Particulate fouling experimental device, prediction method and prediction system for arc-tube heat exchanger

Abstract

The invention discloses a fouling experimental device, provides a particulate fouling resistance prediction method for an arc-tube heat exchanger, and further discloses a corresponding prediction system by utilizing the object-oriented high-level language Delphi. The prediction method comprises establishment of the fouling experimental device, determination of experimental tubular products, determination of geometric dimensions, installation of a measurement and control unit, measurement and processing of parameters, establishment of prediction models, optimization of important parameters, and establishment and application of judgment models and the prediction system. According to the particulate fouling experimental device, the prediction method and the prediction system for the arc-tube heat exchanger, the defect of a local minimum of a neural network and other conventional methods is overcome, the phenomena of under-learning and over-learning are effectively restrained, the problem of generalization in the machine learning theory is solved, the calculated amount is small, the model optimization speed is high, and online monitoring of fouling resistance of a heat-exchange device can be achieved. The most prominent advantage is that small samples can be used for training models. Due to the fact that the fouling characteristics of the heat exchanger are predicted by the models in terms of temperature, flow speed and other parameters which are easy to measure, a lot of manpower and material resources are saved, and a new method is provided for designing a cooling water system under a known water quality condition afterwards and predicting the fouling characteristics.

Description

technical field [0001] The invention relates to the field of fouling and countermeasures of heat exchange equipment in high energy-consuming industries, in particular to an experimental device for particle fouling of arc tube heat exchangers, a prediction method and a prediction system. Background technique [0002] In the prediction of the fouling characteristics of heat exchangers, people have done a lot of research work and achieved certain results. Kern and Seaton first proposed the scaling model that the change of thermal resistance of fouling with time is the difference between deposition rate and erosion rate. Based on this, subsequent researchers further summarized the relationship of thermal resistance of fouling with time into empirical models such as linear, decreasing law, and asymptotic fouling growth, making fouling prediction a big step forward from pure theory to industrial application. Fan Shaosheng from Changsha University of Science and Technology fully c...

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The flow signal is measured by an ultrasonic flowmeter

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