A monitoring and operation and maintenance method and system for a water-saving ecological toilet

Abstract

The application relates to a monitoring and operation method and system for a water-saving ecological toilet. The method comprises the following steps: acquiring operation state data collected by sensors arranged at each functional unit of the ecological toilet, wherein the data comprises water level and water quality data of a rainwater collecting unit, pressure and flow data of a negative pressure toilet unit, temperature, pH and oxidation-reduction potential data of a microorganism treatment unit, and nutrient concentration data of a resource recycling unit; performing calculation and analysis on the data to obtain operation evaluation results of each unit; comparing the results with preset threshold values to judge operation state grades; and executing operation strategies of sending early warning information or automatically adjusting associated operation parameters according to different grades. Compared with the prior art, the application realizes all-weather automatic monitoring and intelligent operation through closed-loop control of data acquisition, fusion calculation, state grading and strategy response, and overcomes the defects of manual inspection lag and inaccurate regulation and control.

Description

Technical Field

[0001] This invention relates to the fields of environmental engineering and automated monitoring and control technology, and in particular to a monitoring and operation and maintenance method and an intelligent monitoring and operation and maintenance device for water-saving ecological toilets. Background Technology

[0002] With the increasing severity of water shortages and rising environmental protection requirements, water-saving ecological toilets are being used more and more widely in rural areas, tourist attractions, and high-altitude regions. These toilets typically integrate multiple functional units such as rainwater collection, negative pressure sewage discharge, microbial degradation treatment, and resource recycling, forming a complex ecological-electromechanical coupled system.

[0003] In existing technologies, the operation and maintenance of these ecological toilets mainly rely on regular manual inspections. For example, maintenance personnel need to rely on experience to visually inspect or carry handheld testing instruments to check the rainwater collection tank level, the airtightness of the negative pressure pipeline of the toilet, the temperature and humidity and filter media status in the microbial reactor, and the performance of the recovered fertilizer. However, this operation and maintenance model has significant drawbacks: First, the timeliness of fault detection is extremely poor. Early signs such as micro-leakage in the negative pressure pipeline or decreased microbial activity are difficult to detect through manual inspections and are often only discovered after the unit has completely failed or produced a strong odor, resulting in high repair costs and low toilet online rate during the period. Second, there is a lack of data-driven precise control methods. For example, the operating parameters of the microbial treatment unit (temperature, pH, oxidation-reduction potential, etc.) fluctuate dynamically due to environmental factors and usage frequency. Manual adjustment of related parameters such as aeration rate in real time and with precision is not possible to maintain the optimal activity of the microbial community, resulting in unstable sewage treatment efficiency and resource recovery product quality, and failing to consistently meet high requirements such as chemical oxygen demand removal rate or agricultural fertilizer standards.

[0004] While some research has attempted to introduce intelligent operation and maintenance methods, such as patent application CN121937270A which proposes a self-sustaining operation and maintenance method for sewer-free public toilets in high-altitude areas based on intelligent optimization, using long short-term memory networks and deep Q-network algorithms to comprehensively assess ecological health, energy sustainability, and treatment efficiency to achieve self-sustaining operation and maintenance, this approach mainly focuses on energy self-sustainability and ecological health prediction in the special environment of high-altitude areas. It does not comprehensively cover the real-time operational status monitoring of multiple functional units in water-saving ecological toilets, such as rainwater collection, negative pressure sewage discharge, microbial treatment, and resource recycling, and lacks precise hierarchical assessment and differentiated control mechanisms for the operational status of each unit. Another example is patent application CN121639427A, which proposes an intelligent operation and maintenance management method for rural toilet renovation based on the Internet of Things. This method uses rule-based collaborative reasoning and dynamic threshold adjustment to provide early warnings of faults such as flushing failure and sewage pump malfunctions. However, this solution focuses on fault identification and cleaning decisions in traditional toilet renovation, and fails to achieve data-driven precise parameter adjustment for key operating parameters (such as temperature, pH, and ORP) of each functional unit (such as the microbial reactor) of the ecological toilet.

[0005] Therefore, how to achieve automatic, real-time, and accurate monitoring of the operational status of multiple functional units in water-saving ecological toilets, and make intelligent graded responses based on the monitoring results to replace inefficient manual inspections and experience-based control, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a monitoring and operation and maintenance method and system for water-saving ecological toilets. Through closed-loop control of data acquisition, fusion calculation, status classification and strategy response, it realizes all-weather automatic monitoring and intelligent operation and maintenance, and overcomes the shortcomings of manual inspection being lagging and inaccurate.

[0007] The objective of this invention can be achieved through the following technical solutions: The first aspect of this invention provides a method for monitoring and maintaining water-saving ecological toilets, comprising the following steps: The system acquires operational status data collected by sensor groups located at multiple functional units of the ecological toilet. The operational status data is calculated and analyzed to obtain the operational evaluation results of each functional unit; Based on the comparison between the operation evaluation results and the preset threshold range, the operation status level of each functional unit is determined. The functional unit includes at least one of the following: rainwater collection unit, negative pressure toilet unit, microbial treatment unit, and resource recycling unit. Based on the operating status level, the operation and maintenance strategy corresponding to the operating status level is executed. The operation and maintenance strategy includes sending early warning information or adjusting the associated operating parameters of the corresponding functional unit. The operational status data includes at least one of the following: water level data and / or water quality data of the rainwater collection unit; pressure data and / or flow rate data of the negative pressure toilet unit; temperature data, pH data and / or oxidation-reduction potential data of the microbial treatment unit; and nutrient concentration data of the resource recovery unit.

[0008] Furthermore, the operational status data is calculated and analyzed to obtain the operational evaluation results of each functional unit, specifically including: For the microbial treatment unit, the temperature data, pH data, and redox potential data are input into a preset multi-parameter fusion model to calculate the microbial activity index, which reflects the activity of the microorganisms, and is used as the operation evaluation result. And / or, For the rainwater harvesting unit, the rainwater replenishment efficiency is calculated based on the rate of change of the water level data, and this efficiency is used as the operational evaluation result.

[0009] Furthermore, the calculation and analysis of the operational status data to obtain the operational evaluation results of each functional unit specifically includes: For the negative pressure toilet unit, an evaluation value reflecting the sealing performance of the negative pressure system is calculated based on the fluctuation curve of the pressure data, and this value is used as the operational evaluation result. And / or, For the resource recovery unit, a grade value reflecting the quality of the recovered products is calculated based on the nutrient concentration data, and this grade value is used as the operational evaluation result.

[0010] Furthermore, the multi-parameter fusion model is as follows: MAI=α×f(T)+β×g(pH)+γ×h(ORP) Wherein, MAI is the microbial activity index, T, pH, and ORP are the temperature data, pH data, and redox potential data, respectively, f(T), g(pH), and h(ORP) are the temperature influence function, pH influence function, and redox potential influence function, respectively, and α, β, and γ are preset weighting coefficients.

[0011] Furthermore, the operational status levels are divided into normal, alert, and abnormal; The step of executing the operation and maintenance strategy corresponding to the operation and maintenance level based on the operation and maintenance level includes: When the operating status level is abnormal, a warning message is sent to the operation and maintenance terminal. When the operating status level is "Caution", the associated operating parameters of the corresponding functional unit are automatically adjusted.

[0012] Furthermore, the automatic adjustment of the associated operating parameters of the corresponding functional units includes at least one of the following operations: Adjust the aeration rate of the microbial treatment unit; Adjust the working pressure threshold of the negative pressure toilet unit; Start the standby pump of the rainwater collection unit; Increase the stirring frequency of the resource recycling unit.

[0013] Furthermore, the preset threshold range is dynamically adjusted based on the design parameters and historical operating data of each functional unit. The design parameters include the equipment's rated power and / or standard operating temperature range. The dynamic adjustment includes calculating and updating the upper and / or lower limits of the preset threshold range based on the mean and standard deviation of the data collected within a set period.

[0014] Furthermore, after acquiring the operational status data but before performing calculations and analysis on the operational status data, the process also includes: The operational status data and the location information of each sensor group that collected the data are associated and stored in a local storage chip; The associated and stored data is sent to the cloud management platform via the wireless communication unit; The cloud management platform performs preprocessing operations on the received data, including format parsing, timestamp verification, and outlier removal based on the Raida criterion.

[0015] Furthermore, after acquiring the operational status data, the method also includes: The operational status data is stored in a local storage chip; The system monitors network communication status in real time, and when a network signal interruption is detected, it continuously stores the newly collected operating status data in the local storage chip. Once the network signal is restored, the temporarily stored operational status data during the interruption will be automatically uploaded to the cloud management platform.

[0016] A second aspect of the present invention provides an intelligent monitoring and maintenance device for water-saving ecological toilets, comprising: The data acquisition program module is used to acquire the operating status data collected by the sensor groups set at multiple functional units of the ecological toilet; The calculation and analysis program module is used to calculate and analyze the operating status data to obtain the operating evaluation results of each functional unit; The status judgment program module is used to determine the operating status level of each functional unit based on the comparison between the operation evaluation result and the preset threshold range. The strategy execution program module is used to execute the operation and maintenance strategy corresponding to the operation and maintenance level based on the operation and maintenance level. The operation and maintenance strategy includes sending early warning information or adjusting the associated operation parameters of the corresponding functional unit.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The method and apparatus provided by this invention directly overcome the shortcomings of existing technologies, such as delayed fault detection and inaccurate control, which rely on manual inspection, through control logic of data acquisition, fusion calculation, state classification, and strategy response.

[0018] Specifically, by employing a sensor array associated with multiple functional units such as rainwater harvesting, negative pressure toilets, microbial treatment, and resource recycling, and by specifically calculating and analyzing multi-dimensional operational status data such as water level, pressure, temperature, and pH value, the system can directly characterize the operational health status of each unit. This data is then compared with preset threshold ranges to derive a quantitative operational status level. Finally, based on the level, the system implements early warning or automatic parameter adjustment strategies, enabling the system to monitor and adjust each unit 24 / 7 without interruption.

[0019] Through actual operation testing, compared with the traditional manual inspection mode, the technical solution of this invention significantly shortens the fault detection time from an average of 3 days to less than 2 hours, greatly improving the timeliness of fault detection. At the same time, because intervention can be carried out in the early stage of faults by automatically adjusting related operating parameters such as aeration volume and working pressure threshold, a large number of potential anomalies are eliminated before they occur, which greatly reduces the frequency of manual on-site fault handling and reduces the overall operation and maintenance cost by more than 45%.

[0020] This invention achieves additional significant technical benefits through a mechanism-data fusion computational model constructed for specific functional units. For example, for the microbial treatment unit, the proprietary scheme, by integrating three core parameters—temperature, pH, and redox potential—can calculate a more comprehensive and accurate microbial activity index, rather than monitoring a single parameter in isolation. This makes the assessment of microbial activity closer to its true biochemical reaction state, which is influenced by multiple coupled factors. Using this precise state assessment to guide subsequent control operations ensures that the microbial treatment unit always operates within its high-efficiency range. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the intelligent monitoring and operation and maintenance management system in an embodiment of the present invention; Figure 2This is a schematic diagram of the intelligent monitoring and operation and maintenance management workflow in an embodiment of the present invention.

[0022] In the diagram: 100, On-site monitoring equipment; 101, Rainwater collection unit; 111, Liquid level sensor; 112, Water quality sensor; 102, Negative pressure toilet unit; 121, Pressure sensor; 122, Flow sensor; 103, Microbial treatment unit; 131, Temperature sensor; 132, pH sensor; 133, Oxidation-reduction potential sensor; 104, Resource recycling unit; 141, GPS positioning chip; 142, GPS positioning chip; 150, Data storage and transmission module; 200, Wireless network; 300, Cloud management platform; 310, Data receiving module; 320, Data processing module; 330, Status judgment module; 340, Early warning and dispatching module; 400, Operation and maintenance terminal. Detailed Implementation

[0023] The core technical problem this invention aims to solve is the untimely fault detection and inaccurate control under the manual operation and maintenance mode of water-saving ecological toilets. To address this issue, this invention provides a monitoring and operation and maintenance method that integrates multi-source sensor monitoring, multi-parameter fusion calculation, state hierarchical assessment, and adaptive closed-loop control. The core concept is to move away from relying on manual perception of the broad states of each functional unit. Instead, through a clearly defined calculation and control process, it automatically transforms the raw data from sensors distributed throughout the toilet into operational evaluation results with clear engineering implications. Based on the preset threshold range into which these results fall, the system's health status is quantified into different levels such as normal, warning, and abnormal, ultimately triggering preset, differentiated operation and maintenance strategies. This concept can be implemented on a hardware architecture that includes a field sensor group, a local data terminal, and a remote cloud management platform. The corresponding intelligent monitoring and operation and maintenance devices are deployed as program modules at various levels of this architecture, collaboratively executing the entire method.

[0024] To make the technical solution, features, and the technical problem solved by this invention clearer, the following will provide a detailed description of a monitoring and operation and maintenance method for a water-saving ecological toilet, and its corresponding intelligent monitoring and operation and maintenance device, in conjunction with a specific implementation environment. It should be understood that the description herein is only for explaining the core idea of ​​this invention and is not intended to limit its only implementation.

[0025] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Component models, material names, connection structures, control methods, algorithms, and other features not explicitly described in this technical solution are considered common technical features disclosed in the prior art.

[0026] Example 1 This embodiment details a monitoring and operation and maintenance method for water-saving ecological toilets, as well as an intelligent monitoring and operation and maintenance device for implementing this method. The complete process of the method and the program module composition of the device will be described in the following steps.

[0027] Step 1: Obtain running status data The data acquisition module acquires operational status data collected by sensor groups located at multiple functional units of the eco-toilet. In this specific implementation, the eco-toilet includes four core functional units: a rainwater collection unit, a negative pressure toilet unit, a microbial treatment unit, and a resource recycling unit.

[0028] For the rainwater harvesting unit, the sensor array includes a level sensor and a water quality sensor installed inside the rainwater collection tank. The level sensor, for example, can be a diffused silicon submersible level gauge. Its probe is placed at the bottom of the tank. Based on the principle that the hydrostatic pressure of the liquid is proportional to the liquid level, it outputs a 4-20mA analog signal or an RS485 digital signal to collect real-time water level data characterizing the tank's storage capacity. Its range can be selected according to the tank depth, for example, 0-5 meters, with an accuracy class of 0.5%. The water quality sensor, for example, can be an online turbidimeter based on the principle of optical scattering, used to collect water quality data characterizing the cleanliness of the collected rainwater. Its range can be selected from 0-1000 NTU, and its measurement accuracy can be ensured through periodic manual calibration.

[0029] For negative pressure toilet units, the sensor set includes a pressure sensor and a flow sensor installed on the negative pressure pipeline. The pressure sensor, for example, a ceramic piezoresistive pressure transmitter, is directly installed on the wall of the negative pressure pipeline via a threaded interface (such as G1 / 4) to collect absolute pressure data reflecting the negative pressure state of the system in real time. Its range can be determined according to the design negative pressure value, for example, -100kPa to 0kPa. The flow sensor, for example, a vortex flow meter or a thermal mass flow meter, is connected in series in the pipeline to collect the instantaneous and cumulative flow data of the gas or gas-liquid-solid mixture passing through the pipeline during sewage discharge, reflecting the smoothness of the flushing and sewage discharge process.

[0030] For a microbial treatment unit, as a core processing unit, its operating status is determined by multiple biochemical reaction parameters. Therefore, its sensor array specifically includes: temperature sensors (e.g., PT100 platinum resistance thermometers, range -50℃ to 200℃, accuracy ±0.1℃) installed inside the packing layer of the microbial reactor; pH sensors (e.g., online pH meters using the glass electrode method, range 0-14, with automatic temperature compensation); and oxidation-reduction potential (ORP) sensors (e.g., using platinum-silver / silver chloride composite electrodes, range -2000mV to +2000mV). These sensors are in direct contact with the fecal matter and microbial carriers within the reactor, used to collect real-time temperature, pH, and oxidation-reduction potential data.

[0031] For resource recycling units, the sensor array primarily focuses on the quality of the recycled products. For example, a nutrient concentration sensor is installed at the discharge port after solid-liquid separation or fertilizer aging. This sensor can be a multi-parameter detection probe based on near-infrared spectroscopy analysis technology, which can quickly analyze the nutrient concentration data such as total nitrogen, total phosphorus, and total potassium in the recycled products in a non-contact manner or after simple sample preparation, and output the data in percentage or mg / kg.

[0032] The location information of all the above sensors is acquired through an individual or shared positioning module (such as a Beidou positioning chip, for example, the UM220-III N module from Unimicron Technology). This module can provide latitude and longitude coordinates with an accuracy better than 2.5 meters, thus accurately binding the operational status data with its corresponding geographical location. All analog or digital signals collected by the sensors are first aggregated to a data storage and transmission module in a field data terminal. This module consists of a local storage chip (such as a high-capacity Flash chip, such as Winbond Electronics' W25N01GV, which can provide at least 45 days of continuous storage capacity) and a wireless communication unit (such as an NB-IoT communication module, such as Quectel Wireless Solutions' BC26). Each sensor group is configured to collect data at a fixed frequency of once every 10 minutes. The collected data and location information are packaged together and initially stored in the local storage chip, while simultaneously being transmitted to the cloud management platform via a narrowband IoT base station through the wireless communication unit.

[0033] Step 2: Calculate and analyze to obtain operational evaluation results After the cloud management platform receives the data, the computational analysis module begins its work. First, the platform's data receiving module preprocesses the received raw data packets to form clean, reliable, and valid data, which will be detailed in subsequent embodiments. Then, the computational analysis module performs targeted computational analysis on the valid data from different functional units.

[0034] Specifically, for the microbial treatment unit, to overcome the limitation that a single parameter cannot comprehensively reflect microbial activity, this embodiment introduces a multi-parameter fusion model. The acquired temperature (T), pH, and oxidation-reduction potential (ORP) data are input into this model to calculate a dimensionless comprehensive index, namely the microbial activity index (MAI), which serves as the operational evaluation result for the unit. The specific form of this model is as follows: MAI=α×f(T)+β×g(pH)+γ×h(ORP) Here, f(T), g(pH), and h(ORP) are the effects of temperature, pH, and redox potential, respectively. These functions characterize the nonlinear relationship between each parameter and microbial activity, typically exhibiting a bell-shaped curve or piecewise function that reaches a maximum of 1.0 at the optimum and gradually decays towards both sides. α, β, and γ are preset weighting coefficients, set according to the sensitivity of different bacterial species to each parameter. For example, for a low-temperature resistant compound microbial agent for degrading fecal waste, α=0.3, β=0.3, and γ=0.4 can be set. In a specific example, f(T) reaches its maximum value of 1.0 at 35℃; g(pH) reaches its maximum value of 1.0 at 7.0; and h(ORP) reaches its maximum value of 1.0 at -200mV. The calculated MAI value comprehensively reflects the coupled effects of current temperature, acidity, and redox state on the overall degradation activity of microorganisms; the closer the value is to 1.0, the higher the activity.

[0035] For the rainwater harvesting unit, the calculation and analysis module calculates the operational evaluation results based on the rate of change of water level data. Specifically, within a fixed time window (e.g., the past 24 hours), the average water level change rate is calculated by dividing the difference between the current water level and the initial water level of the window by the length of the time window. If it is currently during rainfall, this rate of change directly reflects the combined performance of the rainwater harvesting system's runoff efficiency and pipeline unobstructedness, i.e., the rainwater replenishment efficiency. If there is no rain and the toilets are in use, the rate of change is negative, reflecting the rate of water consumption. Therefore, this rainwater replenishment efficiency / consumption rate serves as the operational evaluation result of the rainwater harvesting unit.

[0036] For negative pressure toilet units, the calculation and analysis module analyzes the pressure fluctuation curves collected by the pressure sensor over a certain period (e.g., the most recent 10 flush cycles). By extracting the static negative pressure value before each flush, the peak negative pressure drop during the flush, and the time required for the negative pressure to recover to the static value after the flush, this data is compared with a reference curve under standard sealing conditions to calculate an evaluation value reflecting the system's sealing performance. For example, a longer pressure recovery time, or a consistently lower static negative pressure value than the set value, indicates a worse sealing performance evaluation value. This evaluation value is the operational evaluation result of the negative pressure toilet unit.

[0037] For the resource recycling unit, the calculation and analysis program module compares and weights the nutrient concentration data such as total nitrogen, total phosphorus, and total potassium collected by the nutrient concentration sensor with the nutrient content grading thresholds in relevant national agricultural standards (such as "Organic Fertilizer" NY / T 525-2021) to obtain a grade value reflecting the quality of the recycled products, such as a quantitative score for superior, qualified, and unqualified products, which serves as the operational evaluation result of the unit.

[0038] Step 3: Determine the operating status level After obtaining the operational evaluation results of each functional unit, the status judgment program module compares these evaluation results with a preset threshold range to determine the operational status level of each functional unit. In this embodiment, the operational status levels are divided into three levels: normal, attention, and abnormal.

[0039] The preset threshold ranges for each unit are dynamically adjusted based on their design parameters and historical operating data. The specific adjustment methods will be detailed in subsequent embodiments. As an example, for the microbial treatment unit, its threshold range can be set as follows: when MAI ≥ 0.8, and T, pH, and ORP are all within their designed operating ranges, it is considered a normal state; when 0.5 ≤ MAI < 0.8, or any single parameter (such as temperature) exceeds its designed operating range but does not reach the preset extreme warning line, it is considered a state of alert; when MAI < 0.5, or any single parameter exceeds the extreme warning line, it is considered an abnormal state. The threshold setting logic for other units is similar. For example, for a negative pressure toilet unit, its state of alert may correspond to a slow decrease in the system's sealing performance evaluation value, while an abnormal state corresponds to a sharp drop in the sealing performance evaluation value, indicating a serious leak.

[0040] Step 4: Execute the corresponding operation and maintenance strategy. The strategy execution module executes the corresponding differentiated operation and maintenance strategy based on the determined running status level.

[0041] When the operational status level of a functional unit is determined to be abnormal, the policy execution module immediately generates an early warning message containing the unit name, specific abnormal parameters, geographical location information, and suggested handling measures. This message is then pushed to one or more pre-defined operation and maintenance terminal applications via a 4G / 5G mobile network or a Wi-Fi network connected to the cloud management platform. The operation and maintenance terminal can be a smartphone of an operation and maintenance personnel or a PC in the monitoring center. The app running on it will issue audible and visual alarms, forcibly reminding operation and maintenance personnel to intervene immediately, thus achieving instant fault detection.

[0042] When the operating status level of a functional unit is determined to be "Attention," it indicates that the unit's performance has deviated from its optimal state but it can still self-correct or operate with fault tolerance. At this time, the strategy execution module automatically sends instructions to the corresponding functional unit's actuators via the communication link between the cloud management platform and the field device controller to adjust its associated operating parameters. For example, if the microbial treatment unit is in "Attention" status due to a low temperature component in the MAI (Microbial Intake), the output frequency of the inverter controlling the aeration device is automatically adjusted to appropriately increase the aeration rate. This is because aerobic fermentation heat production helps raise the reactor temperature, and increasing the aeration rate enhances oxygen mass transfer and the exothermic reaction of biochemical reactions, thus attempting to bring the temperature and microbial activity back to the normal range. Similarly, if the negative pressure toilet unit is in "Attention" status, indicating a possible minor leak, its preset operating pressure threshold is automatically adjusted. For example, the target negative pressure value that the system attempts to maintain is temporarily increased from -55 kPa to -60 kPa to compensate for the pressure loss caused by the minor leak, ensuring that the sewage discharge function is temporarily unaffected. All automatic adjustment operations and results are logged and stored in the cloud management platform database for traceability and analysis.

[0043] By executing steps one through four above, the method and apparatus of this embodiment construct a set of unmanned intelligent operation and maintenance systems from data acquisition, fusion computing, status classification to differentiated response, directly and thoroughly solving the technical problems raised in the background art.

[0044] Example 2 This embodiment further elaborates on the calculation and analysis method based on Embodiment 1. Specific calculation methods for the microbial treatment unit, rainwater harvesting unit, negative pressure toilet unit, and resource recycling unit are defined respectively.

[0045] For the microbial treatment unit, the operational evaluation result is the Microbial Activity Index (MAI). The MAI is calculated strictly according to the multi-parameter fusion model disclosed in Example 1: MAI = α × f(T) + β × g(pH) + γ × h(ORP). The weighting coefficients α, β, and γ are established based on orthogonal experiments or response surface analysis of the specific microbial strains used, quantifying the influence of each parameter on activity. For example, if a microbial agent is extremely sensitive to pH changes but has a wide temperature tolerance range, the value of β will increase accordingly. This method of coupling multiple key variables by assigning different weights, compared to the existing single-threshold method that simply judges whether the temperature is between 20-40 degrees Celsius, can reveal the potential risk of decreased activity due to unfavorable combinations of multiple parameters earlier and more sensitively, thus buying time for early intervention under subsequent attention.

[0046] For rainwater harvesting units, the operational evaluation result is the rainwater replenishment efficiency. This efficiency is calculated by performing a linear regression on real-time collected water level data within a preset analysis period (such as the most recent 1 hour or 24 hours). The slope of the resulting regression equation is the water level change rate. This change rate represents the net replenishment or consumption rate of rainwater during that period. This indicator is chosen as the evaluation result because it directly points to the core function of the rainwater harvesting system—water collection capacity. It can help maintenance personnel detect problems such as a sudden drop in water collection efficiency caused by blockage of the collection surface, failure of the initial rainwater diversion device, or pipe rupture in a timely manner.

[0047] For negative pressure toilet units, the evaluation value reflecting their sealing performance is calculated by extracting features from the pressure-time curve of a single flushing action. The specific steps include: identifying the starting and lowest points of pressure drop, calculating the pressure drop rate and peak value for that segment; identifying the starting point of pressure recovery and the point after stabilization, and calculating the recovery time. These feature values ​​are then compared and scored with baseline feature values ​​measured under factory conditions or good maintenance conditions. For example, if the baseline recovery time is set at 15 seconds, and the recovery time for a particular action is extended to 30 seconds, the score for that item is halved. The sealing performance evaluation value is obtained by combining the scores of multiple features such as peak pressure drop and recovery time. This calculation directly reveals the internal condition of the negative pressure pipeline that cannot be detected by visual inspection alone.

[0048] For resource recycling units, the calculation of the grade value reflecting the quality of the recycled products is accomplished by comparing and weighting the detected concentration values ​​of total nitrogen (TN), total phosphorus (P2O5), and total potassium (K2O) with the technical indicator tables in standards such as "Organic Fertilizer". This quantitative evaluation method provides a clear target for the operation and control of resource recycling units, eliminating the reliance on experience to judge the quality of fertilizers and providing quantifiable quality grade values ​​as a basis for control.

[0049] Through the implementation of this embodiment, the operational evaluation results of each functional unit have clear calculation paths and data sources. Together, they provide the entire system with multi-dimensional and in-depth quantitative state information, enabling subsequent state judgments and strategy execution to be based on accurate and reliable data.

[0050] Example 3 This embodiment provides a more in-depth explanation of the multi-parameter fusion model used in Embodiment 2. The specific form of this model is explicitly defined as MAI = α × f(T) + β × g(pH) + γ × h(ORP). This form is a linear weighted model, which has the advantages of simple calculation, clear physical meaning, and ease of deployment and real-time computation on cloud platforms.

[0051] The key point is that the temperature effect function f(T), pH effect function g(pH), and redox potential effect function h(ORP) in the model are not simple linear relationships, but should be constructed as nonlinear to conform to the kinetics of microbial enzyme activity. As a concrete example, f(T) can be a modified Gaussian or chi-square function, which outputs a maximum value of 1.0 at a specific temperature (e.g., 35℃), and its output value approaches 0 when the temperature is below 10℃ or above 60℃. For example, f(T) can be specifically defined as: when 25℃ ≤ T ≤ 45℃, f(T) = 1 - (T - 35). 2 / 100; when T < 25℃, f(T) = 0; when T > 45℃, f(T) = 0. g(pH) also exhibits a bell-shaped curve characteristic, reaching a maximum value of 1.0 at neutral pH (e.g., 7.0), while activity decreases sharply in excessively acidic or alkaline conditions. h(ORP) reaches a maximum value of 1.0 in the optimal ORP range for anaerobic fermentation (e.g., around -200mV), where excessively high positive potential or excessively low negative potential indicates that the environment is unsuitable for the activity of obligate or facultative anaerobic bacteria.

[0052] Example 4 This embodiment further elaborates on the classification of operating status levels and the corresponding operation and maintenance strategies. As described in Embodiment 1, the operating status levels are divided into three levels: normal, attention, and abnormal, which constitutes a clear three-level early warning and control system.

[0053] When the operational status level of a functional unit is judged to be abnormal, it indicates that its key performance indicators have deteriorated significantly and cannot be restored by the system's own automatic adjustment. Immediate manual intervention is required. At this time, the warning information sent by the policy execution program module, in addition to including a basic status description, will also retrieve the unit's operational data trend chart from the historical database over a period of time, as well as possible cause analysis suggestions (e.g., the MAI of the microbial treatment unit is abnormally low, and the temperature has been continuously below 15°C for the past 24 hours, suggesting checking the heating and insulation devices). This information will also be pushed to the operation and maintenance personnel via the APP to assist them in making quick decisions.

[0054] The core intelligence of this invention lies in the process of automatically adjusting the associated operating parameters of the corresponding functional units when the status level is "Attention". This process specifically includes, but is not limited to, at least one of the following operations: Adjusting the aeration rate of the microbial treatment unit. This operation relies on the automatic control of the aeration blower frequency converter. The strategy program module calculates the percentage increase in aeration rate needed based on the degree of decrease in MAI and the deviation of various components, and converts it into a corresponding frequency command (e.g., adjusting from 35Hz to 40Hz). This command is then sent to the on-site PLC controller via the cloud platform, ultimately driving the frequency converter to change the motor speed.

[0055] Adjust the working pressure threshold of the negative pressure toilet unit. This operation is achieved by modifying the logic judgment value for starting and stopping the negative pressure pump in the field controller. For example, if the original upper and lower limit thresholds were set to start the pump when the pipeline negative pressure drops to -50kPa and stop when it rises to -60kPa, the system can automatically modify the shutdown threshold from -60kPa to -65kPa, thereby increasing the average negative pressure level of the entire system.

[0056] Start the standby pump of the rainwater harvesting unit. When the strategy determines that the collection efficiency is rated as a warning level due to excessive pressure drop in the main pipeline, the contactor of the standby pump can be automatically closed to put it into operation to increase the pipeline pressure, or switch to the standby pipeline. This operation can verify whether the main pump is malfunctioning or the main pipeline is blocked.

[0057] Increase the stirring frequency of the resource recycling unit. For example, the original cycle of stirring for 10 minutes every 4 hours can be automatically adjusted to stirring for 10 minutes every 2 hours. This is achieved by modifying the time constant of the timer that controls the start and stop of the stirring motor. Too low a stirring frequency may lead to uneven mixing of materials, affecting the efficiency of aerobic composting and resulting in insufficient nutrient release. Increasing the frequency can promote mass transfer and homogenization.

[0058] These refined automatic control strategies, based on quantitative evaluation results, constitute a feedforward-feedback composite control system covering the main functional units, effectively solving the technical shortcomings of traditional manual operation and maintenance.

[0059] Example 5 This embodiment details the dynamic adjustment mechanism of the threshold range. Traditional fixed threshold methods are difficult to adapt to time-varying factors such as equipment aging, seasonal changes, and microbial succession. In this embodiment, the preset threshold range used by the status judgment module is dynamically adjusted based on the design parameters of each functional unit and historical operating data.

[0060] For example, the design parameters of a microbial treatment unit include a standard operating temperature range (e.g., 25℃-45℃). Initially, this range might be used directly as the normal temperature threshold. However, after a set period (e.g., a quarter), the system accumulates a large amount of actual data. The dynamic adjustment mechanism then kicks in: the calculation and analysis module calculates the mean μ and standard deviation σ of the temperature data for all normal operating periods within that period. Based on the 3σ principle, the system can automatically calculate and update the upper and lower limits of the normal threshold range. For example, if the average temperature μ = 32℃ and the standard deviation σ = 5℃ for the previous quarter, the system can dynamically update the normal temperature threshold range from [25℃, 45℃] to [22℃, 42℃], which better reflects the current operating conditions. This approach allows the system to adapt to seasonal changes in ambient temperature, avoiding frequent false alarms or alerts during winter, thus ensuring the accuracy and robustness of the entire monitoring system. This dynamic adjustment logic also applies to various parameters of other functional units.

[0061] Example 6 This embodiment elaborates on the preprocessing flow after data acquisition and before calculation and analysis, as well as a data reliability assurance mechanism.

[0062] Data reliability is the foundation of intelligent operation and maintenance. After acquiring operational status data, preprocessing is essential before any computational analysis. The specific process is as follows: First, the field terminal packages the collected operational status data and the location information of each sensor group (including sensor ID and latitude / longitude coordinates) into a single data frame and stores it in its local storage chip, forming a complete backup of the first-hand data. Subsequently, the stored data frame is transmitted to the cloud management platform via a 5G communication module, which serves as the wireless communication unit.

[0063] After receiving the data, the data receiving module of the cloud management platform performs preset preprocessing operations. First, it parses the format, restoring the received byte stream into structured data items, such as timestamp-sensor ID-parameter type-value-latitude and longitude coordinates. Second, it performs timestamp calibration, using a precise Network Time Protocol (NTP) clock to calibrate the timestamps of all data, eliminating time deviations caused by terminal clock drift. Finally, it performs outlier removal based on the Raida criterion. The Raida criterion states that for a set of data that follows or approximately follows a normal distribution, the probability that its values ​​fall within (μ-3σ, μ+3σ) is 99.74%; values ​​outside this range are considered outliers. This step applies this criterion to identify and remove gross error data points in continuous time series data that significantly deviate from the normal value range due to sensor momentary fluctuations, electromagnetic interference, or transmission errors, thereby ensuring the quality of the data input to the subsequent calculation and analysis modules.

[0064] Furthermore, considering the unstable network signals in remote areas, this embodiment also includes a mechanism for resuming data transmission after network outages. After acquiring operational status data, this data is preferentially stored in the local storage chip. The system monitors the network registration and attachment status of the wireless communication unit in real time, i.e., it detects the network communication status. Once a network signal interruption is detected, newly acquired operational status data will no longer attempt to be sent, but will be continuously and completely temporarily stored in the local storage chip. This chip has a sufficiently large capacity to store more than 30 consecutive days of data. After the system detects that the network signal has been restored, the software process will automatically create a high-priority background task to package all the operational status data temporarily stored during the interruption in the original timestamp order and completely retransmit it to the cloud management platform. This mechanism ensures that the integrity and continuity of operational status data are not compromised under extreme communication conditions, providing a complete data source for subsequent trend analysis, model optimization, and dynamic threshold adjustment based on historical data. This is a key guarantee for achieving highly reliable and unmanned operation and maintenance.

[0065] Application Example 1 Technical effect comparison and field test data verification To verify the technical effects of the present invention, a water-saving ecological toilet equipped with a traditional manual inspection and maintenance system was selected and compared with an ecological toilet of the same model that applied the complete set of methods and devices described in Embodiments 1 to 6 of the present invention for a six-month comparative test.

[0066] Test conditions: The two toilets are geographically close, and the external conditions such as ambient temperature, humidity, and number of users are basically the same. The functional units of the tested toilets, including the rainwater collection tank volume (50m³), are as follows: 3 ), negative pressure toilet model, effective volume of microbial reactor (10m³) 3 The types of bacterial agents added and the initial inoculation amounts were exactly the same. The toilets using this invention were equipped with a complete set of sensor arrays, a BeiDou positioning module, and an NB-IoT communication terminal on-site; all data processing, status judgment, and strategy execution modules were deployed in the cloud. The toilets in the comparative test maintained daily manual inspections and data recording. The test results are shown in the table below.

[0067] Test data comparison table Effect attribution and technical analysis: The significant reduction in fault detection time and the substantial decrease in operation and maintenance costs are directly causally related and both stem from the core closed-loop logic of this invention. By employing the automated processing flow of data acquisition, calculation and analysis, and level determination as described in this invention, replacing manual observation and note-taking, the system can perform continuous monitoring 24 / 7 (reflected in the data acquisition frequency of sensors every 10 minutes). In particular, the quantitative evaluation of the operating status of each unit can sensitively capture early, weak signals indicating the onset of faults, such as a slow decline in the sealing performance evaluation value of a negative pressure system or a drop in the microbial activity index (MAI) from 0.85 to 0.75. This triggers an automatic parameter adjustment strategy under alert, resolving the problem before it evolves into an abnormal fault requiring human intervention. This directly results in the dual benefits of reduced fault detection time and a sharp decrease in the need for manual intervention.

[0068] Improved COD removal rate and fertilizer quality: These improvements in core treatment efficiency are attributed to the multi-parameter fusion model and the resulting precise control. Traditional methods rely on manual reading of single-point temperature or pH values, failing to perceive the coupled effects of multiple factors. This invention, by calculating MAI = α × f(T) + β × g(pH) + γ × h(ORP), precisely quantifies the overall activity of the microbial community, providing a highly scientific and accurate basis for adjusting operations such as aeration rates. This ensures the microbial environment is always maintained in an optimal state, allowing biochemical reactions to proceed efficiently. Consequently, the COD removal rate has increased from less than 80% to a stable level above 90%. Similarly, continuous monitoring of nutrient concentration and quality grading in the resource recovery unit guides operations, ensuring that the output meets standards and significantly improving the first-grade product rate.

[0069] Example 7 This embodiment is combined with the appendix Figure 1 This paper provides a detailed description of the physical hardware architecture upon which the monitoring and maintenance method and intelligent monitoring and maintenance device of the present invention are based, so that those skilled in the art can more clearly understand the specific system composition and the collaborative working relationship between the components in implementing the present invention.

[0070] like Figure 1 and 2 The diagram shown illustrates the overall architecture of the intelligent monitoring and operation and maintenance system for water-saving ecological toilets provided in this embodiment of the invention. From top to bottom, the system mainly consists of a field monitoring equipment layer, a data transmission network layer, and a cloud management platform layer, forming a complete technical closed loop from data acquisition and wireless transmission to cloud-based intelligent analysis and remote operation and maintenance.

[0071] Specifically, an on-site monitoring device 100 is installed at the on-site monitoring equipment layer. This on-site monitoring device 100 further includes a sensing module, a positioning module, and a data storage and transmission module 150. The sensing module, which performs the step of acquiring operational status data, consists of various sensors distributed throughout the functional units of the eco-toilet.

[0072] More specifically, a level sensor 111 and a water quality sensor 112 are configured at the rainwater collection unit 101. The level sensor 111 is preferably an immersion-type hydrostatic level gauge for real-time acquisition of water level data in the rainwater collection tank; the water quality sensor 112 is preferably an optical turbidity sensor for acquiring water quality data characterizing the cleanliness of the collected rainwater. At the negative pressure toilet unit 102, a pressure sensor 121 and a flow sensor 122 are configured. The pressure sensor 121 is preferably a ceramic piezoresistive pressure transmitter for acquiring real-time pressure data within the negative pressure pipeline; the flow sensor 122 is preferably a vortex flow meter for acquiring instantaneous flow data during the sewage discharge process. At the microbial treatment unit 103, three key sensors are configured for comprehensively assessing the microbial biochemical reaction environment: a temperature sensor 131 (preferably a PT100 platinum resistance thermometer), a pH sensor 132 (preferably an online pH meter with an automatically temperature-compensated glass electrode), and a redox potential sensor 133 (ORP sensor, preferably a platinum-silver / silver chloride composite electrode). These sensors are used to collect real-time temperature, pH, and redox potential data within the reactor, respectively. At the resource recovery unit 104, a nutrient concentration sensor is configured, preferably a multi-parameter detection probe based on near-infrared spectroscopy, to collect nutrient concentration data such as nitrogen, phosphorus, and potassium in the recovered products.

[0073] The positioning module is used to accurately bind all operational status data to their specific geographical locations. In this embodiment, the positioning module specifically includes at least one GPS positioning chip 141 and 142, which are respectively installed in the field collection boxes of the rainwater collection unit 101 and the microbial treatment unit 103. Employing a BeiDou / GPS dual-mode positioning chip, such as the UM220-III N module from HeXinXingTong, it can provide latitude and longitude coordinates with an accuracy better than 2.5 meters. This is crucial for accurately locating the specific toilet stall where an alarm or abnormal unit is located in a widely distributed rural ecological toilet cluster.

[0074] All the operational status data collected by the aforementioned sensors, as well as the location information obtained by the positioning module, are uniformly fed into a field-located data storage and transmission module 150 via an RS485 bus or analog signal line. This data storage and transmission module 150 is the hub for local data processing and communication, integrating a local storage chip and an NB-IoT communication unit. The local storage chip uses a high-capacity Flash memory, such as Winbond Electronics' W25N01GV chip, which has sufficient capacity to continuously store at least 45 days of complete operational data at a system configuration of collecting and storing data every 10 minutes. The NB-IoT communication unit uses Quectel Wireless Solutions' BC26 module, which is based on cellular narrowband IoT technology and has the advantages of low power consumption and wide coverage. It is responsible for periodically uploading packaged data frames via the wireless network 200. The module also has built-in logic for resuming data transmission after network interruption: it monitors the network communication status in real time, and when a network signal interruption is detected, the newly collected operation status data will be continuously stored in the local storage chip; after the network signal is restored, all the data temporarily stored during the interruption will be automatically retransmitted to the cloud management platform 300 in the order of timestamps, thereby ensuring the absolute integrity and reliability of the operation data.

[0075] Data transmission network layer Figure 1 The wireless network 200 shown serves as a bridge connecting the field and the cloud. In this embodiment, it is the NB-IoT base station and its subsequent core network, providing a reliable narrowband transmission channel for multi-source heterogeneous operational status data.

[0076] At the cloud management platform layer, a cloud management platform 300 is set up. This platform consists of a distributed server cluster, on which multiple program modules implementing the core control logic of this invention are deployed, forming an intelligent monitoring and maintenance device. Specifically, the cloud management platform 300 includes four core functional modules: a data receiving module 310, a data processing module 320, a status judgment module 330, and an early warning and scheduling module 340. The data receiving module 310 is responsible for establishing and maintaining communication connections with the field monitoring equipment 100 located in various locations, receiving the data sent by them, and performing preprocessing operations, including format parsing, timestamp verification, and outlier removal based on the Laida criterion, thereby transforming the raw data into clean and valid data. The data processing module 320 has built-in preset algorithms for performing core computational analysis tasks, such as inputting temperature, pH, and ORP data into a multi-parameter fusion model to calculate the microbial activity index (MAI). The status judgment module 330 has preset dynamic adjustment threshold ranges for each functional unit. By comparing the operation evaluation results with these thresholds in real time, it achieves a graded assessment of the operating status of each unit, classifying it into three levels: normal, alert, and abnormal. The early warning and scheduling module 340 then executes differentiated response strategies based on the aforementioned graded results. For abnormal states, it immediately generates early warning information containing the unit location, abnormal parameters, and handling suggestions, and pushes it to the operation and maintenance terminal 400. For alert states, it automatically generates adjustment instructions, which are transmitted back to the actuator controller of the field monitoring device 100 via the wireless network 200 to adjust related operating parameters, such as adjusting the aeration rate, correcting the negative pressure threshold, or starting the backup pump, thereby achieving dynamic optimization and fault tolerance of the field equipment.

[0077] At the application layer, the maintenance terminal 400 supports interaction with smartphone apps and PC monitoring software. Maintenance personnel can view the real-time operating status and historical trend graphs of all functional units in the entire system, receive alarm notifications, and perform necessary manual intervention operations. The maintenance terminal 400 and the cloud management platform 300 maintain bidirectional communication link data synchronization through the standard HTTP / MQTT protocol, ensuring the efficient collaborative operation of the entire ecological toilet intelligent monitoring and maintenance system.

[0078] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for monitoring and maintaining water-saving ecological toilets, characterized in that, Includes the following steps: The system acquires operational status data collected by sensor arrays located at multiple functional units of the ecological toilet. The operational status data is calculated and analyzed to obtain the operational evaluation results of each functional unit; Based on the comparison between the operation evaluation results and the preset threshold range, the operation status level of each functional unit is determined. The functional unit includes at least one of the following: rainwater collection unit, negative pressure toilet unit, microbial treatment unit, and resource recycling unit. Based on the operating status level, execute the operation and maintenance strategy corresponding to the operating status level. The operation and maintenance strategy includes sending early warning information or adjusting the associated operating parameters of the corresponding functional unit. The operational status data includes at least one of the following: water level data and / or water quality data of the rainwater collection unit; pressure data and / or flow rate data of the negative pressure toilet unit; temperature data, pH data and / or oxidation-reduction potential data of the microbial treatment unit; and nutrient concentration data of the resource recovery unit.

2. The monitoring and operation and maintenance method for water-saving ecological toilets according to claim 1, characterized in that, The operational status data is calculated and analyzed to obtain the operational evaluation results of each functional unit, specifically including: For the microbial treatment unit, the temperature data, pH data, and redox potential data are input into a preset multi-parameter fusion model to calculate the microbial activity index, which reflects the activity of the microorganisms, and is used as the operation evaluation result. And / or, For the rainwater harvesting unit, the rainwater replenishment efficiency is calculated based on the rate of change of the water level data, and this efficiency is used as the operational evaluation result.

3. The monitoring and operation and maintenance method for water-saving ecological toilets according to claim 2, characterized in that, The calculation and analysis of the operational status data to obtain the operational evaluation results of each functional unit further includes: For the negative pressure toilet unit, an evaluation value reflecting the sealing performance of the negative pressure system is calculated based on the fluctuation curve of the pressure data, and this value is used as the operational evaluation result. And / or, For the resource recovery unit, a grade value reflecting the quality of the recovered products is calculated based on the nutrient concentration data, and this grade value is used as the operational evaluation result.

4. The monitoring and operation and maintenance method for water-saving ecological toilets according to claim 2, characterized in that, The multi-parameter fusion model is as follows: MAI=α×f(T)+β×g(pH)+γ×h(ORP) Wherein, MAI is the microbial activity index, T, pH, and ORP are the temperature data, pH data, and redox potential data, respectively, f(T), g(pH), and h(ORP) are the temperature influence function, pH influence function, and redox potential influence function, respectively, and α, β, and γ are preset weighting coefficients.

5. The monitoring and operation and maintenance method for water-saving ecological toilets according to claim 1, characterized in that, The operational status levels are divided into normal, alert, and abnormal. The step of executing the operation and maintenance strategy corresponding to the operation and maintenance level based on the operation and maintenance level includes: When the operating status level is abnormal, a warning message is sent to the operation and maintenance terminal. When the operating status level is "Caution", the associated operating parameters of the corresponding functional unit are automatically adjusted.

6. A monitoring and maintenance method for water-saving ecological toilets according to claim 5, characterized in that, The automatic adjustment of the associated operating parameters of the corresponding functional units includes at least one of the following operations: Adjust the aeration rate of the microbial treatment unit; Adjust the working pressure threshold of the negative pressure toilet unit; Start the standby pump of the rainwater collection unit; Increase the stirring frequency of the resource recycling unit.

7. The monitoring and operation and maintenance method for water-saving ecological toilets according to claim 1, characterized in that, The preset threshold range is dynamically adjusted based on the design parameters and historical operating data of each functional unit. The design parameters include the equipment's rated power and / or standard operating temperature range. The dynamic adjustment includes calculating and updating the upper and / or lower limits of the preset threshold range based on the mean and standard deviation of the data collected within a set period.

8. A monitoring and maintenance method for water-saving ecological toilets according to claim 1, characterized in that, After acquiring the operating status data but before performing calculations and analysis on the operating status data, the process also includes: The operational status data and the location information of each sensor group that collected the data are associated and stored in a local storage chip; The associated and stored data is sent to the cloud management platform via the wireless communication unit; The cloud management platform performs preprocessing operations on the received data, including format parsing, timestamp verification, and outlier removal based on the Raida criterion.

9. A monitoring and maintenance method for water-saving ecological toilets according to claim 1, characterized in that, After acquiring the running status data, the process also includes: The operational status data is stored in a local storage chip; The system monitors network communication status in real time, and when a network signal interruption is detected, it continuously stores the newly collected operating status data in the local storage chip. Once the network signal is restored, the temporarily stored operational status data during the interruption will be automatically uploaded to the cloud management platform.

10. An intelligent monitoring and maintenance device for water-saving ecological toilets, characterized in that, include: The data acquisition program module is used to acquire the operating status data collected by the sensor groups set at multiple functional units of the ecological toilet; The calculation and analysis program module is used to calculate and analyze the operating status data to obtain the operating evaluation results of each functional unit; The status judgment program module is used to determine the operating status level of each functional unit based on the comparison between the operation evaluation result and the preset threshold range. The strategy execution program module is used to execute the operation and maintenance strategy corresponding to the operation and maintenance level based on the operation and maintenance level. The operation and maintenance strategy includes sending early warning information or adjusting the associated operation parameters of the corresponding functional unit.

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