Detection method and system for leakage current of heat exchanger

Abstract

The invention provides a detection method and system for leakage current of a heat exchanger. The detection method comprises the steps of collecting process data of a plurality of sample sets of the heat exchanger, calculating a total heat transfer coefficient through an energy-balance equation with the process data as an input condition, calculating scaling heat resistance through a total heat transfer coefficient equation according to the total heat transfer coefficient, carrying out noise elimination processing on the scaling heat resistance, generating scaling heat resistance after noise elimination, calculating the mean value and variance of the scaling heat resistance after noise elimination according to the scaling heat resistance after noise elimination, and judging whether the heat exchanger leaks or not according to the mean value and the variance. Compared with the prior heat exchange leakage current diagnostic technology, the detection method is high in calculation real-time performance and short in time delay, and is not affected by operation conditions of other devices except for the heat exchanger; the wavelet transform theory is adopted to process field data on line, influence on diagnosis results from noise is weakened, calculation accuracy is improved, implementation is facilitated, and the total cost is low.

Description

technical field [0001] The invention relates to the system engineering field of petrochemical industry, in particular to a detection method and system for heat exchanger leakage. Background technique [0002] Heat exchangers are widely used in energy recovery systems in the petrochemical process industry, which can greatly reduce their investment and operating costs. However, due to factors such as corrosion, inconsistent thermal expansion and contraction of various parts of the heat exchanger at high temperatures, and fluid-induced vibration, the heat exchanger is often damaged and leakage occurs from time to time, that is, the tube-side fluid flows into the shell side or the shell-side fluid. It flows into the tube side, causing losses such as pollution between the heat-exchanging media. This leakage phenomenon of the heat exchanger occurs in the casing, which cannot be found by naked eyes, and has great concealment. [0003] At present, by installing flowmeters at the i...

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Problems solved by technology

However, due to factors such as corrosion, inconsistent thermal expansion and contraction of various parts of the heat exchanger at high temperatures, and fluid-induced vibration, the heat exchanger is often damaged and leakage occurs from time to time, that is, the tube-side fluid flows into the shell side or the shell-side fluid. Flowing into the tube side, causing pollution and other losses between the heat-exchanging media

This kind of heat exchanger leakage phenomenon occurs in the shell, which cannot be found by naked eyes, and has great concealment.

[0003] At present, by installing flowmeters at the inlet and outlet of each heat exchanger to monitor the inlet and outlet flows of cold and hot fluids in real time, it is possible to judge whether leakage occurs. However, since petrochemical equipment includes dozens or even hundreds of heat exchangers, Installing flowmeters at the inlet and outlet of each heat exchanger will increase equipment investment costs, and in view of constraints such as space distribution and pipe fitting requirements, it is difficult to install flowmeters in pipe sections between heat exchangers for engineering implementation

In actual production, leakage is often found through regular maintenance. This method also has the following disadvantages: (1) There is a large time lag in the use of regular maintenance to find leakage, which cannot reflect the specific situation in the current heat exchanger in real time. (2) Due to the difficulty in finding the leakage of the heat exchanger in time, it will cause energy loss, which will pollute the materials and affect the product quality, and even cause production hazards

However, with soft measurement technology, due to the complex environment on site, there is a lot of noise in the collected data on site, and noise interference may lead to misjudgment and operation, so it is necessary to process the collected data

In the industrial process, signal noise reduction is an indispensable part. The traditional linear filtering method has a contradiction between protecting the local characteristics of the signal and suppressing the noise due to its singularity of scale. In the actual process, this filtering method must be based on Knowability of the model is the premise, but this condition is often not satisfied in practice

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