Peter Engel

A survey of the application of basic data-driven and model-based methods in process monitoring and fault diagnosis

Abstract Basic data-driven and model-based process monitoring and fault diagnosis methods are surveyed from the application viewpoint. The main objective is to study the needed modifications and/or combined use of these methods under different real operating conditions.

A data-driven approach for sensor fault diagnosis in gearbox of wind energy conversion system

Due to the increase in worldwide energy demand, wind energy technology has been developed rapidly over the past years. With a fast growing of wind power installed capacity, an efficient monitoring system for wind energy conversion system (WEC) is required to ensure operational reliability, high availability of energy production and at the same time reduce operating and maintenance (O&M) costs. The state of the art methodologies for WEC condition monitoring are signal analysis, observer-based approach, neural networks, etc. In this paper, an effective and easy adaptable multivariate data-driven method for wind turbine monitoring and fault diagnosis is introduced, which consists of three parts: 1) off-line training process 2) on-line monitoring phase 3) on-line diagnosis phase. The performance of this method is validated for detection of sensor abnormalities that have occurred in real wind turbines.

A Model-Based Information System for Simulation and Monitoring of Belt Conveyor Systems

Abstract In this paper an information system is presented, which is developed to meet the requirements on simulation and on-line monitoring of large scale belt conveyor systems. The core of this information system is a mathematical model and an observer. Successful applications to a number of belt conveyor systems document the efficiency and performance of the information system.

A Data-Driven Maintenance Support System for Wind Energy Conversion Systems

Abstract With the rapid growth of wind energy installed capacity, optimized maintenance has gained increasingly attentions from both researchers and wind farm owners. Condition-based maintenance (CBM) has been introduced to the wind energy industry in order to ensure the availability and safety of the wind energy conversion (WEC) system, while minimize the operating and maintenance (O&M) costs. In this paper a maintenance decision support system is introduced. By combining the information delivered by the data-driven WEC condition monitoring system and the economical benefits of each possible corrective maintenance action, the decision support system provides the operators with a choice of the most proper maintenance action for the current situation. The performance of the decision support system is tested with data collected from different WECs in a wind farm.

Application of observer-based monitoring technique in belt conveyor systems

Abstract In this paper an information system is presented, which is developed to meet the requirements on simulation, on-line monitoring, quality management and optimum design of large scale belt conveyor systems. The core of this information system is a mathematical model and an observer. Successful application is also presented to illustrate the proposed approach. Copyright© 2002 IFAC