ME-120_ Loadcell-1

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Load Cell Praxedo P. Gacrama III ME120 Experimental Methods Laboratory Section 03 Experimental Date: March 18, 2024 March 25, 2024 0

Abstract The goal of this experiment is to examine the correlation between the load applied by the user and the measured strain from the strain gauge load cell to allow for the experimental calibration of the load cell. The load cell is a device that converts the load into a corresponding electrical signal that is readable using the DAQ Assistant. The experiment includes the amplification and smoothing of the signal so that the signal or results can be accurately examined. By applying specific loads to the strain gauge, one is able to linearly fit, (y=Kx+b), the output voltage in response to the applied load by relating the strain to force, Hooke’s law and the beam bending normal stress equations. Separating force into F*m, one is able to find the proportionality constant (K) which is the slope in this case. The strain gauge generates a signal even when it is unloaded, so there is an offset voltage (b) that must be considered as well. 1

Table of Contents I. Summary…………………………………………………………………………………..2 II. Introduction………………………...…………………………………………………4-5 III. Apparatus and Test Procedure….……………………………………………………….6-7 IV. Results……………………….……………………………………………………...…..8-9 V. Conclusions and recommendations………………………………………………………10 VI. References………………………………………………………………………………..11 VII. Appendices………………………………………………………………………….12-13 2

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Summary The experiment focuses on understanding strain gauge load cells and implementing signal conditioning techniques for signal enhancement. By interfacing a strain gauge load cell with a data acquisition device, students learn to attenuate noise, smooth signals, and experimentally calibrate the load cell. The load cell converts force into electrical signals, utilizing strain gauges that exhibit linear changes in resistance proportional to applied strain. A Wheatstone bridge configuration is employed to measure the small changes in resistance accurately. Amplification of the signal is essential due to its small magnitude, and a proportionality constant (K) is derived to relate the signal voltage to the applied force. Additionally, signal smoothing techniques such as low-pass filtering and moving average computation are applied to improve signal stability. Finally, the experiment concludes with the calibration of the load cell using known masses, enabling the measurement of unknown masses. Theoretical calculations complement experimental findings, aiding in understanding the underlying principles. 3

Introduction A strain gauge is a resistor that experiences a linear change in its electrical resistance in proportion to an applied strain (Al-Mutlaq). As each strain gauge undergoes a change in length, resistance changes in proportion. Each strain gauge has a different sensitivity to strain called the gauge factor. The gauge factor is expressed as the ratio of fractional change in resistance to the fractional change in length (strain) and has a typical value of 2 (Al-Mutlaq). (1) The measured change in resistance of a strain gauge is very small and very difficult to measure accurately. With the use of a Wheatstone bridge, a configuration of resistors with a known input voltage helps to make the results more sensitive and readable. Figure 1. Wheatstone bridge configuration 4

The full bridge load cell has a linear correlation between the load and the voltage signal. With the use of a voltage divider the output voltage is variable. (2) The equation is simplified by substituting the gauge factor and relating the strain to force, Hooke’s law and the beam bending normal stress equations, yielding Equation 3. Objective: 1. Interface a strain gauge load cell with a data acquisition device. 2. Condition a signal by attenuating noise. 3. Smooth a signal with a moving average. 4. Experimentally calibrate a load cell. 5

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Apparatus and Test Procedure Apparatus ● Load Cell(HTC Sensor TAL220) ● Load Cell Mounting Fixture ● NI myDAQ ● Eisco 9-Piece Mass Set ● PC with LABVIEW Procedure 1. Build the VI:Build the front panel as follows, using Figure a reference. Place a Waveform Chart. Title the chart “Unfiltered Signal.” 2. Test the VI by applying a small load to see how the waveform reacts. 3. Create a numeric indicator to implement a low pass filter to attenuate the high frequency noise. 4. The low-pass filter was useful for reducing noise, but the numeric indicator shows that the filtered signal is still somewhat unsteady. One solution is to apply a moving average to the VI. A moving average is the average of the most recent N values. We will start by setting N to 10 values with shift registers. 5. Run the VI and set the Samples in Moving Average vertical slide to 10. Press on the load cell a few times and observe the waveform chart to verify that the array method of calculating the moving average is equivalent to the shift register method. 6. Now change the vertical pointer slide to 500 samples. Press on the load cell and keep the load applied, observing the waveform chart. 6

7. Run the VI. Hang a known mass on the load cell, wait for the reading to stabilize, enter the mass value in grams into the Mass numeric control on the front panel, and click the Record OK button. Repeat this for four different masses and for the condition of no mass (unloaded load cell). Use a large range of masses, keeping in mind you can hook masses together (ex: 500 g, 1000 g, 1500 g, & 1900 g). 8. Record the values for the experimental proportionality constant and voltage offset from your linear regression equation, with reference to Equation 4. 9. Run the VI and input the experimental proportionality constant and the offset voltage into their respective numeric controls. Hang an unknown mass from the load cell. 10. Record the calibrated mass measurement from the VI and compare it with the real mass of the object. Figure 2. Block diagram for experiment 7

Result Once the mass and the corresponding voltage output were plotted, we were able to linearly fit the data points. Utilizing Equation 3, which allowed for the calibration of the strain gauge cell. The slope acts as the proportionality constant K, x, is the mass applied to the beam, and the y-intercept is the offset voltage. The equation y = 4.64 × 10 − 4 − 0.366 is used in LabView to correctly calibrate and solve for the mass when a load is applied. The linear fit is not exact so there is a very small amount of error when recording the calculated mass from LabView. This error may be a result of the variance in the output frequency when recording the data, as seen in figure 3. Excel Result: 8 Mass Signal (mV) 0 0.08995 1 500 - 0.12051 7 1000 - 0.34271 1 1500 - 0.48479 6 1900 - 0.74104 4 500.74

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Figure 3. The linear fit from the experimental data. The slope is shown as descending because I set up the load cell upside-down, therefore recording negative values. Given Values: Moment of Inertia: Base 0.000000002 12.7 mm 0.0127 m Height 12.7 mm 0.0127 m Distance 80 mm GF 2 Vs 5 V d 0.04 m c 0.00635 m E g 70 GPa 9.81 7000000 0000 K_thy 0.00017798 14286 V/Kg 9

Conclusion and Recommendations The lab puts an emphasis on the importance of experimental theories, data collections, and calibration of equipment. When collecting data one must try to gather the most accurate data points to get the most true results. The data can then be used to calibrate the equipment which was strain gauge cell in this case. To collect the best results and eliminate noise in frequency, a filter should be used to help in data acquisition. Calibration is extremely important and must be done periodically in order to ensure the most accurate results. A recommendation to future labs is to allow the student to find the constants to manually derive equation 3 so that they can fully understand the reasoning for the linear fit. 10

Reference Kuphaldt, T. R. (n.d.). Strain gauges. All about circuits.Retrieved from https://www.allaboutcircuits.com/textbook/direct-current/chpt-9/strain-gauges/ Mysore, Ananda. (20 November 2018). “Load Cells” ME 120 Experimental Methods. San Jose State University, San Jose. 11

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Appendices Raw Data Mass Signal (mV) 0 0.089951 500 -0.120517 1000 -0.342711 1500 -0.484796 1900 -0.741044 K Offset Voltage Calibrated Mass Weighed Mass -0.000421 0.092478 500.74 500 Graph 12

Calculation K_thy 13