Application Cases

Experiment Name: Non-Destructive Testing of Pear Hardness Based on Acoustic Vibration Response Method Using High-Voltage Amplifier

Experiment Objective: To detect and distinguish the internal quality differences of pears using a non-destructive testing method.

Test Equipment:
Pears, test bench, piezoelectric beam sensor, ATA-2041 high-voltage amplifier, vibration control and dynamic signal acquisition and analyzer, computer, etc.

Experimental Content:
A detection device using piezoelectric beam sensors for signal excitation and sensing was built. The stability of the device's signal detection was analyzed. The resonant frequency and sound velocity of the pears were extracted to evaluate pear hardness. Then, the hardness evaluated using these two response parameters was subjected to linear regression analysis with the hardness measured by the Magness-Taylor (M-T) puncture method to construct a detection model for pear hardness. In this model, a high-voltage amplifier drives the sensors, and a dynamic signal acquisition and analyzer collects the data.

Experimental Procedure:

(1) Construction of the test platform:

Figure: Acoustic Vibration Detection System for Pear Hardness

(2) Signal acquisition and processing:
Acoustic vibration tests typically use an impact hammer to excite the fruit sample. To reduce signal interference while obtaining a strong excitation response signal, a high-voltage amplifier was used to linearly amplify the Ve signal. Considering that the rated voltage for continuous operation of the sensor is 90 V, the voltage signal was linearly amplified to an excitation signal VE with a peak pulse voltage of 80 V. The piezoelectric beam sensor at the excitation end then caused the sample to vibrate.

Figure: Typical Acoustic Vibration Signal of a Pear

(3) Stability test of the response signal:
The high-voltage amplifier amplified the signal. The same measurement point on the pear was excited and sensed five times repeatedly to observe the stability of the response signal.

Figure: Signals from Repeated Excitation at the Same Excitation Point

(4) Test of the influence of different measurement points on the acoustic vibration test:
Five pears were randomly selected. As shown in the figure, five measurement points were evenly arranged along the equatorial line of each pear for excitation and signal sensing. This was done to observe whether there were differences in the response signals at different excitation/sensing positions on the pear.

(5) Puncture test with skin: Five points were randomly selected on the equator of the pear using a TA.XT Plus texture analyzer for puncture testing. A cylindrical probe with a diameter of 5 mm was used. The puncture speed was set to 1 mm/s, and the puncture depth was 8 mm. The hardness measured by the M-T puncture method was calculated based on the slope of the force-deformation curve before pear puncture rupture. The average of five measurements was taken as the hardness of the pear, S_MT (N/mm).

Figure: Relationship Between Pear Hardness Values Obtained by Different Methods

Experimental Results:

1. This detection device could simultaneously acquire two response parameters: resonant frequency and sound velocity. With the high-voltage amplifier amplifying the signal, repeated excitation and sensing at the same measurement point yielded stable and reliable response signals. When signal excitation and sensing were performed at different positions on the pear's equator, no significant differences (P > 0.05) were found for either response parameter.

2. The hardness evaluated by the resonant frequency method and the sound velocity method for pears were both linearly correlated with the hardness measured by the M-T puncture method. The correlation coefficients were 0.841 and 0.877, respectively. The models established could both be used as models for the non-destructive testing of pear hardness.

3. The combination of the resonant frequency method and the sound velocity method could also detect pear hardness, with a correlation coefficient of 0.938 for the detection model. The sensitivity of this model for detecting pear hardness was 67.30%, which is closest to the sensitivity of the M-T puncture method. When used to distinguish between rough-skinned pears and normal pears, this model exhibited a significantly higher detection accuracy (86.7%). This provides a strategy for the development of non-destructive testing technology for pear hardness using acoustic vibration methods.

   

Figure: Specifications of the ATA-2041 High-Voltage Amplifier