Location:Training / Testing and Measurement / Fundamentals of Engineering Testing Technology Huazhong University of Science and Technology / Signal time difference domain correlation analysis 2

Engineering testing technology is a professional basic course for mechanical majors. The content involves various common physical quantities in the fields of industrial automation, mechanical processing, building control, transportation, modern agriculture and medical instruments, such as: temperature, sound, brightness, pressure, magnetic field strength, Sensor measurement principles such as distance and vibration; as well as commonly used measurement signal analysis methods such as waveform analysis, spectrum analysis, amplitude domain analysis and correlation analysis of sensor measurement signals. In addition, it also includes knowledge of sensor signal amplification, signal modulation and demodulation, signal filtering and computer virtual instruments.
Testing technology is the foundation of all automated measurement equipment and instruments such as CNC machine tools, industrial robots, driverless cars, smart agricultural greenhouses, and electrocardiographs; its role is equivalent to the senses of the machine. Machines and automated measurement equipment and instruments can only be equipped with sensors. Effectively perceive the external world, use signal analysis methods to extract decision-making information such as obstacle distance and machine resonance frequency, and make next automated operations and responses.

This course adopts a practical learning model of learning by doing. In the sensor section, while explaining the theory, the teacher listed many sensor application projects implemented with Arduino; you will have the opportunity to use a thermal resistor + Arduino/STM32 card to implement a small thermometer; you will also have the opportunity to design and implement a small thermometer. Ultrasonic ranging radar and other small applications; improve your understanding of sensor knowledge and practical application capabilities.

In the signal processing part, the teacher uses Matlab to assist teaching and provides example codes for common signal analysis methods. You will have the opportunity to program and practice various common signal analysis methods and small applications based on the sample codes. , such as using a sine wave signal generator to implement a small electronic keyboard, using Fourier transform to implement a computer microphone sound signal acquisition and spectrum analyzer, using filtering knowledge to implement an MP3 equalizer, etc.; improve your understanding and synthesis of signal analysis theory Application Ability.