Abstract: A film thickness measurement apparatus includes: an ECT sensor for measuring a film thickness of a thermal barrier coating formed on a turbine blade; a storage unit for storing a measurement point on the turbine blade which is a point where the film thickness of the thermal barrier coating is measured; a laser displacement meter for measuring a shape of the turbine blade; a measurement position calculation unit for calculating an actual measurement point suitable for actual film thickness measurement using the ECT sensor, based on the shape of the turbine blade measured by the laser displacement meter and the measurement point on the turbine blade stored in the storage unit; and an arm drive unit for driving the ECT sensor to adjust a measurement position of the ECT sensor based on the actual measurement point calculated by the measurement position calculation unit.

Abstract: A film thickness measurement apparatus includes: an ECT sensor for measuring a film thickness of a thermal barrier coating formed on a turbine blade; a storage unit for storing a measurement point on the turbine blade which is a point where the film thickness of the thermal barrier coating is measured; a laser displacement meter for measuring a shape of the turbine blade; a measurement position calculation unit for calculating an actual measurement point suitable for actual film thickness measurement using the ECT sensor, based on the shape of the turbine blade measured by the laser displacement meter and the measurement point on the turbine blade stored in the storage unit; and an arm drive unit for driving the ECT sensor to adjust a measurement position of the ECT sensor based on the actual measurement point calculated by the measurement position calculation unit.

Abstract: A condition diagnosing method capable of executing condition diagnosis considering a secular change is provided. A condition diagnosing method includes a first diagnosing step of determining presence or absence of abnormality in diagnosis data by a latest one class support vector machine, and diagnosing the diagnosis data determined as abnormal as relating to a failure, and a second diagnosing step of determining presence or absence of abnormality in the diagnosis data determined as abnormal in the first diagnosing step by an initial one class support vector machine, diagnosing the diagnosis data determined as abnormal as relating to secular deterioration, and diagnosing the diagnosis data determined as not abnormal as normal.