A novel approach has been developed to diagnose intermittent stochastic faults by combining a generalized polynomial chaos (gPC) method with maximum likelihood estimation. The gPC is used to propagate stochastic changes in an input variable to a measured output variable from which the fault is to be inferred. The fault detection and diagnosis (FDD) problem is formulated as an inverse problem of...

Two model-based fault-tolerant control design strategies are presented for a Diesel Engine Generator (DEG) working as a master generation unit in an islanded microgrid consisting of a hybrid wind-diesel-photovoltaic power system with a Battery Storage System (BSS). A Model Predictive Control (MPC) scheme and a Model Reference Adaptive Control (MRAC) scheme have been selected for precise and sta...

One of the most promising renewable energy technologies is photovoltaics (PV). Fault detection and diagnosis (FDD) becomes more important in order to guarantee high reliability PV systems. FDD systems using machine learning technique aims develop effective models that can provide a better rate accuracy. Recently, numerous based ensemble have been applied different combination techniques. Ensemb...

To prevent process interruption and eventual losses, the need for a reliable fault detection and diagnosis system (FDD) is completely acknowledged. Besides the capability to recognize known faults automatically, a further requirement for a FDD is adaptability. If the model cannot be adapted to deal with changes, variations due to external changes, decaying performance, Poisoning of catalyst etc...

This paper is the second of a two-part review of methods for automated fault detection and diag-nostics (FDD) and prognostics whose intent is to increase awareness of the HVAC&R research and development community to the body of FDD and prognostics developments in other fields as well as advancements in the field of HVAC&R. The first part of the review focused on generic FDD and prognostics, pro...

This paper describes the extension of a building management system with an interface that allows the import of simulation models, control, and fault detection (FDD) algorithms. This interface is based on the Functional Mock-up Interface (FMI), and the Building Automation Java Architecture (Baja) standards. This allows HVAC designers and control vendors a) developing, testing and improving contr...

Poorly maintained, degraded, and improperly controlled equipment wastes an estimated 15% to 30% of energy used in commercial buildings. Much of this waste could be prevented with widespread adoption of automated condition-based maintenance. Automated fault detection and diagnostics (FDD) along with prognostics provide a cornerstone for condition-based maintenance of engineered systems. Although...

Assimilation of cost-effective Fault Detection and Diagnosis (FDD) technique in building management system can save enormous amount of energy and material. In this paper, Recursive Autoregressive Exogenous Algorithm is used to develop dynamic FDD model for variable air volume air handling units. A methodology, based upon frequency response of the model is evolved for automatic fault detection a...

This paper introduces a robust method for performing active actuator fault detection and diagnostics (FDD) in heating ventilation and air conditioning (HVAC) systems. The proposed actuator FDD strategy, for testing whether an actuator is stuck in a given position, is designed on using an invariant hypothesis testing approach and is an improvement of a previous strategy that employed an adaptive...

Intelligence in Industry 4.0 has led to the development of smart buildings with various control systems for data collection, efficient optimization, and fault detection diagnosis (FDD). However, buildings, especially regard heating, ventilation, air conditioning (HVAC) systems, are responsible significant global energy consumption. Digital Twin (DT) technology offers a sustainable solution faci...