High-precision water quality monitoring and intelligent adjusting water softener control system

Abstract

The invention relates to a high-precision water quality monitoring and intelligent adjustment water softener control system, and belongs to the technical field of intelligent water softener adjustment. An image acquisition module is used for performing image acquisition on the surface of a sensor probe and uploading acquired image data to a control terminal; the control terminal identifies and marks a biological membrane area through a convolutional neural network according to the received image data, calculates the percentage of the biological membrane area in the surface area of the probe, judges whether the pollution level is light pollution or moderate pollution or heavy pollution according to the percentage, and performs targeted treatment according to the judged pollution level; finally, the biological membrane on the surface of the sensor probe is separated from the sensor, and the problems that in the prior art, the real-time sensing capability on the coverage degree of the biological membrane is lacked, and meanwhile the removal effect on the stubborn biological membrane is limited are solved.

Description

Technical Field

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

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

[0003] The current mainstream cleaning treatment solutions include sensor surface coating, physical flushing, and chemical inhibition methods. However, this cleaning treatment solution has limitations: firstly, it relies on a single parameter to trigger the cleaning mechanism and lacks the ability to perceive the degree of biofilm coverage in real time; secondly, physical flushing has the risk of damaging the sensor surface coating and has limited effect on removing stubborn biofilms; thirdly, the existing methods fail to form a closed-loop regulation system and it is difficult to achieve precise prevention and dynamic response. To address the above problems, it is urgent to construct a high-precision water quality monitoring and intelligent regulation water softener control system through technological innovation to achieve real-time diagnosis and targeted cleaning of the pollution state of the sensor. Summary of the Invention

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

[0005] The purpose of the invention can be realized by the following technical solutions: A high-precision water quality monitoring and intelligent regulation water softener control system includes a control terminal, a central processor, a sensor module, and an image acquisition module for collecting images of the surface of the sensor probe. The central processor is used to coordinate the data processing and instruction issuance of the sensor module, the image acquisition module, the current module, and the vibration module. The image acquisition module collects images of the surface of the sensor probe and uploads the collected image data to the control terminal. The control terminal identifies and marks the biofilm area through a convolutional neural network according to the received image data, calculates the percentage of its area on the probe surface area, and determines the pollution level as mild pollution or moderate pollution or severe pollution according to the percentage, and performs processing according to the determined pollution level to separate the biofilm on the surface of the sensor probe from the sensor.

[0006] As a further solution of the invention, the sensor module includes a conductivity sensor, a temperature sensor, and an ion-selective electrode, and the conductivity sensor, the temperature sensor, and the ion-selective electrode are respectively used to collect water quality hardness, pH value, and impurity concentration in real time.

[0007] As a further solution of the present invention, it further includes a water flow module for triggering low-pressure water flow flushing, a current module for starting a reverse current, and a vibration module. The water flow module, the current module, and the vibration module are respectively communicatively connected to the control terminal.

[0008] As a further solution of the present invention, the steps for processing according to the judged pollution level are as follows: If the percentage is less than 5%, it is judged as mild pollution, and only the data is recorded without cleaning; if the percentage is greater than or equal to 5% and less than <15%, it is judged as mild 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 severe pollution, and 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 through the vibration module.

[0009] As a further solution of the present invention, the steps for the current module to start a reverse current to dissolve the biofilm on the surface of the sensor probe are as follows: S1: After applying the reverse current, the recovery rate is monitored in real time through a conductivity sensor. If the recovery rate does not reach within ±2% of the initial value, one more cycle is added; S2: After the dissolution is completed, the vibration module vibrates the surface of the probe with an amplitude of 5 - 10 μm until the image detection shows.

[0010] As a further solution of the present invention, the control terminal presets the complete parameter of the probe surface. The image acquisition module acquires an image of the surface of the sensor probe and uploads the acquired image data to the control terminal. The control terminal compares the acquired image data with the complete parameter of the probe surface. If there is damage on the probe surface, the vibration module is prohibited from starting vibration; if there is no damage on the probe surface, the vibration module starts vibration.

[0011] As a further solution of the present invention, the vibration module adopts a gradient amplitude control from low to high.

[0012] As a further solution of the present invention, a ring array piezoelectric sheet is provided on the surface of the probe, and the ring array piezoelectric sheet uniformly covers the surface of the probe.

[0013] As a further solution of the present invention, the vibration module starts and stops synchronously with the water flow module.

[0014] 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 attachment.

[0015] The beneficial effects of the present invention are as follows: In the present invention, an image acquisition module acquires images of the surface of a sensor probe and uploads the acquired 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 the percentage of the biofilm area occupying the probe surface area, and determines the pollution level as mild pollution, moderate pollution, or severe pollution according to the percentage. Targeted treatment is carried out according to the determined pollution level, and finally, the biofilm on the surface of the sensor probe is separated from the sensor, solving the problems in the prior art of lacking the real-time perception ability of the biofilm coverage degree and having limited removal effect on stubborn biofilms. Brief Description of the Drawings

[0016] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 It is a control system diagram of the intelligent adjustable water softener of the present invention. Specific Embodiments

[0018] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will describe in detail the specific embodiments, structures, features, and effects of the present invention with reference to the accompanying drawings and preferred embodiments.

[0019] Please refer to Figure 1, this embodiment provides a high-precision water quality monitoring and intelligent adjustment water softener control system, including a control terminal, a central processor, a sensor module, and an image acquisition module for collecting images of the surface of the sensor probe. The central processor is used to coordinate the data processing and instruction issuance of the sensor module, the image acquisition module, the current module, and the vibration module. The image acquisition module collects images of the surface of the sensor probe and uploads 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 the percentage of its area on the probe surface area, and determines the pollution level as mild pollution or moderate pollution or severe pollution according to the percentage, and processes according to the determined pollution level, so that the biofilm on the surface of the sensor probe is separated from the sensor. This solution integrates the image acquisition module and convolutional neural network technology to solve the problem of insufficient real-time perception ability of the biofilm coverage degree in the prior art. The image acquisition module regularly collects images of the surface of the sensor probe and uploads the data to the control terminal. The central processor uses the convolutional neural network to analyze the images, accurately identifies and marks the biofilm area, and calculates the percentage of its area on 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 degree, effectively remove stubborn biofilms. The image acquisition module is configured with a high-resolution camera and a ring light source to collect images of the surface of the sensor probe; the camera of the image acquisition module is integrated with a polarization filter to eliminate water mist and reflection interference and improve the biofilm recognition accuracy.

[0020] It should be noted that the image acquisition module can monitor the growth of the biofilm in real time and feedback it to the control terminal in time, so that the system can evaluate and process the pollution degree in the first time. The convolutional neural network technology has strong image recognition ability, can accurately identify the biofilm area, and improve the monitoring accuracy. According to the pollution level, the system can automatically adjust the treatment strategy to achieve precise removal of the biofilm and reduce the energy consumption during the removal process. Through real-time monitoring and intelligent adjustment, the system can prevent the overgrowth of the biofilm and reduce the occurrence of pollution accidents. The sensor probe after removing the biofilm can accurately detect the water quality, ensure the efficient operation of the water treatment equipment, and improve the water quality.

[0021] With the rapid development of industrialization, the frequent occurrence of chemical leakage incidents in chemical industrial areas and the resulting deterioration of water source pollution have led to an increase in water pollution. Against this background, as a key device for water quality purification, the core sensor module of water softeners faces severe challenges in complex environments: chemical pollutants and microorganisms are prone to form biofilms and chemical deposits on the surface of sensor probes, seriously affecting the measurement accuracy. Currently, the mainstream cleaning solutions on the market include sensor surface coating, physical flushing, and chemical inhibition methods. However, these cleaning 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 poses a risk of damaging the sensor surface coating and has limited effect on removing stubborn biofilms; third, the existing methods fail to form a closed-loop control system and it is difficult to achieve precise prevention and dynamic response.

[0022] To solve the above problems, in this embodiment, 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 its area on the probe surface area, and determines the pollution level as mild pollution, moderate pollution, or severe pollution according to the percentage. Then, targeted treatment is carried out according to the determined pollution level, and finally, the biofilm on the surface of the sensor probe is separated from the sensor, solving 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.

[0023] Since the current water softeners rely on a single parameter to trigger the cleaning mechanism, it 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, temperature sensor, and ion-selective electrode are respectively used to collect the water quality hardness, pH value, and impurity concentration in real time. Through the combination of the conductivity sensor, temperature sensor, and ion-selective electrode, multiple key parameters of water quality, including hardness, pH value, and impurity concentration, can be comprehensively collected, so as to more accurately judge the water quality condition. The sensor monitors the water quality change in real time, enabling the system to respond to the water quality change in a timely manner and ensuring that the water quality always meets the set standards. By using these high-precision sensors, more accurate data can be provided, which helps to improve the accuracy and efficiency of the regulation system. The system can intelligently adjust the operation of the water softener according to the data collected by the sensors and optimize the water quality treatment process. To avoid the ineffectiveness of a single cleaning method for stubborn biofilms and the easy damage to sensors, in one embodiment, it further includes a water flow module for triggering low-pressure water flow flushing, a current module for starting a reverse current, and a vibration module. The water flow module, the current module, and the vibration module are respectively communicatively connected to the control terminal. By introducing the water flow module (low-pressure flushing), the current module (reverse electrolysis), and the vibration module (mechanical peeling), and through the coordinated work of the control terminal, different cleaning means 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.

[0024] During actual cleaning, due to the mismatch between the cleaning intensity and the pollution degree, resource waste or incomplete cleaning may occur. 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 determined as mild pollution, and only data is recorded without the need for cleaning; if the percentage is greater than or equal to 5% and less than <15%, it is determined as mild 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 determined as severe pollution, and the control terminal controls the current module to start a reverse current to dissolve the biofilm on the surface of the sensor probe and vibrate through the vibration module. By dividing the pollution level according to the biofilm coverage percentage (mild <5%, moderate 5% - 15%, severe ≥15%), recording, low-pressure flushing, and the combination of reverse current and vibration can be respectively adopted, which can achieve an accurate match of the cleaning intensity, reduce energy consumption and sensor wear, and avoid frequent cleaning through threshold setting, thus prolonging the equipment life.

[0025] It should be further noted that through the pollution level division and differential cleaning strategy in the above embodiment, the problems of resource waste or incomplete cleaning caused by the "one-size-fits-all" approach in the cleaning process of traditional water softeners can be solved. Because traditional methods usually rely on a single parameter to trigger cleaning and cannot distinguish the pollution degree, resulting in over-cleaning in the case of mild pollution and insufficient cleaning in the case of severe pollution. When it comes to mild pollution, only data is recorded and cleaning is not started, avoiding meaningless water flow or current consumption. For moderate pollution, low-pressure water flow flushing is adopted to gently remove the loose biofilm with extremely low water consumption and energy consumption. For severe pollution, reverse current dissolution is combined with high-frequency vibration to completely remove the stubborn biofilm. In addition, the high-energy-consuming modules are only started when necessary, reducing the overall energy consumption, decreasing the usage frequency of the water flow module and the current module, and prolonging the equipment maintenance cycle. Cleaning operations are prohibited in the case of mild pollution to avoid mechanical wear caused by frequent flushing or vibration. In the case of severe pollution, the vibration module is only started after confirming that there is no damage to the probe surface (through image comparison). By restricting the cleaning frequency according to the pollution level, the life of the probe coating is prolonged, and the detection error of conductivity or ion concentration caused by surface damage is also avoided.

[0026] In addition, since the content of chemical pollutants in water varies, for water with a high chemical content, a single reverse current may not be able to completely dissolve the stubborn biofilm. In this regard, in one embodiment, the steps of the current module starting the reverse current to dissolve the biofilm on the surface of the sensor probe are: 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 the sensor performance.

[0027] S2: After dissolution is completed, the vibration module vibrates the probe surface with an amplitude of 5-10 μm until the 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.

[0028] 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 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. An 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 a gradient amplitude control from low to high to dynamically adjust the cleaning intensity. The gradient amplitude reduces mechanical stress, avoids the falling off of the probe surface coating, and gradually increases the cleaning intensity to adapt to biofilms with different attachment strengths.

[0029] Furthermore, when the sensor surface is cleaned, 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-shaped array piezoelectric sheet is provided on the probe surface, and the ring-shaped array piezoelectric sheet evenly covers the probe surface. The uniform vibration distribution improves the biofilm removal efficiency, reduces cleaning dead corners, and ensures comprehensive cleaning of the probe surface. In addition, since the cleaning effect may be affected by the lack of synchronization between water flushing and vibration, 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.

[0030] Furthermore, a biofilm is a complex community structure formed by microorganisms (such as bacteria, fungi, and algae) on a solid surface. Its attachment and persistence stem from multiple mechanisms. Therefore, biofilms are prone to attach and difficult to inhibit. To solve this problem, in one embodiment, the surface of the sensor probe is coated with a graphene-silver nanocomposite coating for inhibiting biofilm attachment, which inhibits the initial attachment of biofilms, reduces the cleaning frequency, enhances the corrosion resistance of the probe, and extends its service life. The graphene-silver nanocomposite coating inhibits biofilm attachment and enhances chemical corrosion resistance. The surface of the probe uses a photocatalytic TiO 2 coating, which decomposes organic pollutants under ultraviolet light irradiation to reduce biofilm formation. After the coating is damaged, it can be self-repaired by electrification. There are dual antibacterial mechanisms in the graphene-silver nanocomposite coating. Among them, silver nanoparticles in the dual antibacterial mechanism continuously release Ag + ions, which damage the microbial cell membrane and interfere with DNA replication to inhibit the initial attachment. In addition, the high chemical stability and hydrophobicity of graphene reduce microbial adhesion, and at the same time, as a carrier, it evenly disperses silver nanoparticles to extend the slow-release period. Together with the photocatalytic decomposition of the TiO 2 coating, ultraviolet light excites TiO 2 to generate reactive oxygen species, which oxidize and decompose the organic matter in the barrier and destroy the biofilm structure. Electrification triggers the electrochemical reduction reaction of TiO 2 to repair microcracks or scratches and restore the integrity and functionality of the coating.

[0031] The above are only the preferred embodiments of the present invention and do not impose any form of limitation on the present invention. Although the present invention has been disclosed as above with the preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to the above-disclosed technical content to obtain equivalent embodiments with equivalent changes. However, as long as it does not depart from the technical content of the present invention, any brief modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention still fall 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 invention comprises a control terminal, a central processing unit, a sensor module and an image acquisition module for acquiring images of the surface of the 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 according to 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 according to the percentage. The biofilm on the surface of the sensor probe is separated from the sensor according to the judged pollution level.

2. According to claim 1, a high-precision water quality monitoring and intelligent adjustment water softener control system is characterized in that: 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 respectively used to collect water hardness, pH value and impurity concentration in real time.

3. A high-precision water quality monitoring and intelligent water softener control system according to claim 2, characterized in that: 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 connected to the control terminal for communication.

4. A high-precision water quality monitoring and intelligent water softener control system according to claim 3, characterized in that: 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 the 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.

5. A high-precision water quality monitoring and intelligent water softener control system according to claim 4, characterized in that: The steps of the current module starting the reverse current to dissolve the biofilm on the surface of the sensor probe are: 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.

6. A high-precision water quality monitoring and intelligent water softener control system according to claim 5, characterized in that: 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.

7. A high-precision water quality monitoring and intelligent water softener control system according to claim 6, characterized in that: The vibration module adopts a gradient amplitude control from low to high.

8. The high-precision water quality monitoring and intelligent water softener control system according to claim 6 is characterized in that: An annular array of piezoelectric sheets is arranged on the surface of the probe, and the annular array of piezoelectric sheets uniformly covers the surface of the probe.

9. The high-precision water quality monitoring and intelligent water softener control system according to claim 6 is characterized in that: The vibration module and the water flow module are started and stopped synchronously.

10. The high-precision water quality monitoring and intelligent water softener control system according to claim 1, characterized in that: The surface of the sensor probe is coated with a graphene-silver nanocomposite coating for inhibiting the attachment of biofilms.

Images