Anti-blocking early warning method for fluid filtering device

Abstract

The invention provides a fluid filtering device anti-blocking early warning method which comprises the steps that pressure data of the front end and the rear end of a filtering device are obtained, and the pressure data are collected through sampling pipes installed at the front end and the rear end of the filtering device; the pressure data are input into a differential pressure transmitter, the differential pressure transmitter measures the pressure difference between the front end and the rear end and compares the pressure difference with a preset normal pressure threshold value, and a pressure abnormity mark is obtained; and the mobile application module reads the pressure anomaly identifier output by the differential pressure transmitter, and sends reminding information to the user terminal according to the pressure anomaly identifier, so that the equipment management efficiency and safety are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a fluid filter device anti-blocking early warning method. BACKGROUND

[0002] In the field of industrial equipment operation management, filter devices are an important link to ensure production safety and efficiency, and their stability and reliability are crucial to the entire production process. Especially in the chemical, pharmaceutical and other industries, the running state of the filter device directly affects the product quality and equipment life, so timely discovery and handling of potential problems in equipment operation are particularly critical. However, current technical means often have shortcomings in dealing with this demand, and more effective solutions are needed to improve the level of fine management of equipment.

[0003] The existing tap water filtration anti-blocking early warning method usually relies on periodic equipment inspection or simple pressure data recording when monitoring the running state of the filter device. This approach often fails to capture real-time changes in equipment operation, especially when pressure fluctuations are subtle or in the early stages of abnormal development, making it difficult to respond in a timely manner. More importantly, these methods lack in-depth analysis and classification of abnormal conditions, making it difficult for operators to take targeted measures based on the severity of the problem, increasing the risk of equipment failure.

[0004] Further, a core technical difficulty in this field is how to accurately identify and assess pressure changes in the running of filter devices and convert them into actionable early warning information. Pressure changes, as a key factor reflecting the running state of the equipment, are often indicative of problems such as clogging, leakage, etc. However, since pressure changes can be influenced by a variety of external factors, such as medium viscosity, flow fluctuations, etc., simple pressure data collection cannot accurately determine the nature and severity of the anomaly. For example, in some cases, the pressure difference between the inlet and outlet may temporarily exceed the normal range, but this does not mean that the equipment has a serious problem, but may be a normal fluctuation due to temporary flow increases. How to accurately distinguish the nature of these pressure changes in a complex environment and make reasonable judgments based on their duration and deviation size is a technical problem that needs to be solved.

[0005] Therefore, how to monitor and accurately analyze the characteristics of pressure changes in real time during the operation of filter devices, and generate hierarchical early warning information based on the different characteristics of abnormal conditions, has become a key issue to improve the efficiency and safety of equipment management. SUMMARY

[0006] The present application provides a fluid filter device anti-blocking early warning method, mainly comprising: The system acquires pressure data from the front and rear ends of the filter device, wherein the pressure data is collected through sampling tubes installed at the front and rear ends of the filter device; the pressure data is input into a differential pressure transmitter, which measures the pressure difference between the front and rear ends and compares it with a preset normal pressure threshold to obtain a pressure anomaly indicator; the system reads the pressure anomaly indicator output by the differential pressure transmitter through a mobile application module and sends a reminder message to the user terminal based on the pressure anomaly indicator.

[0007] Furthermore, the acquisition of pressure data at the front and rear ends of the filtration device includes: the sampling tube is made of corrosion-resistant material and fixed at the inlet and outlet positions of the filtration device; inlet pressure data is collected from the inlet and outlet pressure data is collected from the outlet; the inlet pressure data and the outlet pressure data are transmitted to the differential pressure transmitter to support subsequent measurements.

[0008] Furthermore, the step of inputting the pressure data into the differential pressure transmitter includes: the differential pressure transmitter receiving the pressure data and calculating the actual differential pressure value; calculating the deviation between the actual differential pressure value and the preset normal pressure threshold; if the deviation exceeds the preset normal pressure threshold, generating the pressure anomaly identifier and attaching a timestamp; and transmitting the pressure anomaly identifier to the mobile application module.

[0009] Furthermore, the step of reading the pressure anomaly identifier output by the differential pressure transmitter via the mobile application module includes: the mobile application module establishing a communication connection with the differential pressure transmitter and obtaining the pressure anomaly identifier from the differential pressure transmitter; classifying the pressure anomaly identifier to obtain anomaly level data; generating reminder content based on the anomaly level data and sending it to the user terminal via the communication interface.

[0010] Furthermore, the step of calculating the deviation between the actual differential pressure value and the preset normal pressure threshold includes: acquiring the sequence data of the actual differential pressure value and calculating the average deviation value; if the average deviation value is greater than the preset normal pressure threshold, then determining it as a high anomaly level and updating the pressure anomaly identifier; appending the high anomaly level to the pressure anomaly identifier and forwarding it to the mobile application module; the mobile application module adjusting the sending frequency of the reminder information according to the high anomaly level.

[0011] Furthermore, the step of classifying the pressure anomaly identifier by level includes: analyzing the deviation value and timestamp information in the pressure anomaly identifier to determine the duration of the anomaly; comparing the duration of the anomaly with a preset duration threshold to obtain the anomaly level data; if the anomaly level data indicates a severity level, generating detailed reminder content including the location of the filtering device; and sending the detailed reminder content to the user terminal through the communication interface and recording the sending log.

[0012] Furthermore, the step of sending a reminder message to the user terminal based on the stress anomaly identifier includes: the mobile application module processing the stress anomaly identifier to generate a multi-channel reminder signal; converting the multi-channel reminder signal into SMS format and push format; sending the SMS format reminder message to the user terminal and monitoring for confirmation of receipt; if no confirmation is received, then repeatedly sending the push format reminder message.

[0013] Furthermore, transmitting the inlet pressure data and the outlet pressure data to the differential pressure transmitter includes: the sampling tube performing preliminary filtering on the inlet pressure data to obtain filtered inlet data; performing the same preliminary filtering on the outlet pressure data to obtain filtered outlet data; synchronously inputting the filtered inlet data and the filtered outlet data into the differential pressure transmitter; and the differential pressure transmitter calculating a differential pressure sequence based on the filtered inlet data and the filtered outlet data to improve measurement accuracy.

[0014] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a method for early warning of filtration device anomalies based on differential pressure monitoring. By accurately collecting and analyzing pressure data from both the front and back ends of the filtration device, it solves a unique business scenario problem: how to monitor pressure anomalies in real time during the operation of industrial filtration equipment and promptly issue tiered warnings to users to prevent equipment failure or efficiency degradation. This invention collects pressure data by installing corrosion-resistant sampling tubes at the inlet and outlet of the filtration device, and uses a differential pressure transmitter to calculate the deviation between the actual differential pressure value and a preset threshold, generating a timestamped pressure anomaly identifier. Subsequently, a mobile application module performs level classification processing, generating different levels of alert content based on the duration of the anomaly and the degree of deviation, and sending it to the user terminal through multiple channels to ensure timely user response. The core innovation of this invention lies in the seamless integration of pressure monitoring, anomaly classification, and dynamic alert mechanisms, significantly improving the safety and maintenance efficiency of equipment operation and reducing potential risks caused by pressure anomalies. Attached Figure Description

[0015] Figure 1 This is a flowchart of a method for preventing clogging and providing early warning for a fluid filtration device according to the present invention.

[0016] Figure 2 This is a schematic diagram of an anti-clogging early warning method for a fluid filtration device according to the present invention.

[0017] Figure 3 This is another schematic diagram of a fluid filtration device anti-clogging early warning method according to the present invention.

[0018] Figure 4This is another schematic diagram of a fluid filtration device anti-clogging early warning method according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0020] like Figures 1-4 This embodiment of a fluid filtration device anti-clogging early warning method may specifically include: S1, Obtain pressure data at the front and rear ends of the filter device, wherein the pressure data is collected through sampling tubes installed at the front and rear ends of the filter device.

[0021] In one embodiment, step S1 acquires pressure data at the front and rear ends of the filter device, wherein the pressure data is collected through sampling tubes installed at the front and rear ends of the filter device, and specifically includes the following sub-steps.

[0022] Step S11: Install sampling tubes at the front and rear ends of the filter device. The sampling tubes are made of stainless steel to ensure corrosion resistance and long-term stability.

[0023] Sampling tubes are installed before and after the filter to capture pressure changes as water flows through the filtration system. The choice of stainless steel effectively resists corrosion from impurities in tap water, extending the equipment's lifespan.

[0024] Step S12: Continuously measure the pressure collected by the sampling tube using the installed differential pressure transmitter.

[0025] The differential pressure transmitter is connected to a sampling tube to monitor the pressure difference between the upstream and downstream ends in real time. This measurement allows for direct comparison of the upstream and downstream pressure data, forming the basis for abnormal pressure readings.

[0026] In one embodiment, the pressure data acquisition in step S1 can be applied to a household tap water system.

[0027] For example, in a standard residential water pipe system, the filter is installed on the main inlet pipe, and sampling tubes are placed at the filter inlet and outlet, respectively.

[0028] When the normal water pressure is 0.3 MPa, the front-end sampling tube collects a reading of 0.3 MPa. If the pressure drops to 0.25 MPa at the back end due to impurity accumulation, the differential pressure transmitter records a difference of 0.05 MPa. This sampling method can identify the risk of blockage early and improve the filtration effect.

[0029] In another possible implementation, considering different water flow scenarios, such as peak water usage periods, the sampling frequency can be set to once per minute to ensure real-time data. By comparing the collected data with a normal water pressure of 0.2 MPa, anomaly indicators can be generated, which is beneficial for reminding users to clean the filter and avoid water pipe blockage affecting daily use.

[0030] For example, in one embodiment, when installing the sampling pipe in step S11 for an older residential water supply system, pipe diameter matching can be considered, such as using a 20mm diameter stainless steel pipe to fit the existing pipeline. During the measurement process in step S12, if the pressure at the front end is 0.4MPa and at the rear end is 0.35MPa, the difference of 0.05MPa indicates a slight blockage. This provides timely early warning and reduces the risk of water quality degradation.

[0031] The above implementation method ensures accurate collection of pressure data, forming a complete chain from installation to measurement, and ultimately supporting the operation of the tap water filter anti-clogging early warning system.

[0032] S2, input the pressure data into the differential pressure transmitter, the differential pressure transmitter measures the pressure difference between the front and rear ends and compares it with the preset normal pressure threshold to obtain a pressure abnormality indicator.

[0033] In one embodiment, step S2 involves inputting the pressure data into a differential pressure transmitter, which measures the pressure difference between the front and rear ends and compares it with a preset normal pressure threshold to obtain a pressure anomaly indicator. This step specifically includes the following sub-steps.

[0034] Step S21: The collected pressure data at the front and rear ends of the filter is input into the differential pressure transmitter in real time. The pressure data comes from stainless steel sampling tubes installed in front of and behind the filter. These sampling tubes ensure the stability and corrosion resistance of the data acquisition.

[0035] In this embodiment, after receiving the pressure data, the differential pressure transmitter first calculates the pressure difference between the front and back ends, for example, by subtraction. This difference reflects the resistance change caused by the accumulation of impurities inside the filter, thus providing basic data for subsequent comparisons.

[0036] Step S22: Compare the calculated pressure difference with the preset normal pressure threshold, where the preset normal pressure threshold is set based on normal water pressure, for example, the threshold is 0.5 bar. If the difference exceeds the threshold, a pressure abnormality indicator is generated.

[0037] The above comparison process uses a simple threshold judgment logic to ensure real-time performance. For example, during peak household water usage periods, if the difference reaches 0.6 bar, the system immediately marks it as abnormal. This helps to detect potential blockages early and improve the overall filtration effect of the filter.

[0038] In one possible implementation, the threshold in step S22 can be dynamically adjusted according to different application scenarios. For example, in areas with poor water quality, the threshold can be set to 0.4 bar to cover more potential blockages, thus expanding the system's adaptability and reducing the impact of water pipe blockages on users through timely identification.

[0039] Step S23: The obtained pressure anomaly identifier triggers the data transmission mechanism to send the identifier to the App for further processing. The anomaly identifier is a binary flag, with 0 indicating normal and 1 indicating anomaly, ensuring seamless connection with subsequent reminder functions.

[0040] Once the above identifier is generated, it directly affects the App's reading and alarm logic. For example, when the identifier is 1, the App will identify abnormal data and prepare an SMS reminder. This forms a complete chain from measurement to user notification, effectively solving the problem of the filter not being able to be cleaned up in time.

[0041] In one embodiment, the entire process of step S2 can be extended to multi-parameter scenarios, such as combining water flow data to assist pressure difference measurement. Step S211 involves collecting water flow as an auxiliary input, which is then input to the differential pressure transmitter along with the pressure data. Step S212 involves calculating the comprehensive difference, for example, multiplying the pressure difference by a flow coefficient to obtain an adjusted difference. Step S213 involves comparing the difference with a threshold value to generate an identifier. This extension improves detection accuracy; for example, the threshold is 0.3 bar at low flow rates and 0.7 bar at high flow rates, avoiding false alarms and contributing to the continuous improvement of tap water quality.

[0042] Assuming a normal pressure difference of 0.2 bar, when impurities accumulate and cause the difference to reach 0.55 bar, the system generates an anomaly flag, and the app sends an SMS message. This not only reminds the user to clean the area but also reduces water outages caused by blockages, thus improving user convenience.

[0043] In one possible implementation, the flag triggering in step S23 can be applied in industrial water scenarios, such as a threshold of 1.0 bar in a large filtration system. After generating the flag, it can trigger automated cleaning equipment. This expands the applicability from home to industry, but still focuses on anti-clogging warning to ensure logical consistency.

[0044] Through the close connection of these steps, from pressure data input to abnormal indicator output, an efficient monitoring chain is formed, ultimately achieving the effect of timely reminding users to clean the filter and improve water quality. This demonstrates the practical value of the tap water filter anti-clogging early warning system.

[0045] S3, the pressure abnormality indicator output by the differential pressure transmitter is read through the mobile application module, and a reminder message is sent to the user terminal according to the pressure abnormality indicator.

[0046] In one embodiment, step S3 reads the pressure anomaly identifier output by the differential pressure transmitter through the mobile application module, and sends a reminder message to the user terminal based on the pressure anomaly identifier, specifically including the following sub-steps.

[0047] Step S31: The mobile application module obtains real-time output pressure data from the differential pressure transmitter via wireless connection. The differential pressure transmitter is pre-installed before and after the filter. It continuously measures the water pressure difference before and after the filter and compares it with a preset normal pressure threshold. When the differential pressure exceeds the threshold, a pressure abnormality indicator is generated. For example, the threshold is set to 1.2 times the normal pressure.

[0048] Step S32: Verify the obtained pressure anomaly flag to ensure its validity. For example, check whether the data is within the expected range to avoid false alarms caused by transmission interference.

[0049] Step S33: Based on the verified pressure anomaly identifier, the mobile application module is triggered to send an SMS reminder to the user terminal. The reminder includes anomaly details and suggested cleanup time.

[0050] In a household tap water system, when impurities accumulate in the filter, causing the pressure difference between the filter and the filter to increase from the normal 0.5 bar to 0.8 bar, the differential pressure transmitter outputs an abnormality indicator. The mobile application module reads this and immediately sends an SMS message: "Your filter pressure is abnormal. Please clean it promptly." This effectively prevents clogging and ensures stable water quality.

[0051] In one possible implementation, step S3 can be extended to multi-user scenarios, such as for multiple filters in an apartment building. The mobile application module can simultaneously read the identifiers of multiple differential pressure transmitters and send graded alerts according to different identifier levels, such as sending a mild alert for minor anomalies and an emergency alarm for serious anomalies, which improves the applicability of the system.

[0052] In step S31, the wireless connection uses the Bluetooth protocol to ensure stable data transmission. The differential pressure transmitter samples once per minute and compares the differential pressure value with the threshold. If the differential pressure is 1.0 bar, which exceeds the 0.7 bar threshold, an "abnormal level 1" flag is generated.

[0053] The verification process in step S32 includes timestamp checks, such as confirming that the identifier was generated within the last 5 minutes, to filter out old data.

[0054] In step S33, the SMS message is sent using the integrated API interface, with the content customized as "Pressure abnormality: 1.0 bar, it is recommended to clean the filter immediately", thereby reminding the user to take timely action and reduce the risk of water pipe blockage.

[0055] For example, in daily use, if a user is away for an extended period of time, the system detects that the differential pressure gradually increases from 0.4 bar to 0.9 bar, generates an indicator, and sends a reminder through the app. The user can then remotely view and schedule cleaning, which enhances convenience and improves the filtration effect.

[0056] In one embodiment, step S3 can adjust the threshold parameter for different water pressure environments. For example, in high water pressure areas, the threshold can be set to 1.5 times the normal value. After the mobile application module reads the identifier, it sends an alert containing specific pressure difference data, such as "Pressure difference of 0.6 bar is abnormal", which helps users understand the severity of the problem.

[0057] The above adjustments are implemented through the App interface. Users can customize the thresholds, but the system defaults to optimizing based on historical data to ensure accuracy.

[0058] For example, assuming the normal pressure is 0.6 bar and the abnormal time differential pressure reaches 0.9 bar, the App reads the flag and sends a "Warning: The filter may be clogged, affecting water quality. Please clean it." This not only notifies the user of the problem but also emphasizes the effect of improving water quality.

[0059] In one possible implementation, the reminder mechanism in step S3 can be combined with push notifications to supplement SMS messages. For example, when SMS messages fail to be sent, the system can switch to in-app push notifications to ensure that users always receive information.

[0060] Step S31 is extended to periodic reading, once every 10 minutes, to balance power consumption and real-time performance.

[0061] Step S32 includes classifying abnormal indicators, for example, into three levels: low, medium, and high, with a differential pressure increase of 0.2 bar being classified as low.

[0062] Step S33 generates personalized reminders, such as "Based on your usage habits, it is recommended to check once a week," which improves the user experience and promotes regular maintenance.

[0063] For example, in one scenario, the differential pressure transmitter output indicator showed a differential pressure of 1.1 bar. After the App verified this, it sent an "Emergency: High risk of filter blockage, please handle immediately." After the user responded, the water flow returned to normal, proving the effectiveness of the system.

[0064] In one embodiment, the complete process of step S3 forms a closed loop from reading to sending, for example, processing the data immediately after reading to avoid delays.

[0065] If the differential pressure anomaly is identified as "high risk", the system sends a reminder containing cleaning steps, such as "remove the filter and rinse", which directly guides the user and enhances usability.

[0066] The above guidance is based on a pre-stored template to ensure accurate information, which helps to quickly resolve problems and maintain tap water quality.

[0067] The above-mentioned acquisition of pressure data at the front and rear ends of the filter device includes: S11, the sampling tube is made of corrosion-resistant material and fixed at the inlet and outlet positions of the filter device, inlet pressure data is collected from the inlet and outlet pressure data is collected from the outlet; S12, the inlet pressure data and the outlet pressure data are transmitted to the differential pressure transmitter to support subsequent measurements.

[0068] S11, the sampling tube is made of corrosion-resistant material and is fixed at the inlet and outlet of the filter device, and inlet pressure data is collected from the inlet and outlet pressure data is collected from the outlet.

[0069] In one embodiment, the sampling tube in step S11 is made of stainless steel as a corrosion-resistant material. This material can effectively resist corrosion caused by chloride ions and impurities in tap water, ensuring long-term stable operation. When the sampling tube is fixed at the inlet and outlet positions of the filter device, it is installed on the water pipe through a threaded connection. The pressure data collected at the inlet position reflects the water pressure before filtration, and the data collected at the outlet position reflects the water pressure difference after filtration.

[0070] For example, the sampling tube diameter is 10mm. When fixed, the inlet end is 5cm away from the filter inlet and the outlet end is 5cm away from the outlet to minimize pipeline interference. The sampling process is monitored in real time using a built-in pressure sensor. If the inlet pressure data is normally 200kPa and the outlet pressure is 195kPa, it indicates a slight pressure drop.

[0071] In one embodiment, step S11 can be extended to S111, which involves the specific process of selecting a corrosion-resistant material, including assessing the pH value of the water. If the pH is in the range of 6-8, 304 stainless steel is selected; if the pH is below 6, 316 stainless steel is selected to enhance acid resistance. In step S112, sealant is used to ensure no leakage when fixing the sampling tube. Inlet data is converted into digital signals, and outlet data is processed similarly to form a basis for comparing the pressure before and after the sampling.

[0072] For example, in a household tap water system, inlet pressure data is collected once per minute, with outlet pressure collected simultaneously. If the inlet pressure is 250 kPa and the outlet pressure is 240 kPa, it indicates that impurities accumulated in the filter are beginning to affect the flow. This allows for early detection of blockage risks and improves the responsiveness of the early warning system.

[0073] The selection of corrosion-resistant materials in step S11 is based on common pollutants in the tap water environment, such as rust and calcium and magnesium ions. These substances easily cause corrosion of ordinary pipe materials. Using stainless steel can extend the life of the sampling tube to more than 5 years, avoiding the maintenance costs caused by frequent replacements. The fixed position design ensures the accuracy of pressure data and avoids measurement errors caused by pipe bending, thus providing reliable input for subsequent differential pressure calculations.

[0074] In one embodiment, step S11 can adjust the sampling tube length for different water pressure scenarios. For example, in a high-pressure municipal water supply system, the sampling tube length is increased to 20cm to buffer turbulence. Temperature compensation is integrated when collecting inlet pressure data, and the pressure reading is calibrated to the actual value when the water temperature is 20°C. This expansion can cover rural low-pressure water source scenarios, where the inlet pressure is only 100kPa and the outlet pressure is 95kPa. The early warning system uses this information to determine the degree of filter blockage.

[0075] For example, assuming the filtration device is installed on an apartment floor, the inlet data shows a peak pressure of 300 kPa and the outlet pressure of 280 kPa. The pressure difference is calculated by averaging multiple samples, which supports the accuracy of anti-clogging warnings. The beneficial effect is to reduce the frequency of manual inspections by users and improve the consistency of water quality.

[0076] The aforementioned inlet pressure data and outlet pressure data are transmitted to the differential pressure transmitter to support subsequent measurements.

[0077] In one embodiment, the data is transmitted to the differential pressure transmitter via a wired connection, and continuous differential pressure calculation is supported after transmission.

[0078] For example, after the inlet data of 200 kPa and the outlet data of 195 kPa are transmitted, the transmitter calculates the difference of 5 kPa. If the difference exceeds the threshold, an alarm is triggered.

[0079] The above-mentioned input of the pressure data into the differential pressure transmitter includes: S21, the differential pressure transmitter receives the pressure data and calculates the actual differential pressure value; S22, the deviation between the actual differential pressure value and the preset normal pressure threshold is calculated, and if the deviation exceeds the preset normal pressure threshold, the pressure anomaly identifier is generated and timestamp information is attached; S23, the pressure anomaly identifier is transmitted to the mobile application module.

[0080] S21, the differential pressure transmitter receives the pressure data and calculates the actual differential pressure value.

[0081] In one embodiment, the differential pressure transmitter first extracts the upstream and downstream pressure values ​​from the water pressure signals collected by sampling pipes installed before and after the filter. Then, it obtains the actual differential pressure value through subtraction. For example, if the upstream pressure is P1 and the downstream pressure is P2, the actual differential pressure value is P1 minus P2. This calculation ensures the real-time nature of the differential pressure and is beneficial for the accuracy of subsequent anomaly detection.

[0082] S22, calculate the deviation between the actual differential pressure value and the preset normal pressure threshold. If the deviation exceeds the preset normal pressure threshold, generate the pressure anomaly identifier and attach timestamp information.

[0083] In one embodiment, step S22 specifically includes the following sub-steps: S221, obtaining a preset normal pressure threshold, which is set based on normal water pressure, for example, 5 kPa in a household water scenario. S222, calculating the deviation using absolute difference, i.e., the deviation is equal to the actual differential pressure value minus the absolute value of the preset normal pressure threshold. S223, if the calculated deviation is greater than zero, it is determined to be abnormal, and a pressure abnormality identifier is generated. This identifier is a binary flag bit, such as 1 indicating an abnormality, and is appended with the current system timestamp, such as time information in the format YYYY-MM-DD HH:MM:SS. This method forms a logical chain from differential pressure calculation to abnormality marking, ensuring that abnormal data has a time context, making it easy for users to track the progress of filter clogging.

[0084] For example, in a tap water filter anti-clogging early warning system, when the actual differential pressure reaches 8 kPa and the preset threshold is 5 kPa, the deviation is 3 kPa. After exceeding the threshold, an identifier is generated and a timestamp is attached, such as 2023-10-01 14:30:00. This helps users to identify the start time of the blockage in a timely manner and improve cleaning efficiency.

[0085] In one possible implementation, for different water pressure environments, such as peak water usage periods, the preset normal pressure threshold can be adjusted to 6 kPa. The deviation calculation still uses the absolute difference method. If the actual differential pressure is 7 kPa, the deviation of 1 kPa does not exceed the threshold, and no flag is generated. However, if the actual differential pressure rises to 10 kPa, the deviation of 4 kPa exceeds the threshold, and a flag is generated with a timestamp attached. This adjustment covers peak and valley water usage scenarios, which helps reduce false alarms and improve the system's adaptability.

[0086] In extended scenarios, deviation calculation can introduce weighted averaging to smooth short-term fluctuations. For example, the average of five consecutive actual differential pressure values ​​can be compared with a threshold. If the average deviation exceeds the threshold, an identifier is generated and a timestamp is attached. This enhances the robustness of detection, reduces false positives caused by instantaneous water pressure changes, and effectively improves the reliability of filter anti-clogging early warning.

[0087] S23, the pressure anomaly identifier is transmitted to the mobile application module.

[0088] In one embodiment, the differential pressure transmitter sends the generated pressure anomaly identifier along with a timestamp directly to a mobile application module via a wireless communication interface such as Bluetooth. This module then processes the data to trigger an SMS alert. This transmission ensures continuity from anomaly generation to user notification, supporting the overall functionality of the tap water filter anti-clogging early warning system.

[0089] The above-mentioned method of reading the pressure anomaly identifier output by the differential pressure transmitter through the mobile application module includes: S31, the mobile application module establishes a communication connection with the differential pressure transmitter and obtains the pressure anomaly identifier from the differential pressure transmitter; S32, the pressure anomaly identifier is classified into levels to obtain anomaly level data; S33, a reminder message is generated based on the anomaly level data and sent to the user terminal through the communication interface.

[0090] S31, the mobile application module establishes a communication connection with the differential pressure transmitter and obtains the pressure abnormality identifier from the differential pressure transmitter.

[0091] In one embodiment, the mobile application module establishes a connection with the differential pressure transmitter via Bluetooth to ensure stable data transmission. After the connection is established, the module reads identification data from the transmitter.

[0092] S32, perform level classification processing on the pressure anomaly identifier to obtain anomaly level data.

[0093] In one embodiment, the specific process of classifying pressure anomaly indicators by level includes the following sub-steps.

[0094] S321, Extract the differential pressure value from the pressure anomaly identifier and compare it with a preset threshold range. The preset threshold range is based on normal water pressure; for example, normal differential pressure is 0-5 kPa, slight anomaly is 5-10 kPa, moderate is 10-20 kPa, and severe exceeds 20 kPa. These thresholds are obtained through experimental data to ensure accurate classification.

[0095] S322, assign an anomaly level based on the comparison results. For example, if the differential pressure value is 7 kPa, it is classified as a minor level, and corresponding level data is generated.

[0096] S323 stores the level data in a structured format, making it easier to generate reminders later.

[0097] For example, when a water filter is installed in a household water supply line, if impurities accumulate in the filter causing a rise in differential pressure, the categorization process can quickly identify the level of filtration issues, preventing minor problems from escalating into blockages. This categorization allows users to intervene early and improve filtration efficiency.

[0098] One possible implementation considers classification under different water pressure environments. For example, during peak water usage periods, the threshold can be dynamically adjusted to a normal differential pressure of 0-6 kPa and a slight differential pressure of 6-12 kPa to adapt to flow rate changes. This approach improves system adaptability, reduces false alarms, and allows users to clean the filters in a timely manner.

[0099] For example, in an apartment building's water supply system, if the differential pressure indicator shows 15 kPa, it is classified as moderate. The data indicates that there is a moderate accumulation of impurities in the filter screen, reminding users to check it and preventing the water flow from weakening and affecting daily life.

[0100] S33, generate reminder content based on the anomaly level data and send it to the user terminal through the communication interface.

[0101] In one embodiment, based on the anomaly level data, a reminder message containing a level description and suggested actions is generated. For example, for a minor level, the message "Filter is slightly clogged, please check" is generated and then sent to the user's mobile phone via an SMS interface.

[0102] For example, a minor alert can prompt users to clean up early and reduce the risk of water quality deterioration, while a severe alert generates emergency messages such as "Filter is severely clogged, clean immediately" to ensure users respond quickly and improve the overall reliability of the system.

[0103] The above-mentioned deviation calculation based on the actual differential pressure value and the preset normal pressure threshold includes: S221, obtaining the sequence data of the actual differential pressure value and calculating the average deviation value; S222, if the average deviation value is greater than the preset normal pressure threshold, determining it as a high anomaly level and updating the pressure anomaly identifier; S223, appending the high anomaly level to the pressure anomaly identifier and forwarding it to the mobile application module; S224, the mobile application module adjusts the sending frequency of the reminder information according to the high anomaly level.

[0104] The above-mentioned level classification processing of the pressure anomaly identifier includes: S321, analyzing the deviation value and timestamp information in the pressure anomaly identifier to determine the duration of the anomaly; S322, comparing the duration of the anomaly with a preset duration threshold to obtain the anomaly level data; S323, if the anomaly level data indicates a severity level, generating detailed reminder content including the location of the filter device; S324, sending the detailed reminder content to the user terminal through the communication interface and recording the sending log.

[0105] The above-mentioned method of sending a reminder message to the user terminal based on the stress anomaly identifier includes: S34, the mobile application module processes the stress anomaly identifier to generate a multi-channel reminder signal; S35, the multi-channel reminder signal is converted into SMS format and push format; S36, the SMS format reminder message is sent to the user terminal and the receipt confirmation is monitored; S37, if no confirmation is received, the push format reminder message is resent.

[0106] The above-described method of transmitting the inlet pressure data and the outlet pressure data to the differential pressure transmitter includes: S121, the sampling tube performs preliminary filtering on the inlet pressure data to obtain filtered inlet data; S122, the same preliminary filtering is performed on the outlet pressure data to obtain filtered outlet data; S123, the filtered inlet data and the filtered outlet data are synchronously input into the differential pressure transmitter; S124, the differential pressure transmitter calculates a differential pressure sequence based on the filtered inlet data and the filtered outlet data to improve measurement accuracy.

[0107] The specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present invention will not describe the various possible combinations separately. Furthermore, different embodiments of the present invention can also be arbitrarily combined, as long as they do not violate the spirit of the present invention, and should also be considered as part of the content disclosed in the present invention.

Claims

1. A method for preventing clogging and providing early warning in a fluid filtration device, characterized in that, include: Acquire pressure data at the front and rear ends of the filter device, wherein the pressure data is collected through sampling tubes installed at the front and rear ends of the filter device. The pressure data is input into a differential pressure transmitter, which measures the pressure difference between the front and rear ends and compares it with a preset normal pressure threshold to obtain a pressure anomaly indicator. The mobile application module reads the pressure anomaly indicator output by the differential pressure transmitter and sends a reminder message to the user terminal based on the pressure anomaly indicator.

2. The method as described in claim 1, characterized in that, The acquisition of pressure data at the front and rear ends of the filtration device includes: The sampling tube is made of corrosion-resistant material and is fixed at the inlet and outlet of the filter device. Inlet pressure data is collected from the inlet and outlet pressure data is collected from the outlet. The inlet pressure data and the outlet pressure data are transmitted to the differential pressure transmitter to support subsequent measurements.

3. The method as described in claim 1, characterized in that, The step of inputting the pressure data into the differential pressure transmitter includes: The differential pressure transmitter receives the pressure data and calculates the actual differential pressure value; The deviation between the actual differential pressure value and the preset normal pressure threshold is calculated. If the deviation exceeds the preset normal pressure threshold, a pressure anomaly identifier is generated and a timestamp is attached. The pressure anomaly indicator is transmitted to the mobile application module.

4. The method as described in claim 1, characterized in that, The step of reading the pressure anomaly indicator output by the differential pressure transmitter via the mobile application module includes: The mobile application module establishes a communication connection with the differential pressure transmitter and obtains the pressure anomaly identifier from the differential pressure transmitter; The pressure anomaly identifiers are classified into different levels to obtain anomaly level data; Based on the anomaly level data, a reminder message is generated and sent to the user terminal via a communication interface.

5. The method as described in claim 3, characterized in that, The step of calculating the deviation between the actual differential pressure value and the preset normal pressure threshold includes: Obtain the sequence data of the actual differential pressure values ​​and calculate the average deviation value; If the average deviation value is greater than the preset normal pressure threshold, it is determined to be a high abnormality level and the pressure abnormality identifier is updated. The high anomaly level is appended to the pressure anomaly identifier and forwarded to the mobile application module; The mobile application module adjusts the frequency of sending alert messages based on the high anomaly level.

6. The method as described in claim 4, characterized in that, The step of classifying the pressure anomaly identifier by level includes: Analyze the deviation value and timestamp information in the pressure anomaly identifier to determine the duration of the anomaly; The anomaly level data is obtained by comparing the duration of the anomaly with a preset duration threshold. If the anomaly level data indicates a severity level, then a detailed alert containing the location of the filtering device is generated; The detailed reminder content is sent to the user terminal through the communication interface, and the sending log is recorded.

7. The method as described in claim 1, characterized in that, Sending a reminder message to the user terminal based on the pressure anomaly identifier includes: The mobile application module processes the stress anomaly indicator to generate multi-channel alert signals; Convert the multi-channel alert signals into SMS and push notification formats; Send the reminder message in the SMS format to the user terminal and monitor the receipt confirmation; If no confirmation is received, the notification message in the specified push format will be sent again.

8. The method as described in claim 2, characterized in that, The step of transmitting the inlet pressure data and the outlet pressure data to the differential pressure transmitter includes: The sampling tube performs preliminary filtering on the inlet pressure data to obtain filtered inlet data. The same preliminary filtering process is performed on the outlet pressure data to obtain filtered outlet data; The filtered inlet data and the filtered outlet data are simultaneously input into the differential pressure transmitter; The differential pressure transmitter calculates a differential pressure sequence based on the filtered inlet data and the filtered outlet data to improve measurement accuracy.

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