An electronic nose is an intelligent system consists of a sensor network and a pattern recognition system able to know simple and complex odors. As the human nose, the artificial nose must learn to recognize different...
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ISBN:
(纸本)9781467364591
An electronic nose is an intelligent system consists of a sensor network and a pattern recognition system able to know simple and complex odors. As the human nose, the artificial nose must learn to recognize different odors: the learning phase. There are several types of sensors such as fiber optic sensors, piezoelectric sensors, sensor type MOSFET. The performance of the sensor network is discussed by using pattern recognition methods. In this article, we tested Principal Component Analysis (PCA) to evaluate the ability of our sensor array to distinguish between different groups of target gases according to their nature: only in binary mixture and ternary mixture.
In this paper,we introduce an echo state network(ESN) model approach for gas concentration estimation using Metal Oxide(MOX) sensors in Open Sampling System(OSS).Our approach focuses on the compensation of the slow re...
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In this paper,we introduce an echo state network(ESN) model approach for gas concentration estimation using Metal Oxide(MOX) sensors in Open Sampling System(OSS).Our approach focuses on the compensation of the slow response of MOX sensors,while concurrently solving the problem of estimating the gas concentration in *** comparing with S VR algorithm model commonly used in the prediction system,it fully reflects high accuracy of the gas prediction model based on ESN algorithm and the well tracking performance with rapidly changing gases.A prediction model based on ESN can overcome these limitations because of its nonlinear and implicit storage *** this paper,the concentration and variation of gas mixture are predicted successfully.
Accurate and rapid control of the temperature of electric heating furnace in industrial production has important practical significance and application value. In this paper, the electric heating furnace temperature co...
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Accurate and rapid control of the temperature of electric heating furnace in industrial production has important practical significance and application value. In this paper, the electric heating furnace temperature control system is designed based on C51 microcontroller, equipped with temperature sensors, AD conversion module and display module. The PWM control signal, generated by the microcontroller, is used to controlling the working time of the heating resistance wire and the average power output of the resistance wire. the incremental PID algorithm is adopted to realize the temperature control of the electric heating furnace. Experiments show that: in the 0-500 ℃ range, electric heating furnace temperature control time is 60 s, temperature control relative error of up to 1%. The system has the characteristics of low hardware cost, high temperature control accuracy, good reliability and strong anti-interference ability.
In this paper, an active single-object localization system with U-shaped ultrasonic module array is presented. The proposed algorithm in this system has two stages. The first stage is time-of-flight (TOF) estimation o...
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In this paper, an active single-object localization system with U-shaped ultrasonic module array is presented. The proposed algorithm in this system has two stages. The first stage is time-of-flight (TOF) estimation of reflected ultrasonic signals. We analyze several distortion cases of reflection signals and provide solutions to improve the performance of TOF estimation. The second stage is TOF-based object localization. A good localization algorithm can suppress the problems caused by inaccurate TOF estimation and improve the accuracy of target positioning. We propose two object-localization algorithms to estimate the object location. One is the unconstrained least-squares method, and the other is the constrained weighted least-squares method based on the eigenvalues-analyzing technique. The simulation results suggest that the performance of the proposed constrained weighted method is better than that of the unconstrained method. In addition, the median smoother and the outlier exclusion scheme are implemented in the overall system to make the object location estimation more stable. The performance of the proposed system is confirmed by the experiment results, which show that the single-object localization has a considerable degree of accuracy and stability.
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