In industrial production and quality inspection, waveform ultrasonic thickness gauges have become key equipment due to their non-contact and high-precision advantages. However, the original ultrasound signal is susceptible to noise interference, which directly affects the accuracy of thickness measurement. Mastering scientific signal processing techniques is the core link in improving instrument performance.
1、 Noise suppression: To eliminate falsehoods and preserve truth in signals
Ultrasonic signals are easily affected by environmental electromagnetic interference, material scattering, and other factors during propagation, resulting in noise. Common processing methods include combining hardware filtering with software denoising: using a bandpass filter (such as 0.5-10MHz) in hardware to filter out low-frequency drift and high-frequency clutter; At the software level, wavelet transform can be used to separate noise and effective signals through multi-scale decomposition - selecting orthogonal wavelet bases such as db4, decomposing noisy signals into 3-5 layers, thresholding high-frequency coefficients, and reconstructing them, which can effectively preserve the echo edge features. In addition, taking the average of multiple measurements can reduce random noise, especially suitable for the detection of thin-walled parts or high attenuation materials.
2、 Feature extraction: Lock the "identity identifier" of the echo
The thickness calculation depends on the time difference between the first wave and the bottom wave, so it is necessary to accurately identify the echo position. The traditional threshold method is susceptible to noise fluctuations and can be optimized by combining "slope mutation detection+energy centroid method": first calculate the short-term energy gradient of the signal, locate the point of sudden increase in gradient as a candidate echo starting point; Then, by calculating the energy weighted center of the signal near the point, the offset caused by noise can be corrected. For multi-layer structures (such as coatings+substrates), cross-correlation algorithms can be used to match the echo templates of known thickness test blocks, achieving automatic identification of complex interfaces.
3、 Dynamic compensation: adaptive adjustment to cope with the environment
Temperature changes can cause drift in probe sound velocity (such as a change of approximately 1m/s in sound velocity per ℃ in steel), which requires real-time compensation. The temperature of the workpiece can be monitored through an integrated temperature sensor, and the preset sound velocity temperature curve can be called to correct the time difference; If the sound velocity of the material is unknown, the "dual probe measurement method" can be used - using one transmitter and one receiver probe to directly measure the sound velocity and eliminate the influence of coupling layer thickness fluctuations. In addition, the coupling agent state (such as bubbles, dryness) can cause signal attenuation, and the gain can be dynamically adjusted by monitoring the echo amplitude to ensure that weak signals can still be effectively captured.