机器学习在汽车动力传动系统故障分类中的应用

K. Vinisha, E. Kalpana
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引用次数: 0

摘要

本文讨论了一种智能汽车,它具有识别电力传输系统中发生的任何故障的能力。它还通过液晶显示器和移动应用程序向车辆驾驶员发出风险警报。这种智能车辆由不同的传感器组成,这些传感器位于车辆的动力传输系统中。从车辆上收集传感器的值并将其发送给控制器,控制器与一些指定的独立值进行比较。压缩是使用机器学习算法完成的,这对于实现高精度的系统非常有用。通过这种设计,我们甚至可以实现车联网(IoV)的概念,因为我们使用GPS来跟踪车辆,并使用移动应用程序来指示风险。测试进行了,测试结果非常有效。该系统可以减少人员的生命损失,提高车辆的使用寿命。为了实现所需的系统,我们使用了机器学习和python,因为它们是最新的高水平技术,并提供了很高的准确性。
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Effectuation of Machine Learning for Fault Classification on Vehicle Power Transmission System
The present paper discusses about a smart vehiclewhich has the ability to identify any kind of fault occurrence in the power transmission system. It also gives the risk alerts' to the vehicle driver through LCD and at the same time by using a mobile application. This smart vehicle consists of different sensors which are located at the power transmission system of the vehicle. The sensors values from the vehicle are collected and sent to the controller which is compared with some specified independent values. The compression is done using machine learning algorithms which are very useful for achieving a system with high accuracy. With this design we can even achieve the concept of internet of vehicle (IoV), as we are using GPS to track the vehicle and a mobile application to indicate the risk. Thetest was run and outcome of the test was very effective. With the help of this system we can reduce losses of human life and increase the vehicle life span. To achieve the required system we are using machine learning and python, as they are the recentera high level technologies and provide great accuracy.
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