scholarly journals Errors classification method for electric motor torque measurement

2021 ◽  
Vol 4 (1(60)) ◽  
pp. 42-48
Author(s):  
Mykola Kulyk ◽  
Volodymyr Kvasnikov ◽  
Dmytro Kvashuk ◽  
Anatolii Beridze-Stakhovskyi
Keyword(s):  
Electric Motor ◽  
Strain Gauge ◽  
High Speed ◽  
Supply Voltage ◽  
Frequency Converter ◽  
Influence Factors ◽  
Nearest Neighbors ◽  
Measuring Instruments ◽  
Maximum Deviation ◽  
K Nearest Neighbors

The use of high-precision measuring instruments for determining the torque of electric motors in such areas as medicine, motor transport, shipping, aviation requires the improvement of the metrological characteristics of measuring instruments. This, in turn, requires an accurate assessment of their error. Of particular importance is the measurement of power at high-speed installations, where in some cases conventional measurement systems are either unsuitable or have low accuracy. Thus, the use of high-speed turbomachines in aviation, transport, and rocketry creates an urgent need for the development of high-quality measuring instruments for conducting precise research. In turn, in the absence of means for accurately determining the error, attempts are made to predict them. This makes it possible to timely identify the influence of many factors on the accuracy of measuring instruments. The increase in the error arises, as a rule, through abrupt changes in the measurement conditions. Such errors are unpredictable, and their significance is difficult to predict. In the course of the study, the K-nearest neighbors method was used, to establish criteria for which a gross error may occur. The results obtained make it possible to establish threshold values at which the maximum deviation can be established under various conditions of the experiment. In a computational experiment using the K-nearest neighbors method, the following factors were investigated: vibration; temperature rise of measuring sensors; instabilities in the supply voltage of the electric motor, which affect the accuracy of the strain gauge and frequency converter. As a result, the maximum errors were obtained depending on the indicated influence factors. It has been experimentally confirmed that the K-nearest neighbors method can be used to classify deviations of the nominal value of the error of measuring instruments under various measurement conditions. A metrological stand has been developed for the experiment. It includes a strain gauge sensor for measuring torque and a photosensitive sensor for measuring the speed of the electric motor. Signal conversion from these sensors is implemented on the basis of the ESP8266 microcontroller

scholarly journals SYNCHRONOUS ELECTRIC MOTOR WITH HIGHER SPEED ROTATION AND BALANCED ROTOR

2021 ◽  
pp. 19-26
Author(s):  
Anatoly Yu. Afanasyev ◽  
Valeriy G. Makarov ◽  
Alexey A. Petrov ◽  
Pavel F. Kruglov
Keyword(s):  
Electric Motor ◽  
High Speed ◽  
Rotation Speed ◽  
Supply Voltage ◽  
Structural Features ◽  
Output Shaft ◽  
Stator Winding ◽  
Dynamic Balancing ◽  
High Speed Engine ◽  
Urgent Task

Increasing the speed of rotation of electric motors is an urgent task for turbine mechanisms – pumps, fans, compressors. Traditional synchronous motors have a rotation speed that is less than or equal to the frequency of the supply voltage. The article proposes a design and considers the principle of operation of a synchronous electric motor with double rotation speed. It has three reluctance rotors with one pole, for static and dynamic balancing, and the stator winding is supplied with voltages out of phase by π/6. The proposed design of a synchronous motor with eighteen phases of the stator winding and, with three rotors, the axes of which are offset relative to the axis of rotation of the output shaft. The use of such a design makes it possible to double the rotation speed of the output shaft in comparison with the frequency of the supply voltages. A description of the principle of operation of the motor and its mathematical description are given, taking into account the structural features of the stator-rotor magnetic circuit. The main advantage of the proposed engine in comparison with a high-speed engine is static and dynamic balancing.

Temperature Rise Prediction of Oil-Air Lubricated Angular Contact Ball Bearings Using Artificial Neural Network

2019 ◽  
Vol 12 (3) ◽  
pp. 248-261
Author(s):  
Baomin Wang ◽  
Xiao Chang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Temperature Rise ◽  
High Speed ◽  
Ball Bearing ◽  
Influence Factors ◽  
Ball Bearings ◽  
Ann Model ◽  
Angular Contact Ball Bearing ◽  
Artificial Neural

Background: Angular contact ball bearing is an important component of many high-speed rotating mechanical systems. Oil-air lubrication makes it possible for angular contact ball bearing to operate at high speed. So the lubrication state of angular contact ball bearing directly affects the performance of the mechanical systems. However, as bearing rotation speed increases, the temperature rise is still the dominant limiting factor for improving the performance and service life of angular contact ball bearings. Therefore, it is very necessary to predict the temperature rise of angular contact ball bearings lubricated with oil-air. Objective: The purpose of this study is to provide an overview of temperature calculation of bearing from many studies and patents, and propose a new prediction method for temperature rise of angular contact ball bearing. Methods: Based on the artificial neural network and genetic algorithm, a new prediction methodology for bearings temperature rise was proposed which capitalizes on the notion that the temperature rise of oil-air lubricated angular contact ball bearing is generally coupling. The influence factors of temperature rise in high-speed angular contact ball bearings were analyzed through grey relational analysis, and the key influence factors are determined. Combined with Genetic Algorithm (GA), the Artificial Neural Network (ANN) model based on these key influence factors was built up, two groups of experimental data were used to train and validate the ANN model. Results: Compared with the ANN model, the ANN-GA model has shorter training time, higher accuracy and better stability, the output of ANN-GA model shows a good agreement with the experimental data, above 92% of bearing temperature rise under varying conditions can be predicted using the ANNGA model. Conclusion: A new method was proposed to predict the temperature rise of oil-air lubricated angular contact ball bearings based on the artificial neural network and genetic algorithm. The results show that the prediction model has good accuracy, stability and robustness.

scholarly journals Tropical Balls and Its Applications to K Nearest Neighbor over the Space of Phylogenetic Trees

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 779
Author(s):  
Ruriko Yoshida
Keyword(s):  
Supervised Learning ◽  
Phylogenetic Trees ◽  
Nearest Neighbor ◽  
Nearest Neighbors ◽  
High Dimensional ◽  
Learning Method ◽  
Dimensional Vector ◽  
K Nearest Neighbor ◽  
K Nearest Neighbors

A tropical ball is a ball defined by the tropical metric over the tropical projective torus. In this paper we show several properties of tropical balls over the tropical projective torus and also over the space of phylogenetic trees with a given set of leaf labels. Then we discuss its application to the K nearest neighbors (KNN) algorithm, a supervised learning method used to classify a high-dimensional vector into given categories by looking at a ball centered at the vector, which contains K vectors in the space.

A High-Speed Temperature Sensor with Low Supply Sensitivity for SoC Thermal Monitoring

2018 ◽  
Vol 27 (07) ◽  
pp. 1850116
Author(s):  
Yuanxin Bao ◽  
Wenyuan Li
Keyword(s):  
Temperature Sensor ◽  
Conversion Rate ◽  
High Speed ◽  
Supply Voltage ◽  
Ring Oscillator ◽  
Temperature Sensitive ◽  
Cmos Process ◽  
Digital Code ◽  
Thermal Monitoring ◽  
Worst Case

A high-speed low-supply-sensitivity temperature sensor is presented for thermal monitoring of system on a chip (SoC). The proposed sensor transforms the temperature to complementary to absolute temperature (CTAT) frequency and then into digital code. A CTAT voltage reference supplies a temperature-sensitive ring oscillator, which enhances temperature sensitivity and conversion rate. To reduce the supply sensitivity, an operational amplifier with a unity gain for power supply is proposed. A frequency-to-digital converter with piecewise linear fitting is used to convert the frequency into the digital code corresponding to temperature and correct nonlinearity. These additional characteristics are distinct from the conventional oscillator-based temperature sensors. The sensor is fabricated in a 180[Formula: see text]nm CMOS process and occupies a small area of 0.048[Formula: see text]mm2 excluding bondpads. After a one-point calibration, the sensor achieves an inaccuracy of [Formula: see text][Formula: see text]1.5[Formula: see text]C from [Formula: see text]45[Formula: see text]C to 85[Formula: see text]C under a supply voltage of 1.4–2.4[Formula: see text]V showing a worst-case supply sensitivity of 0.5[Formula: see text]C/V. The sensor maintains a high conversion rate of 45[Formula: see text]KS/s with a fine resolution of 0.25[Formula: see text]C/LSB, which is suitable for SoC thermal monitoring. Under a supply voltage of 1.8[Formula: see text]V, the maximum energy consumption per conversion is only 7.8[Formula: see text]nJ at [Formula: see text]45[Formula: see text]C.

scholarly journals Privacy-Enhancing k-Nearest Neighbors Search over Mobile Social Networks

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3994
Author(s):  
Yuxi Li ◽  
Fucai Zhou ◽  
Yue Ge ◽  
Zifeng Xu
Keyword(s):  
Social Networks ◽  
Access Control ◽  
Location Privacy ◽  
Nearest Neighbors ◽  
Search Pattern ◽  
Broadcast Encryption ◽  
Mobile Social Networks ◽  
K Nearest Neighbors ◽  
Fine Grained ◽  
Server Architecture

Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive L-semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.

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