Method, system, equipment and medium for monitoring and regulating water quality of cooling tower

Abstract

The invention relates to the technical field of water quality monitoring of air conditioner refrigerating systems, and provides a cooling tower water quality monitoring and regulation system, system, equipment and medium. In the scheme, real-time multi-dimensional water quality monitoring parameters of water stored in a cooling tower are obtained; and calculating to obtain a real-time monitoring result of the water in the cooling tower and a water quality regulation and control scheme of the water in the cooling tower on the basis of the multi-dimensional water quality monitoring parameters by utilizing a water quality monitoring device constructed on the basis of a deep learning method. According to the deep learning method, automatic real-time monitoring of the water in the cooling tower and water quality regulation and control of the water in the cooling tower can be achieved, manual intervention is not needed, the water quality of the cooling tower can be monitored in real time, water quality regulation and control of the cooling tower in an air conditioner refrigeration system can be responded in time, and agent waste is avoided.

Description

Technical Field

[0001] This application relates to the field of water quality monitoring technology for air conditioning and refrigeration systems, and in particular to a cooling tower water quality monitoring and control system, equipment, and medium. Background Technology

[0002] For many large-scale integrated commercial office buildings, the air conditioning and refrigeration systems consume a large amount of water resources every year. Among them, the cooling water in the cooling tower is wasted the most. This is because after the cooling water has been used for a period of time, the impurities, suspended solids, microorganisms, water hardness and other factors in the water exceed the standards, so the water in the cooling tower needs to be replaced, which wastes a lot of water resources. Therefore, in order to reduce the serious waste of water resources in the air conditioning refrigeration system, artificial cooling towers are currently used to treat and monitor the water stored in the cooling towers. The water quality of the water stored in the cooling towers is currently mainly treated and monitored in the following ways: (1) Chemical agents are continuously added to the cooling tower at fixed time intervals by manual means. This method results in the addition of agents even when the water in the cooling tower has not deteriorated, which leads to waste of agents (the measured waste rate is as high as 35%); (2) Water samples are taken from the cooling tower regularly to determine whether the water has deteriorated. However, the frequency of manual sampling and monitoring is low (usually 6 hours / time), and it is impossible to capture water quality changes in real time; (3) The current PLC control system (the PLC control system controls the operation of each device in the air conditioning refrigeration system) judges whether the water in the cooling tower has deteriorated based on the single parameter of pH value of the water in the cooling tower, ignoring the synergistic effect of microbial growth and scaling.

[0003] Therefore, there is an urgent need for a cooling tower water quality monitoring scheme that can achieve dynamic optimization and control of cooling tower water quality and realize dynamic regulation of water quality. Summary of the Invention

[0004] This application provides a cooling tower water quality monitoring and control system, equipment, and medium to solve problems such as untimely response of cooling tower water quality control, inaccurate water quality monitoring results, and waste of reagents in existing air conditioning and refrigeration systems.

[0005] The first aspect of this application provides a method for monitoring and controlling the water quality of a cooling tower. The method of this application is used to monitor and control the water quality of water stored in a cooling tower in a cooling water treatment system in real time. The method of this application includes: acquiring real-time multi-dimensional water quality monitoring parameters of the water stored in the cooling tower; using a water quality monitoring device built based on a deep learning method, calculating the real-time monitoring results of the water in the cooling tower and the water quality control scheme of the water in the cooling tower based on the multi-dimensional water quality monitoring parameters.

[0006] In some embodiments of this application, the multi-dimensional water quality monitoring parameters include: pH value, conductivity, turbidity, and Legionella bacteria, and the pH value, conductivity, turbidity, and Legionella bacteria are collected in real time by water quality sensors deployed on the cooling tower.

[0007] In some embodiments of this application, the water quality monitoring device includes a pre-trained turbidity anomaly monitoring model, configured to calculate the level of turbidity event corresponding to the turbidity of the water in the cooling tower, and when the level of turbidity event is a high turbidity event, change the working state of the booster pump and valve in the cooling water treatment system to regulate the water quality of the water in the cooling tower.

[0008] In some embodiments of this application, the water quality monitoring device further includes a pre-trained Legionella anomaly monitoring model, configured to calculate the alarm response level corresponding to Legionella based on the Legionella in the water in the cooling tower, and when the alarm response level is a high Legionella alarm, shut down the cold water shortage treatment system, activate double the dosage of disinfectant, and send an emergency maintenance notification to regulate the water quality in the cooling tower.

[0009] In some embodiments of this application, the water quality monitoring device further includes a pre-trained ultraviolet anomaly monitoring model, configured to calculate whether the ultraviolet radiation in the cooling water treatment system is abnormal based on the ultraviolet radiation acquired in the cooling water treatment system, and to close the valves in the cooling water treatment system when the ultraviolet radiation is abnormal, so as to regulate the water quality of the water in the cooling tower.

[0010] In some embodiments of this application, the water quality monitoring device further includes a pre-trained ozone concentration anomaly monitoring model, configured to calculate whether the ozone concentration in the cooling water treatment system is abnormal based on the obtained ozone concentration in the cooling water treatment system, and to close the valve in the cooling water treatment system when the ozone concentration is abnormal, so as to regulate the water quality of the water in the cooling tower.

[0011] In some embodiments of this application, the water quality monitoring device further includes a pre-trained pipeline pressure anomaly monitoring model, configured to calculate whether the pipeline pressure in the cooling water treatment system is abnormal based on the acquired pipeline pressure in the cooling water treatment system, and adjust the pipeline pressure when the pipeline pressure is abnormal, so as to regulate the water quality of the water in the cooling tower.

[0012] The second aspect of this application provides a cooling water treatment system, which includes a cooling tower, and the water quality of the water stored in the cooling tower is monitored and controlled in real time using the cooling tower water quality monitoring and control method described above.

[0013] A third aspect of this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in any of the first aspects of the above embodiments.

[0014] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the first aspects of the above embodiments.

[0015] This application has the following beneficial effects: This application proposes a cooling tower water quality monitoring and control scheme. In this scheme, real-time multi-dimensional water quality monitoring parameters of the water stored in the cooling tower are acquired. A water quality monitoring device built using deep learning methods is then used to calculate the real-time monitoring results of the water in the cooling tower and the water quality control scheme based on these multi-dimensional water quality monitoring parameters. This deep learning approach enables automated real-time monitoring and water quality control of the water in the cooling tower without human intervention. It allows for real-time monitoring of the cooling tower water quality, timely response to water quality control issues in air conditioning refrigeration systems, and avoids chemical waste. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application.

[0017] Figure 1 This is a flowchart illustrating the first embodiment of the cooling tower water quality monitoring and control method provided in this application; Figure 2 This is a schematic diagram of a framework of an embodiment of the water quality monitoring device provided in this application; Figure 3 This is a flowchart illustrating the second embodiment of the cooling tower water quality monitoring and control method provided in this application; Figure 4 This is a schematic diagram of the framework of an embodiment of the electronic device provided in this application; Figure 5 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0018] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0019] In the following description, specific details such as particular system architectures, interfaces, and technologies are presented for illustrative purposes rather than for limiting purposes, in order to provide a thorough understanding of this application.

[0020] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, "many" in this document means two or more. Moreover, the term "at least one" in this document means any combination of at least two of any one or more of a plurality of objects. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0021] As described in the background section, there is an urgent need for a cooling tower water quality monitoring scheme that can achieve dynamic optimization and control of cooling tower water quality and realize dynamic regulation of water quality, in order to solve the problems of untimely response of cooling tower water quality regulation, inaccurate water quality monitoring results, and waste of reagents in existing air conditioning refrigeration systems.

[0022] To address the aforementioned issues, this application proposes a cooling tower water quality monitoring and control scheme. Utilizing a water quality monitoring device built based on deep learning methods, the scheme calculates real-time monitoring results and water quality control measures for the cooling tower based on multi-dimensional water quality monitoring parameters. This deep learning approach enables automated real-time monitoring and water quality control of the cooling tower water without human intervention. It allows for real-time monitoring of the cooling tower water quality, timely response to water quality control issues in air conditioning refrigeration systems, and avoids chemical waste.

[0023] This application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0024] According to one embodiment of this application, a method for monitoring and controlling the water quality of a cooling tower is proposed. This method is used to monitor and control the water quality of water stored in a cooling tower within a cooling water treatment system in real time. Figure 1 As shown, the method of this application includes: acquiring real-time multi-dimensional water quality monitoring parameters of water stored in a cooling tower; using a water quality monitoring device constructed based on a deep learning method, calculating the real-time monitoring results of water in the cooling tower and the water quality control scheme of water in the cooling tower based on the multi-dimensional water quality monitoring parameters.

[0025] In this embodiment, the multi-dimensional water quality monitoring parameters include: pH value, conductivity, turbidity, and Legionella bacteria, and the pH value, conductivity, turbidity, and Legionella bacteria are collected in real time by water quality sensors deployed on the cooling tower.

[0026] As described above, this embodiment uses water quality sensors deployed on the cooling tower to collect multi-dimensional water quality monitoring parameters such as pH value, conductivity, turbidity, and Legionella bacteria in real time. Combined with a water quality monitoring device built based on deep learning, it can perform high-precision and dynamic intelligent assessment and prediction of the water state in the cooling tower. This enables early identification of water quality anomalies (such as corrosion tendency, scaling risk, and microbial growth) and provides water quality control solutions (such as dosage, sewage discharge frequency, and sterilization strategies), thereby significantly improving the operational safety, energy efficiency, and automated management capabilities of the cooling water system.

[0027] In this embodiment, as Figure 2 As shown, the water quality monitoring device includes a pre-trained turbidity anomaly monitoring model, which is configured to calculate the level of turbidity event corresponding to the turbidity of the water in the cooling tower, and change the working state of the booster pump and valve in the cooling water treatment system when the level of turbidity event is a high turbidity event, so as to regulate the water quality of the water in the cooling tower.

[0028] Among them, when the turbidity is greater than 20 NTU, the corresponding turbidity level turbidity event is a high turbidity event.

[0029] The steps of changing the working state of the booster pump and valves in the cooling water treatment system to regulate the water quality in the cooling tower include: setting the working state of the booster pump to increase the speed to 75% for a duration of 300 seconds; and setting the working state of the valves to be fully open for 30 seconds of flushing.

[0030] As described above, this embodiment, by introducing a pre-trained turbidity anomaly monitoring model, can automatically identify abnormal water quality states based on real-time turbidity data. When turbidity exceeds 20 NTU and is determined to be a high turbidity event, the system immediately links and adjusts the working status of booster pumps and valves in the cooling water treatment system (such as increasing sewage discharge, adjusting water flow, or starting filtration) to achieve rapid response and proactive intervention to high turbidity risks. This mechanism not only improves the intelligence and real-time performance of water quality control and effectively prevents problems such as decreased heat exchange efficiency, equipment blockage, or microbial growth caused by the accumulation of suspended solids, but also significantly enhances the stability and operational safety of the cooling system.

[0031] In this embodiment, reference is still made to Figure 2 As shown, the water quality monitoring device also includes a pre-trained Legionella anomaly monitoring model, which is configured to calculate the alarm response level corresponding to Legionella based on the Legionella in the water in the cooling tower, and shut down the cold water shortage treatment system and start double-dose disinfection when the alarm response level is a high Legionella alarm, as well as send an emergency maintenance notification, so as to regulate the water quality in the cooling tower.

[0032] Specifically, when Legionella levels are greater than 0 CFU / mL and less than 4 CFU / mL, the alarm response level is a low-level Legionella alarm; when Legionella levels are greater than 4 CFU / mL, the alarm response level is a high-level Legionella alarm. It should be noted that the Legionella alarm response level threshold of 4 CFU / mL can be set according to the needs of different application scenarios, and the specific threshold is not limited by this.

[0033] As described above, this embodiment, by integrating a pre-trained Legionella anomaly monitoring model, can intelligently determine the alarm response level based on the real-time Legionella concentration detected in the cooling tower water. When the Legionella concentration exceeds 4 CFU / mL and triggers a high-level alarm, the system automatically executes multiple emergency measures—immediately shutting down the cooling water treatment system, initiating a double-dose sterilization program, and simultaneously sending an emergency maintenance notification, thereby quickly curbing the risk of Legionella spread at the source. This mechanism not only significantly enhances the proactive prevention and control capabilities against public health hazards and effectively protects personnel health and system operation safety, but also upgrades water quality management from passive response to intelligent early warning and automatic disposal, meeting relevant health and safety standards.

[0034] In this embodiment, reference is still made to Figure 2 As shown, the water quality monitoring device also includes a pre-trained ultraviolet anomaly monitoring model, which is configured to calculate whether the ultraviolet radiation in the cooling water treatment system is abnormal based on the ultraviolet radiation obtained in the cooling water treatment system, and close the valves in the cooling water treatment system when the ultraviolet radiation is abnormal, so as to regulate the water quality in the cooling tower.

[0035] Among them, ultraviolet radiation is less than 3000. At that time, the ultraviolet radiation was abnormal. It should be noted that the abnormal threshold for ultraviolet radiation is 3000. The threshold can be set according to the needs of different application scenarios, and the specific threshold is not limited by this.

[0036] As described above, this embodiment, by introducing a pre-trained ultraviolet (UV) anomaly monitoring model, can assess in real time whether the UV intensity in the cooling water treatment system is below the effective sterilization threshold (3000 μW / cm²). Once an UV anomaly (i.e., insufficient intensity) is detected, the system immediately and automatically closes the relevant valves, preventing the unsterilized water from continuing to enter the circulation system, thereby preventing microbial growth and water quality deterioration. This mechanism achieves intelligent monitoring and rapid response of key parameters in the disinfection process, effectively ensuring the biosafety of the cooling water system, avoiding the risk of Legionella and other pathogens spreading due to UV failure, and improving the reliability and automated control level of the entire water treatment process.

[0037] In this embodiment, reference is still made to Figure 2As shown, the water quality monitoring device also includes a pre-trained ozone concentration anomaly monitoring model, which is configured to calculate whether the ozone concentration in the cooling water treatment system is abnormal based on the obtained ozone concentration in the cooling water treatment system, and close the valve in the cooling water treatment system when the ozone concentration is abnormal, so as to regulate the water quality in the cooling tower.

[0038] When the ozone concentration exceeds 2.1 ppm, the ozone concentration is considered abnormal. It should be noted that the abnormal ozone concentration threshold of 2.1 ppm can be set according to the needs of different application scenarios, and the specific threshold is not limited by this.

[0039] As described above, this embodiment, by introducing a pre-trained ozone concentration anomaly monitoring model, can monitor the ozone concentration in the cooling water treatment system in real time. When the ozone concentration exceeds the safety threshold (2.1 ppm), it automatically determines an abnormal state and immediately shuts down the system valves, cutting off the circulation path of high-concentration ozone water. This measure effectively prevents equipment corrosion, pipe aging, and potential health risks to personnel caused by excessive ozone, while avoiding water quality imbalance due to excessive oxidation. It ensures the safety and stability of system operation while guaranteeing the sterilization effect, achieving precise, intelligent, and closed-loop control of the ozone disinfection process.

[0040] In this embodiment, reference is still made to Figure 2 As shown, the water quality monitoring device also includes a pre-trained pipeline pressure anomaly monitoring model, which is configured to calculate whether the pipeline pressure in the cooling water treatment system is abnormal based on the obtained pipeline pressure in the cooling water treatment system, and adjust the pipeline pressure when the pipeline pressure is abnormal, so as to regulate the water quality of the water in the cooling tower.

[0041] Specifically, a pipeline pressure exceeding 0.32 MPa is considered abnormal. It should be noted that the abnormal pipeline pressure threshold of 0.32 MPa can be set according to the needs of different application scenarios; the specific threshold is not limited by this.

[0042] As described above, this embodiment, by introducing a pre-trained pipeline pressure anomaly monitoring model, can monitor the pipeline pressure in the cooling water treatment system in real time. When the pressure exceeds the safety threshold (0.32MPa), it is automatically identified as an abnormal state, and a pressure regulation mechanism is triggered (such as adjusting the variable frequency pump speed, opening the pressure relief valve, or optimizing the valve opening). This effectively prevents problems such as pipeline leakage, equipment damage, or sealing failure caused by high pressure. This closed-loop control not only ensures the mechanical safety of the system operation but also indirectly maintains the stability of water quality, avoiding water flow turbulence, cavitation, or uneven chemical distribution caused by pressure fluctuations, thereby improving the reliability, energy efficiency, and intelligent management level of the entire cooling water system.

[0043] In this embodiment, reference is still made to Figure 2As shown, the water quality monitoring device also includes a pre-trained conductivity anomaly monitoring model, which is configured to calculate whether the conductivity is abnormal based on the conductivity of the water in the cooling tower, and magnetize the water when the conductivity is abnormal, so as to regulate the water quality in the cooling tower.

[0044] A conductivity greater than 3000 μS / cm is considered abnormal, and in this case, the water is magnetized to prevent scaling. It should be noted that the abnormal conductivity threshold of 3000 μS / cm can be set according to the needs of different application scenarios; the specific threshold is not limited by this.

[0045] As described above, this embodiment, by introducing a pre-trained conductivity anomaly monitoring model, can monitor the conductivity of water in the cooling tower in real time. When the conductivity exceeds 3000 μS / cm (indicating excessively high concentration of dissolved salts in the water and a significantly increased risk of scaling), it is automatically identified as an abnormal state. Subsequently, a magnetization treatment device is activated to magnetize the circulating water, effectively inhibiting the crystallization and deposition of hardness ions such as calcium carbonate, thereby preventing scaling on the inner walls of heat exchangers and pipes. This mechanism intelligently links water quality parameters with physical scale prevention methods, achieving green and efficient scale control without the need for chemical intervention. This not only extends the service life of equipment but also improves system energy efficiency and operational stability.

[0046] In this embodiment, reference is still made to Figure 2 As shown, the water quality monitoring device also includes a pre-trained pH anomaly monitoring model, which is configured to calculate whether the pH value is abnormal based on the pH value of the water in the cooling tower, and calculate the dosage of chemicals when the pH value is abnormal, so as to regulate the water quality of the water in the cooling tower.

[0047] When the pH value is outside the range of 7.5-9.5, it is considered an abnormal pH value. In this case, chemical treatment should be applied to the water to prevent scaling. It should be noted that the abnormal pH threshold of 7.5-9.5 can be set according to the needs of different application scenarios, and the specific threshold is not limited by this.

[0048] As described above, this embodiment, through the integration of a pre-trained pH anomaly monitoring model, can monitor the pH value of the water in the cooling tower in real time. When it detects that the pH value exceeds the set reasonable range (e.g., 7.5–9.5), it automatically determines that it is abnormal. Then, based on the water quality data, it intelligently calculates the required dosage and performs precise dosing, effectively adjusting the pH to the scale-prevention optimization range, thereby significantly reducing the risk of scaling and equipment damage caused by excessive alkalinity or acid corrosion. At the same time, the system supports flexible configuration of the pH anomaly threshold according to different operating conditions (e.g., water hardness, temperature, circulating load, etc.), taking into account both versatility and scenario adaptability. It realizes the upgrade of cooling water treatment from experience-driven to data-driven and intelligent control, improving the safety, energy efficiency and sustainability of system operation.

[0049] In this embodiment, the water quality control scheme for the cooling tower is obtained as follows: T1. Determine if the ultraviolet radiation is abnormal and if the turbidity is high. If the ultraviolet radiation is abnormal and the turbidity is high, open the valve and collect the wastewater; T2. Determine if the pipeline pressure is abnormal. If the pipeline pressure is abnormal, increase the pipeline pressure and perform suspended solids detection and coarse filtration to remove sand from the water; Use a pre-trained conductivity anomaly monitoring model to determine if the water conductivity is abnormal. If the conductivity is abnormal, magnetize the water to prevent scaling; T3. Repeat the above steps T1-T2. Use a pre-trained pH anomaly monitoring model to determine if the water pH value is abnormal. If the pH value is abnormal, calculate the dosage to achieve precise dosing; T4. Determine if the ozone concentration and ultraviolet radiation are abnormal. If the ozone concentration and ultraviolet radiation are abnormal, perform dual disinfection (UV and / or O3 disinfection).

[0050] As described above, this embodiment constructs a closed-loop, dynamic, and precise cooling tower water quality management scheme through multi-parameter linkage intelligent control logic: when abnormal ultraviolet radiation and high turbidity events are detected, valves are opened in a timely manner to collect wastewater and prevent pollution spread; when the pipeline pressure is abnormal, the pressure is actively adjusted and supplemented by suspended solids detection and coarse filtration to ensure water flow stability and cleanliness; for excessive conductivity, magnetization treatment is automatically initiated to inhibit scaling; for abnormal pH, precise dosing is achieved based on model calculations to avoid overdosing or underdosing; simultaneously, when either ozone or ultraviolet disinfection fails, a UV / O3 dual disinfection mechanism is immediately activated to ensure that microbial risks are controllable. This method achieves a leap from "single-parameter response" to "multi-dimensional synergistic control," significantly improving the safety, adaptability, and operating efficiency of the cooling water system, and effectively preventing scaling, corrosion, biofouling, and public health risks.

[0051] Based on the inventive concept of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the above embodiments. The following is in conjunction with... Figure 4 Please provide a detailed explanation.

[0052] like Figure 4 As shown, it illustrates the electronic device 100 of this application, which may specifically include a processor 110 and a memory 120. The memory 120 is coupled to the processor 110.

[0053] Processor 110 is used to control the operation of electronic devices. Processor 110 may also be referred to as a CPU (Central Processing Unit). Processor 110 may be an integrated circuit chip with signal processing capabilities. Processor 110 may also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The general-purpose processor may be a microprocessor, or processor 110 may be any conventional processor.

[0054] The memory 120 is used to store computer programs and may be RAM, ROM, or other types of storage terminals. Specifically, the memory 120 may include one or more computer-readable storage media, which may be non-transitory or transient. The memory 120 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage terminals or flash memory terminals. In some embodiments, the non-transitory computer-readable storage media in the memory 120 is used to store at least one line of program code.

[0055] The processor 110 is used to execute computer programs stored in the memory 120 to implement the methods described in the various method embodiments of this application.

[0056] In some embodiments, the electronic device may further include a peripheral terminal interface 130 and at least one peripheral terminal. The processor 110, memory 120, and peripheral terminal interface 130 may be connected via a bus or signal line. Each peripheral terminal may be connected to the peripheral terminal interface 130 via a bus, signal line, or circuit board. Specifically, the peripheral terminal includes at least one of a radio frequency circuit 140, a display screen 150, an audio circuit 160, and a power supply 170.

[0057] The peripheral terminal interface 130 can be used to connect at least one I / O (Input / Output) related peripheral terminal to the processor 110 and the memory 120. In some embodiments, the processor 110, memory 120 and peripheral terminal interface 130 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 110, memory 120 and peripheral terminal interface 130 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0058] The radio frequency (RF) circuit 140 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The RF circuit 140 communicates with communication networks and other IoT devices via electromagnetic signals; it is the communication circuit of the electronic device. The RF circuit 140 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals back into electrical signals. Optionally, the RF circuit 140 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, an operator identification module card, etc. The RF circuit 140 can communicate with other terminals through at least one wireless communication protocol. This wireless communication protocol includes, but is not limited to: the World Wide Web, metropolitan area networks, intranets, various generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and / or WiFi (Wireless Fidelity) networks. In some embodiments, the RF circuit 140 may also include circuitry related to NFC (Near Field Communication), which is not limited in this application.

[0059] Display screen 150 is used to display a UI (User Interface). This UI may include graphics, text, icons, videos, and any combination thereof. When display screen 150 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 110 for processing. In this case, display screen 150 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 150, located on the front panel of the electronic device; in other embodiments, there may be at least two display screens, located on different surfaces of the electronic device or in a folded design; in still other embodiments, display screen 150 may be a flexible display screen, located on a curved or folded surface of the electronic device. Furthermore, display screen 150 may be configured as a non-rectangular, irregular shape, i.e., a non-rectangular screen. Display screen 150 may be made of materials such as LCD (Liquid Crystal Display) or OLED (Organic Light-Emitting Diode).

[0060] The audio circuit 160 may include a microphone and a speaker. The microphone is used to collect sound waves from the operator and the environment, converting the sound waves into electrical signals that are input to the processor 110 for processing, or input to the radio frequency circuit 140 for voice communication. For stereo sound acquisition or noise reduction purposes, multiple microphones may be used, each positioned in a different part of the electronic device. The microphone may also be an array microphone or an omnidirectional microphone. The speaker is used to convert electrical signals from the processor 110 or the radio frequency circuit 140 into sound waves. The speaker may be a conventional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can convert electrical signals not only into audible sound waves but also into inaudible sound waves for purposes such as distance measurement. In some embodiments, the audio circuit 160 may also include a headphone jack.

[0061] Power supply 170 is used to supply power to various components in an electronic device. Power supply 170 can be alternating current, direct current, a disposable battery, or a rechargeable battery. When power supply 170 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0062] For a detailed description of the functions and execution processes of each functional module or component in the electronic device embodiments of this application, please refer to the descriptions in the above-described method embodiments of this application, which will not be repeated here.

[0063] In the embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the embodiments of the electronic devices described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some data may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0064] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0065] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0066] Based on the inventive concept of the above embodiments, this application also provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, performs the steps of the method described in any of the above embodiments. The following is in conjunction with... Figure 5 This describes the execution process of the above embodiments on a computer-readable storage medium.

[0067] like Figure 5 As shown, it illustrates the computer-readable storage medium of this application. The integrated units described above, if implemented as software functional units and sold or used as independent products, can be stored in the computer-readable storage medium 200. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions / computer programs to cause an Internet of Things device (which may be a personal computer, server, or network terminal, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, as well as electronic terminals such as computers, mobile phones, laptops, tablets, and cameras that have the aforementioned storage media.

[0068] The execution process of program data in a computer-readable storage medium can be described with reference to the above-described method embodiments of this application, and will not be repeated here.

[0069] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

[0070] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

Claims

1. A method for monitoring and controlling the water quality of a cooling tower, characterized in that, The method is used for real-time monitoring and control of the water quality stored in the cooling tower of a cooling water treatment system, and the method includes: Obtain real-time, multi-dimensional water quality monitoring parameters for the water stored in the cooling tower; A water quality monitoring device based on deep learning is used to calculate the real-time monitoring results of the water in the cooling tower and the water quality control scheme of the cooling tower based on the multi-dimensional water quality monitoring parameters.

2. The cooling tower water quality monitoring and control method according to claim 1, characterized in that, The multi-dimensional water quality monitoring parameters include: pH value, conductivity, turbidity, and Legionella bacteria, and the pH value, conductivity, turbidity, and Legionella bacteria are collected in real time by water quality sensors deployed on the cooling tower.

3. The cooling tower water quality monitoring and control method according to claim 2, characterized in that, The water quality monitoring device includes a pre-trained turbidity anomaly monitoring model, which is configured to calculate the level of turbidity event corresponding to the turbidity of the water in the cooling tower, and change the working state of the booster pump and valve in the cooling water treatment system when the level of turbidity event is a high turbidity event, so as to regulate the water quality of the water in the cooling tower.

4. The cooling tower water quality monitoring and control method according to claim 3, characterized in that, The water quality monitoring device also includes a pre-trained Legionella anomaly monitoring model, which is configured to calculate the alarm response level corresponding to the Legionella based on the Legionella in the water in the cooling tower, and when the alarm response level is a high-level Legionella alarm, shut down the cold water shortage treatment system, start double-dose disinfection, and send an emergency maintenance notification to regulate the water quality in the cooling tower.

5. The cooling tower water quality monitoring and control method according to claim 4, characterized in that, The water quality monitoring device also includes a pre-trained ultraviolet anomaly monitoring model, which is configured to calculate whether the ultraviolet radiation in the cooling water treatment system is abnormal based on the ultraviolet radiation obtained in the cooling water treatment system, and close the valves in the cooling water treatment system when the ultraviolet radiation is abnormal, so as to regulate the water quality of the water in the cooling tower.

6. The cooling tower water quality monitoring and control method according to claim 5, characterized in that, The water quality monitoring device also includes a pre-trained ozone concentration anomaly monitoring model, which is configured to calculate whether the ozone concentration in the cooling water treatment system is abnormal based on the obtained ozone concentration, and close the valve in the cooling water treatment system when the ozone concentration is abnormal, so as to regulate the water quality of the water in the cooling tower.

7. The cooling tower water quality monitoring and control method according to claim 6, characterized in that, The water quality monitoring device also includes a pre-trained pipeline pressure anomaly monitoring model, which is configured to calculate whether the pipeline pressure in the cooling water treatment system is abnormal based on the obtained pipeline pressure in the cooling water treatment system, and adjust the pipeline pressure when the pipeline pressure is abnormal, so as to regulate the water quality in the cooling tower.

8. A cooling water treatment system, characterized in that, The cooling water treatment system includes a cooling tower, and the water quality of the water stored in the cooling tower is monitored and controlled in real time using the cooling tower water quality monitoring and control method as described in claim 1.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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