A device for recycling cleaning water from a sweeper truck

Abstract

This invention relates to the field of sanitation machinery technology and provides a device for recycling cleaning water from a sweeper truck. The device includes: a physical water circuit and filtration assembly, comprising a wastewater tank, a solid-liquid separation device, a precision filtration device, and a clean water tank connected in sequence; a high-pressure water pump with its inlet connected to the clean water tank and its outlet connected to a spraying device; a sensing and detection unit, including a first set of sensors for collecting wastewater quality parameters, a second set of sensors for collecting system status parameters, and a pressure sensor for collecting actual spraying pressure; and an intelligent controller electrically connected to the sensing and detection unit and the high-pressure water pump. This invention simultaneously collects the turbidity and particulate matter concentration values ​​of the recycled wastewater, calculates the pollution intensity using a weighted fusion method, and introduces the turbidity change trend as a correction factor. This allows for timely adjustment of the pollution level when the pollution level rises rapidly, avoiding the lag and misjudgment problems of traditional single-parameter or static threshold judgments.

Description

Technical Field

[0001] This invention belongs to the field of sanitation machinery technology, and in particular relates to a device for recycling cleaning water from a sweeper truck. Background Technology

[0002] As core equipment for urban road cleaning, sweeper trucks simultaneously perform sweeping, washing, and wastewater recycling during operation, and their operational efficiency directly impacts the quality of the public environment. Traditional sweeper trucks consume large amounts of clean water during operation, while simultaneously generating mixed wastewater containing high concentrations of silt, suspended particulate matter, and oil. Direct discharge of this wastewater not only exacerbates water scarcity but may also cause secondary environmental pollution. To address this challenge, cleaning water recycling technology is increasingly being applied to sweeper truck systems. This involves purifying the recycled wastewater through an onboard filtration system and then resupplying it to the spraying unit, achieving a closed-loop utilization of water resources. However, existing water recycling devices have revealed several technical bottlenecks in practical applications.

[0003] The current pollution level determination mechanism relies too heavily on a single water quality parameter, such as simply classifying pollution levels based on turbidity values. It fails to integrate multi-dimensional data such as turbidity and particulate matter concentration, and ignores the dynamic trends of water quality parameters. When turbidity values ​​remain consistently high, the system may misjudge it as a uniform pollution state, while a rapid increase in turbidity values ​​indicates a sudden and severe pollution area. The water requirements for spraying differ fundamentally between the two scenarios, but existing devices cannot accurately identify such changes.

[0004] The target water consumption generation logic lacks dynamic adaptability and does not take into account the pressure difference changes caused by filter clogging of the precision filtration device. As the operation time increases, filter clogging causes the water output capacity to continuously decrease. If not compensated in time, the actual spray volume will be insufficient. At the same time, the impact of vehicle speed fluctuations on the spray density per unit area is also ignored. When operating at high speed, it is necessary to increase the flow rate per unit time to maintain the cleaning effect, but the existing system still uses a fixed flow rate setting.

[0005] The aforementioned defects collectively limit the reliability and resource utilization efficiency of water circulation systems. Therefore, existing technologies urgently need improvement to address these issues. Summary of the Invention

[0006] The purpose of this invention is to provide a device for recycling cleaning water from a sweeper truck, thereby solving the aforementioned problems.

[0007] This invention is implemented as follows: a device for recycling cleaning water from a sweeper truck, comprising:

[0008] The physical water circuit and filtration assembly includes a sewage tank, a solid-liquid separation device, a precision filtration device, a clean water tank connected in sequence, and a high-pressure water pump with its inlet connected to the clean water tank and its outlet connected to a spraying device.

[0009] The sensing and detection unit includes a first set of sensors for collecting water quality parameters of the recycled wastewater, a second set of sensors for collecting system status parameters, and a pressure sensor for collecting actual spraying pressure.

[0010] The intelligent controller is electrically connected to the sensing and detection unit and the high-pressure water pump. The intelligent controller has the following collaborative control modules embedded inside:

[0011] The multi-parameter fusion pollution level determination module takes at least two water quality parameters of the recycled wastewater and the changing trend of the water quality parameters as input, and outputs the road pollution level. The road pollution level increases with the increase of the water quality parameter values, and when the water quality parameters show an upward trend, the pollution level is corrected upward based on the fusion value.

[0012] The multi-factor adaptive water consumption generation module takes the road pollution level, the pressure difference between the front and rear ends of the precision filter device, and the real-time speed of the sweeper as inputs, and outputs the target water consumption. The target water consumption increases with the increase of the road pollution level, increases with the increase of the pressure difference to compensate for the decrease in water output capacity caused by filter blockage, and increases with the increase of vehicle speed to maintain the unit area spraying density during high-speed operation.

[0013] The pressure conversion module takes the target water consumption as input and outputs the target spraying pressure. The target spraying pressure and the target water consumption have a monotonically increasing functional relationship.

[0014] The constant pressure feedback control module takes the target spraying pressure and the actual spraying pressure as inputs and outputs a speed control signal for the high-pressure water pump. By adjusting the speed, the actual spraying pressure tracks the target spraying pressure.

[0015] The forced intervention module, when the pressure difference between the front and rear ends of the precision filter exceeds the preset maximum allowable pressure difference threshold or the turbidity of the purified water exceeds the preset safe turbidity threshold, forcibly cuts off the water inlet to the clean water tank and opens the bypass to allow the purified water to flow back to the sewage tank or be directly discharged.

[0016] A further technical solution is that the first group of sensors includes:

[0017] An influent turbidity sensor is installed at the inlet of the solid-liquid separation device to collect the turbidity value of the recycled wastewater in real time.

[0018] A particulate matter concentration sensor is installed at the inlet of the solid-liquid separation device to collect the concentration value of suspended particulate matter in the recycled wastewater in real time.

[0019] The second set of sensors includes:

[0020] Vehicle speed sensor is used to collect the real-time operating speed of the sweeper truck;

[0021] A differential pressure sensor is installed between the inlet and outlet of the precision filter to collect the pressure difference between the front and back ends of the precision filter.

[0022] The turbidity sensor is installed at the outlet of the precision filter device to collect the turbidity value of the purified water.

[0023] The pressure sensor is a spray end pressure sensor, which is installed on the pipeline between the high-pressure water pump and the spraying device or at the inlet of the spraying device.

[0024] A further technical solution is that the multi-parameter fusion pollution level determination module calculates the road surface pollution level in the following manner:

[0025] The turbidity fusion weighting coefficient is multiplied by the turbidity normalization value, and then the particulate matter concentration weighting coefficient is multiplied by the particulate matter concentration normalization value to obtain the fusion value; where the particulate matter concentration weighting coefficient is equal to 1 minus the turbidity fusion weighting coefficient.

[0026] Calculate the difference between the normalized turbidity value at the current time and the normalized turbidity value at the previous time to obtain the turbidity increment. Then multiply it by the preset turbidity increment influence coefficient and add 1 to obtain the trend correction factor.

[0027] Multiply the fusion value by the trend correction factor, then divide by the preset fusion value-level quantification coefficient, round the result down, and compare it with the preset maximum pollution level to obtain the road pollution level.

[0028] The turbidity normalized value and the particulate matter concentration normalized value are calculated by substituting the sensor measured values ​​into the maximum-minimum normalization formula.

[0029] A further technical solution is that the multi-factor adaptive water consumption generation module calculates the target water consumption in the following manner:

[0030] The baseline water consumption is calculated by multiplying the baseline water consumption by (1 plus the product of the unit water consumption increment coefficient and the road pollution level) to obtain the baseline water consumption; where the unit water consumption increment coefficient is between 0.1 and 0.5.

[0031] Multiply the base water consumption by the road surface wetness coefficient, the congestion compensation coefficient, and the vehicle speed correction function to obtain the target water consumption.

[0032] The initial value of the road surface wetting coefficient is 1.

[0033] A further technical solution is that the blockage compensation coefficient is calculated based on the normalized pressure difference value in the following manner:

[0034] The clogging compensation coefficient is equal to 1 plus the product of the compensation strength coefficient and the pressure difference normalization value; the pressure difference normalization value is calculated by substituting the pressure difference values ​​of the front and rear ends of the precision filter device collected by the pressure difference sensor into the maximum-minimum value normalization formula.

[0035] A further technical solution is that the vehicle speed correction function is a piecewise function:

[0036] When the normalized vehicle speed value is less than or equal to the vehicle speed correction start threshold, the vehicle speed correction function takes the value of 1;

[0037] When the normalized vehicle speed value is greater than the vehicle speed correction threshold, the vehicle speed correction function is set to 1 plus the vehicle speed correction coefficient multiplied by (the difference between the normalized vehicle speed value and the threshold).

[0038] The normalized vehicle speed value is calculated by substituting the real-time operating vehicle speed collected by the vehicle speed sensor into the maximum-minimum normalization formula.

[0039] A further technical solution is that the road surface wettability coefficient is updated based on historical water consumption feedback according to the following recursive relationship:

[0040] The road surface wetness coefficient of the current control cycle is equal to the road surface wetness coefficient of the previous cycle minus the learning step size multiplied by (the ratio of actual water consumption to target water consumption in the previous cycle minus 1), and then compared with the minimum value of the road surface wetness coefficient to take the larger value.

[0041] In a further technical solution, the conversion relationship between the target spraying pressure and the target water consumption in the pressure conversion module is as follows:

[0042] The target spraying pressure is equal to the reference pressure plus the pressure-flow conversion coefficient multiplied by (target water consumption minus reference water consumption); where the pressure-flow conversion coefficient is pre-calibrated based on the flow-pressure characteristic curve of the high-pressure water pump.

[0043] Further technical solutions also include an integral discharge module, which accumulates particulate matter concentration or turbidity values ​​within a sliding time window. When the accumulated value exceeds a preset discharge threshold, the discharge valve at the bottom of the solid-liquid separation device is opened. The length of the sliding time window is negatively correlated with the current road pollution level: the higher the pollution level, the shorter the window length and the faster the discharge response.

[0044] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0045] This invention calculates pollution intensity by simultaneously collecting turbidity and particulate matter concentration values ​​of recycled wastewater and using a weighted fusion method. It also introduces turbidity change trends as a correction factor, which can promptly adjust the pollution level when the pollution level rises rapidly. This avoids the lag and misjudgment problems of traditional single parameter or static threshold judgments, and provides a more reliable control basis for subsequent water consumption adjustment.

[0046] This invention, when generating the target water usage, comprehensively considers the road surface pollution level, the pressure difference of the filtration device (reflecting the degree of filter clogging), and the real-time speed of the sweeper truck. It can dynamically compensate for the decrease in water output caused by filter clogging and maintain the spray density per unit area during high-speed operations. Simultaneously, through feedback updates of the road surface wetting coefficient, it can avoid excessive watering of already wet surfaces, significantly improving water resource utilization efficiency.

[0047] This invention employs a linear conversion model from target water consumption to target spraying pressure, and is calibrated based on the flow-pressure characteristic curve of a high-pressure water pump. Combined with a constant pressure feedback control module, the pump speed is adjusted in real time, ensuring that the actual spraying pressure accurately tracks the target value. This ensures that the actual water consumption meets the operational requirements and avoids uneven cleaning or water waste caused by pressure fluctuations.

[0048] This invention features a forced intervention module that automatically cuts off the water supply and opens a bypass when the pressure difference in the filtration device is too high or the turbidity of the purified water exceeds the standard, preventing secondary pollution or equipment damage caused by the spraying of substandard water. Simultaneously, the integral sewage discharge module dynamically adjusts the length of the sewage discharge window according to the pollution level, accelerating the sewage discharge response during heavy pollution and reducing unnecessary sewage discharge during light pollution, effectively extending the lifespan of the filtration device and reducing the frequency of manual maintenance. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the physical water path and filtration assembly in this invention;

[0050] Figure 2 This is a schematic diagram showing the connection between the intelligent controller and other mechanisms in this invention;

[0051] Figure 3 This is a schematic diagram of the module composition of the intelligent controller in this invention;

[0052] Figure 4 This is a schematic diagram illustrating the operating principle of the intelligent controller in this invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0054] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0055] like Figures 1-4 As shown, an embodiment of the present invention provides a device for recycling cleaning water from a sweeper truck, comprising:

[0056] The physical water circuit and filtration assembly includes a sewage tank, a solid-liquid separation device, a precision filtration device, a clean water tank connected in sequence, and a high-pressure water pump with its inlet connected to the clean water tank and its outlet connected to a spraying device.

[0057] The sensing and detection unit includes a first set of sensors for collecting water quality parameters of the recycled wastewater, a second set of sensors for collecting system status parameters, and a pressure sensor for collecting actual spraying pressure.

[0058] The intelligent controller is electrically connected to the sensing and detection unit and the high-pressure water pump. The intelligent controller has the following collaborative control modules embedded inside:

[0059] The multi-parameter fusion pollution level determination module takes at least two water quality parameters of the recycled wastewater and the changing trend of the water quality parameters as input, and outputs the road pollution level. The road pollution level increases with the increase of the water quality parameter values, and when the water quality parameters show an upward trend, the pollution level is corrected upward based on the fusion value.

[0060] The multi-factor adaptive water consumption generation module takes the road pollution level, the pressure difference between the front and rear ends of the precision filter device, and the real-time speed of the sweeper as inputs, and outputs the target water consumption. The target water consumption increases with the increase of the road pollution level, increases with the increase of the pressure difference to compensate for the decrease in water output capacity caused by filter blockage, and increases with the increase of vehicle speed to maintain the unit area spraying density during high-speed operation.

[0061] The pressure conversion module takes the target water consumption as input and outputs the target spraying pressure. The target spraying pressure and the target water consumption have a monotonically increasing functional relationship.

[0062] The constant pressure feedback control module takes the target spraying pressure and the actual spraying pressure as inputs and outputs a speed control signal for the high-pressure water pump. By adjusting the speed, the actual spraying pressure tracks the target spraying pressure.

[0063] The forced intervention module, when the pressure difference between the front and rear ends of the precision filter exceeds the preset maximum allowable pressure difference threshold or the turbidity of the purified water exceeds the preset safe turbidity threshold, forcibly cuts off the water inlet to the clean water tank and opens the bypass to allow the purified water to flow back to the sewage tank or be directly discharged.

[0064] In this embodiment, the wastewater tank is used to temporarily store mixed wastewater containing impurities such as mud, sand, particulate matter, and oil collected during sweeper operations. As the starting point of the entire water circulation system, it holds the raw wastewater to be treated. A solid-liquid separation device is installed after the wastewater tank to perform preliminary treatment on the collected wastewater. Its main objective is to remove large suspended solids and mud, reducing the burden on subsequent filtration devices and improving overall purification efficiency. A precision filtration device is installed after the solid-liquid separation device to further filter the pre-treated wastewater, removing smaller suspended particles and colloidal substances to meet the water quality requirements for spraying. The clean water tank stores water purified by the precision filtration device; this water will be reused for sweeping operations as cleaning water. It serves as a transfer station for purified water, ensuring a continuous supply of spraying water. The high-pressure water pump inlet is connected to the clean water tank, and the outlet is connected to the spraying device. This pump is responsible for pressurizing the purified water in the clean water tank and delivering it to the spraying device for effective road cleaning. The sensing and detection unit is used to collect various key data during the sweeper's operation in real time, including water quality parameters of recycled wastewater, system operating status parameters, and actual spraying pressure. This data forms the basis for the intelligent controller's decision-making and control. The intelligent controller, acting as the "brain" of the entire device, is electrically connected to the sensing and detection unit and the high-pressure water pump. It internally contains multiple collaborative control modules responsible for receiving sensor data, performing intelligent analysis and decision-making, and issuing control commands to the high-pressure water pump to achieve intelligent management of the recycling of cleaning water.

[0065] When the sweeper truck begins operation, its physical water system and filtration assembly start working. Wastewater on the road surface is collected into the wastewater tank, and then enters the solid-liquid separation device for preliminary treatment, removing larger silt and particles. Subsequently, the water flows into the precision filtration device for fine filtration, and the purified water is stored in the clean water tank, waiting to be sprayed again.

[0066] During this process, the sensing and detection unit operates continuously. The first set of sensors, such as turbidity sensors and particulate matter concentration sensors, collects the water quality parameters of the recycled wastewater entering the solid-liquid separation device in real time. Simultaneously, the second set of sensors, such as vehicle speed sensors, collects the real-time operating speed of the sweeper; differential pressure sensors monitor the pressure difference between the inlet and outlet of the precision filtration device; and spray pressure sensors collect the actual spray pressure at the spraying device in real time. All of this data is transmitted to the intelligent controller.

[0067] After receiving this data, the intelligent controller's internal collaborative control modules begin to work together. First, the multi-parameter fusion pollution level determination module receives the turbidity and particulate matter concentration values ​​of the recycled wastewater and analyzes the changing trends of these parameters. For example, if the current turbidity and particulate matter concentration values ​​are high and have shown a rapid upward trend over a period of time, the module will determine the current road surface pollution level as "severe pollution" and adjust the pollution level upward to anticipate potential sudden heavy pollution areas ahead.

[0068] Next, the multi-factor adaptive water consumption generation module receives the road pollution level of "heavy pollution," along with the differential pressure value of the precision filter and the real-time speed of the sweeper truck. Assuming a slight increase in differential pressure indicates minor filter clogging, and the sweeper truck is traveling at a moderate speed, the module calculates a higher target water consumption based on these inputs. Specifically, the increased pollution level leads to increased water consumption to ensure cleaning effectiveness; the increased differential pressure leads to a further increase in water consumption to compensate for potential reductions in water output due to filter clogging; and the increased vehicle speed also prompts an increase in water consumption to maintain spray density per unit area.

[0069] Subsequently, the pressure conversion module converts this higher target water consumption into a corresponding target spray pressure. Since the target water consumption and target spray pressure have a monotonically increasing relationship, a higher target spray pressure is generated.

[0070] Finally, the constant pressure feedback control module receives this higher target spray pressure and compares it with the actual spray pressure collected by the spray end pressure sensor. If the actual spray pressure is lower than the target pressure, the module immediately outputs a control signal, instructing the high-pressure water pump to increase its speed, thereby increasing the spray flow and pressure, so that the actual spray pressure quickly tracks and stabilizes at the target spray pressure. Thus, the sweeper truck can operate with the optimal water volume and spray pressure to adapt to the current heavy pollution, slightly clogged filter, and medium vehicle speed, ensuring effective cleaning.

[0071] During operation, if the differential pressure of the precision filtration device suddenly and drastically increases, exceeding the preset maximum allowable differential pressure threshold, or if the turbidity sensor detects that the turbidity of the purified water exceeds the preset safe turbidity threshold, the forced intervention module will be activated immediately. At this time, the intelligent controller will issue a command to cut off the inlet channel of the clean water tank and open the bypass, allowing the substandard purified water to flow back to the wastewater tank for reprocessing or be directly discharged. This avoids the use of substandard water for spraying, protects the spraying device, and prevents secondary pollution of the road surface.

[0072] In a preferred embodiment of the present invention, the first group of sensors includes:

[0073] An influent turbidity sensor is installed at the inlet of the solid-liquid separation device to collect the turbidity value of the recycled wastewater in real time.

[0074] A particulate matter concentration sensor is installed at the inlet of the solid-liquid separation device to collect the concentration value of suspended particulate matter in the recycled wastewater in real time.

[0075] The second set of sensors includes:

[0076] Vehicle speed sensor is used to collect the real-time operating speed of the sweeper truck;

[0077] A differential pressure sensor is installed between the inlet and outlet of the precision filter to collect the pressure difference between the front and back ends of the precision filter.

[0078] The turbidity sensor is installed at the outlet of the precision filter device to collect the turbidity value of the purified water.

[0079] The pressure sensor is a spray end pressure sensor, which is installed on the pipeline between the high-pressure water pump and the spraying device or at the inlet of the spraying device.

[0080] In this embodiment, the solution of this application precisely defines the specific types and installation locations of various sensors in the sensing and detection unit, ensuring the accuracy and reliability of the intelligent control of the entire sweeper truck cleaning water recycling device from the data source. Specifically, the first set of sensors, namely the influent turbidity sensor and the particulate matter concentration sensor, are strategically placed at the inlet of the solid-liquid separation device, ensuring that the collected turbidity and particulate matter concentration values ​​can most accurately reflect the original pollution status of the recycled wastewater. This raw, unprocessed data is crucial for the multi-parameter fusion pollution level determination module (as described in claim 1 above) to accurately assess the road pollution level, avoiding misjudgments caused by parameter distortion after the wastewater has undergone preliminary treatment.

[0081] Meanwhile, the second set of sensors, including a vehicle speed sensor, a differential pressure sensor, and an effluent turbidity sensor, each undertakes a key monitoring task. The vehicle speed sensor collects the sweeper's operating speed in real time, providing accurate speed information to the multi-factor adaptive water consumption generation module. This allows the water consumption to be adjusted reasonably according to changes in vehicle speed, thereby ensuring that the spray density per unit area remains consistent at different vehicle speeds, especially during high-speed operations.

[0082] A differential pressure sensor is installed between the inlet and outlet of the precision filtration device to directly and accurately monitor the degree of filter clogging. As the filter gradually becomes clogged, the differential pressure increases. This data is sent to a multi-factor adaptive water consumption generation module to calculate the clogging compensation coefficient, thereby dynamically adjusting the target water consumption to effectively compensate for the decrease in water output caused by filter clogging and ensure that the cleaning effect is not affected.

[0083] A turbidity sensor is installed at the outlet of the precision filter to monitor the turbidity value of the purified water in real time. This data is crucial for the forced intervention module (as described in claim 1 above). Once the turbidity of the purified water exceeds the preset safety threshold, the system can immediately trigger the forced intervention mechanism, cut off the water inlet to the clean water tank and open the bypass to prevent unqualified purified water from being used for spraying, thereby avoiding secondary pollution or nozzle clogging.

[0084] Furthermore, a spray end pressure sensor is installed on the pipeline between the high-pressure water pump and the spraying device, or at the inlet of the spraying device, to acquire pressure data closest to the actual spraying point. This precise actual spraying pressure value is fed back to the constant pressure feedback control module (as described in claim 1 above), enabling it to compare with the target spraying pressure and precisely adjust the speed of the high-pressure water pump, thereby achieving accurate tracking of the target spraying pressure and ensuring the stability and effectiveness of the spraying operation.

[0085] With this comprehensive and precisely positioned sensor configuration, the entire intelligent controller can make decisions and adjustments based on high-quality real-time data, enabling the sweeper truck's water recycling device to operate more precisely and adaptively.

[0086] In a preferred embodiment of the present invention, the multi-parameter fusion pollution level determination module calculates the road surface pollution level according to the following formula. :

[0087]

[0088] in: This is the turbidity fusion weighting coefficient. , This is the particulate matter concentration weighting coefficient. , The coefficient representing the influence of turbidity increment. , This is the fusion value - level quantization coefficient. , for Normalized turbidity value at time point. for Normalized value of particulate matter concentration at any given time. , Preset time interval The normalized turbidity increment within; The preset maximum pollution level, ;

[0089] By The turbidity values ​​collected by the influent turbidity sensor at all times are substituted into the maximum-minimum normalization formula to calculate the maximum and minimum values, which are the maximum and minimum ranges of the turbidity sensor.

[0090] By The particulate matter concentration value collected by the particulate matter concentration sensor at any time is substituted into the maximum-minimum normalization formula for calculation; the maximum and minimum values ​​are the maximum and minimum ranges of the particulate matter concentration sensor, respectively.

[0091] In this embodiment, the multi-parameter fusion pollution level determination module is a collaborative control module embedded within the intelligent controller. Its core function is to comprehensively analyze multiple input parameters and, based on preset logic or algorithms, output a level representing the current degree of road pollution. This module can be implemented by embedded software, running on the microprocessor inside the intelligent controller, or its logic function can be implemented through a programmable logic controller (PLC).

[0092] Road surface pollution level A quantitative indicator that indicates the current level of road surface pollution, usually a discrete integer value, such as from 1 to 5. The higher the number, the more severe the pollution. This level can be used to guide subsequent water consumption decisions.

[0093] Turbidity fusion weighting coefficient The value of turbidity is used to measure the relative importance of turbidity in the determination of pollution level. Its value ranges from 0.5 to 0.9, indicating that turbidity plays a dominant role in the fusion calculation. This weighting coefficient can be preset according to actual operation experience or optimized and adjusted based on historical data through machine learning algorithms.

[0094] Particulate matter concentration weighting coefficient Used to measure the relative importance of particulate matter concentration in pollution level determination, its value is equal to 1 minus the turbidity fusion weighting coefficient. To ensure that the sum of the two weights is 1, this coefficient can also be set according to the actual work scenario and experience.

[0095] Turbidity Increment Influence Coefficient The value of this coefficient, which is used to adjust the strength of the correction of pollution level by the trend of turbidity change, ranges from 0 to 0.5. It represents the corrective effect of the turbidity increment on the pollution level and can be adjusted according to the need for sensitivity to pollution changes.

[0096] Fusion value - level quantification coefficient This coefficient is used to quantify the merged water quality parameter values ​​into discrete pollution levels. Its value ranges from 0.1 to 0.3, affecting the mapping granularity from the merged value to the pollution level. This coefficient can be set according to the required level of detail in the pollution level classification.

[0097] Normalized value of turbidity at time This refers to the current moment. The collected turbidity values ​​of the recycled wastewater are normalized. The purpose of normalization is to eliminate differences in the range and unit of different sensors and convert them into dimensionless values ​​within a uniform range of 0 to 1.

[0098] Normalized value of particulate matter concentration at time This refers to the current moment. The collected particulate matter concentration values ​​from the recycled wastewater are normalized to eliminate dimensional differences and convert them into dimensionless values ​​within a uniform range of 0 to 1.

[0099] Preset time interval Normalized turbidity increment within Indicates the current time The normalized turbidity value and the previous preset time interval The difference between previous normalized turbidity values; this parameter reflects the trend of turbidity change over a short period of time, with a preset time interval. The settings can be configured according to the operating speed of the sweeper and the real-time requirements for responding to changes in pollution.

[0100] Preset maximum pollution level This refers to the highest pollution level that the system can determine. Its value ranges from 3 to 5 and is used to limit the upper limit of the pollution level to prevent the calculation results from exceeding a reasonable range. This maximum level can be set according to the actual application scenario and the cleaning capacity of the sweeper.

[0101] The maximum-minimum normalization formula is a commonly used data normalization method. Its basic form is: X normalized = (XX) min ) / (X max - X min This method can linearly map the original data to the range of 0 to 1, which facilitates the fusion processing of data with different dimensions.

[0102] The solution in this application achieves accurate quantification of road surface pollution levels through a multi-parameter fusion pollution level determination module. This module receives recycled wastewater quality parameters collected from the first set of sensors in the sensing and detection unit (e.g., an influent turbidity sensor and a particulate matter concentration sensor). Specifically, the intelligent controller first acquires the influent turbidity sensor data... The turbidity and particulate matter concentration sensors collect data at all times. The raw data consists of particulate matter concentration values ​​collected at various times. To eliminate differences in measurement range and units between different sensors, these raw data are converted into dimensionless normalized values ​​using a maximum-minimum normalization formula. and This allows them to be compared and fused on a uniform scale. Subsequently, the intelligent controller utilizes preset turbidity fusion weighting coefficients. and particulate matter concentration weighting coefficient For the normalized turbidity value and particulate matter concentration value A weighted average is then used to form a basic integrated pollution intensity value.

[0103] Based on this, in order to capture the dynamic changes in road surface pollution, the system further calculates preset time intervals. Normalized turbidity increment within If the turbidity shows an upward trend (i.e.) If the turbidity increment is greater than 0, it indicates that there may be a sudden area of ​​heavy pollution ahead. In this case, the turbidity increment will affect the turbidity increment coefficient. The baseline pollution intensity value is adjusted upwards, allowing the final pollution level to more sensitively reflect the worsening trend of pollution. The adjusted pollution intensity value is then quantified using a fusion value minus a level quantification coefficient. The data is quantified and rounded down to convert it into discrete road surface pollution levels. To ensure the pollution level is within a reasonable range, the calculation result will also be compared with the preset maximum pollution level. The system compares the two values ​​and takes the minimum to avoid excessively high pollution levels or exceeding the system's processing capacity. This entire process forms a closed-loop, adaptive pollution level determination mechanism, enabling the intelligent controller to output an accurate pollution level reflecting the current road surface condition based on real-time water quality data and its trends. This provides reliable input for the subsequent multi-factor adaptive water consumption generation module, thereby optimizing the overall performance of the cleaning water recycling device.

[0104] In a preferred embodiment of the present invention, the multi-factor adaptive water consumption generation module calculates the target water consumption according to the following formula. :

[0105]

[0106] in This is the unit-level water consumption increment coefficient. , Based on the baseline water consumption, The level of road surface pollution. for Congestion compensation coefficient at any time For vehicle speed correction function; The road surface wettability coefficient. This represents the discrete control cycle number. Indicates the first Road surface wetness coefficient for each control cycle; initial value , , This represents the minimum value of the road surface wettability coefficient. .

[0107] In this embodiment, the multi-factor adaptive water consumption generation module is a functional unit within the intelligent controller. Its core function is to dynamically calculate the optimal target water consumption based on various real-time operating parameters. This module can be implemented as a software program running within the intelligent controller, such as an algorithm executed on an embedded microcontroller or digital signal processor. Normalization of the pressure difference and vehicle speed aims to convert raw data from different sensors (such as the pressure difference before and after the precision filtration device and the real-time speed of the sweeper truck) into a unified numerical range to eliminate dimensional differences and ensure that these parameters can be fairly and accurately integrated in subsequent calculations. Normalization can be achieved using a maximum-minimum normalization method.

[0108] The baseline water consumption in the formula This refers to the initial water consumption required under standard, lightly polluted, and dry road conditions. It can be obtained through experimental calibration or empirical setting. (Unit water consumption increment coefficient) This coefficient is used to quantify the percentage increase in water consumption required for each additional unit of road surface pollution level. This coefficient can usually be adjusted according to actual operational needs.

[0109] Road surface pollution level It is output by the multi-parameter fusion pollution level determination module, which directly reflects the severity of road pollution and is a key input affecting water consumption calculation.

[0110] Congestion compensation coefficient Designed to compensate for the decrease in water output caused by filter clogging in precision filtration devices, its value increases with the degree of filter clogging (reflected by the pressure difference), thereby correspondingly increasing the target water consumption. Vehicle speed correction function. This function adjusts the water usage based on the real-time speed of the sweeper to ensure consistent spray density per unit area at different speeds. For example, at higher speeds, the function uses more water.

[0111] Surface wettability coefficient This is an adaptive parameter reflecting the road surface's moisture level. Its initial value is set to 1, indicating a dry road surface. During continuous operation, this coefficient is adjusted according to actual conditions to appropriately reduce water consumption when the road surface becomes moist, thereby conserving water resources. Discrete control cycle number. This indicates the time step for system control and parameter updates. Minimum road surface wettability coefficient. A lower limit for the road surface wetness coefficient was set to ensure that even when the road surface is very wet, a minimum amount of water can be used to meet basic cleaning needs.

[0112] This multi-factor adaptive water consumption generation module, as a core function of the intelligent controller, receives and processes real-time data from the sensing and detection unit. This module utilizes the road surface pollution level output from the multi-parameter fusion pollution level determination module. As a basis, combined with benchmark water consumption Water usage increment coefficient per unit level The initial water demand was determined to match the level of road pollution. Based on this, the system further incorporates a congestion compensation coefficient. This coefficient is dynamically adjusted based on the differential pressure value of the precision filtration device. When the filter element gradually becomes clogged, causing the differential pressure to increase, This increases the target water consumption, effectively compensating for the reduced water output caused by filter clogging and ensuring that the actual spraying volume remains unaffected. Simultaneously, the vehicle speed correction function... Adjustments are made based on the real-time speed of the sweeper truck, increasing water usage as the speed increases to maintain spray density per unit area and ensure effective cleaning during high-speed operations. Additionally, the road surface wettability coefficient is also considered. It also plays a role in the calculation, with an initial value of 1, indicating a dry road surface. During continuous operation, this coefficient is recursively updated based on historical water usage feedback; as the road surface gradually becomes wet, This reduces the target water consumption, thereby avoiding unnecessary water waste. By organically integrating multiple key factors such as road pollution level, filter clogging status, sweeper speed, and road wetness into the target water consumption calculation formula, this module can generate a highly adaptive target water consumption. The precisely calculated target water consumption is then transmitted to the pressure conversion module, which converts it into the target spray pressure. This pressure then controls the speed of the high-pressure water pump to achieve a precise spray flow rate, thereby maximizing water conservation while ensuring effective cleaning.

[0113] In a preferred embodiment of the present invention, the blockage compensation coefficient Calculate the pressure difference using the following formula based on the normalized pressure difference value:

[0114]

[0115] in for Normalized value of pressure difference at any time , To compensate for the strength coefficient, ; By The differential pressure values ​​collected by the differential pressure sensor at all times are substituted into the maximum-minimum normalization formula to calculate the differential pressure. The maximum and minimum values ​​are the maximum and minimum ranges of the differential pressure sensor, respectively.

[0116] In this embodiment, the plug compensation coefficient This coefficient is used to quantify the impact of filter cartridge clogging on water output in precision filtration devices and to adjust the target water consumption accordingly. Its function is to ensure that when filter cartridge clogging leads to a decrease in water output, the actual spraying effect is maintained by increasing the water consumption. This coefficient can be a dynamically changing value, reflecting the degree of filter cartridge clogging in real time.

[0117] Normalized pressure difference This refers to transforming the raw differential pressure data collected by the differential pressure sensor into a uniform, dimensionless range (e.g., between 0 and 1) through maximum-minimum normalization. This normalization process can eliminate differences between differential pressure sensors of different models or ranges, making the data comparable and facilitating fusion calculations with other parameters.

[0118] Compensation strength coefficient This is an adjustable parameter used to control the intensity or sensitivity of clogging compensation. Its value ranges from 0.2 to 0.8, allowing the system to be flexibly configured according to the specific characteristics of the filter device, the filter material, and the desired compensation effect. For example, for scenarios prone to clogging or requiring high water output, a larger value can be set. A value can be set to provide stronger compensation; conversely, a smaller value can be set. The differential pressure sensor is used to monitor the pressure difference between the inlet and outlet of a precision filtration device in real time. The pressure difference is a key indicator of the degree of filter cartridge clogging; as the filter cartridge becomes clogged, the pressure difference between the inlet and outlet gradually increases. Differential pressure sensors can take various forms, such as differential pressure transmitters, diaphragm differential pressure gauges, or capacitive differential pressure sensors. Their core function is to accurately measure and output an electrical signal representing the pressure difference. The maximum and minimum ranges of a differential pressure sensor refer to the upper and lower limits of the pressure difference values ​​that the sensor can accurately measure and output. These range parameters are provided by the sensor manufacturer and are part of the sensor's inherent properties. When performing maximum-minimum normalization, the sensor's maximum and minimum ranges are directly used as `X` in the normalization formula. max ` and `X min This ensures the accuracy and consistency of the normalization results and avoids errors caused by improperly preset thresholds.

[0119] The solution in this application introduces a congestion compensation coefficient. The system employs a specific calculation method to achieve adaptive compensation for reduced water output capacity caused by filter element clogging in precision filtration devices. Specifically, the system first uses a differential pressure sensor to collect the real-time pressure difference between the inlet and outlet of the precision filter. This pressure difference directly reflects the degree of filter element clogging; a larger pressure difference indicates more severe clogging and a greater reduction in water output capacity. To eliminate the influence of different sensor ranges, the collected raw pressure difference value is processed using a maximum-minimum normalization formula. The maximum and minimum values ​​are directly taken from the maximum and minimum ranges of the differential pressure sensor, resulting in a unified, dimensionless normalized pressure difference value. Its range is between 0 and 1. The intelligent controller then normalizes this differential pressure value. Substitute the values ​​into the preset linear formula to calculate the current congestion compensation coefficient. In this formula, the base value of 1 represents the baseline compensation when the filter element is not clogged, while the linear correction term... Then, depending on the degree of clogging of the filter element ( (Reflects) additional compensation. Compensation intensity coefficient The system can adjust the sensitivity of compensation according to actual needs. The calculated congestion compensation coefficient... The target water consumption is then adjusted by the multi-factor adaptive water consumption generation module. When the filter cartridge becomes increasingly clogged... Enlargement, leading to As the pressure increases, the target water consumption calculated by the multi-factor adaptive water consumption generation module also increases accordingly, effectively compensating for the decrease in water output capacity caused by filter clogging and ensuring that the actual spraying water volume meets operational needs. This adaptive compensation mechanism based on real-time differential pressure feedback enables the sweeper truck to continuously provide a stable and sufficient spraying water volume during long-term operation or when facing different levels of pollution, avoiding a decrease in spraying effect or water waste caused by filter clogging.

[0120] As a preferred embodiment of the present invention, the vehicle speed correction function For piecewise functions:

[0121]

[0122] in for Normalized value of vehicle speed at any time To correct the start threshold for the normalized vehicle speed, This is the vehicle speed correction factor. ; By The real-time operating speed of the sweeper truck, collected by the vehicle speed sensor, is calculated by substituting it into the maximum-minimum normalization formula; the maximum and minimum values ​​are the maximum and minimum ranges of the vehicle speed sensor, respectively.

[0123] In this embodiment, the vehicle speed correction function The piecewise function approach dynamically adjusts the target water consumption correction strategy based on the real-time vehicle speed range. This piecewise design allows the system to employ differentiated control logic under different operating scenarios, enabling more refined water resource management.

[0124] Normalized value of vehicle speed This process transforms the raw vehicle speed data collected by the vehicle speed sensor into a uniform numerical range using a maximum-minimum normalization formula. This eliminates the influence of different sensor ranges and facilitates fusion calculations with other normalized parameters. The normalization process typically uses the sensor's maximum and minimum ranges as the boundaries of the normalization interval to ensure the accuracy and consistency of the transformation.

[0125] Vehicle speed correction start threshold This is a preset critical speed value used to distinguish between low-speed regular operation and high-speed operation modes of the sweeper truck. When the real-time speed is below or equal to this threshold, the system determines it to be low-speed operation and does not perform additional speed correction; when the real-time speed is above this threshold, the speed correction mechanism is activated. This threshold can be set through experimental testing or expert experience based on the specific design of the sweeper truck, the operating environment, and cleaning requirements, and can be flexibly adjusted as a configurable parameter.

[0126] Vehicle speed correction factor This is a key adjustment parameter, with a value range of [0.5, 1.5]. This coefficient determines the intensity of the increase in target water consumption when the vehicle speed exceeds the corrected start threshold. By adjusting... This allows for precise control of water consumption increases during high-speed operations, ensuring consistent spray density per unit area at different vehicle speeds, thus balancing cleaning effectiveness and water resource utilization efficiency. This coefficient can also be calibrated and optimized through actual operational testing.

[0127] The proposed solution uses a segmented vehicle speed correction function to differentiate water consumption for different vehicle speed ranges. This can compensate for the spray density per unit area during high-speed operations and avoid unnecessary increases in water consumption during low-speed operations, thus balancing cleaning effectiveness and water conservation goals.

[0128] The vehicle speed correction function is defined in the form of a piecewise function, distinguishing between two speed ranges: one that does not require correction and one that does. This approach aligns with the actual operational characteristics of sweeper trucks.

[0129] When the vehicle speed does not exceed the correction start threshold, the vehicle speed correction coefficient is set to 1, which will not change the original calculated target water consumption. This is because when the sweeper operates at low speed, the distance traveled per unit time is short, and the original baseline water consumption can already meet the spraying density requirements per unit area. There is no need to increase the water consumption. This can avoid unnecessary waste of water resources when operating at low speed, which is in line with the water-saving design goal.

[0130] When the vehicle speed exceeds the correction threshold, the correction function calculates the correction amount based on the increment of the speed exceeding the threshold, combined with a speed correction coefficient. The final correction coefficient is greater than 1, resulting in an upward adjustment of the target water consumption. The higher the vehicle speed, the greater the magnitude of the speed exceeding the threshold, the larger the correction amount, and the greater the increase in target water consumption. This perfectly matches the requirement for higher flow rates per unit time to maintain the original spray density per unit area during high-speed operations, ensuring effective cleaning even at high speeds and preventing insufficient spraying and inadequate cleaning due to increased vehicle speed.

[0131] The normalization process directly uses the range of the vehicle speed sensor itself as the maximum and minimum values, without requiring additional calibration parameters. The calculation is simple and convenient, and it is compatible with the computing power requirements of the onboard controller. By setting the vehicle speed correction coefficient within a reasonable range, the specific value of the coefficient can be adjusted according to the different models of sweeper trucks and operational needs, ensuring that the correction strength meets the requirements of actual operation.

[0132] As a preferred embodiment of the present invention, the road surface wetting coefficient Updated based on historical water consumption feedback according to the following recursive relationship:

[0133]

[0134] in To learn step length, , For the first Actual water consumption per control cycle; For the first The target water consumption for each control cycle.

[0135] In this embodiment, the road surface wetting coefficient is... Used to quantify the moisture level of a road surface, reflecting its ability to absorb water after washing. Its value typically ranges from a preset minimum value. The value ranges from 1 to 1, where 1 indicates the road surface is completely dry and requires the full amount of water, while lower values ​​indicate the road surface is partially moist and water usage can be reduced. This coefficient allows the system to dynamically adjust water demand based on actual road conditions, avoiding unnecessary resource waste.

[0136] Historical water usage feedback refers to the system comparing the actual water usage data from one or more previous control cycles with the target water usage set for the same period to obtain a basis for changes in road surface wetness. This feedback mechanism can be a direct comparison of the ratio of actual water usage to target water usage, or it can be based on the cumulative or trend analysis of the difference between the two. Its core is to assess the road surface wetness through actual operational results, providing data support for subsequent adjustments to water usage.

[0137] Recursive relationship update refers to the update of road surface wettability coefficient The current value is based on its previous control cycle ( The value of the wetting coefficient is calculated based on historical water consumption feedback. This update method allows the system to learn and adapt to changes in road surface wetness online and continuously, rather than starting from zero each time. For example, a linear recursive formula or a more complex algorithm based on exponential smoothing can be used for updates to ensure the stability and responsiveness of the wetting coefficient.

[0138] Learning Step Size It is an adjustable parameter used to control the road surface wettability coefficient. The adjustment range during each iterative update. A larger learning step size allows the wetting coefficient to respond quickly to changes in road surface wetness, but may cause system fluctuations; a smaller learning step size makes the system response more stable, but may converge more slowly. The setting of this parameter needs to balance the system's response speed and stability, and its value range is usually determined through experience or optimization algorithms, for example, between 0.05 and 0.2.

[0139] For the first The actual water consumption in the first control cycle refers to the water consumption in the second control cycle. Within each control cycle, the actual amount of water sprayed onto the road surface by the sweeper truck through the spraying device is measured. This data can be obtained in real time through the flow sensor of the high-pressure water pump and accumulated, or estimated by comparing the speed of the high-pressure water pump with a pre-calibrated flow curve. Accurately obtaining the actual water usage is crucial for assessing the road surface wetness and updating the wetness coefficient.

[0140] For the first The target water consumption for the first control cycle refers to the water consumption in the first control cycle. Within each control cycle, the theoretical water consumption is calculated by the multi-factor adaptive water consumption generation module based on factors such as the road surface pollution level, the pressure difference between the front and rear ends of the precision filtration device, and the real-time speed of the sweeper truck. This target water consumption represents the ideal water volume required to achieve the expected cleaning effect under the current operating conditions.

[0141] The minimum road surface wetness coefficient is a preset lower limit value used to ensure that even if the road surface is very wet, the system will not reduce water consumption to a level that affects cleaning performance. This minimum value guarantees the basic water needs of sweeping and washing operations and prevents incomplete cleaning due to excessive water conservation. For example, this value can be set between 0.6 and 0.8 to strike a balance between water conservation and cleaning effectiveness.

[0142] This solution utilizes a multi-factor adaptive water consumption generation module within the intelligent controller to generate the target water consumption. At that time, the road surface wetting coefficient was introduced. As a correction factor. In each discrete control cycle In the middle, the system first determines the control cycle based on the previous control cycle. Actual water consumption and target water consumption The ratio, combined with the learning step size To calculate the adjustment amount for the wetting coefficient. Specifically, when Less than When the system detects a discrepancy between the current wetness coefficient and the target water volume, it indicates that the road surface was sufficiently moist in the previous cycle and failed to fully absorb the target water volume. The system will then adjust the current wetness coefficient downwards using a recursive formula based on the difference between the two values. Conversely, if equal to or greater than This indicates that the road surface still needs more water or has already absorbed it completely; the wetting coefficient will not be corrected downwards, thus ensuring the basic water usage. To avoid excessive water conservation affecting the cleaning effect, the updated wetting coefficient... Will be with the preset minimum value The values ​​are compared, and the larger value is taken to ensure that the wetting coefficient never falls below a safe threshold. Initially, the road surface wetting coefficient... Setting it to 1 indicates that the road surface is dry and requires full water usage.

[0143] This solution, working in conjunction with a multi-factor adaptive water consumption generation module, enables the sweeper truck to learn the road surface's moisture level online during continuous operation. The multi-factor adaptive water consumption generation module already dynamically adjusts the target water consumption based on road surface pollution levels, filter clogging, and vehicle speed. This solution further incorporates the ability to perceive and adapt to historical road surface moisture effects. Through this iterative update mechanism, the system continuously corrects its judgment of road surface moisture levels, ensuring that the target water consumption for subsequent operations more accurately reflects the actual needs of the road surface. For example, when the sweeper truck performs a second or third wash on the same road segment, because the road surface is already wet, the system automatically reduces the road surface moisture coefficient based on the water consumption feedback from the previous cycle, thereby reducing the target water consumption. This significantly reduces water consumption while maintaining cleaning effectiveness. This feedback-based adaptive learning capability allows the sweeper truck to manage water resources more intelligently and precisely, solving the problem of water waste caused by the inability of traditional systems to perceive road surface moisture levels.

[0144] In a preferred embodiment of the present invention, the target spray pressure in the pressure conversion module is... With target water consumption The conversion relationship between them is as follows:

[0145]

[0146] in The baseline water consumption; The pressure-to-flow conversion factor, The flow-pressure characteristic curve of the high-pressure water pump is pre-calibrated, with units in megapascals per liter per minute.

[0147] In this embodiment, the pressure conversion module is a functional unit within the intelligent controller. Its main function is to convert the target water consumption calculated by the system into the target spraying pressure required by the high-pressure water pump. This module can be embedded in the intelligent controller as software, for example, by implementing specific algorithm logic through a programming language.

[0148] Target spray pressure It refers to a certain moment The pressure value that the high-pressure water pump needs to output is the control target of the constant pressure feedback control module, ensuring that the spraying device can operate at the desired pressure. This pressure value can be transmitted as a control signal to the high-pressure water pump's drive circuit, or it can be displayed on the operating interface for the operator's reference.

[0149] Target water consumption This refers to the amount of water sprayed per unit time by a sweeper truck to achieve the desired cleaning effect under current operating conditions. This water consumption is usually calculated by a multi-factor adaptive water consumption generation module based on factors such as road surface pollution level, filter clogging, and vehicle speed. Alternatively, it can be an initial or correction value manually set by the operator based on experience.

[0150] Conversion Relationship Formula This is a linear model used to map changes in target water consumption to changes in target spray pressure. The formula can be implemented in a smart controller through software programming, performing the corresponding mathematical calculations.

[0151] Baseline water consumption This is a preset reference water consumption value, which usually represents the system's basic water demand under standard or lightly polluted conditions. It can be a default value preset at the factory based on parameters such as the sweeper truck model and spraying device type, or it can be a minimum operating water consumption set based on actual operating experience.

[0152] Pressure-to-flow conversion factor This is a key parameter that characterizes how the output pressure of a high-pressure water pump responds to changes in flow rate. This coefficient can be obtained through experimental testing, such as in a laboratory setting by controlling the flow rate of the high-pressure water pump and measuring the corresponding pressure output, then fitting the data; alternatively, it can be obtained directly from the datasheet provided by the high-pressure water pump manufacturer. Pre-calibration of the high-pressure water pump's flow-pressure characteristic curve refers to obtaining the actual output pressure data of the high-pressure water pump at different flow rates through a series of experiments or tests before the system is put into use, and establishing its flow-pressure characteristic curve accordingly. This process ensures... The accuracy of the value ensures that it truly reflects the working characteristics of the high-pressure water pump used, thereby guaranteeing that the converted target spray pressure matches the actual water demand.

[0153] This application's solution achieves precise mapping from target water consumption to target spraying pressure by introducing a linear conversion relationship calibrated based on the actual flow-pressure characteristic curve of the high-pressure water pump into the pressure conversion module. Specifically, the multi-factor adaptive water consumption generation module dynamically calculates the target water consumption based on factors such as the current road pollution level, the pressure difference between the front and rear ends of the precision filtration device, and the real-time speed of the sweeper truck. The target water consumption is then transmitted as input to the pressure conversion module. The pressure conversion module uses a preset baseline water consumption... and reference pressure Combined with the pressure-flow conversion coefficient obtained in advance based on the high-pressure water pump flow-pressure characteristic curve. The required target spray pressure is calculated using a linear formula. This conversion method not only meets the basic requirement that the target spraying pressure increases monotonically with the target water consumption, but more importantly, it achieves this through... The pre-calibration ensures that the conversion relationship accurately matches the actual operating characteristics of the high-pressure water pump used, thus eliminating conversion errors caused by differences in pump characteristics. The calculated target spray pressure is then sent to the constant pressure feedback control module as the basis for controlling the high-pressure water pump speed, ensuring that the actual spray pressure accurately tracks the target spray pressure, thereby guaranteeing a high degree of consistency between the actual spray water consumption and the target water consumption calculated by the system based on operational needs. This mechanism enables the entire cleaning water recycling device to precisely adjust the spray pressure according to complex changes in the operating environment (such as road pollution, filter clogging, vehicle speed changes, etc.) to achieve optimal cleaning results and water resource utilization efficiency.

[0154] As a preferred embodiment of the present invention, it also includes an integral sewage discharge module, which accumulates particulate matter concentration or turbidity values ​​within a sliding time window. When the accumulated value exceeds a preset sewage discharge threshold, it controls the sewage discharge valve at the bottom of the solid-liquid separation device to open. The length of the sliding time window is negatively correlated with the current road pollution level: the higher the pollution level, the shorter the window length, and the faster the sewage discharge response.

[0155] In this embodiment, the integral discharge module is a functional module within the intelligent controller. Its main function is to intelligently determine the timing of discharge from the solid-liquid separation device based on the real-time water quality parameters of the recycled wastewater, and control the opening and closing of the discharge valve. This module can be implemented by a specific algorithm executed by the microprocessor in the intelligent controller, or it can be implemented through dedicated hardware logic circuits. Accumulating particulate matter concentration or turbidity values ​​within a sliding time window means that the integral discharge module continuously monitors the particulate matter concentration or turbidity values ​​of the recycled wastewater and accumulates these values ​​over a dynamically adjusted time period. The particulate matter concentration value can be collected by a particulate matter concentration sensor installed at the inlet of the solid-liquid separation device, and the turbidity value can be collected by an influent turbidity sensor installed at the inlet of the solid-liquid separation device. The accumulation method can be summing instantaneous values ​​over a period of time or integrating the average value over a period of time. When the accumulated value exceeds the preset discharge threshold, the discharge valve at the bottom of the solid-liquid separation device opens. This means that when the accumulated pollutant quantity calculated by the integral discharge module reaches the preset safety limit, the intelligent controller sends a control signal to the discharge valve at the bottom of the solid-liquid separation device to open it, thereby discharging the accumulated silt and particulate matter. The discharge valve can be an electric, pneumatic, or hydraulic valve, remotely controlled by the intelligent controller. The length of the sliding time window is negatively correlated with the current road surface pollution level. This means that the time window used for accumulating pollutants is not fixed but dynamically adjusted based on the road surface pollution level output by the multi-parameter fusion pollution level determination module in the intelligent controller. This negative correlation means that the higher the road surface pollution level, the faster the pollutants accumulate, and the system will use a shorter sliding time window to check more frequently whether discharge is needed to ensure timely response; conversely, the lower the pollution level, the slower the pollutants accumulate, and the system will use a longer sliding time window to avoid unnecessary frequent discharges.

[0156] The solution proposed in this application achieves intelligent sewage discharge control of the solid-liquid separation device through an integral sewage discharge module. Specifically, the integral sewage discharge module continuously receives water quality parameters of the recycled wastewater collected from a first set of sensors (such as an influent turbidity sensor and a particulate matter concentration sensor) and accumulates these parameters within a sliding time window inside the intelligent controller. This accumulated value directly reflects the total amount of pollutants accumulated in the solid-liquid separation device over a period of time. When the accumulated value reaches a preset sewage discharge threshold, the integral sewage discharge module triggers a sewage discharge command, controlling the sewage discharge valve at the bottom of the solid-liquid separation device to open and discharge the pollutants. Furthermore, to achieve more refined adaptive control, the integral sewage discharge module also dynamically adjusts the length of the sliding time window based on the current road surface pollution level output by the multi-parameter fusion pollution level determination module in the intelligent controller. When the road surface pollution level is high, indicating a rapid accumulation of pollutants, the integral sewage discharge module shortens the sliding time window, thereby accelerating the sewage discharge response speed, promptly removing large amounts of pollutants, and preventing blockage of the solid-liquid separation device. Conversely, when the road surface pollution level is low, the pollutant accumulation rate is slow, and the integral sewage discharge module extends the sliding time window, reducing unnecessary frequent sewage discharge and thus conserving water resources. This adaptive sewage discharge strategy, based on the cumulative amount of pollutants and the level of road pollution, enables sewage control to be precisely matched to the actual operation scenario, effectively solving the limitations of traditional sewage discharge methods.

[0157] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A device for recycling cleaning water from a sweeper truck, characterized in that, include: The physical water circuit and filtration assembly includes a sewage tank, a solid-liquid separation device, a precision filtration device, a clean water tank connected in sequence, and a high-pressure water pump with its inlet connected to the clean water tank and its outlet connected to a spraying device. The sensing and detection unit includes a first set of sensors for collecting water quality parameters of the recycled wastewater, a second set of sensors for collecting system status parameters, and a pressure sensor for collecting actual spraying pressure. The intelligent controller is electrically connected to the sensing and detection unit and the high-pressure water pump. The intelligent controller has the following collaborative control modules embedded inside: The multi-parameter fusion pollution level determination module takes at least two water quality parameters of the recycled wastewater and the changing trend of the water quality parameters as input, and outputs the road pollution level. The multi-factor adaptive water consumption generation module takes the road pollution level, the pressure difference between the front and rear ends of the precision filter device, and the real-time speed of the sweeper as inputs, and outputs the target water consumption. The pressure conversion module takes the target water consumption as input and outputs the target spraying pressure. The constant pressure feedback control module takes the target spraying pressure and the actual spraying pressure as inputs and outputs a speed control signal for the high-pressure water pump. By adjusting the speed, the actual spraying pressure tracks the target spraying pressure. The forced intervention module, when the pressure difference between the front and rear ends of the precision filter exceeds the preset maximum allowable pressure difference threshold or the turbidity of the purified water exceeds the preset safe turbidity threshold, forcibly cuts off the water inlet to the clean water tank and opens the bypass to allow the purified water to flow back to the sewage tank or be directly discharged.

2. The sweeper washing water recycling device according to claim 1, characterized in that, The first set of sensors includes: An influent turbidity sensor is installed at the inlet of the solid-liquid separation device to collect the turbidity value of the recycled wastewater in real time. A particulate matter concentration sensor is installed at the inlet of the solid-liquid separation device to collect the concentration value of suspended particulate matter in the recycled wastewater in real time. The second set of sensors includes: Vehicle speed sensor is used to collect the real-time operating speed of the sweeper truck; A differential pressure sensor is installed between the inlet and outlet of the precision filter to collect the pressure difference between the front and back ends of the precision filter. The turbidity sensor is installed at the outlet of the precision filter device to collect the turbidity value of the purified water. The pressure sensor is a spray end pressure sensor, which is installed on the pipeline between the high-pressure water pump and the spraying device or at the inlet of the spraying device.

3. The sweeper washing water recycling device according to claim 2, characterized in that, The multi-parameter fusion pollution level determination module calculates the road surface pollution level in the following manner: The turbidity fusion weighting coefficient is multiplied by the turbidity normalization value, and then the particulate matter concentration weighting coefficient is multiplied by the particulate matter concentration normalization value to obtain the fusion value; where the particulate matter concentration weighting coefficient is equal to 1 minus the turbidity fusion weighting coefficient. Calculate the difference between the normalized turbidity value at the current time and the normalized turbidity value at the previous time to obtain the turbidity increment. Then multiply it by the preset turbidity increment influence coefficient and add 1 to obtain the trend correction factor. Multiply the fusion value by the trend correction factor, then divide by the preset fusion value-level quantification coefficient, round the result down, and compare it with the preset maximum pollution level to obtain the road pollution level. The turbidity normalized value and the particulate matter concentration normalized value are calculated by substituting the sensor measured values ​​into the maximum-minimum normalization formula.

4. The sweeper washing water recycling device according to claim 3, characterized in that, The multi-factor adaptive water consumption generation module calculates the target water consumption in the following manner: The baseline water consumption is calculated by multiplying the baseline water consumption by (1 plus the product of the unit water consumption increment coefficient and the road pollution level) to obtain the baseline water consumption. The unit water consumption increment coefficient is between 0.1 and 0.

5. Multiply the base water consumption by the road surface wetness coefficient, the congestion compensation coefficient, and the vehicle speed correction function to obtain the target water consumption. The initial value of the road surface wetting coefficient is 1.

5. The sweeper washing water recycling device according to claim 4, characterized in that, The blockage compensation coefficient is calculated based on the normalized pressure difference value as follows: The clogging compensation coefficient is equal to 1 plus the product of the compensation strength coefficient and the pressure difference normalization value; the pressure difference normalization value is calculated by substituting the pressure difference values ​​of the front and rear ends of the precision filter device collected by the pressure difference sensor into the maximum-minimum value normalization formula.

6. The sweeper washing water recycling device according to claim 5, characterized in that, The vehicle speed correction function is a piecewise function: When the normalized vehicle speed value is less than or equal to the vehicle speed correction start threshold, the vehicle speed correction function takes the value of 1; When the normalized vehicle speed value is greater than the vehicle speed correction threshold, the vehicle speed correction function is set to 1 plus the vehicle speed correction coefficient multiplied by (the difference between the normalized vehicle speed value and the threshold). The normalized vehicle speed value is calculated by substituting the real-time operating vehicle speed collected by the vehicle speed sensor into the maximum-minimum normalization formula.

7. The sweeper washing water recycling device according to claim 4, characterized in that, The road surface wetness coefficient is updated based on historical water consumption feedback according to the following recursive relationship: The road surface wetness coefficient of the current control cycle is equal to the road surface wetness coefficient of the previous cycle minus the learning step size multiplied by (the ratio of actual water consumption to target water consumption in the previous cycle minus 1), and then compared with the minimum value of the road surface wetness coefficient to take the larger value.

8. The sweeper washing water recycling device according to claim 5, characterized in that, In the pressure conversion module, the conversion relationship between the target spraying pressure and the target water consumption is as follows: The target spraying pressure is equal to the reference pressure plus the pressure-flow conversion coefficient multiplied by (target water consumption minus reference water consumption); where the pressure-flow conversion coefficient is pre-calibrated based on the flow-pressure characteristic curve of the high-pressure water pump.

9. The sweeper washing water recycling device according to claim 5, characterized in that, It also includes an integral discharge module, which accumulates particulate matter concentration or turbidity values ​​within a sliding time window. When the accumulated value exceeds a preset discharge threshold, it controls the discharge valve at the bottom of the solid-liquid separation device to open. The length of the sliding time window is negatively correlated with the current road pollution level: the higher the pollution level, the shorter the window length and the faster the discharge response.

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