A high-precision water quality monitoring and intelligent regulation water softener control system

Abstract

The present invention relates to a high-precision water quality monitoring and intelligent regulation water softener control system, belonging to the technical field of intelligent water softener regulation. An image acquisition module is used to capture images of the surface of a sensor probe and upload the captured image data to a control terminal. The control terminal uses a convolutional neural network to identify and mark the biofilm area based on the received image data, calculates the percentage of the biofilm area occupied by the probe surface, and judges the pollution level as light pollution, moderate pollution, or heavy pollution based on the percentage. Targeted treatment is performed based on the judged pollution level, and ultimately the biofilm on the surface of the sensor probe is separated from the sensor. This solves the problem in the prior art of lacking the ability to perceive the degree of biofilm coverage in real time and having limited effect on removing stubborn biofilms.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent water softener regulation, and in particular relates to a high-precision water quality monitoring and intelligent regulation water softener control system. Background Art

[0002] As a key device for water purification, the core sensor module of a water softener faces severe challenges in complex environments: chemical pollutants and microorganisms easily form biofilms and chemical deposits on the surface of the sensor probe, seriously affecting measurement accuracy.

[0003] Current mainstream cleaning solutions include sensor surface coating, physical flushing, and chemical inhibition methods, but these cleaning solutions have limitations: First, they rely on a single parameter to trigger the cleaning mechanism and lack the ability to perceive the extent of biofilm coverage in real time. Second, physical flushing carries the risk of damaging the sensor surface coating and has limited effectiveness in removing stubborn biofilms. Third, existing methods fail to form a closed-loop control system, making it difficult to achieve precise prevention and dynamic response. To address these issues, there is an urgent need to build a water softener control system with high-precision water quality monitoring and intelligent regulation through technological innovation to achieve real-time diagnosis of sensor contamination status and targeted cleaning. Summary of the Invention

[0004] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a high-precision water quality monitoring and intelligent adjustment softener control system, which solves the problems in the prior art of lacking the ability to perceive the degree of biofilm coverage in real time and having limited effect on removing stubborn biofilms.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A high-precision water quality monitoring and intelligent regulation water softener control system includes a control terminal, a central processing unit, a sensor module, and an image acquisition module for capturing images of the sensor probe surface. The central processing unit is used to coordinate data processing and instruction issuance by the sensor module, the image acquisition module, the current module, and the vibration module. The image acquisition module captures images of the sensor probe surface and uploads the captured image data to the control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network based on the received image data, calculates the percentage of the biofilm area in the probe surface, and judges the pollution level as light pollution, moderate pollution, or heavy pollution based on the percentage. Processing is performed according to the judged pollution level to separate the biofilm on the sensor probe surface from the sensor.

[0007] As a further solution of the present invention, the sensor module includes a conductivity sensor, a temperature sensor and an ion-selective electrode, and the conductivity sensor, temperature sensor and ion-selective electrode are used to collect water hardness, pH value and impurity concentration in real time.

[0008] As a further solution of the present invention, it also includes a water flow module for triggering low-pressure water flushing, a current module and a vibration module for starting reverse current, and the water flow module, current module and vibration module are respectively communicated with the control terminal.

[0009] As a further solution of the present invention, the steps for processing according to the judged pollution level are: if the percentage is less than 5%, it is judged as light pollution, only data is recorded, and no cleaning is required; if the percentage is greater than or equal to 5% and less than <15%, it is judged as light pollution, and the control terminal controls the water flow module to trigger low-pressure water flow to flush the surface of the sensor probe; if the percentage is greater than or equal to 15%, it is judged as heavy pollution, and the control terminal controls the current module to start the reverse current to dissolve the biofilm on the surface of the sensor probe and vibrate through the vibration module.

[0010] As a further solution of the present invention, the steps of the current module initiating a reverse current to dissolve the biofilm on the surface of the sensor probe are:

[0011] S1: After applying reverse current, the recovery rate is monitored in real time by the conductivity sensor. If the recovery rate is less than ±2% of the initial value, one cycle is added;

[0012] S2: After dissolution is completed, the vibration module vibrates the probe surface with an amplitude of 5-10 μm until the image detection is displayed.

[0013] As a further solution of the present invention, the control terminal is preset with complete parameters of the probe surface. The image acquisition module acquires images of the sensor probe surface and uploads the acquired image data to the control terminal. The control terminal compares the acquired image data with the complete parameters of the probe surface. If there is damage on the probe surface, the vibration module prohibits starting vibration. If there is no damage on the probe surface, the vibration module starts vibration.

[0014] As a further solution of the present invention, the vibration module adopts gradient amplitude control from low to high.

[0015] As a further solution of the present invention, an annular array of piezoelectric sheets is provided on the surface of the probe, and the annular array of piezoelectric sheets uniformly covers the surface of the probe.

[0016] As a further solution of the present invention, the vibration module and the water flow module are started and stopped synchronously.

[0017] As a further solution of the present invention, the surface of the sensor probe is coated with a graphene-silver nanocomposite coating for inhibiting biofilm adhesion.

[0018] The beneficial effects of the present invention are:

[0019] The present invention uses an image acquisition module to capture images of the sensor probe surface and uploads the collected image data to a control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network based on the received image data, calculates its percentage of the probe surface area, and judges the pollution level as light pollution, moderate pollution, or heavy pollution based on the percentage. Targeted treatment is performed based on the judged pollution level, and ultimately the biofilm on the sensor probe surface is separated from the sensor, solving the problem in the prior art of lacking the ability to perceive the degree of biofilm coverage in real time and having limited effect on removing stubborn biofilms. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0021] Figure 1 This is a diagram of the intelligent adjustment water softener control system of the present invention. DETAILED DESCRIPTION

[0022] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0023] See also Figure 1The present embodiment provides a high-precision water quality monitoring and intelligent regulation water softener control system, including a control terminal, a central processing unit, a sensor module and an image acquisition module for acquiring images of the sensor probe surface. The central processing unit is used to coordinate data processing and instruction issuance of the sensor module, the image acquisition module, the current module and the vibration module. The image acquisition module acquires images of the sensor probe surface and uploads the acquired image data to the control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network based on the received image data, calculates the percentage of the biofilm area occupied by the biofilm area, and determines the pollution level as light pollution, moderate pollution or heavy pollution based on the percentage. The biofilm on the sensor probe surface is processed according to the determined pollution level, so that the biofilm on the sensor probe surface is separated from the sensor probe. This solution solves the problem of insufficient real-time perception of biofilm coverage in existing technologies by integrating an image acquisition module with convolutional neural network technology. The image acquisition module regularly captures images of the sensor probe surface and uploads the data to the control terminal. The central processing unit uses a convolutional neural network to analyze the image, accurately identify and mark the biofilm area, and calculate its percentage of the probe surface area in real time. This method can accurately determine the pollution level and intelligently adjust the working state of the water softener according to the pollution level, effectively removing stubborn biofilms. The image acquisition module is equipped with a high-resolution camera and a ring light source to capture images of the sensor probe surface. The camera of the image acquisition module is integrated with a polarization filter to eliminate water mist and reflection interference, thereby improving the accuracy of biofilm recognition.

[0024] One thing that needs to be explained is that the image acquisition module can monitor the growth of biofilms in real time and provide timely feedback to the control terminal, so that the system can evaluate and process the degree of pollution in the first place. Convolutional neural network technology has powerful image recognition capabilities and can accurately identify biofilm areas, improving monitoring accuracy. According to the pollution level, the system can automatically adjust the treatment strategy to achieve accurate removal of biofilms and reduce energy consumption during the removal process. Through real-time monitoring and intelligent adjustment, the system can prevent excessive growth of biofilms and reduce the occurrence of pollution accidents. After removing the biofilm, the sensor probe can accurately detect water quality, ensure the efficient operation of water treatment equipment, and improve water quality.

[0025] With the rapid development of industrialization, chemical areas and toxic chemical leakage incidents have frequently occurred, leading to increased water pollution. In this context, water softeners, as key equipment for water purification, face severe challenges in complex environments with their core sensor modules: chemical pollutants and microorganisms easily form biofilms and chemical deposits on the surface of sensor probes, seriously affecting measurement accuracy. The mainstream cleaning treatment solutions currently on the market include sensor surface coatings, physical flushing, and chemical inhibition methods, but these cleaning treatment solutions have limitations: first, they rely on a single parameter to trigger the cleaning mechanism and lack the ability to perceive the degree of biofilm coverage in real time; second, physical flushing has the risk of damaging the sensor surface coating and has limited effect on removing stubborn biofilms; third, existing methods have failed to form a closed-loop control system, making it difficult to achieve precise prevention and dynamic response.

[0026] In order to solve the above problems, in this embodiment, the image acquisition module is used to capture images of the sensor probe surface and upload the collected image data to the control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network based on the received image data, calculates its percentage of the probe surface area, and judges the pollution level as light pollution, moderate pollution or heavy pollution based on the percentage. Targeted treatment is performed according to the judged pollution level, and finally the biofilm on the surface of the sensor probe is separated from the sensor, which solves the problem of lack of real-time perception of the degree of biofilm coverage in the existing technology and limited effect on removing stubborn biofilms.

[0027] Since current water softeners rely on a single parameter to trigger the cleaning mechanism, this may lead to misjudgment of water quality. In order to provide a comprehensive, accurate, and intelligent water quality monitoring and regulation solution, in one embodiment, the sensor module includes a conductivity sensor, a temperature sensor, and an ion-selective electrode. The conductivity sensor, the temperature sensor, and the ion-selective electrode are used to respectively collect water hardness, pH value, and impurity concentration in real time. Through the combination of the conductivity sensor, the temperature sensor, and the ion-selective electrode, multiple key parameters of water quality, including hardness, pH value, and impurity concentration, can be comprehensively collected, thereby more accurately judging the water quality condition. The sensor monitors water quality changes in real time, allowing the system to respond to water quality changes in a timely manner to ensure that the water quality always meets the set standards. The use of these high-precision sensors can provide more accurate data, which helps to improve the accuracy and efficiency of the regulation system. The system can intelligently adjust the operation of the water softener based on the data collected by the sensors to optimize the water quality treatment process.

[0028] In order to avoid a single cleaning method being ineffective against stubborn biofilms and easily damaging sensors, in one embodiment, it also includes a water flow module for triggering low-pressure water flushing, a current module for starting reverse current, and a vibration module. The water flow module, current module, and vibration module are respectively communicated with the control terminal, and the water flow module (low-pressure flushing), current module (reverse electrolysis), and vibration module (mechanical stripping) are introduced. Through the coordinated work of the control terminal, differentiated cleaning methods are adopted for different pollution levels, taking into account both efficiency and safety. At the same time, the modular design enhances the flexibility and adaptability of the system.

[0029] During actual cleaning, due to the mismatch between cleaning intensity and pollution degree, resources are wasted or cleaning is incomplete. In order to avoid this problem, in one embodiment, the steps for processing according to the judged pollution level are as follows: if the percentage is less than 5%, it is judged as light pollution, and only data is recorded without cleaning; if the percentage is greater than or equal to 5% and less than <15%, it is judged as light pollution, and the control terminal controls the water flow module to trigger low-pressure water flow to flush the surface of the sensor probe; if the percentage is greater than or equal to 15%, it is judged as heavy pollution, and the control terminal controls the current module to start reverse current to dissolve the biofilm on the surface of the sensor probe and vibrate through the vibration module, and divides the pollution level according to the biofilm coverage percentage (light <5%, moderate 5%~15%, heavy ≥15%), and adopts recording, low-pressure flushing, reverse current and vibration respectively, which can achieve accurate matching of cleaning intensity, reduce energy consumption and sensor wear, and avoid frequent cleaning through threshold setting, thereby extending equipment life.

[0030] It should be further explained that the above-described embodiment, through pollution level classification and differentiated cleaning strategies, can address the resource waste and incomplete cleaning problems caused by the "one-size-fits-all" cleaning process of traditional water softeners. This is because traditional methods generally rely on a single parameter to trigger cleaning and cannot distinguish the degree of pollution, resulting in excessive cleaning for light pollution and insufficient cleaning for heavy pollution. In the case of light pollution, only data is recorded and cleaning is not initiated, avoiding meaningless water flow or current consumption. For moderate pollution, low-pressure water flushing is used to gently remove loose biofilms with extremely low water and energy consumption. For heavy pollution, reverse current dissolution combined with high-frequency vibration can completely remove stubborn biofilms. In addition, high-energy consumption modules are activated only when necessary, reducing overall energy consumption, reducing the frequency of use of the water flow module and current module, and extending the equipment maintenance cycle. Cleaning operations are prohibited in light pollution to avoid mechanical wear caused by frequent flushing or vibration. In heavy pollution, the vibration module is activated only after confirming that the probe surface is intact (through image comparison). Limiting the cleaning frequency based on pollution level extends the life of the probe coating and avoids conductivity or ion concentration detection errors caused by surface damage.

[0031] Furthermore, since the content of chemical pollutants in water varies, a single reverse current may not be able to completely dissolve stubborn biofilms in water with a high chemical content. Therefore, in one embodiment, the current module initiates a reverse current to dissolve the biofilm on the surface of the sensor probe in the following steps:

[0032] S1: After applying reverse current, the recovery rate is monitored in real time through the conductivity sensor. If the recovery rate is less than ±2% of the initial value, one cycle is added, and the number of cycles can be increased up to 5 times. The circulation mechanism ensures that the biofilm is completely dissolved and the cleaning reliability is improved. However, real-time monitoring should also avoid excessive operation to protect sensor performance.

[0033] S2: After dissolution is completed, the vibration module vibrates the probe surface with an amplitude of 5-10 μm until image detection shows that in the chemical area, the system automatically switches to "high pollution mode", increases the reverse current density to 25 mA / cm², and extends the vibration time to 15 seconds / time to deal with stubborn deposits.

[0034] In addition, during actual vibration cleaning, vibration cleaning may cause damage to the probe surface. In order to avoid this problem, in one embodiment, the control terminal is preset with complete parameters of the probe surface. The image acquisition module captures images of the sensor probe surface and uploads the captured image data to the control terminal. The control terminal compares the captured image data with the complete parameters of the probe surface. If there is damage on the probe surface, the vibration module prohibits starting vibration. If there is no damage on the probe surface, the vibration module starts vibration. The active protection mechanism is used to avoid secondary damage, ensure the long-term stability of the probe, and combine image technology to achieve non-destructive testing and improve system safety. In addition, high-amplitude vibration may instantly impact the probe surface. Therefore, the vibration module adopts gradient amplitude control from low to high to dynamically adjust the cleaning force. The gradient amplitude reduces mechanical stress, avoids the probe surface coating from falling off, gradually increases the cleaning force, and adapts to biofilms with different attachment strengths.

[0035] Furthermore, when cleaning the sensor surface, the current module is used to start a combination of reverse current dissolution and vibration. However, local vibration will lead to uneven cleaning. Therefore, in one embodiment, a ring array piezoelectric piece is provided on the probe surface, and the ring array piezoelectric piece evenly covers the probe surface. The uniform vibration distribution improves the efficiency of biofilm removal, reduces cleaning dead corners, and ensures comprehensive cleaning of the probe surface. In addition, since the water flushing and vibration are not synchronized, the cleaning effect may be affected. Therefore, it is necessary to ensure that the vibration module and the water flow module are started and stopped synchronously, and the loose dirt is flushed away by water flow and then the residue is removed by vibration, thereby improving the collaborative efficiency and avoiding the waste of resources caused by using a single module alone.

[0036] Furthermore, biofilm is a complex community structure formed by microorganisms (such as bacteria, fungi, and algae) on solid surfaces. Its attachment and stubbornness are due to multiple mechanisms. Therefore, biofilm is easy to attach and difficult to inhibit. In order to solve this problem, in one embodiment, the surface of the sensor probe is coated with a graphene-silver nanocomposite coating for inhibiting the attachment of biofilm, inhibiting the initial attachment of biofilm, reducing the cleaning frequency, enhancing the corrosion resistance of the probe, and extending the service life. The graphene-silver nanocomposite coating inhibits the attachment of biofilm and enhances the resistance to chemical corrosion. The probe surface adopts a photocatalytic TiO2 coating, which decomposes organic pollutants under ultraviolet irradiation and reduces biofilm formation. The coating can be powered on for self-repair after damage. The graphene-silver nanocomposite coating has a dual antibacterial mechanism, in which the silver nanoparticles in the dual antibacterial mechanism continuously release Ag. + Ions destroy microbial cell membranes and interfere with DNA replication, inhibiting initial attachment. In addition, graphene's high chemical stability and hydrophobicity reduce microbial adhesion. At the same time, it acts as a carrier to evenly disperse silver nanoparticles, prolonging the sustained-release period. Combined with the photocatalytic decomposition of the photocatalytic TiO2 coating, ultraviolet rays stimulate TiO2 to produce active oxygen, oxidatively decompose organic matter in the barrier, destroy the biofilm structure, and power on to trigger the electrochemical reduction reaction of TiO2, repairing microcracks or scratches and restoring the integrity and functionality of the coating.

[0037] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make some changes or modifications to equivalent embodiments using the technical contents disclosed above. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A high-precision water quality monitoring and intelligent adjustment water softener control system, characterized in that: The system comprises a control terminal, a central processing unit, a sensor module and an image acquisition module for acquiring images of the surface of a sensor probe. The central processing unit is used to coordinate data processing and instruction issuance of the sensor module, the image acquisition module, the current module and the vibration module. The image acquisition module acquires images of the surface of the sensor probe and uploads the acquired image data to the control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network based on the received image data, calculates the percentage of the biofilm area in the probe surface area, and judges the pollution level as light pollution, moderate pollution or heavy pollution based on the percentage. The system performs processing based on the judged pollution level to separate the biofilm on the surface of the sensor probe from the sensor. The sensor module comprises a conductivity sensor, a temperature sensor and an ion selective electrode. The conductivity sensor, the temperature sensor and the ion selective electrode are respectively used to acquire water hardness, pH value and impurity concentration in real time. The surface of the sensor probe is coated with a graphene-silver nanocomposite coating for inhibiting the attachment of biofilm. The control terminal is preset with complete parameters of the probe surface. The image acquisition module acquires images of the sensor probe surface and uploads the acquired image data to the control terminal. The control terminal compares the acquired image data with the complete parameters of the probe surface. If there is damage on the probe surface, the vibration module prohibits starting vibration. If there is no damage on the probe surface, the vibration module starts vibration. The vibration module adopts gradient amplitude control from low to high. An annular array of piezoelectric sheets is set on the probe surface, and the annular array of piezoelectric sheets evenly covers the probe surface. The sensor also includes a current module and a vibration module for starting a reverse current. The current module and the vibration module are respectively connected to a control terminal for communication. The control terminal controls the current module to start a reverse current to dissolve the biofilm on the surface of the sensor probe and vibrates the vibration module. The steps of starting the reverse current to dissolve the biofilm on the surface of the sensor probe are as follows: S1: After applying reverse current, the recovery rate is monitored in real time by the conductivity sensor. If the recovery rate is less than ±2% of the initial value, one cycle is added; S2: After the dissolution is completed, the vibration module vibrates the probe surface with an amplitude of 5-10 μm until the image detection is displayed.

2. A high-precision water quality monitoring and intelligent water softener control system according to claim 1, characterized in that: It also includes a water flow module for triggering low-pressure water flushing, and the water flow module is communicatively connected to the control terminal.

3. A high-precision water quality monitoring and intelligent adjustment water softener control system according to claim 2, characterized in that: The steps for processing according to the judged pollution level are as follows: if the percentage is less than 5%, it is judged as light pollution, only data is recorded, and no cleaning is required; if the percentage is greater than or equal to 5% and less than 15%, it is judged as moderate pollution, and the control terminal controls the water flow module to trigger low-pressure water flow to flush the surface of the sensor probe; if the percentage is greater than or equal to 15%, it is judged as heavy pollution.

4. A high-precision water quality monitoring and intelligent water softener control system according to claim 3, characterized in that: The vibration module and the water flow module are started and stopped synchronously.

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