Parameters setting of Frequency Converter PI regulation to ensure the vacuum of the milking process

This paper presents regulation of an asynchronous induction motor so as to create a stable vacuum milk pump using Variable Frequency Drive (VFD). Contribution includes providing information about the usage of the VFD, which regulates the activity of an asynchronous induction motor so that the vacuum pump milking machine creates stable vacuum. The paper describes the functional and time dependence of input values and output parameters of frequency converters at changing electric motor speed. For simulation and verification the milking process a mathematical model of the milking machine was created. The simulation was verified in Matlab/Simulink software. The constructed mathematical model showed symmetric regulation. Control model symmetry was verified at the laboratory of milking machine. The possibility to remove the control valve from milking equipment was proven using the measured data. It was found that constant vacuum values can be maintained. A constant vacuum can be maintained by changing vacuum pump speed. This control is of an accepted standard (ISO 5707: 2007). The power saving control values (on the milking equipment) of the VFD were positive throughout the measuring range. The performance of the milking vacuum pump is normally designed from the maximum air consumption of the milking machine at nominal vacuum (50 kPa), and a performance reserve is added to this. This means that the pump is operated between the ranges 7.53 and 15.06 dm(3) s(-1). By using a vacuum pump controlled by a VFD, power savings can be achieved from 32.50% to 54.02% compared to a control valve.Web of Science167art. no. e025342

Design of an IoT-based monitoring system as a part of prevention of thermal events in mining and landfill waste disposal sites: A pilot case study

This case study deals with the design of a hybrid system for the prevention of thermal events in mining waste disposal sites and landfills. The overall design, real imple mentation, optimization, and experimental verification of the functionality of the entire system are described in detail. Both experimental platforms are built on the Internet of Things (long range wide area network (LoRaWAN) and Sigfox) basis and meet the conditions for autonomous long-term on-site monitoring. The data collected are periodically transmitted wirelessly to a database repository, which processes relevant parameters for the operators of dispatching workplaces. The study is focused on a combination of surface and depth measurement methods. The experimental results clearly confirm the functionality of the proposed solutions, which will enable timely interventions and elimination of underground and surface combustions. Thanks to centralized data collection, a unique database has also been created, which can be used for the implementation of prediction algorithms (based, for example, on machine learning or artificial intelligence).Web of Science72art. no. 550011