Farkhod Kasimov
@tdtu.uz
Automation of Production Processes
Tashkent State Technical University
RESEARCH INTERESTS
Automation of technological processes, modeling of actuators of control systems
Scopus Publications
Scopus Publications
Jiang Ru, Zhang Dong, Farkhod Kasimov, and Wang Xuelin
Springer Nature Switzerland
Nazir Ikramov, Farkhod Kasimov, Akhmadjon Mukhamadjonov, and Takhir Majidov
EDP Sciences
The article discusses the problems of online monitoring of water metering in the irrigation systems of Central Asia, in particular the Republic of Uzbekistan, and identifies existing problems. The development of intelligent level measurement devices is aimed at solving these problems. A technique has been created for developing an intelligent level measurement device capable of operating stably even under various disturbing influences, considering abrupt climate changes. Based on this method, an intelligent device has been developed that allows online measurement of the water flow and its amount flowing in the channel based on measuring the water level in channels with a constant cross-sectional area. The device has the function of automatic selection of alternative networks for the exchange of information, such as GSM or Lora, depending on the conditions of information transmission over long distances. The device also includes the function of autonomous charging using solar energy in places with no power supply. The industrial sample of the device was tested and certified in laboratory and field conditions and at the National Certification Center of the Republic of Uzbekistan, and permission was obtained for its mass production. Because local manufacturers produce this device, it has advantages over its imported counterpart in terms of low cost, the availability of customization options, and easy adaptation to difficult conditions. In exchange for applying a smart filtering algorithm, the stabilization of received signals is improved by 74.2% due to intelligent filtering algorithms in a smart device. The reliability of information decreased by 8.2% in total. This result is less than the 9.5% target for information reliability.
Shuzhou Dong, Qian Li, Han Gao, Farkhod Kasimov, and Dong Zhang
IEEE
With the development of robot technology, the requirement of target recognition accuracy for depalletizing robot based on lidar is constantly improved. In order to solve the problems of large data acquisition error and low target recognition accuracy caused by environmental interference during lidar operation, a new corner feature extraction method is proposed in this paper. Firstly, based on the anomaly detection LOF algorithm, a data preprocessing method is designed to improve the accuracy of lidar data acquisition.; Then, the Douglas-Pucker algorithm is used for data segmentation to obtain the straight line segment features and corner features of the stacking object boundary. The corner features are further determined by re-judgment method to improve the accuracy of corner features. Finally, this paper designs a comparative experiment based on the data collected by lidar, and the experimental results verify the feasibility of the improved algorithm in this paper in terms of outlier removal and corner feature extraction.
Ru Jiang, Farkhod Kasimov, Dong Zhang, and Kulyash Kaliyeva
IOP Publishing
Abstract This article is dedicated to creating a low-cost intelligent agricultural machinery control equipment based on ATmega 328p chip. The created control device is used to directly connect various peripheral sensors and actuators of the intelligent agricultural machinery to the computer. The controller circuit design diagram is given, and the control method is presented. The accuracy of the signal input/output channels of the control device to transmit signals was verified through experiments, and the control device was applied to the intelligent agricultural machinery experiment platform. The experimental results are analyzed and suggestions for further development of the control device are provided.
Ru Jang, Farkhod Kasimov, Dong Zhang, and Kulyash Kaliyeva
IOP Publishing
Abstract The unmanned agricultural machinery can greatly improve operating efficiency and can cover a large area of farmland operations with very little manpower, which saves agricultural investment costs. In this paper, the hardware and software design of unmanned agricultural machinery are introduced, the unmanned agricultural machine is developed, the autonomous driving experiments in different paths are carried out, and the accuracy of the operation is tested. The results of the experiments show that the unmanned agricultural machinery has high tracking accuracy and can meet the needs of field operations.