Optimizing the adaptive circuit of piezoelectric sensors is important in accurately measuring blast waves. This study analyzed the impact of the bandpass cut-off frequencies and quality factor of adaptive circuits on shock wave measurements. We proposed a Multi-objective particle swarm optimization based on weighted Pareto-dominance sort (W-MOPSO) for optimizing the multi-objective function of an adaptive circuit in order to improve precision during shock wave measurements. W-MOPSO obtained a Pareto-optimal solution set through Pareto-dominant sorting of global optimal solutions to the weighted sum of a multi-objective function. The relative mean error in the optimized adaptive circuit mostly ranged between −2% and +2%. Simulations were used to analyze the impact of the optimized adaptive circuit on shock wave measurements. The effectiveness of W-MOPSO was verified through a real-world experiment using a TNT explosive and blast wave gauges. W-MOPSO provided a basis for adapter circuit design and optimization in shock wave measurement.

中文翻译：

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用于爆炸波测量的自适应电路中的W-MOPSO

优化压电传感器的自适应电路对于准确测量爆炸波很重要。这项研究分析了带通截止频率和自适应电路的品质因数对冲击波测量的影响。我们提出了一种基于加权Pareto-优势支配排序（W-MOPSO）的多目标粒子群优化算法，以优化自适应电路的多目标函数，从而提高了冲击波测量的精度。W-MOPSO通过对多目标函数的加权和进行全局最优解的Pareto占优排序，获得了Pareto最优解集。优化的自适应电路中的相对平均误差通常在-2％至+ 2％之间。仿真用于分析优化的自适应电路对冲击波测量的影响。W-MOPSO的有效性通过使用TNT炸药和爆炸波计的真实世界实验进行了验证。W-MOPSO为适配器电路设计和冲击波测量的优化提供了基础。