In woodworking industry; e.g. sawmills; the functioning of the assembly line is relatively monotonic from day to day. Typically; CA is almost entirely used for linear motions. A double acting cylinder is the most common actuator in these applications. The length of the impact; the radius of the piston and radius of the cylinder are the essential key figures of this cylinder type. From these figures and basic dynamics of the cylinder; the air volume per impact can be obtained. When the average values and standard deviation of the air flow in each consumption point (cylinder) is known; statistical methods can be implemented for the total consumption of CA. According to the Central Limit Theorem; the total air consumption; i.e the sum of consumptions in different consumption points; can be assumed to be normal-distributed. Since the consumed air flow is proportional to the compressor’s energy consumption; the trend of energy can also be approximated as a sum of regression curve and normally distributed deviation component. By this result; a confidence interval for energy consumption can be determined. The result is also ready to be used in energy saving calculations in the future.
Also; the adjustable pressure-difference in a two-point controlled compressor has an essential effect on the overall energy efficiency of the system. When this pressure difference is large; the system is not optimal from the viewpoint of energy efficiency. Typically the time series measurements of pressure are somewhat noisy; but some kind of conclusions of stationary behavior can be done. After possible pre-filtering process of the data; it becomes evident that the measurement data signal is typically a periodic shape with strict minimum and maximum values. The consumption of CA is typically dependent on pressure i.e. higher pressure increases consumption making the shape of pressure curve exponential. A stationary time series described by its mean; variance and autocorrelation function makes possible to identify the essential features of the dynamics of the CA system and the type of consumption.
With the appropriate statistical methods; the results of short-time measurements can be applied for predicting the energy consumption trend in a long run. The combination of first principle modeling with measurements opens new methods in energy efficiency techniques especially when designing new pneumatic systems or the improving of existing designs
Keywords: Pneumatics in woodworking industry; time series analysis; estimate; confidence interval; autocorrelation
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