A New Condition Monitoring Approach for Maintenance Management in Concentrate Solar Plants

Abstract

The concentrated solar energy is one of the most important renewable energy source. It is crucial to ensure that the solar receivers work properly to avoid failures, and to increase the reliability, availability, safety and maintainability. Nondestructive testing (NDT) is used in structural health monitoring systems for fault detection and diagnosis (FDD). The main purpose of this paper is to present a novel approach for FDD based on long range ultrasonic technology, together with a signal processing of ultrasonic waves (Shear waves) employing wavelet transforms using a variable window size. A new electromagnetic acoustic transducer (EMAT) generates high frequency waves that flow through the material. A similar transducer is also employed as a sensor to collect the guided wave. These waves have a particular behaviour according to the condition of the material. It is analyse the influence of the temperature in the propagation of an ultrasonic pulse through the material. This information is very useful to carry out a proper signal analysis in order to find cracks or failures on the pipes, the correct operation of the system, etc.

PV System Predictive Maintenance: Challenges, Current Approaches, and Opportunities

“…Ancuta and Cepisca (2011) state: "Reliable predictive and preventive maintenance techniques are needed to assure lifetime efficiency in service" [6]. In addition, Gómez Muñoz and colleagues reasoned about the benefits of monitoring as follows: "Significant discrepancies between the energy measurements can work as an alarm signal to activate maintenance operations" [23].…”

Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring

“…Figure 6 suggest that the support vector regression can fit the wind turbine pitch curve smoothly, however at higher wind speed, its accuracy suffers because of unavailability of sufficient data points. Furthermore, the accuracy of a support vector regression model depends on the quantity and quality of the data as well as the appropriate (6…”

“…Performance monitoring based on the available SCADA data is also a cost-effective approach to turbine condition appraisal, as confirmed by various literature reviews [4,5] that highlight the feasibility of identifying turbine health status using SCADA data, and the vast potential of further enhancing the health monitoring function through sophisticated data analysis. SCADA-based monitoring of the condition of internal components of a wind turbine can be used to optimize maintenance activities and thus reduce O&M costs and increase reliability and production time; see [6][7][8][9].…”

Dirt and mud detection and diagnosis on a wind turbine blade employing guided waves and supervised learning classifiers

“…It is possible to obtain measurements of condition monitoring of the WTB, including data from vibration, acoustic emission, infrared images, etc. The CBM objective is to optimize maintenance activities and reduce costs [14][15][16][17][18][19].…”