This work evaluates variables affecting wind parameters in order to maximally reduce turbulence and trace. In addition, the position of each wind turbine in a farm and the limits of wind turbines are determined in order to determine an optimal distance between them. To this end, a 150 MW wind farm operating 60 wind turbines was studied. The speed and direction of wind was studied using a wind-measuring installation. An optimal mode of operating a wind farm was calculated using the WindFarmer software produced by DNV GL (Norway). Experiments conducted on a site in the south-east of the Republic of Tatarstan showed its suitability for the construction of a wind power plant: the proximity of electrical networks and the absence of large buildings and forests. The wind shear at different heights (at the levels of anemometers) was found to be 0.2. Wind turbines were selected based on a calculation of power factors, which comprised 47 % for Siemens Gamesa SG 3.4-132 3.465MW, 45 % for Vestas V126-3.45 HTq and 29% for Lagerwey L100-2.5 MW. The conducted analysis of the main external factors (ground profile, average wind speed, distance to electrical networks, etc.) affecting the selection of an optimal site for a wind power plant, as well as the calculation of an average wind shear of 0.2, confirmed the suitability of the site under study. According to the calculated capacity factor, Lagerwey L100 and Siemens Gamesa SG 3.4-132 turbines showed the lowest (2.5 MW) and highest (3.465 MW) values, respectively. However, from an economic point of view, a balance between the turbine’s capacity factor and its cost should be achieved.
The paper discusses the diagnostic method of electromyography, which allows assessing the state of functioning of the nerve that innervates the damaged muscle. The method is based on registration and analysis of bioelectrical potentials of muscles and peripheral nerves. Purpose of the study: develop an algorithm of operation and a structural diagram of an electromyography device with the possibility of converting the recording results to a PC, display and smartphone via USB and bluetooth for their analysis. Materials and methods. A method is proposed for measuring muscle function, which involves observing the movement of muscles from the surface of the skin over the muscle. The muscle sensor gives an output signal depending on its activity. Using a surface electrode, you can track the overall movement of the muscles. Using the program for interfacing the Myoware EMG muscle sensor with the Arduino, we obtain an analog signal. The sensor values can be observed on the serial plotter. The next task was to read the sensor data or analog voltage on the LCD1602 display. We have connected the I2C pins (SDA and SCL) of the LCD1602 to A4 and A5 of the Arduino. LCD1602 module displays 2 lines of 16 characters. After downloading the special code LCD1602 via I2C, the display began to display the value of the EMG analog signal, as well as the voltage. The Arduino can communicate with other devices via Bluetooth using the HC-05 (zs-040) module. This module allows the Arduino to connect and communicate with other devices such as a smartphone, computer or other. Results. Based on the results of the study, an idea was obtained of the bioelectric potential that occurs in the muscle. The applied method of fixation of bioelectrical signals in muscles is of practical importance for clinical neurology; its implementation will facilitate and increase the diagnostic accuracy of electrophysiological studies. Conclusion. In this study, a structural diagram of the device and the solution of a technical problem based on technical requirements have been developed, and an algorithm for the device has been developed. 4,963 rubles were spent on the implementation of practical study taking into account the costs of basic and auxiliary materials, as well as other direct costs.
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