Shower room water supply pipe sealing performance detection method

Abstract

The invention discloses a shower room water supply pipe sealing performance detection method, and relates to the field of bathroom product detection, and the method comprises the steps: applying a test pressure to a shower room water supply pipeline at a detection station; in the process of applying the test pressure, the stress distribution change of a sealing interface is monitored in real time through a flexible pressure sensing array arranged at the joint of the water supply pipeline of the shower room; after the linear influence on the stress distribution change caused by the fluctuation of the test pressure is eliminated, the sealing failure risk is predicted according to the nonlinear characteristics of the stress distribution change; and when the sealing failure risk is predicted. According to the invention, acoustic emission signals are collected through an acoustic emission sensor array, and activity screening is carried out on the signals according to a pressure-time history so as to verify risks; and comprehensively judging the sealing performance of the pipeline based on the prediction result of the stress distribution change and the screened acoustic emission verification result.

Description

Technical Field

[0001] This invention relates to the field of sanitary ware product testing, and in particular to a method for testing the sealing performance of shower room water supply pipes. Background Technology

[0002] In the field of bathroom product testing, the sealing performance of shower room water supply pipes is a core quality indicator. Currently, the industry widely uses the static pressure holding test method for this test. This method involves applying a specified pressure to the pipe and holding it for a period of time, monitoring whether the pressure reading drops below a threshold to determine if the seal is qualified. This technical solution is clear in principle, simple to implement, and constitutes the existing benchmark for quality control.

[0003] Traditional methods are essentially a passive assessment of the final result. Their limitation is that they can only identify faults after macroscopic leakage has occurred, and cannot capture early signs before leakage occurs, such as progressive wear of the sealing ring, slight loosening of the threaded connection, or the propagation of micro-cracks inside the material. These potential failure modes may not have caused observable pressure changes in the early stages of pressure holding testing, but the risk of failure already exists. Therefore, existing technologies are unable to achieve predictive assessment of sealing performance and accurate diagnosis of the root cause of failure. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for testing the sealing performance of shower room water supply pipes to solve the problem that existing technologies cannot predict and accurately diagnose the risk of sealing failure before macroscopic leakage occurs.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for testing the sealing performance of a shower room water supply pipe, which includes applying test pressure to the shower room water supply pipe at the testing station; During the application of the test pressure, the stress distribution changes at the sealing interface are monitored in real time by a flexible pressure sensor array installed at the connection of the shower room water supply pipe. After eliminating the linear influence of the test pressure fluctuations on the stress distribution change, the risk of seal failure is predicted based on the nonlinear characteristics of the stress distribution change. When the risk of seal failure is predicted, the corresponding acoustic emission signal is collected by an acoustic emission sensor array installed at the water supply pipe connection of the shower room. The acoustic emission signal is then filtered for activity based on the pressure-time history of the test pressure to verify the risk of seal failure. Based on the predicted results of the stress distribution change and the verification results of the filtered acoustic emission signals, a preliminary state assessment conclusion on the sealing performance of the shower room water supply pipeline is obtained. Based on the preliminary assessment of the sealing performance and the predetermined sealing performance qualification standard, a final judgment on the sealing performance of the shower room water supply pipe is generated.

[0007] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, wherein: Apply test pressure to the shower room water supply line at the testing station, including the following steps: Connect the shower room's water supply pipes to the pressurization pipes at the testing station using quick-connect couplings. After the water supply pipeline of the room is connected to the pressurization pipeline of the testing station, start the electric pressurization pump; After the electric booster pump starts, it raises the internal pressure of the shower room water supply pipe from normal pressure according to the preset loading curve. After the internal pressure of the shower room water supply pipe reaches the target test pressure, it enters the pressure holding stage. After the pressure holding phase ends, the corresponding pressure change procedure is executed according to the selected test mode. This causes the internal pressure of the shower room's water supply pipes to circulate periodically.

[0008] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, wherein: during the application of test pressure, the stress distribution change of the sealing interface is monitored in real time by a flexible pressure sensing array disposed at the connection of the shower room water supply pipe, including the following steps: Based on a flexible pressure sensor array, contact pressure data of the sealing interface at the connection of the water supply pipe in the shower room is collected. The contact pressure data of the sealing interface is transmitted to the central processing unit to generate the dynamic response of the sealing interface. Force distribution cloud map.

[0009] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, wherein: After eliminating the linear influence of fluctuations in test pressure on stress distribution, the risk of seal failure is predicted based on the nonlinear characteristics of stress distribution changes, including the following steps: The central processing unit, based on the recorded pressure-time history of the test pressure, from the sealing interface The linear stress change component caused by fluctuations in the test pressure itself is removed from the dynamic stress distribution cloud map sequence. Extract from the dynamic stress distribution cloud map sequence of the sealing interface after removing the linear stress variation component. Nonlinear stress variation characteristics characterizing the state of the sealing interface itself; By analyzing nonlinear stress variation characteristics through image feature recognition and sequence alignment, and extracting dense... The stress distribution uniformity coefficient at the sealing interface, the location of the maximum stress point at the sealing interface, and the stress relaxation rate at the sealing interface are monitored. The stress distribution uniformity coefficient, the location of the maximum stress point, and the stress relaxation rate of the sealing interface are determined. The stress distribution uniformity coefficient is compared with a preset safety threshold. When the sudden increase in the stress distribution uniformity coefficient exceeds the threshold, it is judged as abnormal. Based on the stress distribution uniformity coefficient of the sealed interface, the location of the maximum stress point, and the stress relaxation rate, The comparison results of preset safety thresholds generate a warning signal for the risk of seal failure.

[0010] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, wherein: when the risk of sealing failure is predicted, the corresponding acoustic emission signal is collected by an acoustic emission sensor array disposed at the connection of the shower room water supply pipe, including the following steps: The seal failure risk warning signal triggers the acoustic emission sensor array to enter a high-precision acquisition mode, capturing acoustic emission signals in the frequency range generated by potential leaks in the shower room water supply pipes. The captured acoustic emission signals are transmitted to the central processing unit.

[0011] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, the following steps are included: After screening the acoustic emission signal based on the pressure-time history of the test pressure to verify the risk of sealing failure: The central processing unit filters out acoustic emission events associated with the moment of pressure change from the received acoustic emission signals based on the recorded pressure-time history of the test pressure. Based on the selected acoustic emission events, the spatial coordinates of potential micro-leakage sources are obtained by using the time difference of the acoustic emission signals arriving at different acoustic emission sensors through the principle of geometric acoustic localization. From the acoustic emission signals contained in the selected acoustic emission events, extract the characteristic parameters of the acoustic emission signal, including amplitude, rise time, duration, signal strength, and frequency components. The acoustic emission signal characteristic parameters are compared with a pre-stored acoustic characteristic database of typical failure modes; Based on the comparison results between acoustic emission signal characteristic parameters and acoustic feature databases of typical failure modes, Generate verification conclusions for the early warning signal of seal failure risk.

[0012] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, the preliminary state assessment conclusion of the sealing performance of the shower room water supply pipe is obtained based on the predicted results of the stress distribution change and the verification results of the screened acoustic emission signals, including the following steps: The predicted results of the stress distribution change and the verification results of the filtered acoustic emission signals are input into the comprehensive judgment logic. The logical relationship between the predicted results of stress distribution changes analyzed by the comprehensive judgment logic and the verification results of the filtered acoustic emission signals is described. Based on the predicted results of stress distribution changes and the verification results of the screened acoustic emission signals... The analysis of the logical relationships between them generates a preliminary assessment of the sealing performance of the shower room's water supply pipes.

[0013] As a preferred embodiment of the shower room water supply pipe sealing performance testing method of the present invention, the final judgment conclusion on the sealing performance of the shower room water supply pipe is generated based on the preliminary state assessment conclusion of the sealing performance and the predetermined sealing performance qualification standard, including the following steps: The preliminary assessment results of the sealing performance of the shower room water supply pipes and the predetermined sealing performance qualification standards are input into the comprehensive judgment logic; The comprehensive judgment logic compares the preliminary status assessment conclusion of the sealing performance of the shower room water supply pipe with the predetermined sealing performance qualification standard. The preliminary assessment of the sealing performance of the shower room water supply pipes is consistent with the predetermined sealing performance. The comparison results with the standard are used to generate the final judgment on the sealing performance of the shower room water supply pipes.

[0014] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the shower room water supply pipe sealing performance testing method as described in the first aspect of the present invention.

[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the shower room water supply pipe sealing performance testing method as described in the first aspect of the present invention.

[0016] The beneficial effects of this invention are as follows: By applying test pressure to the water supply pipe of the shower room; during the pressurization process, the stress distribution change of the sealing interface is monitored in real time through a flexible pressure sensor array, and the linear influence caused by pressure fluctuations is eliminated, and the risk of sealing failure is predicted based on nonlinear characteristics; when a risk is predicted, acoustic emission signals are collected through an acoustic emission sensor array, and the signals are screened for activity based on the pressure-time history to verify the risk; based on the predicted results of stress distribution changes and the screened acoustic emission verification results, the sealing performance of the pipeline is comprehensively judged. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method for testing the sealing performance of the shower room water supply pipe in Example 1.

[0019] Figure 2 This is a schematic diagram of the sensor door opening test in Example 2.

[0020] 1. Shower door, 2. Floor, 3. Simulation board. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "example" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the invention. The appearance of an embodiment in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0024] Example 1, Reference Figure 1 This is the first embodiment of the present invention, which provides a method for testing the sealing performance of a shower room water supply pipe, including the following steps: S1. Apply test pressure to the water supply pipe of the shower room at the testing station.

[0025] S1.1 Connect the shower room water supply pipe to the pressurization pipe at the testing station using a quick-connect coupling. After the shower room water supply pipe is connected to the pressurization pipe at the testing station, start the electric pressurization pump; Furthermore, by connecting the shower room water supply pipes to the pressurization pipes at the testing station using quick-connect couplings, a standardized and repeatable physical interface environment is created. Traditional testing connection methods rely on manual application of Teflon tape, sealant, and thread alignment and tightening on-site. This process is not only inefficient but, more importantly, introduces installation variables that are difficult to quantify and vary from person to person. For example, differences in torque during manual tightening and uneven application of sealant can directly interfere with the subsequent evaluation of the sealing performance of the shower room water supply pipes themselves, leading to reduced reproducibility and comparability of test results. Using quick-connect couplings physically separates and standardizes the test preparation and testing operation. As a precision-manufactured industrial standard component, the quick-connect coupling's sealing reliability and connection consistency have been verified. By using quick-connect couplings, the operation only requires a simple plug-and-play action to establish a known, highly reliable, and leak-free temporary fluid channel between the shower room water supply pipe inlet and the pressure source outlet at the testing station.

[0026] Specifically, it eliminates the uncertainties caused by manual connections, ensuring that the pressurized medium can be introduced into the shower room water supply pipes under test without interference and accurately. This lays the foundation for applying a clean and known test pressure load. The rapid connection feature improves the cycle time and efficiency of the testing process. Starting the electric pressurization pump and applying precise and controllable pressure is the only way to achieve rigorous engineering significance, because at this time any pressure change can be more confidently attributed to the true state of the shower room water supply pipe system, rather than leakage or impedance fluctuations from external connections. This provides a physically clean starting point for the entire testing process, eliminating interference from connection links and achieving a high degree of standardization of testing conditions.

[0027] After the S1.2 electric booster pump starts, it raises the internal pressure of the shower room water supply pipeline from normal pressure according to the preset loading curve. After the internal pressure of the shower room water supply pipeline reaches the target test pressure, it enters the pressure holding stage.

[0028] Furthermore, after the electric booster pump starts, it raises the internal pressure of the shower room water supply pipeline from atmospheric pressure according to the preset loading curve. This reflects the concept of programmed and precise control of the load application process. Unlike simply and crudely raising the pressure directly to the target pressure, the preset loading curve (such as linear pressure increase or step pressure increase) treats the pressure as a dynamic process that changes over time rather than a static final value. The uniform or controlled pressure increase process allows the pressure field, stress field, and sealing components inside the shower room water supply pipeline system to have a smooth establishment and adaptation process. This helps to observe the early nonlinear response that may appear during the pressure rise phase.

[0029] Specifically, for example, stress abrupt changes at certain connection points at specific pressure inflection points may be masked during instantaneous high-pressure tests. The preset loading curve provides a strictly synchronized time reference and excitation source for the subsequent data acquisition of all sensors, enabling the stress distribution change data collected by the flexible pressure sensing array and the signals collected by the acoustic emission sensor array to be accurately correlated in the time domain with the core driving variable of pressure-time history. Analysis based on signal characteristics will lose a reliable reference. After the internal pressure of the shower room water supply pipe reaches the target test pressure according to the predetermined path, it enters the pressure holding stage, creating a stable static load condition to examine the long-term steady-state performance of the sealing system under constant high pressure. During this stage, stress attenuation or energy release phenomena caused by material creep, microstructure relaxation, or extremely small leaks will become prominent.

[0030] It should be noted that by programmatically controlling the loading and holding of stress, not only are real-world usage and testing conditions simulated, but also high-quality, time-aligned load and response datasets are generated for subsequent predictive analysis, making it possible to uncover potential failure risks from dynamic processes rather than static results.

[0031] S1.3 After the pressure holding phase ends, the corresponding pressure change procedure is executed according to the selected test mode to make the internal pressure of the shower room water supply pipe cycle periodically.

[0032] Furthermore, after the pressure holding phase ends, a corresponding pressure change program is executed according to the selected test mode, causing the internal pressure of the shower room's water supply pipes to undergo periodic cycling. This expands the single static pressure test into an accelerated fatigue verification that simulates real, complex service conditions. Traditional seal testing often only focuses on static pressure holding capacity, but it falls far short of reflecting the dynamic loads that the product frequently experiences in actual use, such as water hammer effects and pressure fluctuations caused by temperature changes.

[0033] Specifically, taking the pressure pulse fatigue test mode as an example, the electric pressure pump and pressure relief valve are controlled by a program to make the internal pressure of the shower room water supply pipe cycle periodically between the set upper and lower limits. This periodic cyclic load will actively stimulate and accelerate the evolution of potential defects, such as allowing small cracks to expand and further loosening threaded connections that are in a critical state. Compared with static testing, pressure cycling can expose weak links that perform normally under a single load but have insufficient fatigue resistance more quickly, thereby achieving a more profound assessment of the product's service life and reliability. By simulating actual dynamic working conditions to actively stimulate potential failures, the testing is elevated from static strength verification to the level of dynamic durability assessment.

[0034] S2. During the application of test pressure, the stress distribution changes at the sealing interface are monitored in real time by a flexible pressure sensor array installed at the connection of the shower room water supply pipe.

[0035] S2.1 Based on a flexible pressure sensor array, collect contact pressure data of the sealing interface at the connection of the shower room water supply pipe.

[0036] Furthermore, the macroscopic fluid pressure detection is transformed into a direct perception of the microscopic mechanical state of the sealing pair. Traditional detection methods only monitor the fluid pressure inside the pipeline, which is an indirect and global measurement that cannot reveal the true distribution of contact stress between the sealing ring and the pipe end face. Since sealing failure often begins with abnormal local contact stress, the flexible pressure sensing array, along with the high-resolution electronic skin covering the sealing interface, can directly and synchronously measure the contact positive pressure at every point on the sealing ring with dense sensing units.

[0037] Specifically, the measurement method abandons the indirectness and uncertainty of stress extrapolation through theoretical models or finite element simulations, thereby obtaining first-hand mechanical data with high spatial resolution that reflects the true compression state of the sealing interface. It breaks through the limitation of traditional detection methods that only focus on whether the internal pressure is maintained, and instead directly monitors the fundamental condition of whether the sealing interface is compressed and uniform. This provides an unprecedented data foundation for predicting sealing performance from a mechanical perspective, and obtains true, high-resolution original distribution data of contact stress at the sealing interface.

[0038] S2.2 Transmit the contact pressure data of the sealing interface to the central processing unit to generate a dynamic stress distribution cloud map of the sealing interface.

[0039] Furthermore, the massive discrete pressure data collected by the flexible pressure sensor array is reconstructed by the central processing unit into a two-dimensional stress distribution image, i.e., a static stress distribution cloud map, covering the entire sealing ring and encoded with color or contour lines, by using spatial interpolation algorithms and image rendering technology. As the test progresses, multiple frames of static cloud maps collected in chronological order are strung together to form a dynamic stress distribution cloud map sequence that shows the evolution of the stress field over time.

[0040] Specifically, the abstract numerical flow is transformed into a visualized stress change movie, allowing key features such as the location of stress concentration areas, the evolution of stress distribution uniformity, the migration trajectory of high-stress points, and the stress relaxation process over time to be intuitively observed and quantitatively analyzed by subsequent algorithms. For example, local hot spots appearing on the stress cloud map clearly indicate possible overload points, while the overall change in the cloud map color reflects the trend of stress relaxation. The collected contact pressure data is converted into a visualized dynamic stress distribution image sequence that can be used for time-series feature extraction, transforming massive amounts of data into image information that is easy for humans to observe and machines to process, laying an intuitive data foundation for intelligent feature recognition and failure prediction.

[0041] S3. After eliminating the linear influence of fluctuations in the test pressure itself on the stress distribution change, according to Nonlinear characteristics of stress distribution variation predict seal failure risk.

[0042] S3.1, The central processing unit, based on the recorded pressure-time history of the test pressure, from the sealing interface... The linear stress change component caused by fluctuations in the test pressure itself is removed from the dynamic stress distribution cloud map sequence. Furthermore, the total stress change at the sealing interface consists of two parts: one part is a predictable linear elastic response that is proportional to the change in internal test pressure, which is the physical behavior of the structure under normal stress; the other part is a nonlinear abnormal change caused by potential defects or deterioration of the sealing pair itself (such as creep, loosening, and wear).

[0043] Specifically, if these two effects are not separated, the significant stress changes caused by normal pressure fluctuations will seriously interfere with or even mask the weak nonlinear signals caused by failure risk. By using the known pressure-time history of the test pressure as the excitation source as a reference, linear regression analysis is performed on the stress value of each pixel or region in each frame of the dynamic stress distribution cloud map, thereby estimating and subtracting the linear component that is completely synchronized with the pressure change. This is equivalent to subtracting the background noise caused by the known external load from the observed total stress signal, thus obtaining a purified stress residual sequence that mainly reflects the changes in the health status of the sealing interface itself.

[0044] S3.2 From the sequence of dynamic stress distribution cloud maps of the sealing interface after removing linear stress variation components, Extract the nonlinear stress variation characteristics that characterize the state of the sealing interface itself.

[0045] Furthermore, based on the purified data, the active search for failure symptoms, after load decoupling, mainly retains nonlinear mechanical responses caused by processes such as seal ring creep, local yielding, abrupt changes in friction state, and formation of micro-leakage channels in the dynamic stress distribution cloud map sequence. Nonlinear change characteristics are extracted, such as the continuous attenuation of stress values ​​in specific areas, sudden distortion of stress distribution patterns, or abnormal propagation patterns of stress waves on interfaces. This captures abnormal patterns that deviate from normal linear elastic behavior, which are early manifestations of microscopic changes in the sealing pair material or contact state, appearing much earlier than macroscopic leakage or sudden pressure drops. Identifying abnormal mechanical behavior patterns that predict sealing performance degradation from the processed data allows us to focus on key signals directly related to potential failure mechanisms.

[0046] S3.3 Analyze the characteristics of nonlinear stress variation through image feature recognition and sequence comparison. Extract the stress distribution uniformity coefficient of the sealing interface, track the location of the maximum stress point of the sealing interface, and monitor the stress relaxation rate of the sealing interface.

[0047] Furthermore, by performing image processing on the purified dynamic stress cloud map sequence, the statistical dispersion of the stress distribution of the entire sealing ring, i.e., the stress distribution uniformity coefficient, can be quantified. A deterioration in the coefficient indicates off-center loading or local contact failure. By identifying and recording the pixel coordinates of the stress highest point in the cloud map frame by frame, the trajectory of the maximum stress point location changing over time can be depicted. Abnormal migration of this point may indicate that the sealing ring has twisted or slipped. By continuously monitoring the stress values ​​of specific key points during the pressure holding stage, the stress relaxation rate can be obtained, reflecting the creep characteristics of the material or the decay rate of the connection fastening force.

[0048] Specifically, the method of extracting quantitative indicators from image sequences compresses complex, high-dimensional stress field spatiotemporal evolution information into a few key performance parameters with clear physical meaning and easy-to-set thresholds and trend analysis. It is about quantitatively characterizing the nonlinear stress change features and generating a set of measurable, traceable, and automatically identifiable core parameters for the health status of the sealed interface.

[0049] S3.4, The stress distribution uniformity coefficient, the location of the maximum stress point, and the stress value relaxation of the sealing interface. The rate is compared with the preset safety threshold, and when the sudden increase in the stress distribution uniformity coefficient exceeds the threshold, it is judged as abnormal.

[0050] Furthermore, the preset safety thresholds are determined in advance based on long-term test data of a large number of qualified samples or through a combination of theoretical analysis and experimental verification. For example, the fluctuation range of the stress distribution uniformity coefficient in the steady state stage, the boundary of the allowable drift area of ​​the maximum stress point within the sealing ring, and the upper limit of the stress relaxation rate. The parameters extracted in real time are compared with the corresponding safety thresholds one by one to provide a clear boundary between normal and abnormal for each health status parameter.

[0051] S3.5, Stress distribution uniformity coefficient based on the sealing interface, location of the maximum stress point, and stress value relaxation. The comparison between the relaxation rate and the preset safety threshold generates a warning signal for the risk of seal failure.

[0052] Furthermore, the central processing unit makes a comprehensive judgment based on the comparison results of each parameter and according to predefined logic (for example, an alarm is triggered when any parameter exceeds the limit, or an alarm is triggered when multiple parameters exceed the limit). Once the judgment condition is met, a sealing failure risk warning signal is immediately generated. This signal not only indicates that a potential risk has been predicted, but also serves as a clear instruction to trigger subsequent independent acoustic emission verification processes based on different physical principles, thereby opening a closed-loop detection chain of prediction and verification, and automatically generating risk warnings based on threshold judgments of quantified parameters.

[0053] S4. When the risk of seal failure is predicted, the corresponding acoustic emission signal is collected by an array of acoustic emission sensors installed at the connection of the shower room water supply pipe.

[0054] S4.1 The sealing failure risk warning signal triggers the acoustic emission sensor array to enter the high-precision acquisition mode, capturing the acoustic emission signal in the frequency range generated by potential leakage in the shower room water supply pipe.

[0055] Furthermore, based on an event-triggered, resource-on-demand cascaded detection chain, when a seal failure risk warning signal is generated by the analysis results of the flexible pressure sensor array, this signal is not a simple alarm, but a bus command with clear control functions. This command directly controls the acoustic emission sensor array to switch from a low-power standby state or a regular monitoring state to a high-precision acquisition mode with high sampling rate, high gain, and high bandwidth. This ensures that the high-power, high-data-throughput acoustic emission detection, a precise verification method, is only activated and fully utilized when there is a clearly suspicious target.

[0056] Specifically, for example, in the early stages of a lengthy pressure holding test, if the stress distribution is normal, the acoustic emission sensor array can be in a low-power listening state, recording only baseline noise. Once the stress relaxation rate at a connection point exceeds a threshold and triggers an alarm, the array is immediately activated and focuses on listening to the area surrounding that specific risk point, concentrating on capturing specific frequency band acoustic emission signals related to leakage. This achieves optimized allocation of detection resources and on-demand activation, constructing an efficient, energy-saving, and highly focused sensor scheduling strategy. This avoids data redundancy, processing burden, and energy waste caused by continuous high-intensity acoustic emission monitoring, while ensuring that the most detailed and accurate verification data can be obtained at critical moments.

[0057] S4.2 Transmit the captured acoustic emission signal to the central processing unit.

[0058] Furthermore, the raw analog voltage signal captured by the acoustic emission sensor array is converted from analog to digital, pre-amplified, and filtered by a field-programmable gate array or a dedicated acquisition circuit, forming a digital acoustic emission signal waveform data stream. This stream is then transmitted in real time and synchronously to the central processing unit via wired or wireless communication protocols. The real-time and synchronous transmission is crucial because subsequent acoustic emission signal activity screening, time difference localization, and feature extraction all strictly depend on the precise time correlation between signals and require time-domain alignment with the previously recorded pressure-time history of the test pressure.

[0059] Specifically, the distributed acoustic emission sensor data is aggregated to the central processing unit for centralized analysis, which makes it possible to achieve deep fusion and joint analysis of acoustic emission signals, stress distribution change data, and historical pressure load data under a unified time reference. This is an indispensable data aggregation link for completing the prediction-verification closed loop.

[0060] S5. After screening the acoustic emission signals based on the pressure-time history of the test pressure, the risk of seal failure is verified.

[0061] S5.1 The central processing unit filters out acoustic emission events associated with the time of pressure change from the received acoustic emission signals based on the recorded pressure-time history of the test pressure.

[0062] Furthermore, the acoustic emission signal stream acquired by the opportunity time-domain correlation screening is mixed with a large number of irrelevant signals related to environmental vibration, structural friction, and electronic noise. Instead of using traditional simple amplitude threshold filtering, it utilizes the known physical excitation timing sequence of the test pressure pressure-time history, which is directly related to potential leaks, as a time stamp or synchronization trigger. The central processing unit analyzes the activity of the acoustic emission signal, especially the occurrence time of burst signal clusters, and checks whether these time points are highly correlated or synchronized in the time domain with specific characteristic moments in the pressure history (such as the inflection point of pressure rise, the moment when the pressure reaches its peak, and the moment when abnormal stress relaxation occurs during the pressure holding phase).

[0063] Specifically, only acoustic emission signal clusters that are closely related to these key pressure events in time are identified as valid acoustic emission events that may be excited by load changes, while signals that appear randomly at other times are judged as background noise and filtered out. For example, the repeated appearance of acoustic emission signal clusters at the peak loading moment of the pressure pulse cycle strongly suggests the existence of material damage or leakage related to the load cycle. By using the temporal correlation between load and acoustic activity, the acoustic emission signals are given a clear physical meaning, thereby realizing the intelligent extraction of valid damage signals. Valid acoustic emission events that are causally related to pressure load changes are identified from the continuous acoustic signal stream, which greatly suppresses the interference of irrelevant noise and improves the data purity and result reliability of subsequent localization and pattern recognition analysis.

[0064] S5.2 Based on the selected acoustic emission events, the spatial coordinates of potential micro-leakage sources are obtained by utilizing the time difference between the arrival of the acoustic emission signals at different acoustic emission sensors and applying the principle of geometric acoustic localization.

[0065] Furthermore, acoustic detection is moved from qualitative judgment to precise quantification. An array of acoustic emission sensors is constructed into an acoustic monitoring network. Utilizing the time-of-arrival (TOA) principle in physics, for a selected valid acoustic emission event, the stress wave it generates propagates in the pipe wall or medium. Due to the different propagation path lengths, the waves arrive sequentially at multiple acoustic emission sensors arranged in a specific geometric shape in space with a tiny time difference. The central processing unit accurately measures the time difference between the arrival of the same event signal at each pair of sensors in the array. Combined with the known propagation speed of sound waves in a specific medium (such as water pipe wall material, water, or air), by solving a set of hyperbolic equations, the source point that generated the acoustic emission event, i.e., the precise spatial coordinates of potential micro-leakage sources or material damage points, can be obtained in two-dimensional or three-dimensional space.

[0066] Specifically, by converting high-precision time measurement into spatial positioning capabilities, the detection can not only report the presence of abnormal acoustic activity, but also pinpoint the precise location of the abnormality, such as which threaded connection and which turn experienced a micro-leak. This enables spatial localization of defects or leak points, elevating the detection results from a macroscopic, holistic assessment to a microscopic, localized diagnosis, providing crucial location information for failure analysis and repair.

[0067] S5.3 Extract the amplitude, rise time, duration, signal strength, and frequency component characteristic parameters of the acoustic emission signals from the acoustic emission signals contained in the selected acoustic emission events.

[0068] Furthermore, after screening and localization, each acoustic emission event is associated with a set of original waveform data. The waveforms are then subjected to multi-dimensional feature quantization, transforming them into feature vectors suitable for machine learning and pattern recognition. Amplitude reflects the intensity of energy released by the event; rise time characterizes the suddenness of the event; duration delineates the active length of the event; signal strength is a comprehensive measure of energy; and frequency components are closely related to the microscopic mechanisms of fracture. Different failure mechanisms (such as brittle fracture, ductile tearing, and friction) will produce acoustic emission spectra with different dominant frequencies.

[0069] S5.4 Compare the acoustic emission signal characteristic parameters with the pre-stored acoustic characteristic database of typical failure modes.

[0070] Furthermore, the pre-stored acoustic feature database of typical failure modes is established through a large number of accelerated life tests or simulation tests under controlled laboratory conditions. For example, aging and wear of sealing rings, progressive loosening of threaded connections, and fatigue crack initiation and propagation of pipe materials are simulated on the test bench, and acoustic emission signals of these known failure modes are collected simultaneously. Then, typical values, distribution ranges and correlations of characteristic parameters such as amplitude, rise time and frequency components are extracted and statistically analyzed, thereby constructing a knowledge base of the mapping relationship between failure modes and acoustic features. In actual testing, the characteristic parameters of acoustic emission signals acquired in real time are compared with this database for similarity calculation or mode classification.

[0071] Specifically, known acoustic fingerprint databases are used to identify and classify unknown faults. For example, wear of the sealing ring may produce continuous, low-to-medium amplitude acoustic emission characteristics with a narrow frequency distribution, while loose threads may exhibit sudden, high-amplitude acoustic emission characteristics with a specific resonant frequency. This enables automatic diagnosis of fault types, advancing the detection depth from simply discovering abnormalities to identifying what kind of abnormality, and providing a direct basis for root cause analysis of quality.

[0072] S5.5 Based on the comparison results between the acoustic emission signal characteristic parameters and the acoustic feature database of typical failure modes, a verification conclusion for the sealing failure risk warning signal is generated.

[0073] Furthermore, the central processing unit generates structured verification conclusions based on the degree of matching and confidence level between the feature parameters and the database. For example, if the acoustic emission features highly match the thread loosening mode, a seal failure risk warning signal is generated and acoustic emission verification is obtained, providing a definitive conclusion that the suspected failure mode is thread loosening. If the features are ambiguous and cannot be clearly matched with any typical mode, an uncertain conclusion is generated that the acoustic emission evidence is insufficient and the warning signal cannot be verified. If no valid acoustic emission event is captured, a negative conclusion is generated that no relevant acoustic emission activity was detected and the warning signal fails verification, providing an authoritative verification opinion based on independent acoustic evidence for the previous risk prediction based on stress changes.

[0074] S6. Validation results based on stress distribution variation predictions and filtered acoustic emission signals. A preliminary assessment of the sealing performance of the shower room's water supply pipes was obtained.

[0075] S6.1 The predicted results of stress distribution changes and the verification results of the filtered acoustic emission signals are input into the comprehensive judgment logic.

[0076] Furthermore, the predicted results of stress distribution changes include risk warning information composed of stress anomaly parameters, location, and trends. This is a highly sensitive but potentially interfered, indirect mechanical state evidence. The verification results of the filtered acoustic emission signals include failure evidence composed of acoustic emission event location, characteristic parameters, and mode matching. This is a highly specific but potentially environmentally affected, direct acoustic physical evidence.

[0077] Specifically, the design of the comprehensive judgment logic is not a simple juxtaposition of information, but rather a virtual arbitrator with the capabilities of information standardization, spatiotemporal alignment, and confidence management. It is responsible for receiving two types of evidence that differ in physical principles, data formats, and spatiotemporal attributes, establishing a unified framework that can accommodate and parse heterogeneous information. This paves the way for subsequent deep correlation analysis, and aggregates prediction and verification evidence from different sensing modalities and different physical principles into a unified decision logic entry point, creating the necessary conditions for achieving intelligent decision-making based on multi-source information complementarity and cross-validation.

[0078] S6.2. The logical relationship between the predicted results of stress distribution change and the verification results of the screened acoustic emission signals is analyzed by comprehensive judgment logic.

[0079] Furthermore, the comprehensive judgment logic analyzes the logical relationship between the two from multiple dimensions, including but not limited to: spatial consistency (whether the predicted risk point location and the coordinates of the acoustic emission location overlap or are adjacent in space), temporal correlation (whether the occurrence of stress anomalies is within the time window of the acoustic emission event cluster or has an interpretable chronological order), complementarity of evidence strength (e.g., slight stress parameter anomalies but conclusive acoustic emission evidence, or severe stress parameter anomalies but weak acoustic emission evidence), and matching of failure modes (whether the failure mechanism implied by stress change characteristics, such as stress relaxation, is physically consistent with the mode identified by acoustic emission characteristics, such as seal wear).

[0080] Specifically, for example, if stress distribution changes predict a risk of stress relaxation at a certain threaded connection, and acoustic emission verification detects an acoustic emission event at the same location that highly matches the thread loosening pattern, then the two exhibit a strong synergistic logical relationship in terms of space, mechanism, and strength of evidence. Through multi-dimensional correlation analysis, the inherent connections and contradictions between the evidence can be explored, thereby assessing the credibility of the prediction results and the support strength of the verification conclusions. In-depth analysis of the inherent connection between prediction and verification evidence can identify false correlations, confirm real risks, and provide quantitative support or conflict indicators for the final assessment.

[0081] S6.3 Based on the analysis of the logical relationship between the predicted results of stress distribution changes and the verification results of the screened acoustic emission signals, a preliminary state assessment conclusion of the sealing performance of the shower room water supply pipeline is generated.

[0082] Furthermore, a set of semantic rules for state assessment based on evidence fusion logic is defined. The comprehensive judgment logic outputs a structured preliminary state assessment conclusion based on the strength and nature of logical relationships, rather than just a true or false judgment. Possible assessment conclusions include: when the predicted and verified evidence are highly consistent in space, time, and mechanism and the evidence is sufficient, a high-risk state and a conclusion of conclusive evidence are generated; when there is a clear stress anomaly but acoustic emission verification does not provide sufficient support, or when there is acoustic emission activity but stress monitoring does not show a clear anomaly, a medium-risk or suspicious state and a conclusion of questionable evidence are generated; when the predicted stress distribution change results are not abnormal and there is no acoustic emission verification activity, a low-risk or normal state conclusion is generated.

[0083] S7. Based on the preliminary condition assessment conclusions of the sealing performance and the predetermined sealing performance qualification standards, generate... The final assessment of the sealing performance of the shower room's water supply pipes.

[0084] S7.1 The preliminary status assessment conclusion of the sealing performance of the shower room water supply pipe and the predetermined sealing performance qualification standard are input into the comprehensive judgment logic.

[0085] Furthermore, the predetermined sealing performance qualification standard is not a single threshold, but a structured rule base or knowledge graph that defines the final quality level corresponding to different preliminary state assessment conclusions. For example, the qualification standard may stipulate that: a high-risk state with conclusive evidence corresponds to non-compliance; a medium-risk or questionable state with doubtful evidence may correspond to observation or conditional acceptance and trigger additional testing; while a low-risk or normal state directly corresponds to qualification. The preliminary state assessment conclusion is input along with such a standard.

[0086] Specifically, the results of multi-sensor information fusion (preliminary status assessment conclusions) were standardized and aligned with clear, pre-defined engineering acceptance criteria (qualification standards). This made subsequent operations of the comprehensive judgment logic more evidence-based, avoiding the subjectivity and arbitrariness of ad hoc decisions, providing clear and pre-defined adjudication basis for the final qualification judgment, achieving standardization of the testing process and objectification of the conclusions, and ensuring the consistency of judgment results between different products and different batches.

[0087] S7.2 The comprehensive judgment logic compares the preliminary status assessment conclusion of the sealing performance of the shower room water supply pipe with the predetermined sealing performance qualification standard.

[0088] Furthermore, based on rule-based automated mapping, the comprehensive judgment logic does not perform complex calculations, but rather executes an efficient table lookup or rule matching operation. It accurately compares the received semantic preliminary state assessment conclusions, such as high-risk state, conclusive evidence, medium-risk or suspicious state, and doubtful evidence, with the state descriptions of each level defined in the predetermined sealing performance qualification standard.

[0089] Specifically, for example, the logic will determine whether the high-risk state of the input is conclusive and whether the evidence fully matches the state description conditions corresponding to the unqualified level defined in the qualified standard. The comparison process strictly follows the preset rules, does not introduce additional subjective judgments, and makes a clear and unambiguous logical connection between the state assessment obtained by artificial intelligence or complex algorithms and the qualified standard preset by human experts. According to the preset rules, a clear corresponding quality adjudication path is found for the current preliminary state. The decision-making process is transparent, traceable, and entirely based on objective standards that have been agreed upon in advance.

[0090] S7.3 Based on the comparison between the preliminary status assessment conclusion of the sealing performance of the shower room water supply pipeline and the predetermined sealing performance qualification standard, the final judgment conclusion of the sealing performance of the shower room water supply pipeline is generated.

[0091] Furthermore, the comprehensive judgment logic automatically generates the final judgment conclusion, such as qualified, unqualified, or pending re-inspection. For example, when the preliminary status assessment conclusion is mapped to the unqualified level by the rules, the final judgment conclusion of unqualified is generated; if it is mapped to pending observation, it may generate conclusions such as suggesting a shortened re-inspection cycle or conditional acceptance, and marking risk points. This completes a fully automated closed loop from multi-source data fusion analysis to final quality adjudication, so that the result of the entire intelligent inspection process is no longer complex data or charts that require manual interpretation, but a clear instruction that can be directly used for production flow, quality release, or maintenance decisions. It outputs a clear final quality judgment based on multiple evidence and preset standards, transforming the results of advanced predictive inspection technology into decision outputs that seamlessly integrate with the traditional quality management system, greatly enhancing the practical value and action guidance of the inspection results.

[0092] This embodiment also provides a computer device applicable to the shower room water supply pipe sealing performance testing method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the shower room water supply pipe sealing performance testing method proposed in the above embodiment.

[0093] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0094] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for testing the sealing performance of shower room water supply pipes as proposed in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0095] In summary, this invention applies test pressure to the water supply pipes of a shower room; during the pressurization process, a flexible pressure sensor array monitors the stress distribution changes at the sealing interface in real time and eliminates the linear effects caused by pressure fluctuations, predicting the risk of seal failure based on nonlinear characteristics; when a risk is predicted, an acoustic emission sensor array collects acoustic emission signals, and the signals are screened for activity based on the pressure-time history to verify the risk; based on the predicted results of stress distribution changes and the screened acoustic emission verification results, the sealing performance of the pipe is comprehensively judged.

[0096] Example 2, Reference Figure 2 This is a second embodiment of the present invention, which provides a method for testing the sealing performance of a shower room water supply pipe, including the following steps: Test preparation and platform configuration: Install the shower enclosure door 1 to be tested vertically onto the fixed back wall of the universal testing platform according to its instruction manual, ensuring that its bottom is firmly in contact with the platform floor 2. Adjust the movable side wall of the platform according to the actual dimensions of the shower enclosure product (e.g., assuming it is diamond-shaped with dimensions of 1000mm × 1000mm) to form a suitable testing space with the fixed frame of the shower enclosure, ensuring that there are no strong electromagnetic interference sources nearby. Prepare a standard simulation board 3 with dimensions of 297mm × 297mm and a surface adhesive of 70g / m². 2 Wood pulp copy paper.

[0097] Establishment of testing standards: To measure the width d of the shower room door 1, two test tracks are determined on horizontal planes at vertical heights of 800mm and 200mm from the ground. The spatial position of the tracks satisfies the following conditions: the center line of the track is parallel to the door plane, and the horizontal distance between the track and the center line of the door width is d / 4 (i.e., 1 / 4 of the door width). On the frame of a general testing platform, a precision guiding device can be set up or a laser positioning instrument can be used to calibrate these two standard test tracks.

[0098] The testing process is as follows: With the shower door 1 closed, install the simulation board 3 on a moving device that can be driven by a servo motor and has a position feedback accuracy of more than 1mm, and ensure that the center point of the simulation board is located on the test track and the board surface is facing the sensing area of ​​the shower door.

[0099] High-position test: The control device moves the simulation board along a track 800mm above the ground at a slow speed (≤50mm / s) from far (outside the sensing area) to near (shower door direction). The movement stops immediately when the shower door opens automatically. A high-precision optical scale built into the device records and locks in real-time the vertical distance between the center point of the simulation board and the shower door plane. .

[0100] Low-position test: Repeat the above process and conduct the test on a track 200mm above the ground, recording the vertical distance of the simulated panel when the shower door is open.

[0101] Data processing and judgment: Central processing unit receives distance data and Check the nominal sensor distance value stated in the product manual of this shower enclosure. Calculate the sensing distance deviation for the high and low positions separately: Automatic determination is performed according to standard QB / T 2584-2007: If and If the deviation is not greater than 50mm, the automatic sensor opening performance is deemed qualified; if any deviation is greater than 50mm, it is deemed unqualified.

[0102] Test report generation: The platform automatically generates a structured inspection report, which includes: inspection standards, door width d, test track position diagram, and measured distance. and Nominal distance S, calculated deviation and The report may include a simulation diagram of the position of the panel at the moment the door opens, along with the final judgment.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for testing the sealing performance of a shower room water supply pipe, characterized in that: This includes applying test pressure to the water supply pipes of the shower room at the testing station; During the application of the test pressure, the stress distribution changes at the sealing interface are monitored in real time by a flexible pressure sensor array installed at the connection of the shower room water supply pipe. After eliminating the linear influence of the test pressure fluctuations on the stress distribution change, the risk of seal failure is predicted based on the nonlinear characteristics of the stress distribution change. When the risk of seal failure is predicted, the corresponding acoustic emission signal is collected by an acoustic emission sensor array installed at the water supply pipe connection of the shower room. The acoustic emission signal is then filtered for activity based on the pressure-time history of the test pressure to verify the risk of seal failure. Based on the predicted results of the stress distribution change and the verification results of the filtered acoustic emission signals, a preliminary state assessment conclusion on the sealing performance of the shower room water supply pipeline is obtained. Based on the preliminary assessment of the sealing performance and the predetermined sealing performance qualification standard, a final judgment on the sealing performance of the shower room water supply pipe is generated.

2. The method for testing the sealing performance of shower room water supply pipes as described in claim 1, characterized in that: Apply test pressure to the shower room water supply line at the testing station, including the following steps: Connect the shower room's water supply pipes to the pressurization pipes at the testing station using quick-connect couplings. After the water supply pipeline of the room is connected to the pressurization pipeline of the testing station, start the electric pressurization pump; After the electric booster pump starts, it raises the internal pressure of the shower room water supply pipe from normal pressure according to the preset loading curve. After the internal pressure of the shower room water supply pipe reaches the target test pressure, it enters the pressure holding stage. After the pressure holding phase ends, the corresponding pressure change procedure is executed according to the selected test mode to make the internal pressure of the shower room water supply pipes cycle periodically.

3. The method for testing the sealing performance of shower room water supply pipes as described in claim 2, characterized in that: During the application of the test pressure, a flexible pressure sensor array installed at the water supply pipe connection of the shower room is used to monitor the stress distribution changes at the sealing interface in real time, including the following steps: Based on a flexible pressure sensor array, contact pressure data of the sealing interface at the connection of the water supply pipe in the shower room is collected. The contact pressure data of the sealing interface is transmitted to the central processing unit to generate a dynamic stress distribution cloud map of the sealing interface.

4. The method for testing the sealing performance of shower room water supply pipes as described in claim 3, characterized in that: In the pick After removing the linear impact of fluctuations in test pressure on stress distribution, the risk of seal failure is predicted based on the nonlinear characteristics of stress distribution changes, including the following steps: The central processing unit, based on the recorded pressure-time history of the test pressure, from the sealing interface The linear stress change component caused by fluctuations in the test pressure itself is removed from the dynamic stress distribution cloud map sequence. Extract from the dynamic stress distribution cloud map sequence of the sealing interface after removing the linear stress variation component. Nonlinear stress variation characteristics characterizing the state of the sealing interface itself; By analyzing nonlinear stress variation characteristics through image feature recognition and sequence alignment, and extracting dense... The stress distribution uniformity coefficient at the sealing interface, the location of the maximum stress point at the sealing interface, and the stress relaxation rate at the sealing interface are monitored. The stress distribution uniformity coefficient, the location of the maximum stress point, and the stress value of the sealing interface are relaxed. The rate is compared with the preset safety threshold, and when the sudden increase in the stress distribution uniformity coefficient exceeds the threshold, it is judged as abnormal. Based on the stress distribution uniformity coefficient of the sealed interface, the location of the maximum stress point, and the stress relaxation rate, The comparison results of preset safety thresholds generate a warning signal for the risk of seal failure.

5. The method for testing the sealing performance of shower room water supply pipes as described in claim 4, characterized in that: When the risk of seal failure is predicted, the corresponding acoustic emission signal is collected by an acoustic emission sensor array installed at the water supply pipe connection of the shower room, including the following steps: The seal failure risk warning signal triggers the acoustic emission sensor array to enter a high-precision acquisition mode, capturing acoustic emission signals in the frequency range generated by potential leaks in the shower room water supply pipes. The captured acoustic emission signals are transmitted to the central processing unit.

6. The method for testing the sealing performance of shower room water supply pipes as described in claim 5, characterized in that: After screening the acoustic emission signals for activity based on the pressure-time history of the test pressure, the risk of seal failure is verified, including the following steps: The central processing unit filters out acoustic emission events associated with the moment of pressure change from the received acoustic emission signals based on the recorded pressure-time history of the test pressure. Based on the selected acoustic emission events, the spatial coordinates of potential micro-leakage sources are obtained by using the time difference of the acoustic emission signals arriving at different acoustic emission sensors through the principle of geometric acoustic localization. From the acoustic emission signals contained in the selected acoustic emission events, extract the characteristic parameters of the acoustic emission signal, including amplitude, rise time, duration, signal strength, and frequency components. The acoustic emission signal characteristic parameters are compared with a pre-stored acoustic characteristic database of typical failure modes; Based on the comparison results between the acoustic emission signal characteristic parameters and the acoustic feature database of typical failure modes, a verification conclusion for the sealing failure risk warning signal is generated.

7. The method for testing the sealing performance of shower room water supply pipes as described in claim 6, characterized in that: Based on the predicted results of the stress distribution change and the verification results of the screened acoustic emission signals, a preliminary assessment conclusion on the sealing performance of the shower room water supply pipe is obtained, including the following steps: The predicted results of the stress distribution change and the verification results of the filtered acoustic emission signals are input into the comprehensive judgment logic. The logical relationship between the predicted results of stress distribution changes analyzed by the comprehensive judgment logic and the verification results of the filtered acoustic emission signals is described. Based on the analysis of the logical relationship between the predicted results of stress distribution changes and the verification results of the screened acoustic emission signals, a preliminary state assessment conclusion on the sealing performance of the shower room water supply pipeline is generated.

8. The method for testing the sealing performance of the shower room water supply pipe as described in claim 7, characterized in that, Based on the preliminary assessment of the sealing performance and the predetermined sealing performance qualification standard, a final judgment on the sealing performance of the shower room water supply pipe is generated, including the following steps: The preliminary assessment results of the sealing performance of the shower room water supply pipes and the predetermined sealing performance qualification standards are input into the comprehensive judgment logic; The comprehensive judgment logic compares the preliminary status assessment conclusion of the sealing performance of the shower room water supply pipe with the predetermined sealing performance qualification standard. Based on the comparison between the preliminary assessment of the sealing performance of the shower room's water supply pipes and the predetermined sealing performance qualification standards, a final judgment on the sealing performance of the shower room's water supply pipes is generated.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the shower room water supply pipe sealing performance testing method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the shower room water supply pipe sealing performance testing method according to any one of claims 1 to 8.

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