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CN-122020309-A - Pressure wave characteristic identification system and risk prediction method for building drainage system

CN122020309ACN 122020309 ACN122020309 ACN 122020309ACN-122020309-A

Abstract

The invention discloses a pressure wave characteristic identification system and a risk prediction method of a building drainage system, including multipoint absolute pressure sensor arrays, edge computation gateways, cloud platforms, and related communication links and connection components. The system realizes synchronous acquisition of pressure waveforms of all floors, carries out band-pass filtering and baseline correction on the edge side, extracts the characteristics of peak value, rising edge slope, pulse width, characteristic frequency, cross-layer propagation delay, attenuation and the like, and carries out event identification and source layer positioning. And calculating an impact risk index and a water seal failure probability based on the characteristics, and realizing accurate identification of a drainage event and advanced prediction of cross-layer risk. The invention solves the problems of lag monitoring, difficult positioning and missing risk prejudgment of the existing system, realizes early warning and feedforward protection, and effectively reduces the risk of water seal damage and aerosol transmission.

Inventors

  • ZHAO JING
  • LIU DEHAN
  • CHEN ZIYI
  • XU DAYAN

Assignees

  • 天津大学

Dates

Publication Date
20260512
Application Date
20260202

Claims (7)

  1. 1. The pressure wave characteristic recognition system of the building drainage system is characterized by comprising a multipoint pressure acquisition array, a time synchronization and edge calculation unit, an event recognition unit, a risk prediction unit, a self-calibration and active disturbance module and a linkage control interface; The multipoint pressure acquisition array comprises a high sampling rate absolute pressure sensor (3), an inclined branch pipe (2) and a protection component, wherein one end of the inclined branch pipe (2) is connected with an overhaul port of a drainage vertical pipe (1), and the absolute pressure sensor (3) is arranged at the other end of the inclined branch pipe; the absolute pressure sensor (3) array is used for synchronously collecting pressure waveforms in the vertical pipe; The edge computing gateway (4) is in signal connection with the absolute pressure sensor (3) and is used for carrying out band-pass filtering and baseline correction, abnormal point detection and rejection, feature extraction, event identification and source layer positioning on the acquired data; the roof atmospheric pressure reference station (5) provides zero point reference and time synchronization reference for the edge computing gateway (4); The miniature reversible speed regulation fan (6) is communicated with the vertical pipe ventilation system and is used for ventilation regulation and active disturbance; the cloud platform (7) is connected with the edge computing gateway (4) through a wireless communication link (8) and is used for risk assessment, linkage strategy arrangement and model management; the system is configured in association with the drainage branch pipe (9), the floor drain (10) and the closestool (11) and is used for evaluating and protecting the water sealing state of related appliances; And when the risk assessment exceeds a preset threshold, the linkage control interface pushes prompt information to the miniature reversible speed-regulating fan (6) and the related household terminals by the cloud platform (7).
  2. 2. The system according to claim 1, wherein the absolute pressure sensor (3) synchronously collects absolute pressure data of the pipeline, and the edge computing gateway (4) realizes cross-layer synchronization.
  3. 3. The system according to claim 1, characterized in that the rooftop barometric pressure reference station (5) is adapted to zero-point and temperature drift self-calibration of the channels in a low event window, after calibration to control the static cross-layer differential within preset tolerances.
  4. 4. The system according to claim 1, characterized in that the miniature reversible speed-regulating fan (6) is adapted to apply small, short-term active disturbances for a predetermined period of time to re-estimate the cross-layer propagation delay, attenuation and propagation velocity and to update the identification template and threshold on-line accordingly.
  5. 5. The system according to claim 1, wherein the edge computing gateway (4) has health monitoring and failure isolation functions, including detecting channel congestion, sensor saturation, link loss or time tick anomalies, and de-weighting or isolating suspicious channels.
  6. 6. The system according to claim 1, characterized in that the wireless communication link (8) employs a protocol with encryption and mutual authentication and implements data and control interactions with the edge computing gateway (4).
  7. 7. A method for identifying pressure wave characteristics and predicting risk of a drainage system of a building, which is applied to the system of any one of claims 1 to 6, and is characterized by comprising the following steps: Step A, multipoint pressure wave synchronous acquisition and preprocessing, wherein a cloud platform (7) time synchronization module issues a time reference, an absolute pressure sensor (3) acquires pressure data, and an edge computing gateway (4) executes bandpass filtering, baseline correction, outlier rejection and amplitude normalization; the step B is event feature extraction and database updating, in which an edge computing gateway (4) extracts time domain, frequency domain, time frequency and cross-layer propagation features of pressure waves to form feature vectors and updates a historical event feature database; Step C, mixing identification and source positioning of drainage events, namely adopting a dynamic time warping algorithm to carry out coarse classification, carrying out fine classification through a convolutional neural network model, and positioning event source floors by combining cross-layer propagation delay; Step D, cross-layer risk dynamic prediction and early warning, namely calculating a reverse propagation risk index and a water seal failure probability based on event type and pressure wave characteristics, wherein the reverse propagation risk index is a weighted function of pressure peak value, duration, concurrency and propagation consistency, and the water seal failure probability is logistic regression or logistic function output based on factors such as pressure statistic, temperature and humidity, appliance type and the like; and E, self-calibration and active disturbance optimization of the system, namely calibrating a sensor zero point and a temperature drift through a roof atmospheric pressure reference station (5) in a daily low event window, applying pressure disturbance through a miniature reversible speed regulation fan (6), and updating a propagation baseline and model parameters.

Description

Pressure wave characteristic identification system and risk prediction method for building drainage system Technical Field The invention belongs to the technical field of intelligent control and drainage safety of building environments, and relates to a system and a method for carrying out multipoint synchronous acquisition on pressure waves in a drainage vertical pipe of a building, intelligently identifying drainage events and predicting cross-layer risks, which are suitable for new construction and existing reconstruction of multi-layer and high-rise buildings such as houses, dormitories, apartments and the like. Background Building drainage systems, which serve as potential contaminant and pathogen transmission pathways, in communication with indoor air circuits have been identified as one of the key factors in causing cross-transmission during epidemic situations. According to relevant national specifications, the depth of the water seal of the floor drain is usually not less than 50 mm. However, in actual use, the water seal may be disabled due to evaporation caused by low-frequency use, positive and negative pressure transient caused by movement of a water column in the drainage vertical pipe, ventilation condition change and other factors, so that an indoor space is communicated with a gas path of the drainage system, and the risk that pollutant aerosol in the drainage system enters the room is obviously increased. At present, the drainage system of residential buildings in China mainly uses gravity type non-full flow, and lacks real-time monitoring, operation and maintenance and inspection means aiming at the running state. The operation period depends on single-point liquid level monitoring or peculiar smell complaints and other afterward signals, so that event sources such as blockage, water seal damage, ventilation abnormality and the like are difficult to identify and position in advance timely and accurately. In the aspect of numerical simulation, an equivalent one-dimensional two-phase transient model can be used for boundary evaluation, computational Fluid Dynamics (CFD) can realize fine simulation and reverse tracing, but has limited suitability for complex branch pipes, random occupation modes and multi-source concurrency, and has high computing cost and boundary condition sensitivity, so that the real-time and large-scale deployment requirements of engineering scenes are difficult to meet. In addition, the drainage system is positioned in a building and limited by space and sanitary conditions, the invasive test and long-term control are difficult, and cross-floor multi-point synchronous data are deficient, so that the cross-floor propagation rule and risk look-ahead evaluation capability of pressure waves are insufficient. Therefore, a systematic scheme of combining multipoint synchronous acquisition, edge feature extraction and hybrid identification with riser pressure as a core and coupled with risk index prediction closed loop is needed to realize drainage safe operation guarantee capable of foresight sensing, active positioning and active protection. Disclosure of Invention In order to make up and improve the defects of the prior art, the invention provides a pressure wave characteristic identification system and a risk prediction method of a building drainage system. The method aims at solving the problems that in the prior art, the pressure wave collection of the drainage vertical pipe is not timely and synchronous, the transient characteristic of instantaneous pressure cannot be captured, the identification precision of drainage events is low, the cross-layer propagation characteristic is difficult to use, the source position is difficult to determine, a cross-layer risk prediction model based on the pressure wave characteristic is lacking, the water seal failure and aerosol propagation risk cannot be prejudged in advance, and the like. The technical scheme adopted by the invention for solving the problems is as follows: a riser pressure wave acquisition system for a building drainage system, the system comprising: The multi-point pressure acquisition array is characterized in that a high sampling rate absolute pressure sensor node is led out and installed at the easily accessible position of a drain riser access hole or a branch pipe of each floor by an L-shaped inclined branch pipe, a hydrophobic and breathable film and a detachable filter screen are arranged at the end part of the node to inhibit condensation and dirt blocking, a condensation reflux gradient is arranged in a cavity, and a shell is provided with an IP65 and an anti-corrosion coating. Preferably, the absolute pressure sensor node meets the requirements of a range of 0 to +/-5 kPa or wider, the resolution is less than or equal to 0.1 Pa, the sampling rate is 100-500 Hz, and the typical bandwidth is 0.05-10 Hz. The time synchronization and edge calculation unit is used for deploying 1 edge gateway at each layer, co