Diplomová práce se zabývá studií bezkontaktní a neinvazivní metody pro odhad tepové frekvence z barevných změn obličeje. Bezkontaktní měření je založeno na sn&#...
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Diplomová práce se zabývá studií bezkontaktní a neinvazivní metody pro odhad tepové frekvence z barevných změn obličeje. Bezkontaktní měření je založeno na snímání osob videokamerou a ze získaných obrazových sekvencí jsou vhodným přístupem získány hodnoty tepové frekvence. Teoretická část práce je věnována popisu tepové frekvence a metod vedoucích k měření tepové frekvence z barevných změn v obličeji. Také obsahuje hodnocení sledovacích algoritmů. Praktická část se zabývá popisem programu k bezkontaktnímu měření tepové frekvence a jeho programové řešení. Zároveň práce obsahuje statistické vyhodnocení funkčnosti tohoto řešení.
The paper presents a new approach for a machine vibration analysis and health monitoring combining blind source separation (BSS) and change detection in source signals. So, the problem is translated from the space of ...
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The paper presents a new approach for a machine vibration analysis and health monitoring combining blind source separation (BSS) and change detection in source signals. So, the problem is translated from the space of the measurements to the space of independent sources, where the reduced number of components simplifies the monitoring problem and where the change detection methods are applied for scalar signals. The approach has been tested in simulation and the assessment on a real machine is presented in the last part of the paper.
When dealing with UAV path planning problems, evolutionary algorithms demonstrate strong flexibility and global search capabilities. However, as the number of UAVs increases, the scale of the path planning problem gro...
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When dealing with UAV path planning problems, evolutionary algorithms demonstrate strong flexibility and global search capabilities. However, as the number of UAVs increases, the scale of the path planning problem grows exponentially, leading to a significant rise in computational complexity. The Cooperative Co-Evolutionary algorithm (CCEA) effectively addresses this issue through its divide-and-conquer strategy. Nonetheless, the CCEA needs to find a balance between computational efficiency and algorithmic performance while also resolving convergence difficulties arising from the increased number of decision variables. Moreover, the complex interrelationships between the decision variables of each UAV add to the challenge of selecting appropriate decision variables. To tackle this problem, we propose a novel collaborative algorithm called CCEA-ADVS. This algorithm reduces the difficulty of the problem by decomposing high-dimensional variables into sub-variables for collaborative optimization. To improve the efficiency of decision variable selection in the collaborative algorithm and to accelerate the convergence speed, an adaptive decision variable selection strategy is introduced. This strategy selects decision variables according to the order of solving single-UAV constraints and multi-UAV constraints, reducing the cost of the optimization objective. Furthermore, to improve computational efficiency, a two-stage evolutionary optimization process from coarse to fine is adopted. Specifically, the Adaptive Differential Evolution with Optional External Archive algorithm (jade) is first used to optimize the waypoints of the UAVs to generate a basic path, and then, the Dubins algorithm is combined to optimize the trajectory, yielding the final flight path. The experimental results show that in four different scenarios involving 40 UAVs, the CCEA-ADVS algorithm significantly outperforms the Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Artificial Bee Colon
This work presents the latest advances in ultrasonic testing of concrete structures based on the independent component analysis (ICA) method. This approach has already been successfully applied in other areas of ultra...
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This work presents the latest advances in ultrasonic testing of concrete structures based on the independent component analysis (ICA) method. This approach has already been successfully applied in other areas of ultrasonic testing. Its advantage when compared to other methods is the possibility to separate overlapping ultrasonic returns from closely spaced reflectors by analyzing only few measurements in real time and to locate reflectors using simple triangulation. Experiments were carried out to analyze the efficiency and practical relevance of the jade algorithm. Investigations were performed on polyamide and concrete test objects. The performance of the jade algorithm is evaluated by the quality of separation of multi-channel ultrasonic measurements. The extracted components include signal parts which correlate with the corresponding echo signals in the measurement. Further investigations are planned where the ICA method in combination with the phased array beamforming technique and a suitable transmitter-receiver concept will be used to increase the information gained during ultrasonic non-destructive testing.
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