Building floor water leakage detection method, system and device and storage medium

Abstract

The embodiment of the invention provides a building floor water leakage detection method, system and equipment and a storage medium, and relates to the technical field of building water leakage detection, the method is applied to a detection device comprising a plurality of humidity sensors, and the method comprises the following steps: during a period from construction completion to a target time point, obtaining first humidity data of concrete and determining a minimum humidity value of the first humidity data; when the target time point is reached, second humidity data are obtained, water leakage judgment is carried out in combination with the minimum humidity value, and a detection result representing whether the current position leaks water or not is generated; and the result is sent to a result processing device to determine the position where water leakage occurs first. Therefore, the lowest humidity value is obtained through the first humidity data, and the water leakage detection result is obtained in combination with the second humidity data, so that the water leakage position and the water leakage time near the detection device can be obtained at the first time, damage to the building wall surface due to the fact that water leakage is not found for a long time is reduced, and the water leakage detection efficiency is improved. Therefore, the position where the floor begins to leak water can be timely and accurately obtained.

Description

Technical Field

[0001] This invention relates to the field of building leakage detection technology, and more specifically, to a method, system, equipment, and storage medium for detecting building floor leakage. Background Technology

[0002] With the acceleration of urbanization and the continuous improvement of people's requirements for living quality, the reliability of building interior waterproofing systems has received increasing attention. Especially in wet environments such as bathrooms, kitchens, and balconies, once leakage occurs, it can not only lead to damage to the decoration such as moldy walls and deformed floors, but may also corrode the steel bars of the building structure, causing safety hazards and even causing neighborhood disputes.

[0003] Currently, building waterproofing projects generally use coating-type waterproofing materials to form a dense isolation layer on the concrete substrate to prevent water penetration. However, indoor building waterproofing technology has not yet achieved a lifespan equal to that of the building itself. Most companies in the industry can only offer a maximum of about ten years of leak-proof warranty for their waterproofing products, and this after-sales service does not guarantee that the waterproofing coating will not be damaged or leak. According to market research data, the longer the waterproofing coating is used, the greater the chance of leakage.

[0004] However, by the time users discover leaks in most building waterproofing coatings, the leaks have already spread over a large area or for an extended period, causing significant damage to the walls and resulting in considerable inconvenience, property loss, and even structural damage to the building, making it difficult to pinpoint the exact location of the leak in a timely and accurate manner. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method, system, device and storage medium for detecting water leakage in building floors. The method obtains the minimum humidity value by acquiring the first humidity data through the humidity sensor of the detection device, and obtains the water leakage detection result by combining the second humidity data. This allows for the immediate acquisition of the location and time of water leakage near the detection device, reducing the damage to the building walls caused by water leakage going undetected for a long time, and thus enabling timely and accurate identification of the location where water leakage begins on the floor.

[0006] To achieve the above objectives, in a first aspect, embodiments of the present invention provide a method for detecting water leakage in building floors, applied to a detection device in a water leakage detection system. The detection device comprises multiple devices, each including a humidity sensor. The method includes: during the period from the completion of building floor construction to a target time point, acquiring first humidity data of the concrete detected by the humidity sensor, and obtaining the lowest humidity value in the first humidity data; after the target time point is reached from the current time point, acquiring second humidity data of the concrete detected by the humidity sensor; obtaining a water leakage detection result based on the lowest humidity value and the second humidity data; the water leakage detection result characterizing whether there is a water leakage at the location of the detection device; and sending the water leakage detection result to a result processing device, so that the result processing device can determine the location of the detection device that first detected the leakage from the water leakage detection results fed back by multiple detection devices.

[0007] In this embodiment, a humidity sensor detects humidity, obtaining first humidity data from humid to dry and second humidity data from dry to humid, simulating the humidity change over time from the completion of building construction to occupancy. By comparing the lowest humidity value with the second humidity data, the detection device whose second humidity value is higher than the lowest humidity value is identified first. The leak point is then located near this detection device, allowing for easy location of the leak and triggering an alarm based on the first detected device and the timing of the leak. Thus, by combining the first humidity data obtained from the humidity sensor with the second humidity data to obtain the leak detection result, the location and timing of the leak near the detection device can be determined immediately, reducing damage to the building walls caused by prolonged undetected leaks and enabling timely and accurate identification of the location where the floor leak began.

[0008] In some embodiments, obtaining the lowest humidity value in the first humidity data includes: generating a first humidity time curve based on all first humidity data acquired during the process from the completion of building floor construction to the target time point; if any humidity value in the first humidity time curve reaches a preset humidity value, calculating the slope change rate corresponding to two adjacent time nodes after the preset humidity value in the first humidity time curve; if the slope change rate corresponding to the two adjacent time nodes is lower than the preset change rate, determining that the average humidity value corresponding to multiple time points after the two adjacent time nodes is the lowest humidity value.

[0009] This setup, which uses trend stability rather than absolute values ​​as the criterion, can adapt to the differences in drying cycles under different construction conditions, fully considers the evolution of the physical properties of the building materials themselves, and ensures that the established benchmark truly reflects the actual situation on site, providing a solid data foundation for subsequent leak identification.

[0010] In some embodiments, obtaining the leakage detection result based on the minimum humidity value and the second humidity data includes: obtaining a first slope set corresponding to the first humidity time curve; determining a preset humidity time curve corresponding to the first humidity time curve from multiple preset humidity time curves based on the first slope set; obtaining the actual humidity value of the concrete based on the second humidity data obtained at the current time point and the preset humidity time curve corresponding to the first humidity time curve; generating a second humidity time curve based on all the second humidity data obtained between the target time point and the current time point, and obtaining a second slope set corresponding to the second humidity time curve; obtaining a target humidity time curve from the first humidity time curve based on the humidity value set corresponding to the second slope set, and obtaining a target slope set corresponding to the target humidity time curve; and determining the leakage detection result based on the target slope set, the second slope set, the preset slope set corresponding to the preset humidity time curve, the minimum humidity value, and the actual humidity value.

[0011] This setting allows for multi-dimensional verification and judgment using the target slope set, the second slope set, the preset slope set, the minimum humidity value, and the actual humidity value. Only when multiple indicators simultaneously meet the preset logical relationship will a positive leakage judgment result be output, thereby enhancing the accuracy of leakage judgment.

[0012] In some embodiments, there are multiple humidity sensors, each of which has a corresponding minimum humidity value, a target humidity time curve, and a second humidity time curve. Determining the leakage detection result based on the target slope set, the second slope set, the minimum humidity value, and the actual humidity value includes: if at least two of the multiple humidity sensors meet a preset leakage condition, then the leakage detection result is determined to be a leakage at the location of the detection device. The preset leakage condition is that the actual humidity value corresponding to the humidity sensor is greater than the corresponding minimum humidity value, the number of first slope pairs matching in the target slope set and the second slope set corresponding to the humidity sensor is greater than a first preset threshold, and the error of two slopes in the second slope pairs of the second slope set corresponding to the humidity sensor and the preset slope set is less than or equal to the threshold value. The difference is within the first threshold range; if one of the multiple humidity sensors meets the preset leakage condition, the leakage detection result is determined to be that the location of the detection device is not leaking, and the feedback information that one humidity sensor detected leakage is carried in the leakage detection result and sent to the result processing device, so that the result processing device can determine that the location of the detection device that sent the feedback information is leaking when it receives at least two of the feedback information; the two slopes in the first slope pair are respectively located in the target slope set and the second slope set, and the humidity values ​​corresponding to the two slopes are the same; the slope pair matching represents that the sum of the two slopes is within the preset threshold range; the two slopes in the second slope pair are respectively located in the second slope set and the preset slope set, and the humidity values ​​corresponding to the two slopes are the same.

[0013] This setup effectively distinguishes between genuine leaks and localized disturbances (such as condensation or temporary water accumulation) by detecting leaks through at least two humidity sensors in a single detection device, or by detecting leaks through only one humidity sensor in at least two detection devices, thus preventing false alarms.

[0014] In some embodiments, the detection device includes a temperature sensor, and each preset humidity time curve corresponds to a humidity loss value. The step of obtaining the true humidity value of the concrete based on the second humidity data obtained at the current time point and the preset humidity time curve corresponding to the first humidity time curve includes: determining the humidity loss value according to the preset humidity time curve corresponding to the first humidity time curve; obtaining the temperature compensation value of the humidity sensor on the detection device where the temperature sensor is located based on the temperature data obtained by the temperature sensor; and obtaining the true humidity value based on the second humidity data obtained at the current time point, the humidity loss value, and the temperature compensation value.

[0015] This setup compensates for the second humidity data with humidity loss and temperature compensation values, ensuring stable judgment capabilities even in complex environments with large seasonal temperature differences and drastic diurnal temperature variations. This avoids situations where low temperatures in winter may mask the true leakage signal, or high temperatures and humidity in summer may cause false alarms, significantly improving the environmental adaptability and long-term reliability of leak detection.

[0016] In some embodiments, determining the preset humidity time curve corresponding to the first humidity time curve from multiple preset humidity time curves based on the first slope set includes: comparing the first slope set corresponding to the first humidity time curve with multiple preset slope sets corresponding to the preset humidity time curves; if the error between the two slopes in a third slope pair between the first slope set and one of the preset slope sets is within a third preset threshold range, determining the preset humidity time curve corresponding to the preset slope set as the preset humidity time curve corresponding to the first humidity time curve; the two slopes in the third slope pair are respectively located in the first slope set and the preset slope set, and the humidity values ​​corresponding to the two slopes are the same.

[0017] This setting allows for the priority selection of the preset humidity-time curve with the largest number of matches and the smallest error as the final matching result, and enables the adaptation to different building materials, ensuring the accuracy of subsequent real humidity calculations.

[0018] In some embodiments, during the process from the completion of building floor construction to the target time point, the humidity sensor of the detection device gradually decreases its sampling frequency, and after the target time point is reached from the current time point, the humidity sensor of the detection device gradually increases its sampling frequency.

[0019] This setup, through a three-stage strategy of high-frequency modeling in the early stages of construction, low-frequency standby during the middle stages of construction completion, and high-frequency response when the building reaches its target usage time, greatly extends the service life of the detection equipment while ensuring detection sensitivity, thus meeting the needs of long-term unattended monitoring.

[0020] Secondly, embodiments of the present invention provide a detection device, including a device body and a temperature sensor, a plurality of humidity sensors and a central processing unit located on the device body. The humidity sensors are respectively located around the periphery and the top of the device body. The central processing unit implements the building floor leakage detection method described in the first aspect through a computer program.

[0021] Thirdly, embodiments of the present invention provide a building floor leakage detection system, including a result processing device and a plurality of detection devices as described in the second aspect. The result processing device is used to determine the location of the detection device that first detected the leakage from the leakage detection results fed back by the plurality of detection devices.

[0022] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the building floor leakage detection method as described in the first aspect.

[0023] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A flowchart of a method for detecting water leakage in building floors provided by an embodiment of the present invention; Figure 2 A cross-sectional schematic diagram of the detection device provided in an embodiment of the present invention installed on a ground base layer; Figure 3 This is a schematic diagram of the distribution of the detection device provided in an embodiment of the present invention; Figure 4 for Figure 1 Flowchart of sub-steps S101~S103 of step S100; Figure 5 The humidity-time curve model provided in the embodiments of the present invention; Figure 6 for Figure 1 Flowchart of sub-steps S310~S360 of step S300; Figure 7 for Figure 6 Flowchart of sub-steps S361~S363 of step S360; Figure 8 for Figure 6 Flowchart of sub-steps S331~S333 of step S330; Figure 9 for Figure 6 Flowchart of sub-steps S321~S322 in step S320; Figure 10A block diagram of the detection device provided in an embodiment of the present invention; Figure 11 This is a schematic diagram of the functional modules of the building floor leakage detection system provided in an embodiment of the present invention.

[0026] Icons: 1000 - Detection device; 1100 - Device body; 1200 - Temperature sensor; 1300 - Humidity sensor; 1400 - Central processing unit; 1500 - Memory; 1600 - Bus; 1700 - Wireless transmission module. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0028] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0029] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0030] As described in the background section, by the time most building waterproofing coatings begin to leak and users discover the leak, it has already resulted in extensive or prolonged seepage, causing significant damage to the walls, leading to considerable inconvenience, property loss, and even structural damage to the building, making it difficult to pinpoint the exact location where the leak started.

[0031] Therefore, this invention provides a method for detecting floor leaks, applied to a detection device in a leak detection system. The detection device comprises multiple devices, each including a humidity sensor. The method obtains a minimum humidity value from the humidity sensor and combines this with a second humidity value to obtain the leak detection result. This allows for the immediate identification of the location and duration of the leak near the detection device, reducing damage to building walls caused by prolonged undetected leaks, and enabling timely and accurate identification of the location where the floor leak begins. (See also...) Figure 1 , Figure 1 This invention provides a flowchart of a method for detecting water leakage in building floors, comprising steps S100 to S400: S100. During the period from the completion of the building floor construction to the target time point, acquire the first humidity data of the concrete detected by the humidity sensor, and obtain the lowest humidity value in the first humidity data.

[0032] In some embodiments, building waterproofing systems are at risk of damage due to material aging or structural stress during long-term service. These problems are often insidious and delayed, making them difficult to detect promptly through conventional methods. Therefore, an initial monitoring phase is initiated after the building floor construction is completed. At this time, the newly poured concrete still contains a high moisture content and is undergoing a natural drying process. Each detection device periodically collects humidity information from the surrounding concrete environment through its integrated humidity sensor. The obtained data is defined as the first humidity data. This data records the humidity evolution trajectory from the completion of construction to the point of stable drying, serving as the foundational input for subsequently establishing a localized benchmark model. Figure 2 and Figure 3 As shown, Figure 2 This is a cross-sectional schematic diagram of the detection device provided in an embodiment of the present invention installed on the ground base. Figure 3 This is a schematic diagram showing the distribution of the detection device provided in an embodiment of the present invention. It can be seen that the detection device is evenly distributed within the ground base layer, occupying the center and four corners of the ground base layer.

[0033] Furthermore, the detection device filters and processes the received initial humidity data, identifying intervals where humidity changes tend to level off. A representative value is then extracted as the minimum humidity level for that location under conditions of no external water intrusion. This parameter reflects the lowest humidity level achievable in a specific area under normal operating conditions, forming the core reference threshold for future assessments of abnormal wetting. Therefore, this step, through comprehensive observation of the early drying process, enables independent modeling of each detection point, improving the accuracy and adaptability of individual assessments.

[0034] S200. After the target time point is reached from the current time point, the second humidity data of the concrete detected by the humidity sensor is obtained.

[0035] In some embodiments, when the time progresses to a preset target time point, it indicates that the concrete has completed its main water loss process and entered a long-term service state, subsequently switching to a high-sensitivity monitoring mode. After this, the detection devices continue to operate and collect new humidity readings, which constitute the second humidity data to reflect the current actual humidity status of the concrete. Since the environment has stabilized at this point, if the waterproof coating remains intact, the concrete humidity should be maintained at or slightly above the previously determined minimum humidity value; however, if the coating is damaged and leaks occur, external moisture will penetrate into the monitoring area along capillary channels, causing a localized increase in humidity.

[0036] During this process, secondary humidity data is continuously collected at a high sampling frequency to capture any subtle changes that may occur. This secondary humidity data includes not only instantaneous readings but also continuous sampling sequences over a period of time, providing support for subsequent trend analysis. In essence, the acquisition of secondary humidity data represents a transition from the learning and modeling phase to the anomaly identification phase, and the quality of the collected data directly impacts the reliability and timeliness of leak detection.

[0037] S300: Obtain the leakage detection result based on the lowest humidity value and the second humidity data; the leakage detection result indicates whether there is a leak at the location of the detection device.

[0038] In some embodiments, after obtaining the minimum humidity value and the second humidity data, the core discrimination logic is executed. For example, the detection device compares the real-time acquired second humidity data with the minimum humidity value of the first humidity data to preliminarily determine whether there is a humidity exceeding the limit. However, numerical comparison alone is insufficient to eliminate interference from environmental fluctuations or measurement noise; therefore, a comprehensive analysis combining trends, rate characteristics, and multi-dimensional compensation mechanisms is also necessary.

[0039] Specifically, a curve model reflecting the current wetting process is constructed using secondary humidity data, and key parameters such as slope set and rate of change are extracted and matched with historical drying models for verification. Temperature compensation and material property correction are also introduced to improve judgment accuracy. The final leakage detection result is not a simple binary conclusion, but a comprehensive judgment integrating multiple indicators to accurately characterize whether actual leakage occurs at the location of the detection device; this represents the transformation from raw data to intelligent decision-making and constitutes the technical core of the entire method.

[0040] S400: Send the leakage detection results to the result processing device so that the result processing device can determine the location of the first detection device that detected the leakage from the leakage detection results fed back by multiple detection devices.

[0041] In some embodiments, after completing its local judgment, each detection device sends its generated leak detection result to the gateway via its own wireless transmission module, and finally uploads it to the backend management system or other form of result processing device. Because multiple spatially distributed detection devices are deployed, and each outputs its judgment independently, the result processing device can perform time-series comparison of feedback information from different locations to identify which detection device first meets the leak judgment logic.

[0042] In this process, the geographical location of the detection device that first triggered the alarm is prioritized as the most likely leak location. This allows the time-priority positioning strategy to fully utilize the spatially progressive characteristics of leak diffusion: moisture typically spreads outward from the point of damage, and sensors closer to the leak detect humidity changes earlier. For example, if a detection device near the drain outlet sends a leak signal six hours earlier than its neighboring device B, it can be reasonably inferred that the leak is closer to the area where device A is located. Through multi-point collaborative analysis, the leak location is accurately pinpointed, providing clear guidance for subsequent maintenance.

[0043] In some embodiments, for step S100, one possible implementation of the present invention is provided, see [link to relevant documentation]. Figure 4 , Figure 4 for Figure 1 The flowchart of sub-steps S101~S103 of step S100, wherein steps S101~S103 include: S101. Generate a first humidity time curve based on all the first humidity data obtained during the process from the completion of the building floor construction to the target time point.

[0044] In this embodiment, to more intuitively demonstrate the dynamic characteristics of the concrete drying process, the system arranges all initial humidity data collected between the completion of construction and the target time point in chronological order and fits them into a continuous function curve, namely the initial humidity-time curve. The horizontal axis of this curve represents time, and the vertical axis represents humidity, fully presenting the overall trend of concrete transitioning from a high humidity state to a stable low humidity state within a specific area. Typically, as... Figure 5 As shown, Figure 5 The humidity time curve model provided in this embodiment of the invention has time on the horizontal axis and humidity value on the vertical axis. The first humidity time curve is a segment of RH from RH0. The entire humidity time curve shows a change pattern of rapid decrease in the early stage, slow decrease in the middle stage, and gradual flattening in the later stage.

[0045] For example, an interpolation algorithm is used to smoothly connect discrete sampling points to ensure that the curve can truly reflect the continuity of humidity evolution. The second humidity time curve is not only a data visualization tool, but also the basic carrier for subsequent extraction of key parameters (such as slope and inflection point). It carries the unique dryness characteristics of the detection point where the current detection device is located, and provides the original basis for subsequent matching of standard models and extraction of feature sets.

[0046] S102. If a humidity value in the first humidity time curve reaches a preset humidity value, calculate the rate of change of the slope of the two adjacent time nodes after the preset humidity value in the first humidity time curve.

[0047] In this embodiment, when the humidity value in the first humidity-time curve is detected to have dropped to a certain preset humidity value, the stability determination process is initiated. The preset humidity value mentioned here refers to an empirical threshold pre-set based on different cement grades, backfill material types, and ambient temperature and humidity conditions, used to indicate that the drying process has entered its final stage. In practical applications, the preset humidity value can be dynamically adjusted based on an experimental database to ensure applicability to various building scenarios.

[0048] Furthermore, within a time period following the preset humidity value, the slopes of the tangent lines at two adjacent time points are selected, and their relative rate of change, i.e., the slope change rate, is calculated. This reflects the degree to which the drying rate slows down. For example, if the slope in the previous period is -0.8% / day and in the next period is -0.2% / day, the rate of change is relatively large; conversely, if the slopes in the two periods are -0.3% / day and -0.28% / day respectively, the rate of change is extremely small, indicating that the water loss process has tended to stagnate. The slope change rate can be used to quantify the convergence degree of the drying process, providing a quantitative basis for determining whether a steady state has been reached.

[0049] S103. If the rate of change of the slope corresponding to two adjacent time nodes is lower than the preset rate of change, determine the average humidity value of multiple time points after the two adjacent time nodes as the lowest humidity value.

[0050] In this embodiment, when the calculated rate of change of the slope is lower than the preset rate of change, it is determined that the concrete humidity has basically stabilized and entered a long-term equilibrium state. Under this premise, the arithmetic mean of the humidity sampling values ​​at multiple consecutive time points is extracted, and this mean is used as the final minimum humidity value. This effectively avoids the influence of short-term environmental disturbances that may affect a single reading, and improves the reliability of the benchmark value.

[0051] For example, this mean calculation covers a sustained and stable sampling period, such as daily average readings over seven consecutive days, ensuring that the extracted minimum humidity value is statistically significant. It should be noted that this value is not a theoretical minimum, but rather represents the typical minimum level achievable at that location under normal conditions.

[0052] In some embodiments, for step S300, one possible implementation of the present invention is provided, see [link to relevant documentation]. Figure 6 , Figure 6 for Figure 1 The flowchart of sub-steps S310~S360 of step S300, wherein steps S310~S360 include: S310. Obtain the first slope set corresponding to the first humidity time curve.

[0053] In this embodiment, a set of key mathematical features, namely a first slope set, is extracted from the generated first humidity-time curve. This set consists of local slopes in several intervals on the curve, with each slope representing the average water loss rate within that period. For example, in the interval from day 1 to day 7, if the humidity drops from 80% to 65%, the corresponding slope is -2.14% / day; in the interval from day 30 to day 45, if it drops from 40% to 38%, the slope is -0.13% / day.

[0054] In this process, the analysis is divided into multiple segments according to fixed time windows or key turning points. The slope of each segment is calculated and summarized into a set. This set not only reflects the overall drying rate but also retains the characteristics of stage-specific changes, providing data support for subsequent comparison with the standard model. It can be understood that this first slope set is essentially a digital signature of the drying process, which can be used to identify the material category and construction conditions to which it belongs.

[0055] S320. Determine the preset humidity time curve corresponding to the first humidity time curve from multiple preset humidity time curves based on the first slope set.

[0056] In this embodiment, the extracted first slope set is compared with multiple preset slope sets corresponding to preset humidity-time curves stored locally or in the cloud to find the best match. The preset humidity-time curves mentioned here are derived from a large amount of experimental data accumulated in the early stages, covering typical drying modes under different cement grades, aggregate types, and construction processes. When a preset slope set and the first slope set show a high degree of consistency at key nodes, the preset curve is considered the most suitable reference model for the current environment.

[0057] For example, a similarity algorithm is used to evaluate the matching degree between candidate models, and the curve with the smallest error and the most matching is selected first. For instance, if a detection point uses C30 concrete, it will be automatically matched to the standard dry model of the C30 category, rather than the C25 or C40 model, so as to realize the detection system's adaptability to different building materials and provide an accurate source of parameters for subsequent compensation calculations.

[0058] S330. Obtain the actual humidity value of the concrete based on the second humidity data obtained at the current time point and the preset humidity time curve corresponding to the first humidity time curve.

[0059] In this embodiment, after determining the most suitable preset humidity-time curve, the associated material characteristic parameters are further obtained and corrected by combining them with real-time acquired second humidity data, thereby outputting a more accurate humidity value that reflects the actual moisture state. This process comprehensively considers background changes caused by non-leakage factors, such as the release of moisture from the concrete itself and the influence of environmental temperature changes, to avoid misjudgment.

[0060] For example, firstly, the corresponding humidity loss value is obtained based on the selected preset humidity-time curve to subtract the background attenuation caused by natural evaporation; simultaneously, the temperature compensation value provided by the temperature sensor is combined to correct the reading deviation caused by thermal drift. After this double correction, the obtained true humidity value more accurately reflects whether there is external water intrusion, significantly improving the system's judgment accuracy in complex environments.

[0061] S340. Generate a second humidity time curve based on all the second humidity data obtained between the target time point and the current time point, and obtain the second slope set corresponding to the second humidity time curve.

[0062] In this embodiment, a new function curve, namely the second humidity time curve, is constructed using all the second humidity data collected after the target time point, as shown below. Figure 5 As shown, the curve represents a gradual increase after the initial RH0 level. The second humidity-time curve reflects the current wetting dynamics of the concrete, with time on the horizontal axis and the corrected actual humidity value on the vertical axis. When no leakage occurs, this curve should remain relatively flat or fluctuate slightly; however, once water ingress occurs, the curve will show a continuous upward trend.

[0063] Furthermore, the second humidity-time curve is segmented and analyzed to extract the local slopes for each time period, forming a second slope set. This set characterizes the rate of change of the current wetting process and is a key input for subsequent mirror comparison with historical drying models. In other words, this set not only contains information on whether the humidity has increased, but also details of how it increases, providing strong support for identifying actual leakage.

[0064] S350. Obtain the target humidity time curve from the first humidity time curve based on the humidity value set corresponding to the second slope set, and obtain the target slope set corresponding to the target humidity time curve.

[0065] In this embodiment, the humidity values ​​involved in the second slope set are used as query keys to find the corresponding curve segment at the same humidity level in the first humidity time curve. This segment is called the target humidity time curve. The target humidity time curve represents the water loss path within the same humidity range during the historical drying process, and theoretically, it should be a mirror image of the wetting path of the current second humidity time curve.

[0066] Specifically, the local slope of the target humidity time curve is extracted to form a target slope set, which is then compared with the current second slope set. If the two are close in value but opposite in sign (i.e., one positive and one negative), it indicates that the current wetting process is symmetrical with the historical drying process, which is consistent with the physical mechanism of leakage.

[0067] S360 determines the leakage detection result based on the target slope set, the second slope set, the preset slope set corresponding to the preset humidity time curve, the minimum humidity value, and the actual humidity value.

[0068] In this embodiment, a multi-dimensional joint discrimination mechanism is activated, comprehensively utilizing the target slope set, the second slope set, the preset slope set, the minimum humidity value, and the actual humidity value for logical operations. A positive leakage detection result is output only when multiple conditions are simultaneously met. These conditions include: the current actual humidity value exceeds the minimum humidity value; there are a sufficient number of matching slope pairs between the second slope set and the target slope set; and the error between the second slope set and the preset slope set is within an acceptable range. For example, weighted scoring or Boolean logic is used to integrate various indicators, ensuring high confidence in the judgment result. This overcomes the limitations of traditional threshold-based alarms and introduces a multi-dimensional verification mechanism based on physical process consistency, significantly reducing the false alarm rate.

[0069] In some embodiments, there are multiple humidity sensors, each humidity sensor having a corresponding minimum humidity value, a target humidity time curve, and a second humidity time curve; for step S360, an embodiment of the present invention provides a possible implementation method, see [link to relevant documentation]. Figure 7 , Figure 7 for Figure 6 The flowchart of sub-steps S361~S363 of step S360, wherein steps S361~S363 include: S361. If at least two of the multiple humidity sensors meet the preset leakage conditions, the leakage detection result is determined to be leakage at the location of the detection device. The preset leakage conditions are: the actual humidity value corresponding to the humidity sensor is greater than the corresponding minimum humidity value; the number of first slope pairs matching the target slope set and the second slope set corresponding to the humidity sensor is greater than the first preset threshold; and the error between the two slopes in the second slope pair of the second slope set corresponding to the humidity sensor and the preset slope set is within the range of the first threshold.

[0070] In this embodiment, considering the potential risk of false triggering from a single sensor, a multi-channel collaborative verification mechanism is implemented. Each detection device integrates multiple humidity sensors arranged in various directions to collect data from the left, right, and top. A set of preset leakage conditions is set for each humidity sensor, including three core indicators: First, the current actual humidity value must exceed a specific minimum humidity value; second, between the target slope set and the second slope set, there must be a sufficient number of first slope pairs, i.e., pairs of slopes with similar values ​​at the same humidity level, and their sum must fall within the allowable error range; third, the second slope pairs between the second slope set and its corresponding preset slope set must also meet error constraints. When at least two sensors simultaneously meet all the above conditions, it is determined that leakage has indeed occurred in the area where the detection device is located, and a positive leakage detection result is output, effectively distinguishing between actual seepage and local interference (such as condensation, temporary water accumulation, etc.), preventing false alarms.

[0071] S362. If one of the multiple humidity sensors meets the preset leakage condition, the leakage detection result is determined to be that there is no leakage at the location of the detection device. The feedback information that one humidity sensor detected leakage is carried in the leakage detection result and sent to the result processing device so that the result processing device can determine that there is leakage at the location of the detection device that sent the feedback information when it receives at least two feedback information.

[0072] In this embodiment, when only a single sensor meets the preset leakage conditions, it is not immediately recognized as a leakage event. Instead, a warning feedback message is generated indicating that "a suspicious signal exists at this location." Although this information does not constitute a final judgment, it is still encapsulated and uploaded to the result processing device along with the normal results. However, the result processing device receives similar feedback from multiple detection devices. When two or more detection devices in the same spatial area report such information, it can be determined that there is a systemic leakage risk in that area, triggering a centralized investigation command. The leakage result is corrected in the feedback information, and it is determined that two or more detection devices have leaked. This achieves an organic combination of local judgment and global collaboration, improving the overall system's fault tolerance and response flexibility.

[0073] S363, the two slopes in the first slope pair are located in the target slope set and the second slope set respectively, and the humidity values ​​corresponding to the two slopes are the same; the slope pair matching characterizes that the sum of the two slopes is within the preset threshold range; the two slopes in the second slope pair are located in the second slope set and the preset slope set respectively, and the humidity values ​​corresponding to the two slopes are the same.

[0074] In this embodiment, matching the first slope pair means that the two curves have similar rates of change at the same humidity level, reflecting the consistency of the physical process. For example, if at the 40% humidity point, the slope in the target slope set is -0.4% / h, while the slope in the second slope set is +0.38% / h, then the sum of the two is -0.02% / h. If this value falls within the preset threshold range of ±0.1% / h, then the match is considered successful. This mechanism verifies whether the current wetting process conforms to the reverse characteristics of the historical drying process.

[0075] Similarly, the second slope pair is used to confirm that the current response pattern is consistent with the standard model. When the difference between a slope in the second slope set and the corresponding value in the preset slope set is less than a set error limit, the change characteristic is considered to be within the expected range. This corresponding value can be obtained by finding the corresponding preset slope in the preset slope set based on the humidity value corresponding to a slope in the second slope set.

[0076] In some embodiments, the detection device includes a temperature sensor, and each preset humidity time curve corresponds to a humidity loss value; for step S330, an embodiment of the present invention provides a possible implementation method, see [link to relevant documentation]. Figure 8 , Figure 8 for Figure 6 The flowchart of sub-steps S331~S333 of step S330, wherein steps S331~S333 include: S331. Determine the humidity loss value based on the preset humidity time curve corresponding to the first humidity time curve.

[0077] In this embodiment, the humidity loss value associated with the previously matched preset humidity-time curve is obtained. The humidity loss value reflects the amount of humidity reduction caused by natural evaporation per unit time under a specific material system, and is used to deduct background changes caused by non-leakage factors. For example, C30 concrete may naturally release 0.05% moisture per day at room temperature; this value is used as the humidity loss value for subsequent correction. During this process, the humidity loss value is experimentally calibrated and fixed in the model to ensure consistency and accuracy for each call.

[0078] S332. Based on the temperature data obtained by the temperature sensor, obtain the temperature compensation value of the humidity sensor on the detection device where the temperature sensor is located.

[0079] In this embodiment, temperature data is simultaneously collected at the same location, and a built-in algorithm is used to look up a table or calculate a temperature compensation value for the current temperature zone. This temperature compensation value is a correction coefficient pre-calibrated based on the sensor's characteristic curve, used to compensate for electrical parameter drift caused by temperature changes. For example, in low-temperature environments, the sensor output may be too low, resulting in an inaccurate reading; after compensation, the true humidity level can be restored. This process ensures that the system maintains stable judgment capabilities even in complex environments with large seasonal temperature differences and drastic diurnal temperature variations. Therefore, the introduction of a temperature compensation mechanism significantly improves the system's environmental adaptability and long-term reliability.

[0080] S333: Obtain the true humidity value based on the second humidity data, humidity loss value, and temperature compensation value obtained at the current time point.

[0081] In this embodiment, the detected humidity value of the real-time acquired second humidity data is subtracted from the humidity loss value and a temperature compensation value is added to finally output the true humidity value, for example, the true humidity value RHt=RH 检测 -m0+T 补偿 RH 检测 Here, m0 represents the humidity measurement value from the second humidity data set, and T represents the humidity loss value. 补偿 This corresponds to the temperature compensation value. The true humidity value comprehensively considers the material's own moisture release effect and environmental thermodynamic interference, and can more accurately reflect whether there is external water intrusion. For example, if the original reading is 32%, after deducting the influence of daily natural release of 0.05% and adding a +0.8% compensation due to low temperature, the final true humidity value is 32.75%, which ensures the authenticity and consistency of the measurement results and provides high-quality input for subsequent intelligent judgment.

[0082] In some embodiments, for step S320, one possible implementation of the present invention is provided, see [link to relevant documentation]. Figure 9 , Figure 9 for Figure 6 The flowchart of sub-steps S321~S322 of step S320, wherein steps S321~S322 include: S321. Compare the first slope set corresponding to the first humidity time curve with the preset slope set corresponding to multiple preset humidity time curves.

[0083] In this embodiment, the extracted first slope set is compared one by one with multiple candidate preset slope sets in the database. Under the same humidity value, the correspondence between two sets of slopes is found, i.e., the third slope pair, and the absolute error between each pair of slopes is calculated. This comparison process uses a vector similarity algorithm or a multi-dimensional matching strategy to evaluate the consistency of the overall profile, rather than a single numerical comparison. For example, if the drying rate of a certain detection point is generally slow, but the proportion of each stage is highly consistent with a certain preset slope set, it can still be determined as a match. Thus, this method improves the error tolerance and applicability of the model matching.

[0084] S322. When the error between the two slopes in the third slope pair of the first slope set and one of the preset slope sets is within the range of the third preset threshold, the preset humidity time curve corresponding to the preset slope set is determined to be the preset humidity time curve corresponding to the first humidity time curve; the two slopes in the third slope pair are respectively located in the first slope set and the preset slope set, and the humidity values ​​corresponding to the two slopes are the same.

[0085] In this embodiment, when the error of one or more pairs of third slope pairs falls within the range of a third preset threshold, the preset slope set is deemed to be highly consistent with the current measured situation, and its corresponding preset humidity time curve is used as the matching result. The third slope pair can be identified by the humidity value corresponding to a certain slope in the first slope set, and the corresponding preset slope can be found in the preset slope set based on the corresponding humidity value. This process is similar to fingerprint recognition, confirming the overall category through the degree of matching of local features. The selected preset humidity time curve not only provides a standardized reference but also carries a set of corresponding compensation parameters to ensure that subsequent real humidity calculations have material-level accuracy. Therefore, this method improves the system's universality and intelligence level in diverse building scenarios.

[0086] In some embodiments, during the process from the completion of building floor construction to the target time point, the sampling frequency of the humidity sensor of the detection device gradually decreases, and after the target time point is reached from the current time point, the sampling frequency of the humidity sensor of the detection device gradually increases.

[0087] Based on the same inventive concept disclosed above, the embodiments of the present invention also provide a block diagram of a detection device for performing the above method. Please refer to... Figure 10 The device includes a main body 1100 and a temperature sensor 1200, multiple humidity sensors 1300 and a central processing unit 1400 located on the main body 1100. The humidity sensors 1300 are located around the circumference and top of the main body 1100.

[0088] The detection device 1000 includes a device body 1100, a temperature sensor 1200, multiple humidity sensors 1300, a central processing unit 1400, a memory 1500, a bus 1600, and a wireless transmission module 1700. The central processing unit 1400 and the memory 1500 are connected via the bus 1600, and the central processing unit 1400 communicates with external devices via the wireless transmission module 1700. The humidity sensors are located around the perimeter and on the top of the device body. The central processing unit 1400 uses a computer program to implement the aforementioned method for detecting building floor leakage.

[0089] The central processing unit 1400 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed through integrated logic circuits in the hardware of the central processing unit 1400 or through software instructions. The central processing unit 1400 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processing unit (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0090] The memory 1500 is used to store computer programs. For example, the detection device in the embodiment of the present invention includes at least one software function module that can be stored in the memory 1500 in the form of software or firmware. After receiving the execution instruction, the central processing unit 1400 executes the program to implement the building floor leakage detection method in the embodiment of the present invention.

[0091] The memory 1500 may include high-speed random access memory (RAM) 1500, and may also include non-volatile memory 1500. Optionally, the memory 1500 may be a storage device built into the central processing unit 1400, or it may be a storage device independent of the central processing unit 1400.

[0092] Bus 1600 can be ISA bus 1600, PCI bus 1600, or EISA bus 1600, etc. Figure 10 It is indicated by only one double-headed arrow, but does not mean that there is only one bus 1600 or one type of bus 1600.

[0093] Based on the above method, embodiments of the present invention also provide a building floor leakage detection system corresponding to the above method, such as... Figure 11As shown, Figure 11 This is a schematic diagram of the functional modules of the building floor leakage detection system provided in this embodiment of the invention. It should be noted that the basic principle and technical effects of the building floor leakage detection system provided in this embodiment are the same as those in the above method embodiments. For the sake of brevity, parts not mentioned in this embodiment can be referred to the corresponding content in the method embodiments.

[0094] In this embodiment, the building floor leakage detection system includes a result processing device and multiple detection devices as described above. The result processing device is used to determine the location of the detection device that first detected the leak from the leakage detection results returned by the multiple detection devices. The result processing device includes a gateway and a back-end management system.

[0095] For example, the gateway module judges the leakage detection results of the detection device. On the one hand, the gateway module receives and processes the leakage detection results fed back by the detection device to determine which detection device leaked first. On the other hand, it sends the result of which detection device leaked first to the background management system.

[0096] For example, the back-end management system judges the leakage detection results of the detection device, the gateway module sends the leakage detection results fed back by the detection device to the back-end management system, the back-end management system receives and processes the leakage detection results sent by the gateway module, and determines which detection device leaked first.

[0097] Each detection device includes a temperature sensing module, three humidity sensor modules, a central processing unit, a unit module, and a wireless transmission module. The humidity and temperature sensors each have two probes. The humidity sensing module acquires the initial humidity data of the concrete detected by the humidity sensors during the process from the completion of building floor construction to the target time point, and obtains the lowest humidity value from the initial humidity data; after the target time point is reached from the current time point, it acquires the second humidity data of the concrete detected by the humidity sensors. It can be understood that the humidity sensing module is a humidity sensor, and the temperature sensing module is a temperature sensor.

[0098] The central processing unit is used to process the data collected by the humidity sensing module and the temperature sensing module to obtain the first humidity time curve, the second humidity time curve, the target humidity time curve, the humidity loss value, the temperature compensation value, and the actual humidity value. This facilitates the comparison and output of the leakage detection results based on the above data.

[0099] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program thereon. When executed by the central processing unit 1400, the computer program implements the building floor leakage detection method described above. This computer-readable storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0100] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting water leakage in building floors, characterized in that, A detection device used in a leak detection system, wherein there are multiple detection devices, each including a humidity sensor, and the method includes: During the period from the completion of the building floor construction to the target time point, the first humidity data of the concrete detected by the humidity sensor is obtained, and the lowest humidity value in the first humidity data is obtained. After the target time point is reached at the current time point, the second humidity data of the concrete detected by the humidity sensor is obtained; Based on the minimum humidity value and the second humidity data, a leakage detection result is obtained; the leakage detection result indicates whether there is a leak at the location of the detection device. The leakage detection results are sent to the result processing device so that the result processing device can determine the location of the first detection device that detected the leakage from the leakage detection results fed back by multiple detection devices.

2. The method according to claim 1, characterized in that, The lowest humidity value obtained from the first humidity data includes: The first humidity time curve is generated based on all the first humidity data obtained during the period from the completion of the building floor construction to the target time point; If a humidity value in the first humidity time curve reaches a preset humidity value, calculate the rate of change of the slope of the two adjacent time nodes after the preset humidity value in the first humidity time curve. If the rate of change of the slope corresponding to two adjacent time nodes is lower than the preset rate of change, the average humidity value of multiple time points after the two adjacent time nodes is determined to be the lowest humidity value.

3. The method according to claim 2, characterized in that, The step of obtaining the leakage detection result based on the lowest humidity value and the second humidity data includes: Obtain the first slope set corresponding to the first humidity-time curve; Based on the first slope set, determine the preset humidity time curve corresponding to the first humidity time curve from multiple preset humidity time curves; The actual humidity value of the concrete is obtained based on the second humidity data acquired at the current time point and the preset humidity time curve corresponding to the first humidity time curve. A second humidity time curve is generated based on all the second humidity data obtained between the target time point and the current time point, and a second slope set corresponding to the second humidity time curve is obtained. Based on the set of humidity values ​​corresponding to the second slope set, the target humidity time curve is obtained from the first humidity time curve, and the target slope set corresponding to the target humidity time curve is obtained. Based on the target slope set, the second slope set, the preset slope set corresponding to the preset humidity time curve, the minimum humidity value, and the actual humidity value, the leakage detection result is determined.

4. The method according to claim 3, characterized in that, The humidity sensor comprises multiple sensors, each having a corresponding minimum humidity value, a target humidity time curve, and a second humidity time curve; the determination of the leakage detection result based on the target slope set, the second slope set, the minimum humidity value, and the actual humidity value includes: If at least two of the multiple humidity sensors meet the preset leakage conditions, the leakage detection result is determined to be leakage at the location of the detection device; the preset leakage conditions are: the actual humidity value corresponding to the humidity sensor is greater than the corresponding minimum humidity value; the number of first slope pairs matching the target slope set and the second slope set corresponding to the humidity sensor is greater than a first preset threshold; and the error between the two slopes in the second slope pair of the second slope set corresponding to the humidity sensor and the preset slope set is within the first threshold range. If one of the multiple humidity sensors meets the preset leakage condition, the leakage detection result is determined to be that there is no leakage at the location of the detection device. The feedback information that one humidity sensor detected leakage is carried in the leakage detection result and sent to the result processing device, so that when the result processing device receives at least two of the feedback information, it determines that there is a leakage at the location of the detection device that sent the feedback information. The two slopes in the first slope pair are located in the target slope set and the second slope set, respectively, and the humidity values ​​corresponding to the two slopes are the same; the slope pair matching indicates that the sum of the two slopes is within a preset threshold range; the two slopes in the second slope pair are located in the second slope set and the preset slope set, respectively, and the humidity values ​​corresponding to the two slopes are the same.

5. The method according to claim 3, characterized in that, The detection device includes a temperature sensor, and each preset humidity-time curve corresponds to a humidity loss value. The process of obtaining the true humidity value of the concrete based on the second humidity data acquired at the current time point and the preset humidity-time curve corresponding to the first humidity-time curve includes: The humidity loss value is determined based on the preset humidity time curve corresponding to the first humidity time curve. Based on the temperature data obtained by the temperature sensor, the temperature compensation value of the humidity sensor on the detection device where the temperature sensor is located is obtained; The true humidity value is obtained based on the second humidity data acquired at the current time, the humidity loss value, and the temperature compensation value.

6. The method according to claim 3, characterized in that, The step of determining the preset humidity time curve corresponding to the first humidity time curve from multiple preset humidity time curves based on the first slope set includes: The first slope set corresponding to the first humidity time curve is compared with the preset slope set corresponding to multiple preset humidity time curves; If the error between two slopes in the third slope pair of the first slope set and one of the preset slope sets is within the range of a third preset threshold, the preset humidity time curve corresponding to the preset slope set is determined to be the preset humidity time curve corresponding to the first humidity time curve; the two slopes in the third slope pair are respectively located in the first slope set and the preset slope set, and the humidity values ​​corresponding to the two slopes are the same.

7. The method according to any one of claims 1-6, characterized in that, During the process from the completion of the building floor construction to the target time point, the humidity sensor of the detection device gradually reduces its sampling frequency. After the target time point is reached from the current time point, the humidity sensor of the detection device gradually increases its sampling frequency.

8. A detection device, characterized in that, The device includes a main body and a temperature sensor, multiple humidity sensors, and a central processing unit located on the main body. The humidity sensors are located around the periphery and at the top of the main body, respectively. The central processing unit implements the building floor leakage detection method according to any one of claims 1-7 through a computer program.

9. A building floor leakage detection system, characterized in that, It includes a result processing device and a plurality of detection devices as described in claim 8, wherein the result processing device is used to determine the location of the detection device that first detected the leak from the leak detection results fed back by the plurality of detection devices.

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 building floor leakage detection method as described in any one of claims 1-7.

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