In automotive development, in order to evaluate the rust prevention performance of a new structure and materials, it is indispensable to quantitatively grasp the corrosive environment of a local commercial site. In this regard, this research aims to propose a new method for predicting the life of materials used in automotive body and to set up the optimal antirust specification for selecting such materials by taking into account environmental factors for the estimation of corrosion rate.

　　The ACM type corrosion sensor （Atmospheric Corrosion Monitor, henceforth, ACM sensor） used for monitoring of the atmospheric corrosion environment of a bridge or a residence was applied for monitoring of automobile corrosive environment. An ACM sensor detects the galvanic electric current of iron and silver couple when it is damped with the sea salt particle. In addition, it gives the time of wetness which depends on the amount of sea salt deposit. In atmospheric corrosion environment, these environmental factors （amount of salt and time of wetness） are grasped quantitatively and the corrosion amount of material is predicted. In severe automobile corrosive environment, for example, in winter where a snow melting agent are used, the characteristics of the ACM sensor were utilized further and iron corrosion current was detected. From the result of the ACM sensor, we surmised that the direct measuring of the iron corrosion amount could be carried out in high salt content. Therefore, the ACM sensor was carried in the car and actual corrosive environment measurement was performed. However, the galvanic current of the ACM sensor and the mass loss of iron coupons were not in agreement. It was assumed that the output of the ACM sensor was affected by the thickening of the rust, which increased the resistance of the rust layer.

　　In the future, this problem will be solved by rectifying resistance of the iron rust and we are able to estimate the amount of iron corrosion.

中国腐蚀与防护网官方QQ群：140808414
《中国腐蚀与防护网电子月刊》征订启事
摘要阅读联系：郭静 电话：010-82387968-802
QQ: 815397784 邮箱：guojing733@163.com