Development of a prototype of a reed level gauge fault identification device

A specialized diagnostic algorithm was developed and experimentally tested for the automatic detection of anomalies in the operation of reed-switch level meters with a standardized 4-20 mA current output. The first stage involved a detailed analysis of typical failures common to this class of sensors, including contact sticking, zero drift, signal line breaks, and false triggering due to external vibrations or magnetic interference. Particular attention was paid to the specifics of operation on ships, where high humidity, temperature fluctuations, and mechanical stress accelerate component degradation. The most vulnerable design components were identified, quantitative reliability criteria were defined, and technical requirements for the diagnostic module were formulated, including those for speed, accuracy, and resistance to false triggering. The algorithm operates by comparing the current analog signal value with the expected behavior determined by external control commands and the history of previous measurements, including dynamic patterns of level changes. To improve reliability, a sliding analysis window and adaptive thresholds are used, taking into account the current operating mode of the object. The implementation is based on a microcontroller with hardware support for analog-to-digital conversion, ensuring compactness, low power consumption, and compatibility with industrial interfaces. Laboratory testing confirmed the device's ability to reliably detect both static and dynamic faults, including the absence of a response to a level change in the presence of a control action. The proposed solution can be used standalone or integrated into existing ship power management systems, increasing their fault tolerance through the early detection of hidden defects. This work opens up prospects for expanding the diagnostic functionality of analog sensors in conditions with limited access to maintenance, particularly in onshore infrastructure and autonomous power facilities.