The efficient operation of industrial processes requires the timely and accurate diagnosis of faults in process equipment, particularly sensors, as acting on faulty measurement data can result in inefficient or dangerous operation. A common fault mode in industrial pressure sensors is mechanical damage resulting in the leakage of the internal oil (used to transmit external pressure to the sensing element) and the development of an air pocket within the device. In previous work, we have experimentally determined the faulty measurement characteristics of a commercial pressure sensor, where the sensor manufacturer has provided modified sensors with calibrated degrees of oil loss. The current paper develops a mathematical model of this tensoresistive pressure sensor, which describes and explains the impact that oil loss, and hence the presence of an air pocket, has on the static measurement response.

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The Industrial Internet of Things (IIoT) and Industry 4.0 require new intelligent sensor designs with enhanced functionality, including local diagnostics. In previous work, we have experimentally investigated an important fault mode of a commercial pressure sensor, working in partnership with the sensor manufacturer who has provided modified sensors with calibrated levels of the fault condition. We have further developed simple signal processing techniques to detect the fault condition, based on a low cost noise analysis. In the current paper, we describe the development of a prototype wireless pressure transmitter. This transmitter monitors the analogue output of the pressure sensor, and applies the diagnostic procedures in real time. The resulting pressure measurement in engineering units, together with diagnostic information, are both communicated wirelessly to a receiving system.

Introduction. 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.