Model-based structural monitoring using in-operation system identification

Development of methodologies to identify dynamic models
based on in-operation data, with an additional focus on
monitoring and fault prediction and diagnosis. Applications
in a variety of different sectors will be pursued.

The project's main objective is to develop, implement and validate methods to estimate a structural dynamics model from in-operation measured data. Such models are not only expected to describe the actual dynamic behaviour more accurately than laboratory model test models, in many cases they are the only ones which can be estimated. The application of such models will be investigated for the following problems: - to improve the reliability of response predictions to actual loads - to improve the accuracy and reliability of numerical (FEM - Finite Element Method) models - to permit the monitoring and diagnosis of the structural behaviour during the product life - to optimise the design and performance of process control systems. To achieve these objectives, the following activities will be performed: - Feasibility assessment and requirement definition The required base line know-how for in-operation system identification will be collected. A principal evaluation will be made on how such models can be applied to the described problems (response predictions, FEM updating, monitoring and damage diagnosis). This will result in a requirement definition for further research and prototype development. - Development and enhancement of in-operation structural identification techniques More specifically, methods using only response measurements (with assumptions for the unknown excitation to be verified) will be investigated. Indirect time domain, correlation (NExT), subspace, principal field as well as AR (AutoRegressive) and ARMA (AutoRegressive Moving Average) methods will be investigated. - Development and enhancement of a FEM-correlation approach using operational data The capabilities of available FEM correlation (first) and updating methods (ultimately) have to be reviewed for the application of in-operation measured models and the required improvements related to the direct use of response data needs to be implemented. Especially the decomposition of in-operation modes on a FEM basis and the use of the a priori (FEM) data to enhance the operational data needs to be researched. - Development and enhancement of a model-based monitoring and damage diagnosis approach Since the in-operation models represent the actual state of the product, their interpretation in terms of the integrity of the structure (and the possible onset and location of damage) will be investigated. - Integration of modelling with control The applicability (and methdology) to use in-operation identified models for control system and controller optimisation will be studied with specific focus on multi-variate process control. - Implementation A prototype version of the developed methodologies needs to be implemented and integrated into a CAE (Computer-Aided Engineering) platform that supports the standard functionalities for dynamic model usage (forced response predictions, system modification predictions, FEM correlation and updating). Specific attention will be paid to data exchange and user interaction requirements. - Validation and Exploitation Throughout the project, focused validations in a variety of different industrial sectors will be performed. These will include road transport, rail transport, air transport and civil structures. The methods will also be validated for use with operational condition-simulation tests (shaker table qualification, chassis dynamometer, street simulator tests, etc.). Using the validation results, a detailed exploitation plan will be prepared and a requirement definition for a commercial products based on the developed prototypes will be provided.
Project ID: 
1 562
Start date: 
Project Duration: 
Project costs: 
2 500 000.00€
Technological Area: 
Market Area: 

Raising the productivity and competitiveness of European businesses through technology. Boosting national economies on the international market, and strengthening the basis for sustainable prosperity and employment.