The article describes an advanced system for predicting damage to hydropneumatic suspension arms used in the suspension of tracked vehicles, such as the Borsuk infantry fighting vehicle (IFV). The system is based on the analysis of signals collected from a measuring system mounted directly on the suspension arm, which allows for monitoring its key operating parameters in real time. The main input data include the pressure and temperature of nitrogen in the gas chamber and the suspension arm position, which are compared with the reference characteristics for early detection of potential faults. Typical damage, such as seal leakage, is manifested by a reduced nitrogen pressure value in specific suspension arm positions, which allows for quick identification of the problem and taking preventive measures before a more serious failure occurs. The predictive model takes into account key factors influencing pressure: pre-charge pressure, depending on the suspension arm position in the vehicle and track tension (e.g. higher for the first and sixth suspension arms in the Borsuk BWP vehicle), temperature, which, according to the Clapeyron equation, affects the gas pressure, the position of the suspenion arm, which changes the volume of the nitrogen chamber and thus the pressure. The system compares the actual pressure with the theoretical one, calculated based on a mathematical model describing the relationship between nitrogen pressure and its volume and temperature. If the actual pressure is 10–20% lower than expected, the suspenion arm is marked as “to be verified” (yellow indicator), and if it drops by more than 20% - “to be replaced” (red indicator). The model also takes into account gas transformations, such as adiabatic and isothermal, to precisely predict pressure changes. Thanks to this, the system supports timely maintenance, improving vehicle reliability and performance in difficult off-road conditions.

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Model of a System Enabling the Use of Signals from the Measuring System on the Hydropneumatic Suspension Arm to Predict Its Damage Using the Reference Characteristic

  • Paweł Radzik,
  • Krzysztof Herbuś,
  • Kamil Dworak

摘要

The article describes an advanced system for predicting damage to hydropneumatic suspension arms used in the suspension of tracked vehicles, such as the Borsuk infantry fighting vehicle (IFV). The system is based on the analysis of signals collected from a measuring system mounted directly on the suspension arm, which allows for monitoring its key operating parameters in real time. The main input data include the pressure and temperature of nitrogen in the gas chamber and the suspension arm position, which are compared with the reference characteristics for early detection of potential faults. Typical damage, such as seal leakage, is manifested by a reduced nitrogen pressure value in specific suspension arm positions, which allows for quick identification of the problem and taking preventive measures before a more serious failure occurs. The predictive model takes into account key factors influencing pressure: pre-charge pressure, depending on the suspension arm position in the vehicle and track tension (e.g. higher for the first and sixth suspension arms in the Borsuk BWP vehicle), temperature, which, according to the Clapeyron equation, affects the gas pressure, the position of the suspenion arm, which changes the volume of the nitrogen chamber and thus the pressure. The system compares the actual pressure with the theoretical one, calculated based on a mathematical model describing the relationship between nitrogen pressure and its volume and temperature. If the actual pressure is 10–20% lower than expected, the suspenion arm is marked as “to be verified” (yellow indicator), and if it drops by more than 20% - “to be replaced” (red indicator). The model also takes into account gas transformations, such as adiabatic and isothermal, to precisely predict pressure changes. Thanks to this, the system supports timely maintenance, improving vehicle reliability and performance in difficult off-road conditions.