Proximal-based recursive implementation for model-free data-driven fault diagnosis

We present a novel problem formulation for model-free data-driven fault diagnosis, in which possible faults are diagnosed simultaneously to identifying the linear time-invariant system. This problem is practically relevant for systems whose model cannot be identified reliably prior to diagnosing possible faults, for instance when operating...

High-Speed Tapping Mode AFM Utilizing Recovery of Tip-Sample Interaction

We propose to use the State Estimation by Sum-of-Norms Regularisation (STATESON-)algorithm for recovering the tip-sample interaction in high-speed tapping mode atomic force microscopy (AFM). This approach enables accurate sample height estimation for each independent cantilever oscillation period, provided that the tip-sample interaction...

Data-Driven Fault Diagnosis under Sparseness Assumption for LTI Systems

Model-based fault diagnosis for dynamical systems is a sophisticated task due to model inaccuracies, measurement noise and many possible fault scenarios. By presenting faults in terms of a dictionary, the latter obstacle is recently addressed using well-known techniques for recovering sparse information (e.g. lasso). However, current state-of...

Particle detection using closed-loop active model diagnosis

We demonstrate a novel closed-loop input design technique on the detection of particles in an imaging system such as a fluorescence microscope. The probability of misdiagnosis is minimized while constraining the input energy such that for instance phototoxicity is reduced. The key novelty of the closed-loop design is that each next input is...

Closed-loop active object recognition with constrained illumination power

Some applications require high level of image-based classification certainty while keeping the total illumination energy as low as possible. Examples are minimally invasive visual inspection in Industry 4.0, and medical imaging systems such as computed tomography, in which the radiation dose should be kept “as low as is reasonably achievable”...

Phase retrieval from overexposed PSF: A projection-based approach

We investigate the general adjustment of projection-based phase retrieval algorithms for use with saturated data. In the phase retrieval problem, model fidelity of experimental data containing a non-zero background level, fixed pattern noise, or overexposure, often presents a serious obstacle for standard algorithms. Recently, it was shown...

Closed-Loop Active Model Diagnosis Using Bhattacharyya Coefficient: Application to Automated Visual Inspection

This manuscript presents an improvement of state-of-the-art Closed-Loop Active Model Diagnosis (CLAMD). The proposed method utilizes weighted Bhattacharyya coefficients evaluated at the vertices of the polytopic constraint set to provide a good trade-off between computational efficiency and satisfactory input choice for separation of candidate...