CN-121539748-B - Intelligent gas terminal energy-saving control Internet of things system and method

CN121539748BCN 121539748 BCN121539748 BCN 121539748BCN-121539748-B

Abstract

The invention provides an intelligent gas terminal energy-saving control Internet of things system and method, which relate to the technical field of Internet of things, and the method is executed based on an intelligent gas management platform of the intelligent gas terminal energy-saving control Internet of things and comprises the steps of acquiring gas use data and gas image data of a target user through an intelligent gas object platform; the method includes determining a combustion state distribution based on gas usage data, gas image data, determining an energy saving parameter based on the combustion state distribution in response to the combustion state distribution satisfying a preset condition, and determining an energy saving instruction and a slave adjustment instruction based on the energy saving parameter to adjust a valve opening of a valve regulating device based on the energy saving instruction and the slave adjustment instruction. Through evaluating the combustion state, the energy-saving parameter is adjusted according to the combustion state, so that the gas flow rate is properly reduced, and the provided gas flow rate is ensured to achieve the effects of energy saving and environmental protection under the condition of meeting the user demand.

Inventors

SHAO ZEHUA
LI YONG
CHEN YUNBAI
WANG JUN

Assignees

成都秦川物联网科技股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260115

Claims (6)

1. The intelligent gas terminal energy-saving control Internet of things system is characterized by comprising an intelligent gas user platform, an intelligent gas service platform, an intelligent gas management platform, an intelligent gas sensing network platform and an intelligent gas object platform which are connected in sequence; The intelligent gas object platform comprises a supervision sensing device, an image acquisition device and a sound acquisition device, wherein the supervision sensing device and the image acquisition device are arranged on a gas terminal, the supervision sensing device is configured to acquire gas use data of a target user, the image acquisition device is configured to acquire gas image data of the target user, and the sound acquisition device is configured to acquire gas sound data of the target user; the intelligent gas management platform is configured to: acquiring the gas use data and the gas image data of a target user through the intelligent gas object platform; determining combustion state distribution based on the gas use data and the gas image data, wherein the combustion state distribution comprises gas impurity content and combustion insufficient value, and the combustion insufficient value refers to the mass ratio of CO in substances generated after insufficient combustion of the gas; Determining an energy saving parameter based on the combustion state distribution in response to the combustion state distribution meeting a preset condition, the preset condition including the combustion insufficient value being greater than a sufficiency threshold, the sufficiency threshold negatively related to the gas impurity content; Determining an energy-saving instruction and a driven adjustment instruction based on the energy-saving parameter to adjust the valve opening of a valve regulating device based on the energy-saving instruction and the driven adjustment instruction, wherein the energy-saving instruction refers to an instruction for adjusting the gas flow rate of an adjacent pipeline, and the driven adjustment instruction refers to an instruction for adjusting the gas flow rate of an upstream pipeline of the adjacent pipeline; wherein the determining a combustion state distribution based on the gas usage data, the gas image data includes: Determining the combustion state distribution through a state prediction model based on the fuel gas usage data, the fuel gas image data and the fuel gas sound data, wherein the state prediction model is a machine learning model and comprises a feature extraction layer, a first prediction layer, a second prediction layer and a correction layer, and the feature extraction layer, the first prediction layer, the second prediction layer and the correction layer are all machine learning models; the method comprises the steps of determining gas usage characteristics based on gas usage data by a characteristic extraction layer, determining first state distribution based on the gas usage characteristics and gas image data by a first prediction layer, determining second state distribution based on the gas usage characteristics and gas sound data by a second prediction layer, determining combustion state distribution based on the gas usage characteristics, the first state distribution, the second state distribution and user characteristics by a correction layer, wherein the user characteristics comprise user types and average gas consumption, the training process of a state prediction model comprises dividing a first sample data set into a training set and a testing set according to preset rules based on the user characteristics corresponding to a first training sample in the first sample data set, training and testing an initial state prediction model based on the training set and the testing set, and obtaining the state prediction model, wherein the learning rate corresponding to each first training sample in the training set is related to iteration rounds and subsequent energy saving amplitude of the first training sample, and the average energy saving amplitude is a difference value between the average energy saving amplitude of the gas and the energy saving amplitude before adjustment.
2. The system of claim 1, wherein the intelligent gas management platform is further configured to: Determining candidate energy-saving parameters; Determining a predicted heat value based on the candidate energy saving parameter and the combustion state distribution; Determining a demand heat value based on the user characteristics; Determining a demand satisfaction degree of the candidate energy saving parameter based on the estimated heat quantity value and the demand heat quantity value, and And determining the energy-saving parameter based on the demand satisfaction.
3. The system of claim 2, wherein the intelligent gas management platform is further configured to: And determining the estimated heat value through a heat value prediction model based on the candidate energy saving parameters and the combustion state distribution, wherein the heat value prediction model is a machine learning model.
4. An intelligent gas terminal energy-saving control method is characterized in that the method is realized based on the intelligent gas terminal energy-saving control internet of things system according to claim 1, and the system comprises an intelligent gas user platform, an intelligent gas service platform, an intelligent gas management platform, an intelligent gas sensing network platform and an intelligent gas object platform which are connected in sequence; The intelligent gas object platform comprises a supervision sensing device, an image acquisition device and a sound acquisition device, wherein the supervision sensing device and the image acquisition device are arranged on a gas terminal, the supervision sensing device is configured to acquire gas use data of a target user, the image acquisition device is configured to acquire gas image data of the target user, and the sound acquisition device is configured to acquire gas sound data of the target user; the method is executed by an intelligent gas management platform and comprises the following steps: acquiring the gas use data and the gas image data of a target user through the intelligent gas object platform; determining combustion state distribution based on the gas use data and the gas image data, wherein the combustion state distribution comprises gas impurity content and combustion insufficient value, and the combustion insufficient value refers to the mass ratio of CO in substances generated after insufficient combustion of the gas; Determining an energy saving parameter based on the combustion state distribution in response to the combustion state distribution meeting a preset condition, the preset condition including the combustion insufficient value being greater than a sufficiency threshold, the sufficiency threshold negatively related to the gas impurity content; Determining an energy-saving instruction and a driven adjustment instruction based on the energy-saving parameter to adjust the valve opening of a valve regulating device based on the energy-saving instruction and the driven adjustment instruction, wherein the energy-saving instruction refers to an instruction for adjusting the gas flow rate of an adjacent pipeline, and the driven adjustment instruction refers to an instruction for adjusting the gas flow rate of an upstream pipeline of the adjacent pipeline; wherein the determining a combustion state distribution based on the gas usage data, the gas image data includes: Determining the combustion state distribution through a state prediction model based on the fuel gas usage data, the fuel gas image data and the fuel gas sound data, wherein the state prediction model is a machine learning model and comprises a feature extraction layer, a first prediction layer, a second prediction layer and a correction layer, and the feature extraction layer, the first prediction layer, the second prediction layer and the correction layer are all machine learning models; the method comprises the steps of determining gas usage characteristics based on gas usage data by a characteristic extraction layer, determining first state distribution based on the gas usage characteristics and gas image data by a first prediction layer, determining second state distribution based on the gas usage characteristics and gas sound data by a second prediction layer, determining combustion state distribution based on the gas usage characteristics, the first state distribution, the second state distribution and user characteristics by a correction layer, wherein the user characteristics comprise user types and average gas consumption, the training process of a state prediction model comprises dividing a first sample data set into a training set and a testing set according to preset rules based on the user characteristics corresponding to a first training sample in the first sample data set, training and testing an initial state prediction model based on the training set and the testing set, and obtaining the state prediction model, wherein the learning rate corresponding to each first training sample in the training set is related to iteration rounds and subsequent energy saving amplitude of the first training sample, and the average energy saving amplitude is a difference value between the average energy saving amplitude of the gas and the energy saving amplitude before adjustment.
5. The method of claim 4, wherein determining an energy saving parameter based on the combustion state profile in response to the combustion state profile meeting a preset condition comprises: Determining candidate energy-saving parameters; Determining a predicted heat value based on the candidate energy saving parameter and the combustion state distribution; Determining a demand heat value based on the user characteristics; Determining a demand satisfaction degree of the candidate energy saving parameter based on the estimated heat quantity value and the demand heat quantity value, and And determining the energy-saving parameter based on the demand satisfaction.
6. The method of claim 5, wherein said determining an estimated heat value based on said candidate energy saving parameter and said combustion state profile comprises: And determining the estimated heat value through a heat value prediction model based on the candidate energy saving parameters and the combustion state distribution, wherein the heat value prediction model is a machine learning model.

Description

Intelligent gas terminal energy-saving control Internet of things system and method Technical Field The specification relates to the technical field of Internet of things, in particular to an intelligent gas terminal energy-saving control Internet of things system and method. Background With the development of social economy, the application of combustible gases such as natural gas as non-renewable energy sources in life and industrial production of people is becoming wider, and the consumption is increasing year by year. The problem that how to develop the energy-saving management of the fuel gas is urgent to be solved in the current fuel gas operation while meeting the requirements of human production and living. Different combustion use conditions exist due to the differences of gas pipelines, gas equipment, environments and the like of different gas end users. Therefore, the energy-saving management of the fuel gas needs to formulate corresponding energy-saving measures and management strategies according to specific situations. Therefore, it is desirable to provide an intelligent gas terminal energy-saving control internet of things system and method, which are beneficial to formulating corresponding gas energy-saving measures and management strategies according to gas combustion. Disclosure of Invention The intelligent gas terminal energy-saving control Internet of things system comprises an intelligent gas user platform, an intelligent gas service platform, an intelligent gas management platform, an intelligent gas sensing network platform and an intelligent gas object platform which are sequentially connected, wherein the intelligent gas object platform comprises a supervision sensing device and an image acquisition device, the supervision sensing device and the image acquisition device are arranged on a gas terminal, the supervision sensing device is configured to acquire gas use data of a target user, the image acquisition device is configured to acquire gas image data of the target user, the intelligent gas management platform is configured to acquire the gas use data and the gas image data of the target user through the intelligent gas object platform, determine combustion state distribution based on the gas use data and the gas image data, respond to the combustion state distribution to meet preset conditions, determine energy saving parameters based on the combustion state distribution, and determine an energy saving instruction and a driven adjustment instruction based on the energy saving parameters so as to adjust the valve opening of a valve regulating device based on the energy saving instruction and the driven adjustment instruction. The intelligent gas terminal energy-saving control method is executed by an intelligent gas management platform and comprises the steps of acquiring gas use data and gas image data of a target user through the intelligent gas object platform, determining combustion state distribution based on the gas use data and the gas image data, determining energy-saving parameters based on the combustion state distribution in response to the combustion state distribution meeting preset conditions, and determining an energy-saving instruction and a driven adjustment instruction based on the energy-saving parameters to adjust valve opening of a valve regulating device based on the energy-saving instruction and the driven adjustment instruction. The energy-saving combustion system has the beneficial effects that the combustion state is evaluated, and the energy-saving parameters are adjusted according to the combustion state, so that the gas flow rate is properly reduced, and the energy-saving and environment-friendly effects are achieved under the condition that the provided gas flow rate meets the requirements of users. Drawings The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein: FIG. 1 is an exemplary block diagram of an intelligent gas terminal energy conservation control Internet of things system according to some embodiments of the present description; FIG. 2 is an exemplary flow chart of a method of intelligent gas terminal power saving control according to some embodiments of the present description; FIG. 3 is an exemplary schematic diagram of a state prediction model shown in accordance with some embodiments of the present description; FIG. 4 is an exemplary flow chart for determining energy saving parameters according to some embodiments of the present description. Detailed Description In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are