基于电导率和氢传感器功率模糊推理系统的奶牛乳腺炎检测系统

Muhammad Syahrial Rukmana, A. Rakhmatsyah, Aulia Arif Wardana
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引用次数: 1

摘要

本研究建立了利用电导率(EC)和氢功率(pH)传感器检测奶牛乳腺炎的筛选方法系统。利用模糊逻辑对EC和pH传感器的值进行了分析,明确了它们之间的真值。奶牛的乳腺炎会造成损失,降低牛奶产量和质量。目前,检测牛奶中的乳腺炎仍然是通过观察牛奶的颜色变化和分析奶牛的行为来手工进行的。本文利用Mamdani型模糊推理系统设计了一个乳腺炎检测系统,最终结果将显示在android智能手机上。测试结果表明,该系统的检测精度值为79.2%。该系统适用于用于检测奶牛乳腺炎的替代筛选方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mastitis Detection System in Dairy Cow Milk based on Fuzzy Inference System using Electrical Conductivity and Power of Hydrogen Sensor Value
This study build a system for screening method to detect mastitis in dairy cow milk using Electrical Conductivity (EC) and Power of Hydrogen (pH) sensor. The value of EC and pH sensor is analyze using fuzzy logic to clarify the truth value between it. Mastitis in cows can cause loss and decrease milk production and quality in the dairy farmer industry. Currently, detecting mastitis in cow’s milk still done manually by looking at the color change of the milk and analyzing the cow behavior. This paper has designed a mastitis detection system using the Mamdani type fuzzy inference system and the final result will be displayed on an Android-based smartphone. From the test result, it was found that the system has 79.2% detection accuracy value. This system is suitable for alternative screening method that used to detect mastitis in dairy cow milk.
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