Temperature robust PCA based stress monitoring approach

In this paper, a guided wave temperature robust PCA-based stress monitoring methodology is proposed. It is based on the analysis of the longitudinal guided wave propagating along the path under stress. Slight changes in the wave are detected by means of PCA via statistical T2 and Q indices. Experimental and numerical simulations of the guided wave propagating in material under different temperatures have shown significant variations in the amplitude and the velocity of the wave. This condition can jeopardize the discrimination of the different stress scenarios detected by the PCA indices. Thus, it is proposed a methodology based on an extended knowledge base, composed by a PCA statistical model for different discrete temperatures to produce a robust classification of stress states under variable environmental conditions. Experimental results have shown a good agreement between the predicted scenarios and the real onesPostprint (author's final draft

Development of a robust structural health monitoring system for wind turbine foundations

The construction of onshore wind turbines has rapidly been increasing as the UK attempts to meet its renewable energy targets. As the UK’s future energy depends more on wind farms, safety and security are critical to the success of this renewable energy source. Structural integrity is a critical element of this security of supply. With the stochastic nature of the load regime a bespoke low cost structural health monitoring system is required to monitor integrity. This paper presents an assessment of ‘embedded can’ style foundation failure modes in large onshore wind turbines and proposes a novel condition based monitoring solution to aid in early warning of failure

Structural health monitoring for wind turbine foundations

The construction of onshore wind turbines has rapidly been increasing as the UK attempts to meet its renewable energy targets. As the UK’s future energy depends more on wind farms, safety and security are critical to the success of this renewable energy source. Structural integrity of the tower and its components is a critical element of this security of supply. With the stochastic nature of the load regime a bespoke low cost structural health monitoring system is required to monitor integrity of the concrete foundation supporting the tower. This paper presents an assessment of ‘embedded can’ style foundation failure modes in large onshore wind turbines and proposes a novel condition based monitoring solution to aid in early warning of failure. The most common failure modes are discussed and a low-cost remote monitoring system is presented

Damage Tolerant Active Contro l: Concept and State of the Art

Damage tolerant active control is a new research area relating to fault tolerant control design applied to mechanical structures. It encompasses several techniques already used to design controllers and to detect and to diagnose faults, as well to monitor structural integrity. Brief reviews of the common intersections of these areas are presented, with the purpose to clarify its relations and also to justify the new controller design paradigm. Some examples help to better understand the role of the new area

Vibration-based methods for structural and machinery fault diagnosis based on nonlinear dynamics tools

This study explains and demonstrates the utilisation of different nonlinear-dynamics-based procedures for the purposes of structural health monitoring as well as for monitoring of robot joints

PCA based stress monitoring of cylindrical specimens using PZTs and guidedwaves

Since mechanical stress in structures affects issues such as strength, expected operational life and dimensional stability, a continuous stress monitoring scheme is necessary for a complete integrity assessment. Consequently, this paper proposes a stress monitoring scheme for cylindrical specimens, which are widely used in structures such as pipelines, wind turbines or bridges. The approach consists of tracking guided wave variations due to load changes, by comparing wave statistical patterns via Principal Component Analysis (PCA). Each load scenario is projected to the PCA space by means of a baseline model and represented using the Q-statistical indices. Experimental validation of the proposed methodology is conducted on two specimens: (i) a 12.7 mm (1/2”) diameter, 0.4 m length, AISI 1020 steel rod, and (ii) a 25.4 mm (1”) diameter, 6m length, schedule 40, A-106, hollow cylinder. Specimen 1 was subjected to axial loads, meanwhile specimen 2 to flexion. In both cases, simultaneous longitudinal and flexural guided waves were generated via piezoelectric devices (PZTs) in a pitch-catch configuration. Experimental results show the feasibility of the approach and its potential use as in-situ continuous stress monitoring application.Peer ReviewedPostprint (published version

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Detailed state of the art review for the different on-line/in-line oil analysis techniques in context of wind turbine gearboxes

The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water, and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required to allow a better maintenance regime to be established. Current technologies available specifically for this purpose include Fourier transform infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyze different characteristics of the oil. The information individually would not be highly accurate but combined it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy, and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy, and solid state viscometers

Principal component analysis and perturbation theory–based robust damage detection of multifunctional aircraft structure

A fundamental problem in structural damage detection is to define an efficient feature to calculate a damage index. Furthermore, due to perturbations from various sources, we also need to define a rigorous threshold whose overtaking indicates the presence of damages. In this article, we develop a robust damage detection methodology based on principal component analysis. We first present an original damage index based on projection of the separation matrix, and then, we drive a novel adaptive threshold that does not rely on statistical assumptions. This threshold is analytic, and it is based on matrix perturbation theory. The efficiency of the method is illustrated using simulations of a composite smart structure and experimental results performed on a conformal load-bearing antenna structure laboratory test

In-sewer field-evaluation of an optical fibre-based condition monitoring system

A Fiber Bragg Grating (FBG) based monitoring system for continuous humidity and temperature measurement has been designed and evaluated experimentally in a sewer environment with high corrosion rates, humidity and the presence of gaseous hydrogen sulfide. The monitoring system has been designed specifically for field use, including packaging prepared for the harsh environment and the challenges of the operation. The system is battery powered and has hardware for controlling the interrogation equipment, power management, data logging and 4G connectivity. Results obtained show the long-term performance, over a 6-month period of non-stop monitoring of real-time data using the same probe. The data acquired was compared to the environmental data of temperature and precipitation for this period from the same location, which showed a good correlation between the expected and the measured data values. The data obtained point to the success of the optical fibre-based sensor system for monitoring in these harsh environments over long periods