Study On Theory And Key Technologies Of Atmospheric Pressure Plasma Arc Cleaning

Metal parts are widely used in aircraft, automobiles, ship manufacturing, and etc. Their quality and reliability are determined by the countermeasures of each link in parts processing. As an indispensable link in modern industrial production, cleaning technology plays an important role on the treatment process of metal surface. Besides it can reflect the quality management level of an enterprise, the choice of cleaning methods and the control of cleaning quality not only are involved in energy conservation, technical safety, environmental protection and other major issues, but also have a direct impact on product performance and quality. As a new cleaning technology, atmospheric pressure plasma arc (APPA) cleaning can meet needs of metal parts cleaning and development trend of cleaning technology, such as high-performance, non-polluting, low energy consumption and etc. Furthermore, compared with traditional, other non-direct contact and dry-cleaning technology, APPA has attracted increasing attention of domestic and foreign scholars. Although some achievement have been achieved in a few aspects such as generation methods of plasma, choice of working gas and evaluation methods of cleaning quality, there still exist some problems including cleaning mechanism that are required further theoretical and methodological researches, due to APPA cleaning being a multidisciplinary research field, which merged the thermo-physical effect and chemical reaction.According to substrate surface for the types of pollutants, as well as the characteristics of distribution, a three-dimensional coupled thermo-mechanical model about APPA acting on the cleaned metal parts has been established, by virtue of the theory of heat transfer and finite element method. In this thesis, Energy coupling mechanism of APPA cleaning speckle particle pollutants and layered dense pollutants have been studied respectively. Moreover, the effect of process parameters such as APPA power, scanning speed, substrate thickness and contaminant thickness on the interface temperature, interface cleaning force and cleaning strain has been revealed, so as to provide theoretical basis for the choice of process parameters during atmospheric pressure plasma arc cleaning metal parts.According to the mobile cleaning interface, changeful calculation region and non-linear boundary conditions along the thickness direction, in this thesis, a mathematical model of reactive kinetics in the metal surface contaminant cleaning using APPA has been developed, by means of thermal conduction differential equation and Arrhenius equation. Afterwards, reactive kinetics parameters such as activation energy and pre-exponential factor are calculated. On this basis, the intrinsic relationship between contaminant removal percentages, removal rate and influencing factors such as cleaning time and ambient temperature of APPA cleaning are revealed and validated with related experiments results. The results indicated that contaminant removal percentages increase with cleaning time increasing until the contaminant is drastically cleaned by APPA. Furthermore, the ambient temperature of APPA on the contaminant surface affects the removal percentages strongly. The removal percentages increase with the increase of the ambient temperature. To avoid the damage of metal substrate surface because of higher temperature and ensure the removal rate of the contaminant, the appropriate temperature which lies between the contaminant decomposition temperature and damage temperature of metal substrate.According to the fact that energy distribution of APPA having a significant effect on cleaning quality and arc properties including current density distribution and temperature distribution being difficult to achieved by direct measurement methods, a three-dimensional axisymmetric mathematical model, including the influence of the swirl exiting in the plasma torch, has been developed to describe the heat transfer and fluid flow within a combined plasma arc with magneto-hydrodynamics equations and Maxwell equations. In this model, a mapping method and a meshing method of variable step-size are adopted to mesh the calculation domain and to improve the results precision. To overcome a problem from the coexistence of non-transferred arc and transfer arc and the coupling between electric, magnetic, heat flow and fluid flow phenomena in the combined plasma arc, a sequential coupling method and a physical environment approach are introduced into the finite element analysis on jet characteristics of the combined plasma arc. Furthermore, the jet characteristics of combined plasma arc such as temperature, velocity, current density and electromagnetic force are studied; the effects of working current, gas flow and the distance from the nozzle outlet to the anode on the distributions of temperature, velocity and current density are also revealed. Compared with the collection and diagnosis on the combined plasma arc by CCD, the results show that the simulated value appears to be in good agreement with measured value under the conditions of the same process parameters.According to the problem that the energy distribution of plasma arc being limited in smaller region and the temperature gradient of plasma arc having more variation in the arc column owing to the avalanche effect of gas discharge and the constraint of plasma arc by its own magnetic field, an external transverse alternating magnetic field is applied to APPA to create a plasma for cleaning a large metal surface. On the basis, two mathematical models are developed to describe the oscillating amplitude of the plasma arc root along the metal surface and the heat flux density distribution of plasma arc on the metal surface, respectively. The behavior of plasma arc under the external transverse triangular alternating magnetic field imposed perpendicular to the plasma current is discussed, and the effect of process parameters such as working gas flow rate, arc current, magnetic flux density and the distance from the nozzle outlet to the anode workpiece on the form and heat flux distribution of plasma arc are also revealed and validated with related experiments results. The results show that it is feasible to control the shape and heat flux density of APPA with the external transverse alternating magnetic field, which can expand the region of plasma arc thermal treatment and flatten the heat flux density upon the workpiece, so as to ensure APPA cleaning quality and to simultaneously improve the cleaning efficiency of APPA cleaning. Furthermore, the oscillating amplitude of plasma arc increases and the heat flux density gradient upon the workpiece decrease with the magnetic flux density enhancing. However, an overly strong magnetic field results in the plasma arc unstable. Under the same magnetic flux density, less gas flow rate and arc current, more distance from the nozzle outlet to the anode cause the oscillating amplitude to increase. Contrarily, the more gas flow rate and arc current, the more heat flux density peak increase. Moreover, more distance from nozzle outlet to workpiece descends the heat flux density peak.According to the fact that APPA cleaning being a complicated and non-linear process, cleaning quality being influenced by process parameters and the interaction of different parameters being complex, based on many experiments on APPA cleaning, an intelligent predictive model of the non-linear relationship between cleaning quality (water contact angle of cleaned surface) and process parameters is established with the research of Least Squares Support Vector Machines (LS-SVM) and Principal Component Analysis (PCA). Afterwards, Artificial Fish Swarm Algorithm (AFSA) is introduced to optimize established control model of cleaning quality and to obtain the optimum process parameters under a certain range of these parameters. The results indicate that it is feasible to apply PCA-SVM and AFSA in forecasting the cleaning quality and determining the process parameters of APPA cleaning. The maximum relative error and MAPE error are 3.05% and 2.605%, respectively. It is obvious to reduce the water contact angle of cleaned surface and to improve cleaning quality of APPA cleaning with above optimum process parameters.