In the last years, the interest in the field of Prognostics and Health Management (PHM) has been growing in many industrial fields. The objective of PHM is to switch from a time-based (scheduled) maintenance to a predictive maintenance with advantages in terms of reliability and safety. This paper presents the thermodynamic method for the fault detection of an axial piston pump which is a critical component in many hydraulic systems; the method was developed for the evaluation of the overall efficiency which is an important parameter to monitor the machine health state. Through the measurements of temperatures and pressures at suction and delivery ports the method allows to calculate the efficiency avoiding the use of costly sensors, such as speed and torque sensors. The paper investigates the possibility of utilizing the pump overall efficiency evaluated through the thermodynamic method as a reliable parameter for the fault detection. The machine under study is a variable displacement axial-piston pump with external drainage equipped with a load sensing regulator. The thermodynamic method was already validated in a previous work by comparing it with the standard approach, based on the direct measurement of the mechanical power. The proposed method requires the measurement of the delivery and drain flow rates involving the use of expensive flowmeters which could prevent its usage in online applications; this limit should be overcome with the development of low-cost solutions for flow rate measurements. A preliminary investigation of the pump failure modes was conducted to identify the most important faults which need to be considered. An experimental campaign was carried out on a laboratory test bench with the pump in the flawless state and in faulty states. The faulty states were realized by introducing components with artificial faults into the pump. The pump was accurately instrumented to monitor all the main variables, i.e. pressures, temperatures, flow rates, swash plate angle and shaft torque and speed. Different operating conditions were considered and each test was repeated several times in order to acquire a suitable population to verify the repeatability of the data. The experiments demonstrate the method capability of detecting some but not all of the incipient faults tested in steady-state conditions as a consequence of temperature variations which have the most important influence on efficiency estimation. Future works will include the development of innovative solutions to measure flow-rates and the testing of other faults to further verify the reliability of the method.

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