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The article deals with the diagnostics of components surface after painting by camera system in real-time. This solution is especially suitable for implementation to automatized production line above the conveyor belt. The faults on the part surface can be detected as scratches, imperfect surface coverage and dirt stuck to the surface. The scratch detection is based on edge detectors, imperfect coverage are checked by histogram comparison and all other errors are detected by counter detectors. The developed software uses open source library OpenCV and is written in C++ language. The software solution is platform independent. Final algorithm is implemented to embedded device based on SoC.

Pneumatic artificial muscles belong to a category of nonconventional pneumatic actuators that are distinctive for their high power/weight ratio, simple construction and low price and maintenance costs. As such, pneumatic artificial muscles represent an alternative type of pneumatic actuator that could replace the traditional ones in certain applications. Due to their specific construction, PAM-based systems have nonlinear characteristics which make it more difficult to design a control system with good performance. In the paper, a gray-box model (basically analytical but with certain experimental parts) of the one degree-of-freedom PAM-based actuator is derived. This model interconnects the description of pneumatic and mechanical part of the system through a set of several nonlinear differential equations and its main purpose is the design of intelligent control system in simulation environment. The model is validated in both open-loop and closed-loop mode using the measurements on real plant and the results confirm that model performance is in good agreement with the performance of real actuator.

This paper deals with usability of MEMS sensors for diagnostics of mechatronics system state wirelessly. We can acquire basic kinematics and dynamics mechanism parameters (spatial position, speed, acceleration, vibration, angular rate, orientation, etc.) and some environment condition (local/remote temperature, humidity, pressure, electromagnetic noise) by MEMS sensors. Acquired data are sent to remote application in desktop computer. This system can replace expensive and separate diagnostic tools by small integrated solution with one wireless communication interface (with limitation of MEMS sensors precision). This solution can be battery powered with long operation time, because there is used new wireless technology based on Bluetooth 4 protocol (Low Energy/Smart Bluetooth). Some of integrated MEMS sensors measures same variable on different measuring principle. For example angle can be acquired from three different sensors: magnetometer, accelerometer or gyroscope. Combination of these sensor data can significantly improve value accuracy. The designed diagnostic tool can serve as an inertia measuring unit IMU or Wireless IMU (WIMU).

This article describes the vision system, which is designed for diagnostics of defects in casted products. In the first part an overview about image processing, edge and pattern recognition algorithms and current status in available free and commercial vision libraries is found. For the described task we selected open source Aforge .NET library. The next part describes common defects in casted products. Modular education system MPS 500 from Festo with conveyor and palette with plastic parts is used for simulation of production system. This system contains an industrial robot which can be used for sorting defective parts. The selected vision library is used for two level diagnostics of algorithm implementation. The first level algorithm detects position of part, its dimensions and edge disturbances. The second algorithm detects any defects inside of a part. The basic algorithm is presented only for circular shape with red color texture, but can be easily extended to other basic shapes by shape detector.