Sensitivity predicating coating material containing phenyl fluorine sensitive matter

Abstract

The invention discloses a sensitive predictive coat material with the phenylfluorone sensitive material used in the aluminum alloy surface, which is made up of the 0.2-0.8 weight of phenylfluorone fluorescence sensing material, 0.01-0.05 weight of activating agent and residue agglomerant. The invention uses the fluorescence corrosion sensing intelligent coat as the monitoring instrument; the fluorescence compound is as the corrosion sensing material. By using the character of fluorescence change after compounding with the special metal ion in different oxidation, reducing and pH value, it combines with the coat to monitor. The technology has the high sensitivity to monitor the aluminum alloy corrosion, which can detect the aluminum ion of ppm. So it can provide the ability to appraise the corrosion state and get the important corrosion environment information.

Description

technical field [0001] The present invention relates to a coating material, more particularly, refers to a sensitive predictive coating material containing phenylfluorone sensitive substance which is applied to the surface of aluminum alloy and used for monitoring the corrosion status of aluminum alloy. Background technique [0002] At present, aluminum alloys are widely used in the manufacture of aircraft skins, fuselage frames, rotors, propellers, fuel tanks, wall panels and landing gear struts. During the service process, in order to reduce the safety hazards of aluminum alloy structural parts during service and improve the safety and service life of equipment in complex environments, it is of great significance to effectively monitor and control the corrosion process of aluminum alloys. [0003] The technologies currently applied to corrosion monitoring generally include: (1) ultrasonic thickness measurement, which can repeatedly measure equipment in operation, but it is...

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Problems solved by technology

[0003] The technologies currently applied to corrosion monitoring generally include: (1) ultrasonic thickness measurement, which can repeatedly measure equipment in operation, but it is difficult to obtain sufficient sensitivity to track and record changes in corrosion rate; (2) linear polarization method (LPR), the linear polarization method responds quickly to changes in corrosion conditions and can obtain instantaneous corrosion rates, but it is not suitable for applications in media with poor conductivity. When there is a dense oxide film or passivation film on the surface of the equipment, or even accumulated When corroding products, false capacitance will be generated, which will cause large errors and even fail to measure; (3) Potential method, the potential method has been used in the monitoring of cathodic protection systems for many years, and is used to determine the conditions for localized corrosion to occur. But it cannot reflect the corrosion rate; (4) AC impedance method, which has greater reliability for high-resistance electrolytes and a wide range of medium conditions, but it takes a long time to measure AC impedance in a wide frequency range. This makes it difficult to monitor the corrosion rate in real time, which is not suitable for actual on-site corrosion monitoring; (5) Electrochemical noise method, which includes electrochemical potential noise (EPN) and electrochemical current noise (ECN), which reflects the Corrosion causes slight fluctuations in corrosion potential or galvanic current. Exploratory research has begun on the application of these technologies in industrial production; (6) Thin-layer activation method (TLA). Determination of total metal loss with high sensitivity, and field imaging technology (FSM), which is applied to real-time on-site monitoring of submarine oil pipelines. This technology can also perform corrosion monitoring on inaccessible parts, such as nuclear power plant equipment with radiation hazards Monitoring of cracks in hazardous areas, etc.

The corrosion monitoring methods mentioned above have limited ability to monitor the corrosion process online, and cannot combine the characteristics of on-site detection of corrosion damage, in-situ detection of corrosion parts, and quantitative evaluation of corrosion speed.

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