simulate radar returns to analyse rotary systems. Employing Sammon mapping as a dimensionality reduction procedure in conjunction with 2D visualisation, the study demonstrates the characterisation of dynamic deflection parameters using a fast, portable ground-based interferometric radar (GBR). Comparisons between the GBR results with those of a Leica AR20 GPS indicate a divergence ±12.79 mm. The study utilises SHM framework to acquire, normalise, extract, and validate GBR signals within an SHM framework for structures under test or for deflection validation of the new system. Further, it contributes to the non-contact structural fatigue damage detection during design, testing, and operating stages of rotary structures blade tips.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0503

Deflection characterisation of rotary systems using ground-based radar

This paper describes the use of non-contact quasi monostatic ground-based radar (GBR) for system health monitoring (SHM) of the blades of wind turbines. It focusses on the deflection monitoring of these blades and validates the results from the design parameters extracted from numerical simulations during the design stage.
Using a 3-tier SHM framework, acquisition of deflection in the time-domain is done by the GBR. These results are then transformed into the frequency-domain using a fast Fourier transform (FFT) to obtain the resonant frequencies as second step in the 3-step SHM framework. The third step of validation / hypothesis testing of the measured results with initial simulated design parameter is then effected to demonstrate that the GBR can be used for deformation health monitoring of composite blades and towers.
The work demonstrates that the GBR can be deployed as a non-contact, real-time monitor that can measure deflections and natural-vibration frequencies of wind turbines blades. This enables smart monitoring of dynamic structures in urban and non-urban settings.

Novel non-contact deformation health monitoring of towers and rotating composite based wind turbine blades using interferometric ground-based radar

In this study a three bladed vertical axis wind turbine with a target performance of 500W was fabricated. The sizing was a rotor diameter of 2m and length of 1.6 m with a chord length of 0.2 m. A NACA 0021 air foil was chosen because of its thickness (21% of chord) and its self-starting behavior. The blade material used was Glass fibre reinforced plastics (GFRP). Blade production started with making of a wooden master blade that was used to form the mould. From the mould blade copies were produced. The produced blade was then laminated, dried, trimmed, and smoothed. The power coefficient of the turbine was tested using an industrial wind fan. The turbine was subjected to wind speeds ranging from 4 m/s to 15 m/s. A battery was used to provide the load in the experiment and controlled by an inverter. A direct drive Axial Flux Permanent Magnet (AFPM) generator developed for small scale vertical axis wind turbine (VAWT) was coupled to the turbine rotors to determine the electricity generation capacity. A speed of 14 m/s gave the highest power of 190 W at 280 rpm, 12 m/s gave the highest power as 156 W at 230 rpm, 10 m/s gave the highest power as 120W at 180 rpm while 8 m/s gave the highest power as 96 W at 140 rpm. The rated RPM for the Generator was 280. The turbine torque was 1.56Nm at an RPM of 175. The cost of production of this studies Rotor blade with all components was about Kshs. 50,000. This cost included buying of the shaft, hubs and bearing (Kshs. 25,000) and the blades amounted to about Kshs. 21,000. When compared to a HAWT turbine of same sizing it costs between 100,000-200,000. Most of the local suppliers do not supply VAWT; the international price of VAWT of same sizing is about US$ 1,000. In conclusion the blade produced in this study is cheaper when compared to locally produced HAWT and VAWT prices in international market. It was also established that the turbine has high torque but low rotational speed and a high gear ratio generator when used may achieve higher power output

Francis Xavier Ochieng

Papers

A review of ground-based radar as a noncontact sensor for structural health monitoring of in-field wind turbines blades

Performance Analysis of a Direct Drive Permanent Magnet Generator for Small Wind Energy Applications

Deflection characterisation of rotary systems using ground-based radar

Novel non-contact deformation health monitoring of towers and rotating composite based wind turbine blades using interferometric ground-based radar

Development of a Low Cost Rotor Blade for a H - Darrieus Wind Turbine