Current Issue : April-June Volume : 2022 Issue Number : 2 Articles : 5 Articles
With the application of more electric aircraft (MEA) technology, variable frequencies and high power ratings become import features of aero-generators. The brushless synchronous generator, which has a three-stage structure, is the most commonly used type of aero-generator. Due to the variation of operating conditions, the implementation of generator controllers becomes more and more difficult. In this paper, a state space model of a generator is derived and the influence of different operating conditions on the frequency response characteristics of the generator is revealed. Based on a fuzzy PI controller, an additional fuzzy logic controller is applied to modify the PI parameters of the voltage loop by introducing the generator speed to cope with the speed variation. Finally, the results of the simulations and experiments demonstrate that the dual fuzzy PI controller can improve both the steady-state and dynamic performance of the brushless synchronous generator, verifying the previous theoretical study....
In order to study machine translation more in-depth, it is particularly important for the research of artificial intelligence with fuzzy algorithms to convert an unfamiliar language into a mature language. ,e neural network translation model has been developed in recent years and has achieved rich research results. Aiming at the current lack of accuracy of neural machine translation (NMT), which may cause ambiguity, this paper takes English machine translation as an example and proposes an artificial intelligence machine translation optimization model based on fuzzy theory. On the basis of NMTmodel translation, first the semantics of English machine translation is classified, a semantic selection model is built, then the analytic hierarchy process is used to determine the semantic order of English machine translation, and the corresponding fault-tolerant operation is carried out to the error-prone errors, weight the semantics, and introduce the fuzzy theory to arrange the English semantics of English machine translation. Finally, the performance of the model is analyzed through specific application experiments. ,e results show that the accuracy of the machine translation selection permutation model is improved by nearly 4.5% and can reach more than 90% compared with other models, and the timeliness is better than other models, which is improved by nearly 15%, which has obvious advantages....
&e study of engineering geology emphasizes the combination of theory and practice, and it highlights the comprehensive cultivation of curricular theory, curricular practice, and comprehensive skills. It is necessary to establish a set of effective methods to evaluate the achievement of training objectives to track, test, and improve the quality of curricular learning. In this paper, the principle of the fuzzy analytic hierarchy process based on entropy is used to construct an evaluation index system for the goal achievement degree of engineering geology courses, and the primary indicators mainly include knowledge, ability, and quality. Based on the actual situation, five curricular achievement levels are determined, that is, the comment set V� {very low, low, medium, high, very high}. Relying on the engineering geology course resource database of Xuchang University, the course goal achievement degree is evaluated, and the results show that the engineering geology course achievement degree is high. &is method is suitable not only for the evaluation of the achievement of curricular objectives but also for the evaluation of the achievement of engineering education graduation requirements. &is method can also help us find different courses and teaching weak links supporting the index points, indicate the direction and provide support for teachers to continuously improve their teaching and management methods, and effectively promote a continuous improvement in teachers’ teaching level and teaching quality....
Analog electronic circuits play an essential role in many industrial applications and control systems. The traditional way of diagnosing failures in such circuits can be an inaccurate and time-consuming process; therefore, it can affect the industrial outcome negatively. In this paper, an intelligent fault diagnosis and identification approach for analog electronic circuits is proposed and investigated. The proposed method relies on a simple statistical analysis approach of the frequency response of the analog circuit and a simple rule-based fuzzy logic classification model to detect and identify the faulty component in the circuit. The proposed approach is tested and evaluated using a commonly used low-pass filter circuit. The test result of the presented approach shows that it can identify the fault and detect the faulty component in the circuit with an average of 98% F-score accuracy. The proposed approach shows comparable performance to more intricate related works....
Continuous stirring tank reactors are widely used in the chemical production process, which is always accompanied by nonlinearity, time delay, and uncertainty. Considering the characteristic of the actual reaction of the continuous stirring tank reactors, the fault detection problem is studied in terms of the T-S fuzzy model. Through a fault detection filter performance analysis, the sufficient condition for the filtering error dynamics is obtained, which meets the exponential stability in the mean square sense and the given performance requirements. The design of the fault detection filter is transformed into one that settles the convex optimization issue of linear matrix inequality. Numerical analysis shows the effectiveness of this scheme....
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