The paper employs the method of characteristics to solve the transient flow control equations of pipelines, verifies the accuracy of the numerical method using data from existing literature, and establishes a simple pumping station water supply system. It investigates the detection of blockages and leaks in the pipelines of the system while considering variations in pipe elevation and pump boundary conditions. It is found that pressure waves generated by rapid closure of end valves reflect when they reach the locations of blockages and leaks. The reflected pressure waves back to the valve cause abrupt changes in pressure signals, and different types of faults result in different forms of abrupt changes. Based on the time of the abrupt change and the wave speed of the pipeline, the locations of blockages and leaks can be calculated. The final research results confirm that the method demonstrates high precision in locating blockages and leaks across different parameters, with detection errors below 1% under ideal conditions. Moreover, it effectively identifies blockages and leaks at points of pipe elevation changes and pipe connections. Importantly, it displays strong applicability even in scenarios where both blockages and leaks coexist within the system.

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Cavitation and particle erosion are critical factors affecting the performance and durability of hydraulic machinery. This study employs a combined numerical simulation approach by integrating a cavitation model with a Discrete Phase Model (DPM) erosion model. It examines single erosion and cavitation-erosion synergy under varying cavitation inducer angles. The results show that intensified vorticity behind the inducer increases particle concentration and sliding erosion, leading to higher erosion rates and larger erosion areas compared to the single erosion model. Additionally, a direct correlation is established between cavitation occurrences, particle velocity, vorticity, and erosion rates at different rotational speeds. Comparative analysis with experimental data indicates an 11.52% improvement in predictive accuracy for wear using the cavitation-erosion synergy model. These findings provide valuable insights for predicting wear in hydraulic machinery under cavitation and particle erosion conditions, contributing to enhanced equipment reliability and extended service life.

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