Automatic cleaning and maintenance control method and system for water quality monitoring equipment and medium

Abstract

The invention discloses an automatic cleaning and maintenance control method and system for water quality monitoring equipment and a medium, and belongs to the field of water quality monitoring. The method comprises the steps that pure water generated by a built-in pure water production assembly of equipment serves as a measurement anchor point, and whether sensors are normal or not is judged on the basis of comparison results of detection numerical values of the sensors in a pure water environment and a preset pure water threshold value; monitoring operation state parameters of the pure water production assembly, and dynamically adjusting and updating the pure water threshold value corresponding to each sensor; when the value of the sensor deviates from the threshold value, first-stage pure water flushing is executed; if not, second-stage maintenance is started according to the sensor type, the optical sensor performs optical path self-cleaning or backwashing, and the electrochemical sensor performs electrode cleaning; and detecting again after maintenance, and locking the sensor and generating a fault alarm if the sensor is still not recovered. Through dynamic threshold configuration, progressive maintenance and sensor adaptive cleaning, the problems of reference drift and deep pollution are solved, the data credibility is improved, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of water quality monitoring technology, and in particular to automatic cleaning and maintenance control methods, systems and media for water quality monitoring equipment. Background Technology

[0002] With increasingly stringent requirements for industrial production and environmental protection, online water quality monitoring equipment has been widely used in fields such as drinking water safety, wastewater treatment, industrial process control, and environmental monitoring. This type of equipment typically requires long-term, continuous, unattended operation outdoors or in the field to acquire real-time water quality data.

[0003] Currently, the maintenance of online water quality monitoring equipment that operates on-site for extended periods primarily relies on regular manual inspections and troubleshooting. When data anomalies, drift, or sensor contamination occur, specialized technicians typically need to travel to the site with tools and reagents. On-site maintenance generally includes steps such as preparing standard solutions for manual calibration, manually flushing pipelines with pure water, manually draining residual liquid from pipelines, and manually performing zero-point or range calibration.

[0004] However, the above-mentioned on-site maintenance model that relies on manual labor has the following technical defects and shortcomings: 1. Manual on-site maintenance requires a significant amount of commuting and on-site operation time for technicians. Especially when monitoring points are scattered and geographically remote, maintenance costs increase dramatically, resulting in high equipment operation and maintenance expenses.

[0005] 2. The quality of on-site maintenance is highly dependent on the professional knowledge and experience of the technicians. Differences in the standardization of operation by different personnel and limitations of on-site environmental conditions (such as water quality and temperature) may lead to inconsistent maintenance results, making it difficult to guarantee the consistency and effectiveness of calibration and cleaning.

[0006] 3. Because the health status of the equipment itself cannot be monitored in real time, responses are often reactive only after obvious data anomalies have occurred or equipment malfunctions have taken place. During the period from when a problem occurs to when human intervention is needed, the monitoring data is either unreliable or incomplete, causing critical water quality anomaly monitoring windows to be missed, thus affecting the continuity and accuracy of environmental monitoring data.

[0007] 4. For some complex equipment failures, such as internal scaling of sensors, contamination of optical mirrors, and biofilm growth in pipelines, simple on-site flushing and calibration often cannot eradicate the problem. This may require technicians to make multiple trips to the site, or the equipment may operate with the problem for a long time, further accelerating the aging of the equipment.

[0008] 5. Existing technologies typically use a fixed pure water reference value as the basis for sensor calibration. However, pure water production components (such as RO membranes) will age over time or change with deployment location, causing the pure water reference value to drift. If the initial threshold is still used, it will cause frequent false alarms or calibration failure.

[0009] 6. Existing maintenance methods are relatively simple, typically involving only rinsing with pure water. For deep contamination such as scale buildup on optical mirrors and electrode passivation, simple rinsing is insufficient to remove it completely; furthermore, differentiated cleaning methods are not adopted for the different contamination characteristics of optical and electrochemical sensors.

[0010] Therefore, how to overcome the problems of low efficiency, high cost, slow response, low standardization, benchmark drift, and difficulty in eradicating deep pollution caused by the reliance on manual maintenance of water quality monitoring equipment in the existing technology, and achieve efficient, convenient, automated, and intelligent maintenance of the equipment, has become an urgent technical problem to be solved in this field. Summary of the Invention

[0011] To achieve the above-mentioned objectives and other advantages of the present invention, a first objective of the present invention is to provide an automatic cleaning and maintenance control method for water quality monitoring equipment, comprising the following steps: The pure water production component built into the water quality monitoring equipment generates pure water, which is then used as a measurement anchor point and introduced into the water path where each sensor is located. Based on the comparison between the detection values ​​of each sensor in the pure water environment and the preset pure water threshold, it is determined whether each sensor is in the normal operating range. Monitor the operating status parameters of the pure water production components, and dynamically adjust and update the pure water threshold corresponding to each sensor according to the operating status parameters to adapt to changes in the pure water reference value caused by aging of the pure water production components or changes in equipment deployment location. When the detection value of any sensor deviates from its corresponding pure water threshold, the first-level maintenance process is executed, which involves continuously rinsing the sensor with pure water. If the detection value still does not return to the threshold after the first-level maintenance process is completed, the second-level maintenance process is initiated according to the type of sensor. For optical sensors, optical path self-cleaning or physical backwashing is performed, and for electrochemical sensors, electrode cleaning is performed.

[0012] Furthermore, the sensor includes one or more of the following: a water quality sensor for detecting TOC values, a turbidity sensor, a residual chlorine sensor, a conductivity sensor, and a TDS sensor; Furthermore, the pure water threshold includes: a constant preset for the water quality sensor, a constant preset for the turbidity sensor, a constant preset for the residual chlorine sensor, a constant preset for the conductivity sensor, and a constant preset for the TDS sensor.

[0013] Furthermore, the pure water production assembly includes a pretreatment filter cartridge and a filtration assembly connected in sequence; the pretreatment filter cartridge is used to remove particulate impurities, residual chlorine and organic matter from the raw water, and the filtration assembly is used to allow water molecules to pass through to generate pure water; The operating status parameters include one or more of the following: the usage time of the filter component, the cumulative water production of the filter component, and the influent water quality of the filter component.

[0014] Furthermore, the step of performing optical path self-cleaning for the optical sensor is as follows: When calibrating the optical sensor using pure water, the current light intensity signal value is recorded and used as the reference value for the cleanliness of the mirror surface. During subsequent monitoring, when the light intensity signal value is detected to have decreased by more than the preset light path contamination threshold compared to the reference value, it is determined to be mirror contamination, and a physical backwash cleaning process is triggered.

[0015] Furthermore, the physical backwash cleaning process includes: Control the water circuit switching to introduce the pre-stored cleaning solution into the water circuit of the optical sensor for soaking; After soaking for a preset time, the water is drained, and then the water path of the optical sensor is rinsed with pure water.

[0016] Furthermore, the electrode cleaning step performed on the electrochemical sensor is as follows: The electrochemical sensor was calibrated using pure water, the current data value was recorded, and it was used as a reference value. When the deviation of the data detected by the electrochemical sensor from the reference value exceeds the preset scaling threshold, it is determined that there is abnormal scaling on the electrode of the electrochemical sensor. The cleaning agent is automatically extracted from the micro cleaning tank containing special cleaning agent and the electrode is circulated and rinsed. After rinsing, the electrodes are rinsed and calibrated again using pure water.

[0017] Furthermore, if the sensor fails to return to the threshold after the second-level maintenance process, the sensor is locked, its status is marked as abnormal, and a sensor fault alarm is generated.

[0018] Furthermore, the step of locking the sensor includes: The use of this sensor for collecting and reporting water quality monitoring data is suspended. The sensor status is displayed as faulty or requiring maintenance on both the local device interface and the cloud platform interface. Subsequent water quality monitoring reports marked the data from this sensor as invalid or for reference only.

[0019] Furthermore, it also includes a multi-sensor joint diagnostic step: When multiple sensors simultaneously detect values ​​that deviate from their corresponding pure water threshold values, the following judgment is performed: If the number of the multiple sensors reaches or exceeds the preset group anomaly threshold, it is determined to be a water quality anomaly, a water quality anomaly alarm is generated, and the maintenance process for the individual sensor is suspended. If the number of the multiple sensors is lower than the preset group anomaly threshold, a maintenance process is performed on each sensor separately, and the sensor is determined to be a sensor-specific anomaly.

[0020] Furthermore, the preset threshold for cluster anomalies is dynamically adjusted based on the historical water quality fluctuation characteristics of the monitored water source: Collect water quality monitoring data of the water source within a preset historical time period, and calculate the fluctuation frequency index and fluctuation amplitude index of the water quality monitoring data; Based on the fluctuation frequency index and fluctuation amplitude index, the monitored water source is divided into several preset water quality stability levels; Based on the water quality stability level, the corresponding group anomaly threshold is queried from the preset threshold mapping table and set. Each water quality stability level corresponds to a preset threshold for cluster anomalies, and the higher the water quality stability level, the lower the corresponding threshold for cluster anomalies.

[0021] Furthermore, it also includes abnormal diagnosis and alarm procedures: During maintenance, the abnormal status of multiple sensors is monitored simultaneously; When the number of sensors in an abnormal state is detected to reach or exceed a preset threshold, an alarm message is generated and issued indicating that the device may have physical damage.

[0022] Furthermore, it also includes network maintenance steps: Multiple water quality monitoring devices located at the same site are connected to the cloud platform for networking; The cloud platform performs group analysis on monitoring data uploaded by multiple devices from the same water source; When the analysis results show that the value of a single device deviates systematically from the values ​​of other devices from the same water source, the cloud platform sends a command to that single device to trigger the execution of a maintenance process, so that the monitoring data of that device is consistent with the data of other devices from the same water source.

[0023] Furthermore, it also includes remote maintenance steps: Receive remote human instructions via cloud platform; Based on the remote manual instructions, maintenance procedures are independently triggered for several sensors on a designated device.

[0024] Furthermore, it also includes intelligent diagnosis and maintenance steps based on a water pollution characteristic database: A water pollution feature database is pre-established, which contains various pollution types and their corresponding sensor signal change characteristics; Real-time monitoring of the detection data from each sensor, extracting its changing trends, temporal relationships, and fluctuation patterns; The extracted features are compared with the features in the water pollution feature database to identify the pollution type; Based on the identified pollution type, the preset maintenance procedure corresponding to that pollution type is initiated.

[0025] Furthermore, the water pollution feature database includes one or more of the following features and their corresponding maintenance procedures: Within the biological pollution monitoring window, when the cumulative increase in TOC value exceeds the first biological threshold and the cumulative decrease in residual chlorine value exceeds the second biological threshold, it is identified as biological pollution, and ultraviolet sterilization or ozone sterilization is initiated. Within the chemical pollution monitoring window, if the instantaneous increase in TOC value exceeds the chemical threshold while the residual chlorine and turbidity values ​​remain stable, it is identified as chemical pollution, and solvent cleaning is initiated. Within the particulate matter monitoring window, if the instantaneous increase in turbidity exceeds the particulate threshold and the variance of turbidity fluctuation exceeds the fluctuation threshold, while conductivity and residual chlorine remain stable, particulate matter contamination is identified, and a high-flow-rate backwash is initiated. When the turbidity value at a single monitoring sampling point exceeds the first bubble threshold, it is determined that there are bubbles or foreign objects in the sensor, and the sensor is emptied and then refilled with water. When the turbidity value at a single monitoring sampling point is lower than the second bubble threshold, it is determined that the calibration is abnormal or that bubbles in the filter cartridge have entered the sensor. After purging, water is added and recalibrated. When the turbidity value exceeds the third bubble threshold at multiple consecutive monitoring sampling points, it is determined that there is a partial cavity in the sensor water circuit, and the cavity is emptied and then water is refilled.

[0026] Furthermore, it also includes predictive maintenance steps: Real-time monitoring of the detection values ​​of each sensor, and calculation of the rate of change of the detection values ​​of each sensor within a preset time window; When the rate of change of any sensor exceeds the preset rate threshold for that sensor, and the current detection value of that sensor has not exceeded its corresponding pure water threshold, a preventive maintenance warning is generated, or a maintenance process for that sensor is automatically triggered when the equipment is idle.

[0027] Furthermore, the rate of change includes an increase rate and a decrease rate; the preset time window is dynamically adjusted according to the type of sensor; The time window preset for the TOC sensor and turbidity sensor is shorter than the time window preset for the residual chlorine sensor and conductivity sensor.

[0028] A second objective of this invention is to provide a water quality monitoring system, comprising: One or more water quality monitoring devices, the devices including pure water production components, multiple sensors, valves and pumps that can control water circuit switching, as well as miniature cleaning tanks and sterilization devices; The cloud platform is communicatively connected to the water quality monitoring equipment. The system is configured to perform the aforementioned automatic cleaning and maintenance control methods.

[0029] A third objective of the present invention is to provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-described automatic cleaning and maintenance control method.

[0030] Compared with the prior art, the beneficial effects of the present invention are: This invention provides an automatic cleaning and maintenance control method, system, and medium for water quality monitoring equipment. Utilizing a built-in pure water production component, pure water serves as a unified measurement anchor point, enabling automatic diagnosis and calibration of sensor status. In daily operation, no on-site technical personnel are required, and no standard solution preparation is needed, completely changing the traditional reliance on manual on-site maintenance and significantly reducing operation and maintenance costs and manpower input.

[0031] To address deep contamination issues such as chemical pollution and scale buildup on electrochemical sensor electrodes, this invention pre-loads specialized cleaning solvents and agents into the equipment, automatically performing solvent cleaning or electrode cleaning when needed. This tiered strategy, using pure water for routine maintenance and solvents for deep cleaning, ensures both convenience for daily maintenance and effective resolution of complex contamination problems.

[0032] This invention effectively solves the problem of pure water reference value drift caused by aging of filter components or changes in equipment deployment location by monitoring the operating status parameters of pure water production components in real time, such as the usage time of filter components, cumulative water production, and influent water quality, and dynamically adjusting and updating the pure water threshold corresponding to each sensor. It also avoids false alarms and calibration failures caused by static thresholds.

[0033] This invention establishes a progressive maintenance strategy consisting of a first-stage pure water rinsing and a second-stage deep cleaning. For light contamination, a simple pure water rinse is sufficient for rapid recovery; for deep contamination, targeted deep cleaning is initiated based on the sensor type. This progressive maintenance mechanism saves resources while ensuring that deep contamination is effectively addressed.

[0034] This invention employs differentiated cleaning methods to address the different contamination characteristics of optical and electrochemical sensors: optical sensors undergo optical path self-cleaning or physical backwashing, while electrochemical sensors undergo electrode cleaning, ensuring that all types of sensors receive the most effective deep cleaning.

[0035] When a sensor malfunction is detected, the present invention automatically switches the water circuit to flush only the malfunctioning sensor with pure water or solvent until it returns to normal. This precise maintenance method avoids unnecessary flushing of the entire system, saves pure water and energy, and ensures that the maintenance process does not affect the normal operation of other sensors.

[0036] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Specific embodiments of the present invention are given in detail below with reference to the accompanying drawings. Attached Figure Description

[0037] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 Flowchart of automatic cleaning and maintenance control method for water quality monitoring equipment; Figure 2 This is a schematic diagram of the water circuit for a water quality monitoring device. Figure 3 The graph shows the change of the pure water threshold of each sensor with the usage time of the RO membrane. Figure 4 This is a flowchart of the self-cleaning process for an optical sensor's optical path. Figure 5 This is a flowchart of a physical backwash cleaning process. Figure 6 Flowchart for cleaning electrochemical sensor electrodes; Figure 7 Flowchart for locking the sensor; Figure 8 A bar chart comparing the recovery rates of traditional flushing and the progressive maintenance method of this invention; Figure 9 Flowchart for multi-sensor joint diagnostics; Figure 10 Flowchart for dynamically adjusting preset cluster anomaly thresholds based on historical water quality fluctuation characteristics of monitored water sources; Figure 11 This is a flowchart for anomaly diagnosis and alarm processing; Figure 12 The effect of multi-sensor joint diagnosis on reducing the false diagnosis rate is shown in the figure; Figure 13 For network maintenance flowchart; Figure 14 For remote maintenance flowchart; Figure 15 A flowchart for intelligent diagnosis and maintenance based on a water pollution feature database; Figure 16 Predictive maintenance flowchart; Figure 17 Improve the slope plot to predictively maintain key performance indicators; Figure 18 This is a schematic diagram of a computer device. Figure 19 This is a schematic diagram of a computer-readable storage medium. Detailed Implementation

[0038] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0039] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0040] The drawing numbers in this application are only used to distinguish the steps in the scheme and are not used to limit the execution order of the steps. The specific execution order is as described in the specification.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0042] Existing maintenance methods for water quality monitoring equipment suffer from the following technical drawbacks: reliance on manual on-site handling leads to low efficiency and high costs; reactive response mechanisms result in data lag and compromised effectiveness; low standardization of operations leads to uncontrollable maintenance quality; and a lack of intelligent diagnostic capabilities makes it difficult to eradicate complex problems. Therefore, this invention provides an automatic cleaning and maintenance control method and system for water quality monitoring equipment, enabling automated and intelligent maintenance of the equipment.

[0043] This method can be executed by the main control unit of the water quality monitoring system. The main control unit can be implemented in the form of software and / or hardware, and is generally integrated into any electronic device with network communication capabilities, such as a mobile terminal, PC, or server.

[0044] Example 1 An automatic cleaning and maintenance control method for water quality monitoring equipment, such as Figure 1 As shown, it includes the following steps: S1. Control the pure water production component built into the water quality monitoring equipment to generate pure water, and use the pure water as a measurement anchor point to enter the water path where each sensor is located. Based on the comparison results of the detection values ​​of each sensor in the pure water environment and the preset pure water threshold, determine whether each sensor is in the normal operating range. In this embodiment, the water quality monitoring system includes water quality monitoring equipment and a cloud platform. The water quality monitoring equipment internally includes a pure water production component, multiple sensors, a water circuit system, a main control unit, a storage unit, and a communication unit. The cloud platform communicates with multiple water quality monitoring devices, receiving monitoring data uploaded by the devices and performing functions such as network analysis, remote command issuance, and data storage.

[0045] The pure water production assembly includes a pretreatment filter cartridge and a filtration assembly connected in sequence; wherein, the pretreatment filter cartridge is used to remove particulate impurities, residual chlorine and organic matter from the raw water, and the filtration assembly is used to allow water molecules to pass through to generate pure water.

[0046] Optionally, the pretreatment filter element includes a PP cotton filter element and an activated carbon filter element. The PP cotton filter element is used to remove large particulate impurities such as silt and rust from the raw water, and the activated carbon filter element is used to adsorb residual chlorine, organic matter and odors to protect the subsequent filtration components from clogging or oxidation.

[0047] Preferably, such as Figure 2 As shown, the filtration assembly uses an RO reverse osmosis membrane filter element to allow water molecules to pass through and generate pure water, while dissolved salts, colloids, bacteria, etc., are trapped and discharged. In this embodiment, the pure water generated by the filtration assembly is used as the measurement anchor point. The pure water produced by the RO membrane is stable in quality, with a TOC value generally between 0.1-0.3 mg / L, a turbidity value between 0.01-0.1 NTU, a residual chlorine value close to 0 mg / L, a conductivity value of approximately 10 μS / cm, and a TDS value of approximately 20 ppm. These characteristic values ​​form the basis for the preset pure water threshold of each sensor.

[0048] Multiple sensors include one or more of the following: a water quality sensor (i.e., a TOC sensor) for detecting TOC values, a turbidity sensor, a residual chlorine sensor, a conductivity sensor, and a TDS sensor, each used to detect the corresponding water quality parameter.

[0049] The water system includes an inlet pipe, a pure water pipe, an outlet pipe, and multiple control valves (valve 1 to valve 14) and a water pump. By controlling the opening and closing of different valves, pure water can be directed into the designated sensor water circuit.

[0050] The main control unit uses an embedded processor to execute the control method of this invention and coordinate the work of each component.

[0051] The storage unit is used to store preset pure water thresholds, maintenance logs, diagnostic rules, etc. for each sensor.

[0052] The communication unit is used for data interaction with the cloud platform.

[0053] This embodiment achieves the generation and introduction of pure water through step S1. Specifically, as follows... Figure 2 As shown, the main control unit controls the pure water production component to start and generate pure water; at the same time, it controls the water pump to start and controls the corresponding valve combination to supply pure water to the water circuits where each sensor 120 is located, according to the required sensor water circuits.

[0054] This embodiment also achieves numerical acquisition and status judgment through step S1. Specifically, the main control unit reads the detection values ​​of each sensor in a pure water environment in real time, reads the preset pure water threshold of each sensor from the storage unit, compares the detection values ​​with the thresholds, and determines whether each sensor is in the normal operating range.

[0055] The preset pure water thresholds include constants dtoc for the water quality sensor, dntu for the turbidity sensor, dcl for the residual chlorine sensor, dec for the conductivity sensor, and dtds for the TDS sensor. These constant values ​​can be dynamically set according to different environments and RO membrane conditions to adapt to different detection environments, and the automatic maintenance of a specific sensor can also be turned off individually.

[0056] For example, dtoc can be set to 0.2 mg / L and adjusted within the range of 0.1-0.3 depending on the RO membrane condition; dntu can be set to 0.15 NTU and adjusted within the range of 0.1-0.2; dcl can be set to 0 mg / L; dec can be set to 10 μS / cm; and dtds can be set to 20 ppm.

[0057] Taking the TOC sensor as an example, if its reading is within the range of dtoc ± 0.05 mg / L, it is considered normal; if it exceeds this range, it is considered abnormal. Similarly, a turbidity sensor reading outside the range of dntu ± 0.05 NTU is considered abnormal, a residual chlorine sensor reading above 0.1 mg / L is considered abnormal, a conductivity sensor reading deviating from the range of dec ± 2 μS / L is considered abnormal, and a TDS sensor reading deviating from the range of dtds ± 5 ppm is considered abnormal.

[0058] To address the issue of pure water reference value drift caused by RO membrane aging; and in response to changes in equipment deployment location, the system can automatically re-collect pure water reference values ​​in the new environment and update the thresholds. S2, Monitor the operating status parameters of the pure water production components, and dynamically adjust and update the pure water thresholds corresponding to each sensor based on the operating status parameters to adapt to changes in pure water reference values ​​caused by aging of the pure water production components or changes in equipment deployment location; Specifically, the operating status parameters of the pure water production components are monitored periodically or in real time. These operating status parameters include one or more of the following: usage time of the filtration component (i.e., RO reverse osmosis membrane filter element), cumulative water production, and influent water quality. These parameters reflect the degree of performance degradation of the RO membrane and are important bases for dynamically adjusting the pure water threshold.

[0059] Then, based on the operating status parameters, the pure water threshold corresponding to each sensor is dynamically adjusted and updated; or, in response to a change in the equipment deployment location, the pure water reference value in the new environment is re-collected, and the pure water threshold corresponding to each sensor is updated accordingly.

[0060] Because RO membranes age over time, the quality of the purified water they produce will change. For example, a new RO membrane might produce purified water with a TOC value of 0.1 mg / L, which could rise to 0.3 mg / L after one year of use. If 0.1 mg / L is still used as the threshold, it will lead to frequent false alarms.

[0061] Therefore, in this embodiment, the main control unit periodically (e.g., weekly) monitors the operating status parameters of the pure water production components, including the usage time of the RO membrane, the cumulative water production of the RO membrane, and the influent water quality of the RO membrane. Based on these parameters, the system calculates the theoretical pure water values ​​of each sensor under the current RO membrane condition and updates the pure water thresholds in the storage unit. For example, if the dtoc is set to 0.1 mg / L under the new RO membrane condition, and the RO membrane performance declines after one year of use, the dtoc can be dynamically adjusted to 0.25 mg / L, always maintaining it within the theoretical range of 0.1-0.3 mg / L. Similarly, dntu is dynamically adjusted within the range of 0.1-0.2 NTU, dec is adjusted within the range of 8-12 μS / cm, and dtds is adjusted within the range of 15-25 ppm.

[0062] To quantitatively illustrate the impact of RO membrane aging on the pure water threshold of each sensor, this embodiment records the changes in the pure water reference values ​​of each sensor during the RO membrane's service life, as shown in Table 1.

[0063] Table 1. Relationship between RO membrane usage time and changes in pure water baseline values ​​of various sensors. As shown in Table 1, the pure water baseline values ​​of all sensors show an upward trend with the increase of RO membrane usage time. Taking the TOC sensor as an example, the pure water TOC value is approximately 0.10 mg / L when the membrane is new, rising to approximately 0.18 mg / L after 6 months of use, and to approximately 0.26 mg / L after 12 months of use. If dynamic threshold adjustment is not performed and the initial 0.10 mg / L is still used as the judgment benchmark, the sensor will be frequently misjudged as abnormal, triggering unnecessary flushing operations.

[0064] Figure 3 Table 1 shows the curves illustrating the change in pure water threshold values ​​for each sensor over the RO membrane's usage time. Taking the TOC sensor as an example, the horizontal axis represents the RO membrane usage time (months), and the vertical axis represents the TOC pure water threshold value (mg / L). In the new membrane state, the initial dtoc value is approximately 0.10 mg / L; as the RO membrane's usage time increases, the TOC value in the pure water gradually rises, reaching approximately 0.26 mg / L after one year of use. It can be seen that the dynamic threshold consistently follows the actual performance changes of the RO membrane, adjusting the threshold to a reasonable range and effectively avoiding misjudgments caused by fixed thresholds.

[0065] Similarly, Figure 3 The pure water threshold variation curves of the turbidity sensor, conductivity sensor, and TDS sensor are also shown. Table 2 further provides a comparison of the errors of each sensor when using a fixed threshold and the dynamic threshold of the present invention.

[0066] Table 2 Comparison of errors between fixed threshold and dynamic threshold As shown in Table 2, when using a fixed threshold, the absolute error of the TOC sensor reached +0.16±0.04 mg / L after one year of use, resulting in a final measured value that was approximately 0.16 mg / L lower than expected. However, after applying the dynamic threshold adjustment of this invention, the residual error was only -0.01±0.04 mg / L, with the numerical deviation controlled within 0.1 mg / L. Similarly, the residual errors of the dynamic thresholds for turbidity, conductivity, and TDS sensors were all close to zero, significantly better than the fixed threshold scheme. This verifies the effectiveness of the dynamic threshold configuration step of this invention. By monitoring the RO membrane status in real time and dynamically updating the pure water threshold, measurement errors caused by RO membrane aging can be significantly reduced, ensuring the accuracy of the monitoring data.

[0067] Furthermore, when the equipment is moved from location A to location B, the baseline value of the pure water produced by the RO membrane will differ due to the different water quality in the two locations. In this case, technicians can issue instructions through the cloud platform to trigger the system to re-collect the baseline value of pure water in the new environment, that is, to continuously pass pure water through for 30 minutes, take the stable average value, and update the pure water threshold of each sensor accordingly.

[0068] S3. When the detection value of any sensor deviates from its corresponding pure water threshold, the first-level maintenance process is executed, that is, the sensor is continuously rinsed with pure water. If the detection value still does not return to the threshold after the first-level maintenance process is completed, the second-level maintenance process is started according to the type of sensor. For optical sensors, optical path self-cleaning or physical backwashing is performed, and for electrochemical sensors, electrode cleaning is performed.

[0069] This embodiment implements progressive maintenance through step S3. Specifically, when any sensor reading deviates from its corresponding pure water threshold, for example, a TOC sensor reading of 0.8 mg / L, far exceeding dtoc, the main control unit generates a trigger signal. The main control unit then initiates the first-level maintenance process for that sensor: Control the valves and pump body, and open the corresponding water circuit valve combination according to the type of abnormal sensor; such as Figure 2 As shown, if the TOC sensor malfunctions, turn on the water pump and open valves 3 and 4, while closing other valves, so that pure water flows only through the TOC sensor water circuit. If the turbidity sensor malfunctions, turn on the water pump and open valves 3 and 14, while closing other valves, so that pure water flows only through the turbidity sensor's water path. If the residual chlorine sensor malfunctions, turn on the water pump and open valves 3 and 9, while closing other valves, so that pure water flows only through the residual chlorine sensor circuit. If the conductivity sensor malfunctions, turn on the water pump and open valves 3 and 9, while closing other valves, so that pure water flows only through the conductivity sensor's water path. If the TDS sensor malfunctions, turn on the water pump and open valves 3 and 9, while closing other valves, so that pure water flows only through the TDS sensor water path; The sensor is continuously rinsed with pure water. The rinsing time can be dynamically adjusted according to the degree of contamination of the sensor. In this embodiment, the default rinsing time is 5 minutes, which can be extended to 30 minutes if the contamination is severe.

[0070] During the rinsing process, the main control unit continuously monitors the reading of the sensor and compares it with the corresponding pure water threshold in real time; taking the TOC sensor as an example, it continuously monitors whether its reading returns to the dtoc range.

[0071] Once the sensor reading returns to the threshold range and remains stable for 10 seconds, the main control unit determines that the first-level maintenance is successful, stops flushing, closes the valve, records the maintenance log to the storage unit, and ends the maintenance process. If the sensor reading does not return to the threshold range after 30 minutes of continuous flushing, it is determined to be deeply contaminated, and the second-level maintenance process is initiated.

[0072] The second-level maintenance process initiates the corresponding deep cleaning based on the sensor type. For devices including optical sensors, such as TOC sensors and turbidity sensors, a self-cleaning function for the optical path can be added. In some embodiments, such as... Figure 4 As shown, the optical path self-cleaning step for the optical sensor is as follows: S31. When calibrating the optical sensor using pure water, record the current light intensity signal value and use it as the reference value for the cleanliness of the mirror surface. S32. During subsequent monitoring, when the detected light intensity signal value attenuates beyond the preset optical path contamination threshold compared to the reference value, it is determined to be mirror contamination, and a physical backwashing cleaning process is triggered. Wherein, for example... Figure 5 As shown, the physical backwash cleaning process includes: S321, Control the water circuit switching, and introduce the pre-stored cleaning solution into the water circuit of the optical sensor for soaking; S322. After soaking for a preset time, drain the water and then rinse the water path of the optical sensor with pure water.

[0073] Specifically, when calibrating the optical sensor using pure water, the main control unit records the current light intensity signal value I0 and stores it in the storage unit as a reference value for the cleanliness of the mirror surface.

[0074] During subsequent normal monitoring, the system continuously monitors the light intensity signal value I. When the detected light intensity signal value I decreases beyond the preset light path contamination threshold (in this embodiment, the threshold is set to 20%) compared to the baseline value I0 of the mirror cleanliness, for example, when the light intensity signal value I decreases to 0.75 * the baseline value I0 of the mirror cleanliness, it is determined to be mirror contamination even if the water quality is normal at this time.

[0075] For devices that include optical sensors (such as TOC sensors and turbidity sensors), this embodiment adds an optical path self-cleaning function.

[0076] At this point, the system triggers a physical backwash cleaning process: Control the water circuit switching, close the inlet water pipe, open the cleaning fluid pipe, and introduce the pre-stored citric acid cleaning solution (concentration 5%) into the water circuit of the optical sensor; Soak the cleaning solution in the sensor flow cell for 30 minutes to dissolve organic matter and inorganic salt deposits on the mirror surface; After soaking, turn on the pure water pipeline and use pure water to thoroughly rinse the water circuit of the optical sensor until the pH value of the rinsing waste liquid returns to neutral and the light intensity signal value returns to more than 95% of the reference value.

[0077] For optical sensors (TOC sensor / turbidity sensor) in water quality monitoring equipment, this embodiment records the light intensity signal value during the pure water calibration stage as a benchmark for mirror cleanliness. Even if the water quality is normal in subsequent tests, if the light intensity signal attenuates beyond this benchmark, mirror contamination can be identified, triggering physical backwashing cleaning, such as soaking the water path in citric acid solution for a certain period followed by rinsing with pure water to achieve a cleaning effect.

[0078] For devices that include electrochemical sensors, the device also includes a miniature cleaning tank storing a specialized cleaning agent; such as Figure 6 As shown, the electrode cleaning step performed on the electrochemical sensor is as follows: S33. Use pure water to calibrate the electrochemical sensor, record the current data value, and use it as a reference value; S34. When the deviation of the data detected by the electrochemical sensor from the reference value exceeds the preset scaling threshold, it is determined that there is abnormal scaling on the electrode of the electrochemical sensor, and cleaning agent is automatically extracted from the micro cleaning tank and the electrode is circulated and rinsed. S35. After rinsing, rinse and calibrate the electrodes with pure water.

[0079] In this embodiment, for devices containing electrochemical sensors, such as residual chlorine sensors, conductivity sensors, and TDS sensors, a miniature cleaning tank is added inside the device, which stores a special cleaning agent.

[0080] The scaling threshold can be preset according to the sensor type. For example, for a conductivity sensor, when the deviation of the detected value from the reference value exceeds ±5%, it is determined to be abnormal scaling; for a residual chlorine sensor, when the response time exceeds the reference value by 20%, it is determined to be abnormal scaling.

[0081] When sensor detection data indicates abnormal scaling on the electrode, such as prolonged sensor response time, abnormal reading fluctuations, or a continuous deviation of the detection value from the reference value, the system automatically initiates the electrode cleaning procedure. 5 mL of cleaning agent was extracted from the micro cleaning tank and injected into the measuring cell of the electrochemical sensor; Start the circulation pump to circulate the cleaning agent over the electrode surface for 3 minutes; After rinsing, drain the cleaning waste liquid and then rinse the electrode repeatedly with pure water (at least 3 times) until the pH value of the rinsing solution is consistent with that of pure water. Finally, pure water was introduced for calibration to confirm that the electrode response had returned to normal.

[0082] For devices containing electrochemical sensors, such as residual chlorine sensors, conductivity sensors, and TDS sensors, this embodiment adds a small reagent compartment to the system to store special cleaning agents. When the diagnostic logic determines that the electrode has abnormal scaling, a small amount of cleaning agent is automatically extracted and circulated to rinse the electrode, followed by pure water rinsing and calibration.

[0083] If a sensor fails to return to normal after the second-level maintenance process, the sensor is locked, its status is marked as abnormal, and a sensor fault alarm is generated. For example, Figure 7 As shown, the step of locking the sensor includes: S36. Suspend the use of this sensor for collecting and reporting water quality monitoring data; S37. Display the sensor status as faulty or requiring maintenance on the device's local and cloud platform interfaces; S38. Subsequent water quality monitoring reports should mark the data from this sensor as invalid or for reference only.

[0084] This embodiment establishes a two-tiered progressive maintenance strategy: Level 1 maintenance, i.e., continuous flushing with pure water, is performed for light contamination; Level 2 maintenance, i.e., optical path self-cleaning or physical backwashing cleaning is performed for optical sensors, and electrode cleaning is performed for electrochemical sensors, is performed. This tiered strategy can quickly handle light contamination and effectively solve deep contamination problems. Simultaneously, the closed-loop verification and fault locking mechanism after Level 2 maintenance ensures that the maintenance effect is traceable and fault data can be blocked, guaranteeing the authenticity and reliability of the monitoring data. To verify the progressive maintenance effect of this invention, a comparative test was conducted between this invention and the traditional pure water flushing method. Based on the field test data, a recovery rate comparison bar chart was plotted, as shown below. Figure 8 As shown.

[0085] Depend on Figure 8 It can be seen that, under mild pollution conditions, the recovery rate of traditional flushing is about 80%, while the recovery rate of the progressive maintenance of this invention can reach 95%, an improvement of 15%; under moderate pollution conditions, the recovery rate of traditional flushing is about 50%, while the recovery rate of the progressive maintenance of this invention can reach 90%, an improvement of 40%; under severe pollution conditions, the recovery rate of traditional flushing is about 20%, while the recovery rate of the progressive maintenance of this invention can reach 80%, an improvement of 60%.

[0086] The above results show that the progressive maintenance strategy of the present invention has a significantly better recovery rate than the traditional pure water flushing method under all levels of pollution. In particular, under moderate and heavy pollution conditions, the recovery rate is improved by as much as 40% to 60%, which fully verifies the effectiveness of the graded maintenance strategy of the present invention.

[0087] To differentiate between water quality anomalies and sensor malfunctions, in some embodiments, such as Figure 9As shown, it also includes S4, a multi-sensor joint diagnostic step: When multiple sensors simultaneously detect values ​​that deviate from their corresponding pure water threshold values, the following judgment is performed: S41. Determine whether the number of sensors whose detected values ​​deviate from their corresponding pure water thresholds has reached or exceeded the preset group abnormal threshold. S42. If the number of the multiple sensors reaches or exceeds the preset group abnormality threshold, it is determined to be a water quality abnormality, a water quality abnormality alarm is generated, and the maintenance process for a single sensor is suspended. Specifically, if the number of deviating sensors reaches or exceeds the preset group abnormal threshold (in this embodiment, the threshold is set to 4), for example, if TOC, turbidity, residual chlorine, and conductivity are all abnormal, it is determined that the raw water quality has changed drastically, a water quality abnormality alarm is generated, and the automatic maintenance process for individual sensors is suspended to avoid unnecessary flushing.

[0088] S43. If the number of the multiple sensors is lower than the preset group anomaly threshold, then a maintenance process is performed on each sensor and it is determined to be a sensor-specific anomaly.

[0089] Among them, such as Figure 10 As shown, the preset threshold for cluster anomalies is dynamically adjusted based on the historical water quality fluctuation characteristics of the monitored water source: S421. Collect water quality monitoring data of the water source within a preset historical time period, and calculate the fluctuation frequency index and fluctuation amplitude index of the water quality monitoring data. S422. Based on the fluctuation frequency index and fluctuation amplitude index, the monitored water source is divided into multiple preset water quality stability levels. S423. Based on the water quality stability level, query and set the corresponding group anomaly threshold from the preset threshold mapping table; Each water quality stability level corresponds to a preset threshold for cluster anomalies, and the higher the water quality stability level, the lower the corresponding threshold for cluster anomalies.

[0090] Specifically, if the number of deviating sensors is lower than the group anomaly threshold, for example, only the TOC sensor is abnormal while other sensors are normal, it is determined to be a TOC sensor-specific anomaly, and maintenance procedures are performed on each abnormal sensor.

[0091] The threshold for cluster anomalies is not fixed but dynamically adjusted based on the historical water quality fluctuation characteristics of the monitored water source: The system collects water quality monitoring data of the monitored water source over the past 30 days, calculates the fluctuation frequency (number of times exceeding the limit per unit time) and fluctuation amplitude of each parameter, such as standard deviation / mean; Based on the fluctuation frequency and amplitude, the water source is divided into three water quality stability levels: stable, fluctuating, and highly fluctuating; In the preset threshold mapping table, stable water sources correspond to a lower cluster anomaly threshold (e.g., 3), and highly fluctuating water sources correspond to a higher cluster anomaly threshold (e.g., 5); When the water quality characteristics of the water source change, the system automatically reclassifies the level and updates the threshold.

[0092] During automatic maintenance, multiple indicators can be simultaneously assessed for abnormalities. If three or more indicators show abnormalities, an alarm can be triggered, indicating potential physical damage to the water quality monitoring equipment. In some embodiments, such as... Figure 11 As shown, it also includes S5, anomaly diagnosis and alarm steps: S51. During maintenance, monitor the abnormal status of multiple sensors simultaneously; S52. When the number of sensors in an abnormal state is detected to reach or exceed a preset threshold, an alarm message is generated and issued indicating that the device may have physical damage.

[0093] During automatic maintenance, if the main control unit simultaneously detects abnormal states of multiple sensors, such as TOC, turbidity, and residual chlorine all deviating from their thresholds, it needs to determine whether the problem is due to water quality abnormalities or equipment malfunction. When the number of sensors detected in abnormal states reaches or exceeds a preset threshold (in this embodiment, the threshold is set to 3), it is determined that the equipment may have physical damage, such as RO membrane rupture or pipeline leakage. An alarm message is generated and uploaded to the cloud platform via the communication unit, while a message "Equipment may be damaged, please inspect" is displayed on the local screen.

[0094] To verify the effectiveness of the multi-sensor joint diagnostic method of this invention, it was compared with the traditional single threshold judgment method. A graph illustrating the reduction in false positive rate was plotted based on field test data, as shown below. Figure 12 As shown in the figure, with a false positive rate of 100% for the traditional method, the figure demonstrates the reduction in false positive rate achieved by the multi-sensor joint diagnosis of the present invention.

[0095] Depend on Figure 12 It is known that traditional solutions have a high misjudgment rate when water quality anomalies are mistakenly identified as equipment malfunctions. This invention significantly reduces this misjudgment rate to approximately 4%. Furthermore, when equipment malfunctions are mistakenly identified as water quality anomalies, this invention reduces the misjudgment rate to approximately 2%. This demonstrates that through multi-sensor joint diagnosis, this invention can accurately distinguish between water quality anomalies and equipment malfunctions, effectively avoiding unnecessary maintenance or missed detections due to misjudgments, and significantly improving the accuracy and reliability of diagnosis.

[0096] For multiple water quality monitoring devices at the same customer site, network maintenance can be implemented. For example, if multiple devices use the same raw water but different purified water, after the data is uploaded to the cloud platform, the cloud platform will analyze multiple data sets in groups. If the values ​​of devices with the same water source are abnormal, maintenance can be performed on individual data streams to ensure consistency of values ​​for devices with the same water source. In some embodiments, such as Figure 13 As shown, it also includes S6 and network maintenance steps: S61. Connect multiple water quality monitoring devices located at the same site to the cloud platform for networking; S62. The cloud platform performs group analysis on monitoring data uploaded by multiple devices from the same water source; S63. When the analysis results show that the value of a single device has a systematic deviation from the values ​​of other devices with the same water source, the cloud platform sends an instruction to the single device to trigger the execution of the maintenance process, so that the monitoring data of the device is consistent with the data of other devices with the same water source.

[0097] This embodiment applies to situations where multiple devices are deployed at the same customer site. For example, three water quality monitoring devices, namely Device A, Device B, and Device C, are deployed on-site, all connected to a cloud platform for networking, and all three devices use the same source of raw water.

[0098] The cloud platform performs group analysis on the monitoring data uploaded by the three devices. Under normal circumstances, the readings of the three devices should be basically consistent. On a certain day, the cloud platform found that the TOC reading of device A was consistently high, while the readings of devices B and C were normal.

[0099] The cloud platform determined that device A had a systematic deviation, so it sent a remote command to device A to trigger the aforementioned maintenance process. After receiving the command, device A automatically started pure water rinsing and calibration. After maintenance was completed, the TOC reading of device A returned to the same level as devices B and C.

[0100] After water quality monitoring equipment is connected to the cloud platform, remote manual calibration can be performed on any device and any indicator based on actual conditions, minimizing the need for on-site personnel to handle problems. In some embodiments, such as Figure 14 As shown, it also includes S7 and remote maintenance steps: S71. Receive remote manual instructions via cloud platform; S72. Based on the remote manual instruction, independently trigger the execution of maintenance procedures for several sensors on a designated device.

[0101] When complex problems occur in on-site equipment, or when technicians wish to intervene manually, they can select a specific device (such as device A) and a specific sensor (such as a residual chlorine sensor) through the remote maintenance interface of the cloud platform, click the remote maintenance button, and the cloud platform will send remote manual instructions to device A. After receiving the instructions, device A will independently trigger and execute the maintenance process. The entire operation process is recorded in the operation log for easy traceability.

[0102] In order to accurately identify the type of pollution and perform targeted maintenance, in some embodiments, such as Figure 15 As shown, it also includes S8, intelligent diagnosis and maintenance steps based on a water pollution feature database: S81. A water pollution feature database is established in advance, which contains multiple types of pollution and their corresponding sensor signal change features; The water pollution feature database includes one or more of the following features and their corresponding maintenance procedures: Within the biological pollution monitoring window, when the cumulative increase in TOC value exceeds the first biological threshold and the cumulative decrease in residual chlorine value exceeds the second biological threshold, it is identified as biological pollution, and ultraviolet sterilization or ozone sterilization is initiated. Within the chemical pollution monitoring window, if the instantaneous increase in TOC value exceeds the chemical threshold while the residual chlorine and turbidity values ​​remain stable, it is identified as chemical pollution, and solvent cleaning is initiated. Within the particulate matter monitoring window, if the instantaneous increase in turbidity exceeds the particulate threshold and the variance of turbidity fluctuation exceeds the fluctuation threshold, while conductivity and residual chlorine remain stable, particulate matter contamination is identified, and a high-flow-rate backwash is initiated. When the turbidity value at a single monitoring sampling point exceeds the first bubble threshold, it is determined that there are bubbles or foreign objects in the sensor, and the sensor is emptied and then refilled with water. When the turbidity value at a single monitoring sampling point is lower than the second bubble threshold, it is determined that the calibration is abnormal or that bubbles in the filter cartridge have entered the sensor. After purging, water is added and recalibrated. When the turbidity value exceeds the third bubble threshold at multiple consecutive monitoring sampling points, it is determined that there is a partial cavity in the sensor water circuit, and the cavity is emptied and then water is refilled.

[0103] Specifically, through extensive experiments and the accumulation of field data, the sensor signal characteristics of different pollution types are summarized to establish a feature library. Among them, the sensor signal characteristics of biological pollution are a slow and continuous increase in TOC value, indicating the accumulation of organic matter produced by microbial reproduction and metabolism, while the residual chlorine gradually decreases (microbial cell material reaction consumes chlorine), and the diagnosis is the presence of biofilm growth in the water system; the sensor signal characteristics of chemical pollution are a sudden increase in TOC value, but no significant change in residual chlorine and turbidity, and the diagnosis is the intrusion of chemical pollutants such as organic solvents; the sensor signal characteristics of particulate matter pollution are a sudden increase in turbidity accompanied by violent fluctuations, a slight increase in TOC, and stable conductivity / residual chlorine, and the diagnosis is a surge in particulate matter in the pipeline; if the turbidity value is high at a certain point, such as greater than the standard value +0.2, it is judged that there may be air bubbles or foreign objects in the sensor module, and it is necessary to drain and refill water; if the turbidity value is low at a certain point, such as a value of 0 or negative, it is judged that it may be a calibration abnormality, that is, air bubbles in the filter cartridge have entered the sensor module and stayed there, and it is necessary to recalibrate with pure water; if the turbidity value is consistently high, such as greater than the standard value +0.2, it is judged that there may be some cavity in the water system of the sensor module, and it is necessary to drain and refill water.

[0104] S82. Monitor the detection data of each sensor in real time and extract its changing trend, time sequence relationship and fluctuation pattern; S83. Compare the extracted features with the features in the water pollution feature database to identify the pollution type; S84. Based on the identified pollution type, start the preset maintenance program corresponding to that pollution type.

[0105] Specifically, the system monitors the detection data from each sensor in real time, extracts its changing trends, temporal relationships, and fluctuation patterns, and compares them with features in the feature library. For example, if it detects that within a 4-hour monitoring window, the TOC value slowly rises from 0.5 mg / L to 0.9 mg / L, with a cumulative increase of 0.4 mg / L, exceeding the biological threshold of 0.3 mg / L, while the residual chlorine value slowly decreases from 0.3 mg / L to 0.1 mg / L, with a cumulative decrease of 0.2 mg / L, exceeding the consumption threshold of 0.15 mg / L, the system identifies this as biological contamination and initiates ultraviolet irradiation sterilization for 30 minutes or ozone sterilization.

[0106] For example, when the turbidity value suddenly increases from 1 NTU to 15 NTU within 1 minute, the instantaneous increase exceeds the particle threshold of 10 NTU, and the fluctuation variance exceeds the fluctuation threshold within the following 5 minutes, while the conductivity and residual chlorine values ​​remain stable, the system identifies it as particulate matter pollution and starts a high-flow-rate backwash, with the flow rate being 5 times the normal monitoring flow rate, lasting for 2 minutes.

[0107] To achieve the upgrade from passive response to proactive prediction, in some embodiments, such as Figure 16As shown, it also includes S9, the predictive maintenance step: S91. Monitor the detection values ​​of each sensor in real time and calculate the rate of change of the detection values ​​of each sensor within a preset time window. Specifically, the rate of change includes an increase rate and a decrease rate; the preset time window is dynamically adjusted according to the type of sensor; wherein, the preset time window for TOC sensor and turbidity sensor is shorter than the preset time window for residual chlorine sensor and conductivity sensor.

[0108] In this embodiment, the time window of different sensors can be dynamically adjusted according to their characteristics. For TOC and turbidity sensors, which have fast response and are prone to fluctuation, the time window is set to be shorter, such as 1 hour; for residual chlorine and conductivity sensors, which change slowly, the time window is set to be longer, such as 24 hours.

[0109] S92. When the rate of change of any sensor exceeds the preset rate threshold for that sensor, and the current detection value of that sensor has not exceeded its corresponding pure water threshold, a preventive maintenance warning is generated, or a maintenance process for that sensor is actively triggered when the equipment is idle.

[0110] The system monitors the detection values ​​of each sensor in real time and calculates their rate of change within a preset time window. For example, for the TOC sensor, the time window is set to 24 hours, and its average hourly rate of increase is calculated.

[0111] When the TOC sensor's rise rate is detected to be 0.02 mg / L·h, exceeding the preset rate threshold of 0.015 mg / L·h, but the current detected value of 0.45 mg / L has not yet exceeded the pure water threshold of 0.5 mg / L, the system generates a preventative maintenance warning: the TOC sensor drift rate is too fast and is expected to exceed the limit in 48 hours, so early maintenance is recommended.

[0112] Meanwhile, the system detected that the device was currently in an idle state, i.e., without any monitoring tasks, so it proactively triggered an automatic calibration process for the TOC sensor to calibrate it back to normal in advance, thus avoiding subsequent data exceeding limits.

[0113] To verify the predictive maintenance effectiveness of this invention, it was compared with traditional reactive maintenance methods. Based on six months of monitoring statistics (n=30 devices) in a certain area, a slope chart of the improvement of key predictive maintenance indicators was plotted, as shown below. Figure 17 As shown.

[0114] Depend on Figure 17It is evident that by adopting the predictive maintenance of this invention, the number of sudden failures can be reduced from 4 times per year to 1 time per year, reducing unplanned downtime by approximately 10 days annually. The number of times technicians need to be on-site is reduced to near zero, the effective data acquisition rate is close to 100%, the sensor maintenance cycle is approximately once per month, the fault response time is less than 1 day, and the mean time between failures (MTBF) of the equipment is increased to 500 hours.

[0115] The above results demonstrate that the predictive maintenance strategy of this invention, by monitoring the rate of change of sensor values ​​in real time, proactively triggers maintenance before a failure occurs, effectively avoiding sudden failures and unplanned downtime, and significantly improving the reliability and data continuity of the equipment.

[0116] This embodiment provides an automatic cleaning and maintenance control method for water quality monitoring equipment. Utilizing the equipment's built-in pure water production component, and using pure water as a unified measurement anchor point, it achieves automatic diagnosis and calibration of the sensor's status. In daily operation, no on-site technical personnel are required, and no standard solution needs to be prepared, completely changing the traditional model that relies on manual on-site maintenance, significantly reducing operation and maintenance costs and manpower input.

[0117] To address deep contamination issues such as chemical pollution and scale buildup on electrochemical sensor electrodes, this embodiment pre-fills the equipment with dedicated cleaning solvents and cleaning agents, automatically performing solvent cleaning or electrode cleaning when needed. This tiered strategy of using pure water for routine maintenance and solvents for deep cleaning ensures both convenience for daily maintenance and effective resolution of complex contamination problems.

[0118] This embodiment effectively solves the problem of pure water reference value drift caused by aging of filter components or changes in equipment deployment location by monitoring the operating status parameters of pure water production components in real time, such as the usage time of filter components, cumulative water production, and influent water quality, and dynamically adjusting and updating the pure water threshold corresponding to each sensor. It also avoids false alarms and calibration failures caused by static thresholds.

[0119] This embodiment establishes a progressive maintenance strategy consisting of a first-stage pure water rinsing and a second-stage deep cleaning. For light contamination, a simple pure water rinse is sufficient for quick recovery; for deep contamination, targeted deep cleaning is initiated based on the sensor type. This progressive maintenance mechanism saves resources while ensuring that deep contamination is effectively addressed.

[0120] This embodiment employs differentiated cleaning methods to address the different contamination characteristics of optical and electrochemical sensors: optical sensors undergo optical path self-cleaning or physical backwashing, while electrochemical sensors undergo electrode cleaning, ensuring that all types of sensors receive the most effective deep cleaning.

[0121] When a sensor malfunction is detected, this embodiment automatically switches the water path and only flushes the malfunctioning sensor with pure water or solvent until it returns to normal. This precise maintenance method avoids unnecessary full-system flushing, saves pure water and energy, and ensures that the maintenance process does not affect the normal operation of other sensors.

[0122] Example 2 Based on the same concept, this embodiment also provides a water quality monitoring system that applies the automatic cleaning and maintenance control method provided in Embodiment 1. For a detailed description of the automatic cleaning and maintenance control method provided in Embodiment 1, please refer to the corresponding description in the above method embodiments, which will not be repeated here.

[0123] It is understood that the water quality monitoring system provided in this embodiment includes hardware structures and / or software modules corresponding to each function in order to achieve the above-mentioned functions. Combining the units and algorithm steps of the examples disclosed in this embodiment, this embodiment can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solution of this embodiment.

[0124] A water quality monitoring system, comprising: One or more water quality monitoring devices, the devices including pure water production components, multiple sensors, valves and pumps that can control water circuit switching, as well as miniature cleaning tanks and sterilization devices; The cloud platform is communicatively connected to the water quality monitoring equipment. The system is configured to execute the above-described automatic cleaning and maintenance control method. For a detailed description of the method, please refer to the corresponding description in the above method embodiments; it will not be repeated here.

[0125] The water quality monitoring system of this embodiment may include the following processes: The pure water anchor point self-diagnosis module is used to control the pure water production component built into the water quality monitoring equipment to generate pure water, and to use the pure water as a measurement anchor point to enter the water path where each sensor is located. Based on the comparison results of the detection values ​​of each sensor in the pure water environment with the preset pure water threshold, it is determined whether each sensor is in the normal operating range. The dynamic threshold configuration module is used to monitor the operating status parameters of the pure water production components, and dynamically adjust and update the pure water threshold corresponding to each sensor according to the operating status parameters, so as to adapt to the changes in the pure water reference value caused by the aging of the pure water production components or the change of equipment deployment location. The progressive self-maintenance module is used to execute the first-level maintenance process when the detection value of any sensor deviates from its corresponding pure water threshold, that is, to continuously rinse the sensor with pure water; if the detection value still does not return to the threshold after the first-level maintenance process is completed, the second-level maintenance process is started according to the type of sensor, that is, optical path self-cleaning or physical backwashing cleaning is performed for optical sensors, and electrode cleaning is performed for electrochemical sensors.

[0126] Based on the technical solutions of the above embodiments, optionally, the sensor includes one or more of the following: a water quality sensor for detecting TOC value, a turbidity sensor, a residual chlorine sensor, a conductivity sensor, and a TDS sensor; Furthermore, the pure water threshold includes: a constant preset for the water quality sensor, a constant preset for the turbidity sensor, a constant preset for the residual chlorine sensor, a constant preset for the conductivity sensor, and a constant preset for the TDS sensor.

[0127] Based on the technical solutions of the above embodiments, optionally, the pure water production assembly includes a pretreatment filter cartridge and a filtration assembly connected in sequence; the pretreatment filter cartridge is used to remove particulate impurities, residual chlorine and organic matter from the raw water, and the filtration assembly is used to allow water molecules to pass through to generate pure water; The operating status parameters include one or more of the following: the usage time of the filter component, the cumulative water production of the filter component, and the influent water quality of the filter component.

[0128] Based on the technical solutions of the above embodiments, optionally, the step of performing optical path self-cleaning for the optical sensor is as follows: When calibrating the optical sensor using pure water, the current light intensity signal value is recorded and used as the reference value for the cleanliness of the mirror surface. During subsequent monitoring, when the light intensity signal value is detected to have decreased by more than the preset light path contamination threshold compared to the reference value, it is determined to be mirror contamination, and a physical backwash cleaning process is triggered.

[0129] Based on the technical solutions of the above embodiments, optionally, the physical backwashing cleaning process includes: Control the water circuit switching to introduce the pre-stored cleaning solution into the water circuit of the optical sensor for soaking; After soaking for a preset time, the water is drained, and then the water path of the optical sensor is rinsed with pure water.

[0130] Based on the technical solutions of the above embodiments, optionally, the electrode cleaning step for the electrochemical sensor is performed as follows: The electrochemical sensor was calibrated using pure water, the current data value was recorded, and it was used as a reference value. When the deviation of the data detected by the electrochemical sensor from the reference value exceeds the preset scaling threshold, it is determined that there is abnormal scaling on the electrode of the electrochemical sensor. The cleaning agent is automatically extracted from the micro cleaning tank containing special cleaning agent and the electrode is circulated and rinsed. After rinsing, the electrodes are rinsed and calibrated again using pure water.

[0131] Based on the technical solution of the above embodiments, optionally, when the sensor still fails to return to the threshold after the second-level maintenance process, the sensor is locked, its status is marked as abnormal, and a sensor fault alarm is generated.

[0132] Based on the technical solution of the above embodiments, optionally, the step of locking the sensor includes: The use of this sensor for collecting and reporting water quality monitoring data is suspended. The sensor status is displayed as faulty or requiring maintenance on both the local device interface and the cloud platform interface. Subsequent water quality monitoring reports marked the data from this sensor as invalid or for reference only.

[0133] Optionally, based on the technical solution of the above embodiments, a multi-sensor joint diagnostic step is also included: When multiple sensors simultaneously detect values ​​that deviate from their corresponding pure water threshold values, the following judgment is performed: If the number of the multiple sensors reaches or exceeds the preset group anomaly threshold, it is determined to be a water quality anomaly, a water quality anomaly alarm is generated, and the maintenance process for the individual sensor is suspended. If the number of the multiple sensors is lower than the preset group anomaly threshold, a maintenance process is performed on each sensor separately, and the sensor is determined to be a sensor-specific anomaly.

[0134] Based on the technical solution of the above embodiments, optionally, the preset abnormal threshold for mass outbreaks is dynamically adjusted according to the historical water quality fluctuation characteristics of the monitored water source: Collect water quality monitoring data of the water source within a preset historical time period, and calculate the fluctuation frequency index and fluctuation amplitude index of the water quality monitoring data; Based on the fluctuation frequency index and fluctuation amplitude index, the monitored water source is divided into several preset water quality stability levels; Based on the water quality stability level, the corresponding group anomaly threshold is queried from the preset threshold mapping table and set. Each water quality stability level corresponds to a preset threshold for cluster anomalies, and the higher the water quality stability level, the lower the corresponding threshold for cluster anomalies.

[0135] Optionally, based on the technical solution of the above embodiments, an anomaly diagnosis and alarm step is also included: During maintenance, the abnormal status of multiple sensors is monitored simultaneously; When the number of sensors in an abnormal state is detected to reach or exceed a preset threshold, an alarm message is generated and issued indicating that the device may have physical damage.

[0136] Optionally, based on the technical solution of the above embodiments, a network maintenance step is also included: Multiple water quality monitoring devices located at the same site are connected to the cloud platform for networking; The cloud platform performs group analysis on monitoring data uploaded by multiple devices from the same water source; When the analysis results show that the value of a single device deviates systematically from the values ​​of other devices from the same water source, the cloud platform sends a command to that single device to trigger the execution of a maintenance process, so that the monitoring data of that device is consistent with the data of other devices from the same water source.

[0137] Optionally, based on the technical solution of the above embodiments, a remote maintenance step is also included: Receive remote human instructions via cloud platform; Based on the remote manual instructions, maintenance procedures are independently triggered for several sensors on a designated device.

[0138] Based on the technical solutions of the above embodiments, optionally, an intelligent diagnosis and maintenance step based on a water pollution feature database is also included: A water pollution feature database is pre-established, which contains various pollution types and their corresponding sensor signal change characteristics; Real-time monitoring of the detection data from each sensor, extracting its changing trends, temporal relationships, and fluctuation patterns; The extracted features are compared with the features in the water pollution feature database to identify the pollution type; Based on the identified pollution type, the preset maintenance procedure corresponding to that pollution type is initiated.

[0139] Based on the technical solutions of the above embodiments, optionally, the water pollution feature database includes one or more of the following features and their corresponding maintenance procedures: Within the biological pollution monitoring window, when the cumulative increase in TOC value exceeds the first biological threshold and the cumulative decrease in residual chlorine value exceeds the second biological threshold, it is identified as biological pollution, and ultraviolet sterilization or ozone sterilization is initiated. Within the chemical pollution monitoring window, if the instantaneous increase in TOC value exceeds the chemical threshold while the residual chlorine and turbidity values ​​remain stable, it is identified as chemical pollution, and solvent cleaning is initiated. Within the particulate matter monitoring window, if the instantaneous increase in turbidity exceeds the particulate threshold and the variance of turbidity fluctuation exceeds the fluctuation threshold, while conductivity and residual chlorine remain stable, particulate matter contamination is identified, and a high-flow-rate backwash is initiated. When the turbidity value at a single monitoring sampling point exceeds the first bubble threshold, it is determined that there are bubbles or foreign objects in the sensor, and the sensor is emptied and then refilled with water. When the turbidity value at a single monitoring sampling point is lower than the second bubble threshold, it is determined that the calibration is abnormal or that bubbles in the filter cartridge have entered the sensor. After purging, water is added and recalibrated. When the turbidity value exceeds the third bubble threshold at multiple consecutive monitoring sampling points, it is determined that there is a partial cavity in the sensor water circuit, and the cavity is emptied and then water is refilled.

[0140] Optionally, based on the technical solution of the above embodiments, a predictive maintenance step is also included: Real-time monitoring of the detection values ​​of each sensor, and calculation of the rate of change of the detection values ​​of each sensor within a preset time window; When the rate of change of any sensor exceeds the preset rate threshold for that sensor, and the current detection value of that sensor has not exceeded its corresponding pure water threshold, a preventive maintenance warning is generated, or a maintenance process for that sensor is proactively triggered when the equipment is idle.

[0141] Based on the technical solutions of the above embodiments, optionally, the rate of change includes an increase rate and a decrease rate; the preset time window is dynamically adjusted according to the type of sensor; The time window preset for the TOC sensor and turbidity sensor is shorter than the time window preset for the residual chlorine sensor and conductivity sensor.

[0142] This embodiment provides a water quality monitoring system that utilizes a built-in pure water production component, using pure water as a unified measurement anchor point to achieve automatic diagnosis and calibration of sensor status. In daily operation, no on-site technical personnel are required, and no standard solution needs to be prepared, completely changing the traditional model that relies on manual on-site maintenance and significantly reducing operation and maintenance costs and manpower input.

[0143] To address deep contamination issues such as chemical pollution and scale buildup on electrochemical sensor electrodes, this embodiment pre-fills the equipment with dedicated cleaning solvents and cleaning agents, automatically performing solvent cleaning or electrode cleaning when needed. This tiered strategy of using pure water for routine maintenance and solvents for deep cleaning ensures both convenience for daily maintenance and effective resolution of complex contamination problems.

[0144] This embodiment effectively solves the problem of pure water reference value drift caused by aging of filter components or changes in equipment deployment location by monitoring the operating status parameters of pure water production components in real time, such as the usage time of filter components, cumulative water production, and influent water quality, and dynamically adjusting and updating the pure water threshold corresponding to each sensor. It also avoids false alarms and calibration failures caused by static thresholds.

[0145] This embodiment establishes a progressive maintenance strategy consisting of a first-stage pure water rinsing and a second-stage deep cleaning. For light contamination, a simple pure water rinse is sufficient for quick recovery; for deep contamination, targeted deep cleaning is initiated based on the sensor type. This progressive maintenance mechanism saves resources while ensuring that deep contamination is effectively addressed.

[0146] This embodiment employs differentiated cleaning methods to address the different contamination characteristics of optical and electrochemical sensors: optical sensors undergo optical path self-cleaning or physical backwashing, while electrochemical sensors undergo electrode cleaning, ensuring that all types of sensors receive the most effective deep cleaning.

[0147] When a sensor malfunction is detected, this embodiment automatically switches the water path and only flushes the malfunctioning sensor with pure water or solvent until it returns to normal. This precise maintenance method avoids unnecessary full-system flushing, saves pure water and energy, and ensures that the maintenance process does not affect the normal operation of other sensors.

[0148] Example 3 A computer device 100, such as Figure 18 As shown, the device includes a memory 110, a processor 120, and a computer program 130 stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of an automatic cleaning and maintenance control method for a water quality monitoring device. For a detailed description of the method, please refer to the corresponding description in the above method embodiments; it will not be repeated here.

[0149] Example 4 A computer-readable storage medium, such as Figure 19 As shown, a computer program is stored thereon. When executed by a processor, the computer program implements the steps of an automatic cleaning and maintenance control method for a water quality monitoring device. For a detailed description of the method, please refer to the corresponding description in the above method embodiments, which will not be repeated here.

[0150] The number of devices and processing scale described herein are for the purpose of simplifying the description of the invention. Applications, modifications, and variations of the invention will be readily apparent to those skilled in the art.

[0151] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

[0152] The apparatus, computer device, and non-volatile computer storage medium and method provided in the embodiments of this specification are corresponding. Therefore, the apparatus, computer device, and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, computer device, and non-volatile computer storage medium will not be repeated here.

[0153] Those skilled in the art will also know that, besides implementing the controller in the form of purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller take the form of logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices included within it for implementing various functions can also be considered structures within that hardware component. Alternatively, the devices for implementing various functions can be considered as both software units implementing the method and structures within a hardware component.

[0154] The systems, apparatuses, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above apparatuses are described separately as various units based on their functions. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0155] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0160] This specification may be described in the general context of computer-executable instructions, such as program units, that are executed by a computer. Generally, program units include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification may also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program units may reside in local and remote computer storage media, including storage devices.

[0161] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0162] The above description is merely an embodiment of this specification and is not intended to limit the scope of one or more embodiments of this specification. Various modifications and variations can be made to one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of one or more embodiments of this specification.

Claims

1. An automatic cleaning and maintenance control method for water quality monitoring equipment, characterized in that, Includes the following steps: The pure water production component built into the water quality monitoring equipment generates pure water, which is then used as a measurement anchor point and introduced into the water path where each sensor is located. Based on the comparison between the detection values ​​of each sensor in the pure water environment and the preset pure water threshold, it is determined whether each sensor is in the normal operating range. Monitor the operating status parameters of the pure water production components, and dynamically adjust and update the pure water threshold corresponding to each sensor according to the operating status parameters to adapt to changes in the pure water reference value caused by aging of the pure water production components or changes in equipment deployment location. When the detection value of any sensor deviates from its corresponding pure water threshold, the first-level maintenance procedure is executed, which is to continuously flush the sensor with pure water. If the measured value still does not return to the threshold after the first-level maintenance process is completed, the second-level maintenance process is initiated according to the type of sensor. For optical sensors, optical path self-cleaning or physical backwashing cleaning is performed, and for electrochemical sensors, electrode cleaning is performed.

2. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, The sensor includes one or more of the following: a water quality sensor for detecting TOC values, a turbidity sensor, a residual chlorine sensor, a conductivity sensor, and a TDS sensor; Furthermore, the pure water threshold includes: a constant preset for the water quality sensor, a constant preset for the turbidity sensor, a constant preset for the residual chlorine sensor, a constant preset for the conductivity sensor, and a constant preset for the TDS sensor.

3. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 2, characterized in that, The pure water production assembly includes a pretreatment filter cartridge and a filtration assembly connected in sequence; the pretreatment filter cartridge is used to remove particulate impurities, residual chlorine and organic matter from the raw water, and the filtration assembly is used to allow water molecules to pass through to generate pure water; The operating status parameters include one or more of the following: the usage time of the filter component, the cumulative water production of the filter component, and the influent water quality of the filter component.

4. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, The optical path self-cleaning step for the optical sensor is as follows: When calibrating the optical sensor using pure water, the current light intensity signal value is recorded and used as the reference value for the cleanliness of the mirror surface. During subsequent monitoring, when the light intensity signal value is detected to have decreased by more than the preset light path contamination threshold compared to the reference value, it is determined to be mirror contamination, and a physical backwash cleaning process is triggered.

5. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 4, characterized in that, The physical backwash cleaning process includes: Control the water circuit switching to introduce the pre-stored cleaning solution into the water circuit of the optical sensor for soaking; After soaking for a preset time, the water is drained, and then the water path of the optical sensor is rinsed with pure water.

6. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 4, characterized in that, The electrode cleaning step is performed on the electrochemical sensor. The electrochemical sensor was calibrated using pure water, the current data value was recorded, and it was used as a reference value. When the deviation of the data detected by the electrochemical sensor from the reference value exceeds the preset scaling threshold, it is determined that there is abnormal scaling on the electrode of the electrochemical sensor. The cleaning agent is automatically extracted from the micro cleaning tank containing special cleaning agent and the electrode is circulated and rinsed. After rinsing, the electrodes are rinsed and calibrated again using pure water.

7. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 6, characterized in that, If the sensor fails to return to the threshold after the second-level maintenance process, the sensor is locked, its status is marked as abnormal, and a sensor fault alarm is generated.

8. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 7, characterized in that, The step of locking the sensor includes: The use of this sensor for collecting and reporting water quality monitoring data is suspended. The sensor status is displayed as faulty or requiring maintenance on both the local device interface and the cloud platform interface. Subsequent water quality monitoring reports marked the data from this sensor as invalid or for reference only.

9. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes a multi-sensor joint diagnostic step: When multiple sensors simultaneously detect values ​​that deviate from their corresponding pure water threshold values, the following judgment is performed: If the number of the multiple sensors reaches or exceeds the preset group anomaly threshold, it is determined to be a water quality anomaly, a water quality anomaly alarm is generated, and the maintenance process for the individual sensor is suspended. If the number of the multiple sensors is lower than the preset group anomaly threshold, a maintenance process is performed on each sensor separately, and the sensor is determined to be a sensor-specific anomaly.

10. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 9, characterized in that, The preset threshold for cluster anomalies is dynamically adjusted based on the historical water quality fluctuation characteristics of the monitored water source: Collect water quality monitoring data of the water source within a preset historical time period, and calculate the fluctuation frequency index and fluctuation amplitude index of the water quality monitoring data; Based on the fluctuation frequency index and fluctuation amplitude index, the monitored water source is divided into several preset water quality stability levels; Based on the water quality stability level, the corresponding group anomaly threshold is queried from the preset threshold mapping table and set. Each water quality stability level corresponds to a preset threshold for cluster anomalies, and the higher the water quality stability level, the lower the corresponding threshold for cluster anomalies.

11. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes abnormal diagnosis and alarm procedures: During maintenance, the abnormal status of multiple sensors is monitored simultaneously; When the number of sensors in an abnormal state is detected to reach or exceed a preset threshold, an alarm message is generated and issued indicating that the device may have physical damage.

12. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes network maintenance steps: Multiple water quality monitoring devices located at the same site are connected to the cloud platform for networking; The cloud platform performs group analysis on monitoring data uploaded by multiple devices from the same water source; When the analysis results show that the value of a single device deviates systematically from the values ​​of other devices from the same water source, the cloud platform sends a command to that single device to trigger the execution of a maintenance process, so that the monitoring data of that device is consistent with the data of other devices from the same water source.

13. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes remote maintenance steps: Receive remote human instructions via cloud platform; Based on the remote manual instructions, maintenance procedures are independently triggered for several sensors on a designated device.

14. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes intelligent diagnosis and maintenance steps based on a water pollution feature database: A water pollution feature database is pre-established, which contains various pollution types and their corresponding sensor signal change characteristics; Real-time monitoring of the detection data from each sensor, extracting its changing trends, temporal relationships, and fluctuation patterns; The extracted features are compared with the features in the water pollution feature database to identify the pollution type; Based on the identified pollution type, the preset maintenance procedure corresponding to that pollution type is initiated.

15. The automatic cleaning and maintenance control method for a water quality monitoring device as described in claim 14, characterized in that, The water pollution feature database includes one or more of the following features and their corresponding maintenance procedures: Within the biological pollution monitoring window, when the cumulative increase in TOC value exceeds the first biological threshold and the cumulative decrease in residual chlorine value exceeds the second biological threshold, it is identified as biological pollution, and ultraviolet sterilization or ozone sterilization is initiated. Within the chemical pollution monitoring window, if the instantaneous increase in TOC value exceeds the chemical threshold while the residual chlorine and turbidity values ​​remain stable, it is identified as chemical pollution, and solvent cleaning is initiated. Within the particulate matter monitoring window, if the instantaneous increase in turbidity exceeds the particulate threshold and the variance of turbidity fluctuation exceeds the fluctuation threshold, while conductivity and residual chlorine remain stable, particulate matter contamination is identified, and a high-flow-rate backwash is initiated. When the turbidity value at a single monitoring sampling point exceeds the first bubble threshold, it is determined that there are bubbles or foreign objects in the sensor, and the sensor is emptied and then refilled with water. When the turbidity value at a single monitoring sampling point is lower than the second bubble threshold, it is determined that the calibration is abnormal or that bubbles in the filter cartridge have entered the sensor. After purging, water is added and recalibrated. When the turbidity value exceeds the third bubble threshold at multiple consecutive monitoring sampling points, it is determined that there is a partial cavity in the sensor water circuit, and the cavity is emptied and then water is refilled.

16. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 1, characterized in that, It also includes predictive maintenance steps: Real-time monitoring of the detection values ​​of each sensor, and calculation of the rate of change of the detection values ​​of each sensor within a preset time window; When the rate of change of any sensor exceeds the preset rate threshold for that sensor, and the current detection value of that sensor has not exceeded its corresponding pure water threshold, a preventive maintenance warning is generated, or a maintenance process for that sensor is automatically triggered when the equipment is idle.

17. The automatic cleaning and maintenance control method for water quality monitoring equipment as described in claim 16, characterized in that, The rate of change includes the rate of increase and the rate of decrease; the preset time window is dynamically adjusted according to the type of sensor. The time window preset for the TOC sensor and turbidity sensor is shorter than the time window preset for the residual chlorine sensor and conductivity sensor.

18. A water quality monitoring system, characterized in that, include: One or more water quality monitoring devices, the devices including pure water production components, multiple sensors, valves and pumps that can control water circuit switching, as well as miniature cleaning tanks and sterilization devices; The cloud platform is communicatively connected to the water quality monitoring equipment. The system is configured to perform the automatic cleaning and maintenance control method as described in any one of claims 1 to 17.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the automatic cleaning and maintenance control method as described in any one of claims 1 to 17.

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