Sensors output

Modern subsea trees, manifolds, (EH), etc., are commonly controlled via a complex Electro-Hydraulic System. Electricity is used to power the control system and to allow for communication or command signalling between surface and subsea. Signals sent back to surface will include, for example, subsea valve status and pressure/ temperature sensor outputs. Hydraulics are used to operate valves on the subsea facilities (e.g. subsea tree and manifold valves). The majority of the subsea valves are operated by hydraulically powered actuator units mounted on the valve bodies. 

Because of the wide range of the sensors, only four different sensor units are needed to cover the entire range of dp spans from 100 kN/m2 to 20 MN/m2 (4 in water to 3000 lb/in2) An internal temperature sensor monitors the temperature of the pressure sensor and is used to compensate the sensor output for the effects of temperature changes. The sensor temperature may also be transmitted digitally for monitoring, alarming, and for other appropriate applications. 

It is worth remarking that a gas sensor array is a mere mathematical construction where the sensor outputs are arranged as components of a vector. Arrays can also be utilized to investigate the properties of chemical sensors, or even better, the peculiar behaviour of a sensor as a component of an array. In this chapter, the more common sensor array methodologies are critically reviewed, including the most general steps of a multivariate data analysis. The application of such methods to the study of sensor properties is also illustrated through a practical example. 

Consider an SBR array with N sensors and M pulses. If the incoming wavefront makes an azimuth angle az and elevation angle Oel with reference to the array, define the first sensor output to be x t) and... 

In this experiment, you will become familiar with an instrumentation amplifier circuit that is used to amplify weak sensor output signals. 

Fig. 5.12. Sensor responses upon exposure to different concentrations of CO at a hotpiate tem-peratrue of 275 °C and 40% reiative hmnidity. A higher sensor signai corresponds to a iower resistance vaiue of the sensitive iayer. The digitai sensor output from 200 to 280 covers a resistance range from 250 to 50 kfi...

When a chemical or biochemical reaction takes place in the sensor area, only the light that travels through this arm will experience a change in its effective refractive index. At the sensor output, the intensity (I) of the light coming from both arms will interfere, showing a sinusoidal variation that depends on the difference of the effective refractive indexes of the sensor (Neff,s) and reference arms (Neff,R) and on the interaction length (L) ... 

Figure 4. Theoretical sensor output as a function of the air-fuel ratio...

Sensor output during core of e"x w at [he 64th ply of the composite... 

Figure 4.6 Plot of e" x a> versus time of the sensor output at the sixty-fourth ply of the thick epoxygraphite laminate during cure in the autoclave...

Figure 4.7 shows the correlation between the viscosity and the ionic mobility based on isothermal runs for this system as monitored by the value of e" (5 kHz). A representative calibration curve relating the FDEMS sensor output to degree of cure is shown in Figure 4.8. Unlike viscosity, separate calibration curves for different temperatures must be generated from the isothermal runs because they are temperature dependent.

The sensor output can be used to test the validity of processing models such as the Loos-Springer model [30]. Sensor measured values of t] can be compared with the Loos-Springer model predictions. Figure 4.14 is a comparison of the model s predictions and the measured values at the sixty-fourth ply. Agreement in the viscosity s time dependence and magnitude with the predictions of models is essential if the model is to be verified and used with confidence. 

These results are obtained from the FDEMS sensor output as shown in Figure 4.16 and using the calibration plots such as shown in Figure 4.7. Wetout times at the nine sensor locations shown in Figure 4.17 are ... 

Figure 4.21 shows the sensor output for the smart automated sensor expert system-controlled run. The resin reached the center sensor at 37 min. The viscosity is maintained at a low value by permitting slow increases in the temperature. At 60 min, fabric impregnation was complete. The resin was advanced during a 121 °C hold to a predetermined value of degree of cure of 0.35, based on the Loos model s predictions of the extent of the exothermic effect. This value of a is clearly dependent on panel thickness. Then at 130 min, the ramp to 177°C was begun. Achievement of an acceptable complete degree of cure was determined by the sensor at 190 min. Then the cure process was shut down. 

Figure 4.21 Sensor output for the smart automated sensor expert system-controlled run...

The objective of the Springer KBES is twofold To ensure a high-quality part in the shortest autoclave curing cycle duration. This KBES is similar to QPA in that sensor outputs are combined with heuristics not with an analytical curing model. The rules for compaction dictate that dielectrically measured resin viscosity be held Constant during the First temperature hold in the autoclave curing run. The autoclave temperature is made to oscillate about the target hold temperature in an attempt to attain constant viscosity. Full pressure is applied from the cure cycle start. 

The direct transformation from the output pattern to the taste quality was performed here as one trial of expressing the actual human sensation using the output electrical pattern. A similar trial was done for evaluation of the strengths of sourness and saltiness, which will be mentioned later. These two trials depend on the utilization of simple transformation equations by extracting typical properties of output patterns. This method is effective if some data on sensory tests, using humans as a standard, can be obtained to compare with the sensor outputs. However, the expressions for the tastes of beer are obscure because they are not described by the five basic taste qualities. The purpose of the application of the taste sensor is also to express these kinds of obscure terms of human sense in scientific terms. 

Figure 18. Degree of sourness defined by tartaric acid concentration using the sensor output (a) and comparison between the sensor and humans (b).

Approximations (3) and (4) would be the most serious for enzymatic sensors in which the sensor output is related to the change of pH, because for such sensors the buffer capacity would have to be low and constant. However, for sensors that use some other reactants/products besides hydrogen ion, a large excess of buffer would mitigate the effects of these assumptions. To some extent, they can be also mitigated by the experimental design, as we show later. 

Nevertheless, we still cannot identify which sensor is correct. For that, we need to go to the third-order level by performing, for example, a preseparation. If the two sensors are placed at the outlet of a chromatographic column, the signal for the pure sample is shown in Fig. 10.3a and the contaminated sample is shown in Fig. 10.3b. There, the retention time for pure standards Irs is different from the retention time for the interferant tfa, which strongly affects the response of the ISE but does not affect the optical sensor output to a significant degree. One such interference could be, for example, a different ionic strength of the unusual ... 

In the device of Fig.6a (sensor with distributed cavity), depending on the dimensions of the pores of the diffusion barrier, the oxygen diffusion can be bulk diffusion or Knudsen diffusion(ll). In the former case, the sensor output (limiting current Ig) is given by Eq. (9). Knudsen diffusion occurs when the average pore diameter is much smaller than the mean free path of the gas molecules, in which case collisions between molecules and pore walls are the dominant events. In this case(121. Dq -k T /2,and... 

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