Sensor and Its Application

Sensor and Its Application

Saifur Rahman (Najran University, Saudi Arabia), Abdullah S. Alwadie (Najran University, Saudi Arabia), S. Hasan Saeed (Integral University, India) and Faizan A. Khan (Integral University, India)
DOI: 10.4018/978-1-5225-6989-3.ch013
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Electronic nose systems are used to deliver a pattern response to a listed odor, and pattern recognition software is used to perform odor recognition and discrimination by using a series of sensors. The method of electronic noses generally includes time taking measurements in a non-standard test and error process. The sensory panel problem can be solved by electronic nose. For this purpose, a sensor model is used to design sensor array. The generated signal of these sensor array is used further to classify a mixture of two gases using principle component analysis (PCA)-based classification analysis. During classification, the efficiency of PCA classification has been checked over the different signal preprocessing technique. Continuous real monitoring of odor is done at specific sites in the field over hours, days, weeks, or even months. An electronic machine can also avoid many other troubles linked with the employ of human panels. Each and every variability, adaptation (becoming minimum sensitive during extended exposure), and revelation to hazardous compounds all come to mind.
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Description Of Error Models

Figure 1 shows sensor A, B, C and D are designed at different parameters. Figure 2 shows the block diagram of the designed sensor and figure 3 shows the Simulink model for mixture of two gases for each sensor in which the sensor parameter used for feature extraction is sensor element conductance Gs. Feature evaluation Gs is evaluated using following equation:

GS = G0Te-EA0/KT + K1Te-EA1/KTC1n1KT + K 2Te-EA2/KTC2n2KT +… KmixTe- EAmix/KTC1n1KTC2n2KT(1)
  • (Llobet et al., 2001)

Where K = Boltzmann‘s constant, T = Absolute Temperature, C1 & C2 =Concentration of gas1 & gas2, K1T &K2T= pre exponential factors of sensitivities to ethanol and methane, n1 & n2= pre factors of power law exponent for oxides, Kmix= pre exponential factor of the change in conductance caused by the interaction of the two species, EA= activation energies (Llobet et al., 2001). The dependence on the baseline and power law factor on the temperature has been studied elsewhere (Clifford & Tuma, 1983; Vilanova et al., 1998).

Figure 1.

Sensor Array Simulink Model for four different sensors

Figure 2.

Block diagram of designed sensor

Figure 3.

Simulink model for mixture of two gases for each sensor


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