Precise metering method and metering device for fluid delivery system based on artificial intelligence

Abstract

The invention relates to an artificial intelligence-based precise measuring method and measuring device for a fluid conveying system. The measuring method includes the following steps: Step 1: Install a measuring device capable of measuring flow Q, pressure P, temperature T, vibration V and noise I. In the fluid system, the data of five basic parameters of flow Q, pressure P, temperature T, vibration V, and noise I are obtained as the measurement model data; step 2: perform graphical processing of the measurement model data; The value of the measured data is set as Dt=(Qt Pt Tt Vt At), and the value is compared with the measurement model to determine whether the value is correct; if the value is correct, output the data directly; If it is abnormal, you need to get the number of wrong data, and adjust the parameters of the abnormal value before outputting the data. The invention realizes a micro-artificial intelligence, which can accurately measure and online accurately check the parameters of the fluid system, improve the operation safety of the fluid system, improve the measurement means, and reduce the overall cost.

Description

technical field [0001] The invention relates to the field of fluid delivery systems, in particular to an artificial intelligence-based precise measurement method and measurement device for a fluid delivery system. Background technique [0002] The pipeline transportation of fluid medium is used in all aspects of production and life, where the fluid medium refers to liquid, gas or gas-liquid two-phase medium. In actual engineering, it is necessary to measure the following data for the fluid delivery system: five basic parameters: flow (Q), pressure (P), temperature (T), vibration (V), and noise (I), to ensure precise management of the delivery medium . [0003] These five kinds of data are measured through five kinds of sensors, namely: flow sensor, pressure sensor, temperature sensor, vibration sensor, and noise sensor. These five sensors are usually installed on the fluid system delivery pipeline respectively, and there are the following problems in actual engineering: ...

AI Technical Summary

Problems solved by technology

The source hole will actually bring safety hazards to the fluid system, such as the explosion of the weld seam at the connection pipe between the source hole and the sensor, resulting in medium leakage, etc.

However, the existing pipelines have too many source holes, and each sensor needs to correspond to a source hole

[0005] ② Vibration and noise sensing signals are easily affected by the external environment, and users often cannot read the actual values ​​of such parameters in the fluid system, so users often do not choose to install these two types of sensors

However, in the actual process, users often cannot find the measurement failure in time or the calibration requires professional personnel and equipment, so there is a phenomenon that the measurement work is generally not in place, which brings passiveness to the management of the fluid system.

And we can think that: the sensor parameters are correct within one year of use, and failures may occur after one year, and the occurrence of such failures is random, and the existing technology cannot achieve the accuracy of quantitative fixed-point analysis data, so as to Determine whether there is a problem with each sensor

[0007] ③In the past, artificial intelligence required the use of cloud terminals for machine learning, and the data center thus established had high energy consumption and caused environmental pollution

[0008] ③At present, when the fluid medium flows through the whole system through the pump or high water level, the past engineering experience is to calculate the head loss and pipeline pressure of each part of the system to determine the required pump power or the length of the delivery distance, but when the pump motor When the frequency changes or the opening of the valve in the pipeline changes, the delivery flow will change. At this time, the head loss of each part of the fluid system is different from the delivery flow before the change, but there is no corresponding instrument measurement

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