Fault detection and diagnosis for large solar thermal systems: A review of fault types and applicable methods

• Published in: Solar energy Vol. 197; pp. 472 - 484
• Main Authors: Faure, Gaëlle, Vallée, Mathieu, Paulus, Cédric, Tran, Tuan Quoc
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.02.2020; Pergamon Press Inc; Elsevier
• Subjects: Algorithms; Diagnosis; Engineering Sciences; Failure modes, effects and criticality analysis; Fault detection; Fault diagnosis; Life span; Literature reviews; Mechanics; Solar energy; Solar heating; Solar thermal; Thermics; Fault diagnosis; Failure modes, effects and criticality analysis; Fault detection; Solar thermal
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2020.01.027

All technical processes are subject to dysfunctions during their lifespan, and large solar thermal systems (LSTS) are no exception to this rule. The development of robust fault detection and diagnosis (FDD) methods is therefore a key issue. This paper reports on a review of faults types that can affect LSTS as well as the current approaches to detect and diagnose them. After a brief description of the system, a literature review of its dysfunctions is presented and the results of a study to complete and organize the inventory of these faults are described. The critical faults are defined. The state of the art of the research concerning FDD methods for LSTS is then detailed and demonstrates that this topic is of current interest. Finally, the performance of current algorithms is evaluated by two different ways: first along a list of desirable characteristics of a FDD method for LSTS, second along the ability of each method to detect the critical faults. This evaluation shows that there is room for some improvements in detecting and diagnosing faults for LSTS and these avenues are discussed.