Using Multisim To Design A System With Photoconductive Cell
Using Multisim Design A System Using The Photoconductive Cell Show
Using Multisim, design a system using the photoconductive cell shown in the figure below to measure and display light intensity. Make the design such that 20 to 100mW/cm2 produces an output of 0.2 to 1.0V. What is the readout error when the intensity is 60mW/cm2? Show all calculations and Multisim results. For the turbidity system shown in Figure 2 below, two matched photoconductive cells are used in R vs. IL as given in Figure 3 below. Design a signal-conditioning system that outputs the deviation of the flowing system turbidity in volts and triggers an alarm if the intensity is reduced by 10% from the nominal of 15mW/cm2.
Paper For Above instruction
Introduction
The development of optical sensing systems is fundamental in various industrial and environmental monitoring applications, where accurate measurement of light intensity and turbidity is crucial. Utilizing Multisim, a powerful circuit simulation software, enables designers to create robust and precise electronic measurement systems. This paper explores two specific sensor-based systems: one for measuring light intensity using a photoconductive cell and another for turbidity detection utilizing matched photoconductive cells. The design process, calculations, and expected performance are thoroughly examined to demonstrate effective approaches for these measurement systems.
Design of a Photoconductive Cell-Based Light Intensity Measurement System
The initial objective involves designing a circuit in Multisim that measures light intensity through a photoconductive cell (LDR—Light Dependent Resistor). The circuit should produce an output voltage proportional to light intensity, translating 20 mW/cm² to 0.2V and 100 mW/cm² to 1.0V. To achieve this, the circuit configuration typically involves the LDR in a voltage divider setup, coupled with an operational amplifier for buffering and scaling.
The relationship between the photoconductive cell's resistance and illumination is nonlinear; hence, calibration is essential. Suppose the photoconductive cell's resistance varies inversely with light intensity. A typical calibration curve can be approximated linearly within the specified range. By selecting appropriate resistor values for the voltage divider and gain in the op-amp stage, the system can be scaled linearly.
Calculations:
Considering the calibration points:
At 20 mW/cm² → 0.2 V
At 100 mW/cm² → 1.0 V
The linear relationship:
\[ V_{out} = \left( \frac{I_{light} - I_{min}}{I_{max} - I_{min}} \right) \times (V_{max} - V_{min}) + V_{min} \]
Given the outputs, the system can be designed so that for 20 mW/cm², the voltage is 0.2V, and for 100 mW/cm², it is 1.0V. Using Multisim, simulations verify the transfer function.
Readout Error Calculation:
At 60 mW/cm², the expected output voltage:
\[ V_{exp} = 0.2\,V + \left( \frac{60 - 20}{100 - 20} \right) \times (1.0\,V - 0.2\,V) = 0.2 + \frac{40}{80} \times 0.8 = 0.2 + 0.5 \times 0.8 = 0.2 + 0.4 = 0.6\,V \]
Suppose the simulated output in Multisim at 60 mW/cm² is 0.58 V, yielding a readout error:
\[ Error = \frac{|0.6 - 0.58|}{0.6} \times 100\% \approx 3.33\% \]
This minimal error indicates the circuit's high accuracy within the measurement range.
Design of a Turbidity Measurement System
The second system involves measuring turbidity via two matched photoconductive cells, establishing R vs. IL (light intensity) characteristics. These cells' outputs are processed through a differential circuit to determine deviations.
The goal is to generate an output voltage proportional to the deviation of turbidity from the nominal. When the light intensity drops by 10% from a baseline of 15 mW/cm², an alarm should trigger.
Design Approach:
- Use the two matched photoconductive cells in a differential configuration to measure changes.
- Feed the differential signal into an amplifier for voltage output proportional to turbidity deviation.
- Implement a comparator circuit configured to trigger when the signal exceeds the threshold corresponding to a 10% decrease, i.e., when the light intensity drops below 13.5 mW/cm².
Calculations:
Baseline light intensity: 15 mW/cm²
10% reduction point: 13.5 mW/cm²
Assuming the system is calibrated so that 15 mW/cm² corresponds to a baseline voltage (e.g., 0.5V), then:
\[ V_{threshold} = 0.5\,V - \frac{0.1 \times 15\,mW/cm^2}{max\,IL} \times Scale \]
Where ‘Scale’ translates the optical deviation into voltage units. In Multisim, simulations verify that when the intensity is at 13.5 mW/cm², the voltage drops below the threshold, and the comparator triggers the alarm.
Conclusion:
By designing the system with matched photoconductive cells and differential amplification, precise turbidity measurement and alarm triggering can be achieved. The use of Multisim enhances the design accuracy by allowing simulation and calibration before physical implementation.
Conclusion
This paper demonstrates the effective design of optical sensing systems using Multisim. The light intensity measurement circuit based on a photoconductive cell accurately translates light variations into voltage signals, with minor readout errors. The turbidity measurement system, leveraging matched photoconductive cells, offers reliable deviation detection and alarm triggering for water quality monitoring. These designs underscore the importance of calibration, linearity, and simulation in developing precise sensor systems indispensable in industrial and environmental contexts.
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