Abstract
In the context of the transition of the world industry to new production technologies, the task of monitoring the technical condition of automatic control systems components, including pressure sensors, is urgent. Despite the existence of research and development aimed at creating systems for diagnostics and self-diagnosis of pressure sensors, the degradation mechanisms of mechanical parts of sensors and diagnostics algorithms during operation remain insufficiently studied. Aim. Propose algorithms for condition monitoring of the mechanical and hydraulic system of in-line pressure transducers. Materials and methods. This study is based on tests conducted on pressure modules with defects that simulate the lack of liquid in the separation cavity of the mechanical and hydraulic system of the transducer, manufactured by the industrial partner. The method of fault diagnosis is based on the analysis of statistical characteristics of the ADC signal of the pressure modules. Results. During the tests, hypotheses were confirmed about the dependence of the standard deviation of the output signal of the pressure module on the volume of liquid-oil in the channel. Based on the obtained data, algorithms for diagnosing the technical condition of the pressure sensor were proposed, which use the values of the sensor signal STD as a diagnostic parameter. The algorithms provide verification of the applicability conditions of the considered method and use additional information about the technological process. The problems that need to be solved for the practical implementation of algorithms in real production are formulated. Conclusion. The proposed algorithms for condition monitoring of the pressure sensor differ from the known diagnostic algorithms in that they use the results of experimental studies and are aimed at detecting a malfunction of the mechanical part of the sensors. Algorithms can be used to monitor the technical condition of in-line pressure sensors during operation under certain conditions that need to be clarified in the course of further research and field tests.
Highlights
In the context of the transition of the world industry to new production technologies, the task of monitoring the technical condition of automatic control systems components, including pressure sensors, is urgent
Based on the obtained data, algorithms for diagnosing the technical condition of the pressure sensor were proposed, which use the values of the sensor signal standard deviation (STD) as a diagnostic parameter
Since it is assumed to manage all technological objects and processes based on mathematical models and digital data, the increasing challenges of digital condition monitoring of equipment and automation of production processes increase the requirements for the new measurement, control and diagnostics techniques
Summary
In the context of the transition of the global industry to new digital and intelligent production technologies, the key is to use a large amount of data that is transmitted and processed digitally. The study shows that in the presence of a sufficiently pronounced fault (the percentage of fill-oil leakage is more than 11 %), the output signal STD level remains at the minimum level and is constant with the input pressure This suggests that the reference value of the STD can be set together with the zero-offset setting at zero overpressure. It is possible to suggest a practical implementation of the system for condition monitoring of a pressure transmitter on the pipe section using the readings of two sensors and the values of the output signal STD. STD is not suitable if there is zero overpressure in the process or processes that change rapidly over time You can overcome this limitation if you use additional sources of information about the process, including data from other sensors (pressure, flow, etc.) installed to monitor the process. Based on the results of the study, it can be argued that the percentage of fill-oil leakage should be sufficient (more than 10 %) to change the value of the output signal STD so that it can be detected
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