Low-power consumption network monitoring module for building equipment energy flow

Abstract

The invention relates to a network monitoring module, and particularly relates to a low-power consumption network monitoring module for a building equipment energy flow. The invention aims to solve a technical problem of providing a low-power consumption network monitoring module, which is low in energy consumption, long in service life and wide in application range, for a building equipment energy flow. In order to solve the technical problem, the invention provides a low-power consumption network monitoring module for the building equipment energy flow. The low-power consumption network monitoring module comprises a power supply, a signal awakening module, a wireless temperature sensor and an anode line, wherein the signal awakening module comprises a shell, an expansion liquid tank, a piston, an L-shaped push rod, a rack, a gear, a rotating rod, an arc-shaped switch and a trigger device, and the power supply is connected with the signal awakening module through the anode line. According to the invention, variations in heat are converted into variations in rotation of the rotating rod, the arc-shaped switch on the rotating rod is contacted with an arc-shaped block in the rotating process, then the arc-shaped switch connects the anode line, and the wireless temperature sensor operates.

Description

technical field [0001] The invention relates to a network monitoring module, in particular to a network monitoring module for energy flow of low-power building equipment. Background technique [0002] The network monitoring, evaluation and optimization method of building equipment energy flow, using coupling optimization technology to evaluate the efficiency of regional energy use. Use energy consumption as an important optimization index to evaluate the efficiency of regional energy use, and establish an energy dispatching system; monitor, analyze and evaluate based on energy flow networks; establish an expert system for diagnosing abnormal energy consumption. Predict the energy consumption of each process or the comprehensive energy consumption per unit of energy based on the annual, quarterly, and monthly planning data of building use, as well as historical energy data and climate data. Using intelligent budget algorithms such as linear regression, neural network, and su...

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the shortcomings of high energy consumption, short service life and narrow application range of the current network monitoring module for energy flow of construction equipment, the technical problem to be solved by the present invention is to provide a low energy consumption, long service life and wide application range Wide network monitoring module of low-power building equipment energy flow

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