Integration of STM32 Microcontroller with Arm Cortex Architecture into the 8-Bit Measurement Circuit Customized for Real-Time Data Acquisition on Propeller Shaft to Increase Data Speed and Accuracy

Abstract

Propeller shafts transmit torque and high-speed rotational movement from the engine to related equipment. Expected propeller shaft functions are calculated and designed by using an analytical and numerical approaches. The verification tests are significant in that they provide feedback to the design and development processes. Therefore, acquiring accurate data from power transmission equipment is becoming even more important. This paper focuses on the study of circuit boards customized for use in the validation tests of the propeller shafts. It should be noted that these measurement circuits were integrated on the propeller shafts. These measurement circuits were used to acquire data such as torque, temperature, etc. in real time. Especially with instantaneous signals such as torque, data loss can occur due to low microcontroller resolution. Therefore, it was aimed to develop to the microcontroller to 32-bit resolution from 8-bit resolution to increase data speed and accuracy. As the first step, an INA125P operational amplifier was installed to amplify the low voltage values gathered from the gages and the sensors. The gain value of the amplifier was calculated in order to provide the highest data resolution and sensitivity. And then, ADS1115 analog to digital converter circuit with a rate of 860 samples per second and 16-bit resolution was used to interpret the analog data. A low pass filter was installed to remove noise from the output signal. Embedded code was also locally developed for the hardware installed. The system was calibrated on a validated test rig. Real-time torque and temperature data were acquired from the propeller shaft. It is observed that compared to the previous 8-bit system, the data accuracy and integrity from the new 32-bit board has increased by a factor of 5 to 100 Hz. The collected data was found to be 99.4% compatible with the validated test rig data. © 2023 Published by ISRES.