用手机振动检测液体粘度，实现30种液体95%以上识别
Smartphone-Based Identification of Unknown Liquids via Active Vibration Sensing
- 通过主动振动测量液体粘度，利用手机加速度计采集信号
- 均方相对误差仅2.9%，30类液体平均识别准确率达95.47%
- 无需机器学习，多阶段信号处理有效抑制干扰与采样不足
传统液体识别设备对公众难以获取。本文证明了使用商用轻量级设备（如智能手机）识别未知液体的可行性。核心思路是不同液体分子具有不同的黏度系数，导致相对运动时需克服不同的能量壁垒。基于此，我们提出一种新型方法，通过主动振动测量液体黏度。然而，利用手机内置加速度计构建鲁棒系统面临诸多挑战：欠采样、自干扰及液量变化的影响。为此，我们未采用机器学习，而是通过多阶段信号处理重建原始信号并消除干扰。实验表明，该方法可实现2.9%的平均相对误差，并在30种液体上达到95.47%的平均识别准确率。
原文摘要 · Abstract (English)
Traditional liquid identification instruments are often unavailable to the general public. This paper shows the feasibility of identifying unknown liquids with commercial lightweight devices, such as a smartphone. The key insight is that different liquid molecules have different viscosity coefficients and therefore must overcome different energy barriers during relative motion. With this intuition in mind, we introduce a novel model that measures liquids' viscosity based on active vibration. However, building a robust system using built-in smartphone accelerometers is challenging. Practical issues include under-sampling, self-interference, and the impact of liquid-volume changes. Instead of machine learning, we tackle these issues through multiple signal processing stages to reconstruct the original signals and cancel out the interference. Our approach estimates liquid viscosity with a mean relative error of 2.9% and distinguishes 30 types of liquids with an average accuracy of 95.47%.
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