On a free surface not having crevice structures, micro pits on the order of several μm in diameter that are repassivated immediately are called meta-stable pits. The role of the micro pit as an initiation site of crevice corrosion was examined by comparing the meta-stable pitting corrosion potential （V'cMS） of SUS304 steel measured on the free surface with the critical potential for crevice corrosion （VCREV）. VCREV presented the similar value to V'cMS. It was also revealed that micro pits, as well as SUS304 stainless steel surface, were hard to be repasivated at pH≥2.0, meaning that micro pits can be initiation sites of crevice corrosions. Investigating Cl－ concentration and pH dependencies on each potential, the influences of these factors were also examined in terms of the contribution to a crevice corrosion initiation. Cl－ ions, which have V'cMS and VCREV less noble, will directly contribute to a crevice corrosion initiation by facilitating micro pit initiations. pH decrease accelerating a passivation dissolution would promote a crevice corrosion initiation indirectly by increasing a Cl－ migration into a crevice structure.
Steel pipes used for the transportation of materials, such as tap water and gas, can leak due to corrosion. Therefore, monitoring the conditions of these pipes is significantly important. In this study, an inspection and monitoring method for evaluating the corrosion losses of steel pipes was developed using the acoustic emission （AE） method. First, steel pipes with different corrosion losses were installed, and AE monitoring was performed for one month. Corrosion loss was evaluated using an intensity ratio representing the maximum amplitude of wavelet coefficient of the longitudinal and flexural modes in the AE signals （i.e., AE wavelet coefficient ratio） resulting from the fractures caused by rust. The AE wavelet coefficient ratio changed with increasing corrosion depth, and a relationship between the corrosion loss and the change in the AE wavelet coefficient ratio was observed. This result indicated that the corrosion loss could be evaluated using AE monitoring. Next, a thermal cycle was applied to the corroded areas of the steel pipes, and the AE signals were monitored. The fracturing resulting from the rust produced several AE signals, and the AE wavelet coefficient ratio changed depending on the corrosion depth. Therefore, the corrosion loss could also be evaluated by applying the AE wavelet coefficient ratio to an AE measurement test with a thermal cycle.
The analysis algorithm named ACCESS was developed for galvanic sensor data, in order to qualitatively evaluate the corrosion rate. The analysis uses record of humidity along with the sensor data to extract outlier galvanic outputs that arise during rainfall. The quantitativeness of the analysis was verified using the field data observed in an exposure site and 19 transmission towers along a Japanese coastal area. The corrosion rates estimated from the sensor signals and measured using standard coupons were found to be in good agreement. The high corrosion season and its environmental features were extracted from the results of the short-term analysis of the corrosion rate, especially in the season of storm approach and snowfall.