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A monitoring point layout optimization method based on fluid wave signals and improved genetic algorithm was proposed to meet the leakage monitoring technology requirements of water supply pipelines in refining enterprises. Based on the propagation model of fluid wave signals in pipelines, the wave velocity and attenuation characteristics of fluid wave signals caused by leakage were analyzed. A monitoring point layout optimization model was constructed based on the introduction of factors such as the shortest interval between adjacent monitoring points, sensor cost, pipeline imbalance, pipeline flow rate, and pipeline risk level as constraints. Improvements were made to the traditional genetic algorithm to address the issue of duplicate encoding in the algorithm. The established monitoring point layout optimization method was validated using a simulated pipeline network case. Firstly, the shortest interval parameter was used to constrain the monitoring points to avoid the problem of overlapping monitoring ranges caused by close monitoring points. Then, the optimal number of monitoring points was obtained using the pipeline network coverage and its change rate as performance indicators to achieve the goal of economic layout. Finally, the improved genetic algorithm was used to solve the optimization model, and the optimal layout results for monitoring points were obtained. The results of simulated pipeline network and actual pipeline network testing have illustrated that under the premise of selecting different constraint factors, the optimized layout of monitoring points can be effectively distributed in the pipeline area where the objective function value of the optimization model is higher, verifying the reliability of the established layout optimization method.