Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.

Development of a state-variable filter for a motion control application.

In collaboration with G.D. SpA I attended an internship with the purpose of developing a filter for the position control of industrial machines during testing and maintenance operations. The filter elaborates a signal in position provided by an electonic handwheel, in order to enable the application to be controlled with a signal in velocity with arbitrarily dynamics chosen during the design phase. Limiting the dynamics of the filter provide a more stable and less demanding reference trajectory which reduce the vibrations and tracking errors of the motor controlled by it. It also prevents misusages of the handwheel from the technician which could end up in harmful interferences between the mechanical parts moved by the handwheel.

Study of an advanced transport system exploiting magnetic levitation: the Beckhoff XPlanar

The transport system is one of the most important components to be chosen in the design of an automatic machine. There is a wide variety of different choices that can be made in picking this element, each one having its own strengths and its own drawbacks. If it is desired to obtain some elaborate behaviour from the transport system, it is a good idea to think about some flexible and advanced solutions. Among these transport systems, the newest is the Beckhoff XPlanar. This transport system exploits magnetic levitation to move some passive magnetic movers on a completely customizable plane, in an entirely contact-free way. This provides a fast, clean, and noiseless motion, which is extremely desirable in a modern automatic machine. The purpose of this Thesis is to analyse the potentialities and the problems of this new device, starting from the basics. After having presented in detail the topic, an analysis on the hardware components needed to build this system is performed. Then, it is conducted a study on the concepts needed to know how to build a controller having the purpose of dealing with this system. After that, the various types of motion are studied and executed and, later on, some experiments on the real kit are carried out. These studies start from the diagnostic and involve other analyses that are used to test the limits of this transport system. In performing these analyses, it is noticed how the kit presents some problems in reaching the limits of the dynamics. Finally, two different types of station cycle are implemented, which are useful to get a rough idea on the potentialities of this new advanced transport system.

Axis control optimization: autotuning techniques and frequency response analysis of industrial mechatronic systems

In the field of industrial automation, there is an increasing need to use optimal control systems that have low tracking errors and low power and energy consumption. The motors we are dealing with are mainly Permanent Magnet Synchronous Motors (PMSMs), controlled by 3 different types of controllers: a position controller, a speed controller, and a current controller. In this thesis, therefore, we are going to act on the gains of the first two controllers by going to find, through the TwinCAT 3 software, what might be the best set of parameters. To do this, starting with the default parameters recommended by TwinCAT, two main methods were used and then compared: the method of Ziegler and Nichols, which is a tabular method, and advanced tuning, an auto-tuning software method of TwinCAT. Therefore, in order to analyse which set of parameters was the best,several experiments were performed for each case, using the Motion Control Function Blocks. Moreover, some machines, such as large robotic arms, have vibration problems. To analyse them in detail, it was necessary to use the Bode Plot tool, which, through Bode plots, highlights in which frequencies there are resonance and anti-resonance peaks. This tool also makes it easier to figure out which and where to apply filters to improve control.