In the final assignment, I designed a method of automated air leakage detection. I had to find a method to easily detect real-time air leakage. From a review of already established methods for air leakage detection and exclusion criteria, I have identified the two most promising methods, named the method with an ultrasonic sensor for distance detection and the method using a microphone. The Arduino microcontroller and a mobile phone were selected as the most suitable for testing the design of the measuring system. Frequency analysis of sound was performed with air leakage from the inner tube of a race bike and an air spring. After testing, the method using a mobile microphone turned out to be more promising than the Arduino microcontroller with restriction of detecting high frequencies of sound. Measurements have shown that air leakage is a source of sound generation at frequencies above 25 kHz. The obtained measurements were confirmed by measurements in an anechoic chamber of the LDSTA laboratory. Additionally, a frequency analysis of various sound sources in the industrial environment was performed. Typical ambient frequencies have been shown to be below 25 kHz, which increases the applicability of the automated air leakage detection design even in a noisy industrial environment.
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