Intelligent air cleaning, filtering and purifying control system and method

Abstract

The invention relates to the technical field of building environment and industrial ventilation and purification equipment operation control, discloses an intelligent air cleaning, filtering and purification control system and method, and aims to solve the problems that the filtering energy consumption is high, and the cleaning opportunity and strength are difficult to match. The self-adaptive sampling based on the air steady-state index and the triggering rule with the filtering load indication quantity as the core are provided, and the triggering rule comprises emergency, accumulation, the minimum interval and the low-load time period; at least two candidate cleaning schemes are generated, and under the constraint that the minimum air supply and recovery target is met, the candidate cleaning scheme with the lowest predicted energy consumption is optimized to be executed; monitoring air supply and energy consumption in an execution period, and collecting when a termination condition is met; the evaluation period is based on the recovery effect and the unit cleaning energy consumption self-correction parameter. The system is composed of an acquisition and standardization module, a load judgment and trigger module, a scheme generation and preferential selection module, an execution monitoring module, an effect evaluation module and a self-correction module, and the overall energy consumption can be reduced while air supply is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of building environment and industrial ventilation and purification equipment operation control, in particular to an intelligent air cleaning, filtering and purification control system and method. BACKGROUND

[0002] Air purification and ventilation filtering technology has evolved from coarse / middle efficiency fiber filter material to high efficiency filtration (such as HEPA) and then to system level intelligent control. The bag and cartridge system commonly used in industrial and public building scenarios forms mechanical rapping, back blowing, pulse blowing and other dust removal methods to maintain air permeability and pressure drop; in the field of air conditioning and ventilation, with the popularization of variable air volume, demand control ventilation and other strategies, the coupling relationship between filtration resistance and fan energy consumption and air supply capacity is increasingly valued. In the past decade, the promotion of Internet of Things, edge computing and building automation standardization has made sensor, actuator and gateway collaboration a normal state, operation data can be online, rules can be remotely issued, and status can be closed loop monitored. Therefore, the integration of operation and maintenance around online monitoring, triggering cleaning, effect evaluation and parameter self-correction has become the development direction of intelligent air purification / filtering equipment.

[0003] Despite the continuous improvement of infrastructure, engineering practice still has obvious shortcomings: first, many systems still use fixed cleaning periods or single threshold triggers, which cannot balance the clogging evolution speed, air supply guarantee and energy consumption constraints, and are prone to excessive cleaning or cleaning lag; second, the filtration module, automatic cleaning module and fan control are often run with separate logic, lacking coordination constraints on cleaning intensity, partition size and upper limit speed of the fan, often triggering and amplifying energy consumption and fluctuations during high load periods; third, the data side often uses fixed sampling / upload frequency, which lacks resolution in steady state and abnormal state; fourth, the pressure difference after cleaning, air supply recovery and unit cleaning energy consumption lack quantitative evaluation and parameter backwriting, making it difficult to form a self-correcting closed loop. Therefore, an intelligent air cleaning, filtering and purification control system and method are needed that can coordinate filtration, automatic cleaning and intelligent control under clear rules, balance low load priority and energy consumption upper limit, and adaptively correct parameters. SUMMARY

[0004] (I) Technical problems solved

[0005] In view of the deficiencies in the prior art, the present application provides an intelligent air cleaning, filtering and purification control system and method, which solves the above problems.

[0006] (II) Technical solutions

[0007] To achieve the above purpose, the present application provides the following technical solutions: an intelligent air cleaning, filtering and purification control method, the method comprising:

[0008] S1: Collect and standardize the operation parameters of the intelligent air cleaning and filtering purification device; when the air steady-state index in a continuous preset time window is lower than a steady-state threshold, switch the time interval of collection and uploading from a first sampling interval to a second sampling interval, the second sampling interval being greater than the first sampling interval; when the air steady-state index recovers to be higher than the steady-state threshold, switch back to the first sampling interval;

[0009] S2: Perform filtering load determination on the standardized operation parameters, and generate a cleaning trigger signal or a delayed cleaning trigger mark according to a preset trigger rule; the trigger rule at least includes an emergency trigger condition, a cumulative trigger condition, a minimum cleaning interval, and a low load period condition;

[0010] S3: When the cleaning trigger signal or the delayed cleaning trigger mark meets the low load period condition, form at least two candidate cleaning schemes and select the optimal one for execution; the candidate cleaning schemes are combined according to a preset rule for cleaning action type, partition number, and fan speed upper limit, and the optimal execution is to preferentially select the cleaning scheme with the lowest predicted energy consumption under the premise of meeting the preset minimum air supply guarantee value and the cleaning recovery target; if the predicted energy consumption is the same, the one with shorter total downtime is selected, and the selected scheme is determined as the target cleaning scheme;

[0011] S4: Perform the cleaning action according to the target cleaning scheme, and monitor the air supply volume and the cumulative cleaning energy consumption in real time during the execution; continue to execute when the air supply volume is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the energy consumption upper limit of this round; end the cleaning of this round when the cleaning termination condition is met;

[0012] S5: After the cleaning ends or is terminated in advance, monitor the recovery of the filtering load indicator and the air supply volume within a preset evaluation period, and count the cleaning energy consumption of this round to form a cleaning effect evaluation result; when the evaluation result is lower than the cleaning recovery target, increase the intensity level of the next cleaning action or expand the partition number according to the preset rule; when the unit cleaning energy consumption exceeds the set upper limit, reduce the cleaning action intensity or shrink the partition number according to the preset rule; when the filtering load indicator is lower than the recovery threshold for multiple times, increase the threshold for the cumulative trigger condition or lengthen the minimum cleaning interval.

[0013] Preferably, the operation parameters at least include filter screen pressure difference or air supply volume; when no flow sensor is configured, the fan speed is converted into equivalent air supply volume according to a preset linear conversion relationship, and is used for calculation of the air steady-state index and switching determination of the time interval.

[0014] Preferably, the air steady-state index is determined by the following way:

[0015] Within a preset time window, the relative fluctuation degree of each operating parameter is calculated, which is the ratio of the difference between the maximum and minimum values of the operating parameter within the preset time window to the average level thereof;

[0016] The relative fluctuation degrees of the operating parameters are compared, and the maximum thereof is taken as the air steady-state index of the window.

[0017] Preferably, the filter load determination is based on the filter load indicator, which is the larger of the following two:

[0018] The percentage of the rise of the filter screen pressure difference relative to the baseline level and the percentage of the drop of the supply air volume relative to the baseline level.

[0019] Preferably, the triggering rule is specifically:

[0020] The emergency triggering condition is that the filter load indicator reaches a first threshold value within a single time window and lasts for no less than a preset duration; the cumulative triggering condition is that the number of times that the filter load indicator reaches a second threshold value within adjacent multiple time windows reaches a preset number of times; the minimum cleaning interval is used to limit the shortest time between two cleanings; and the low-load period condition is determined according to a preset calendar or a supply air gear position being in a low gear;

[0021] When the emergency triggering condition or the cumulative triggering condition is met and the minimum cleaning interval is reached, if the low-load period condition is established, a cleaning triggering signal is generated; if the low-load period condition is not established, a delayed cleaning triggering marker is generated, and the cleaning is automatically triggered when the low-load period condition is established.

[0022] Preferably, the cleaning action type of the candidate cleaning scheme includes at least two of a short pulse back-flushing, a vibration cleaning and a partition wheel stop cleaning; wherein the offline proportion of the partition wheel stop cleaning is no more than a preset upper limit.

[0023] Preferably, the predicted energy consumption is estimated based on the rated power of the relevant execution unit and the planned action duration, and the additional energy consumption of the fan generated for maintaining the supply air during cleaning is considered.

[0024] Preferably, the upper limit of the current round energy consumption is a fixed proportion of the on-duty energy budget; when the cumulative cleaning energy consumption reaches the upper limit of the current round energy consumption and the supply air volume is no less than the minimum supply air guarantee value, the unexecuted cleaning action is marked as a delayed task and is executed in the next low-load period.

[0025] Preferably, the cleaning termination condition is specifically that the filter load indicator in two consecutive time windows is lower than a recovery threshold value or the falling rate of the filter screen pressure difference reaches a preset target.

[0026] Preferably, the present application also provides an intelligent air cleaning filtration purification control system, which comprises:

[0027] An operation parameter acquisition and standardization module is configured to acquire and standardize operation parameters of the intelligent air cleaning filtration purification device; when an air steady state index in a continuous preset time window is lower than a steady state threshold, a time interval of acquisition and uploading is switched from a first sampling interval to a second sampling interval, the second sampling interval being greater than the first sampling interval; when the air steady state index is restored to be higher than the steady state threshold, the first sampling interval is switched back.

[0028] A filtration load determination and trigger decision module is configured to determine filtration load based on the standardized operation parameters, and generate a cleaning trigger signal or a delayed cleaning trigger mark according to a preset trigger rule; the trigger rule at least includes an emergency trigger condition, an accumulated trigger condition, a minimum cleaning interval, and a low load period condition.

[0029] A cleaning scheme generation and optimal execution module is configured to form at least two candidate cleaning schemes and perform optimization when the cleaning trigger signal or the delayed cleaning trigger mark meets the low load period condition; the candidate cleaning schemes are combined according to a preset rule for cleaning action type, partition number, and fan speed upper limit, the optimization is to preferentially select a cleaning scheme with the lowest predicted energy consumption under the premise of meeting a preset minimum air supply guarantee value and a cleaning recovery target; if the predicted energy consumption is the same, the one with shorter total downtime is selected, and the selected scheme is determined as a target cleaning scheme.

[0030] An execution coordination and process monitoring module is configured to execute a cleaning action according to the target cleaning scheme, and monitor air supply and cumulative cleaning energy consumption in real time during the execution; the execution continues when the air supply is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the upper limit of the current energy consumption; the current cleaning is ended when a cleaning termination condition is met.

[0031] A cleaning effect evaluation and self-correction module is configured to monitor the recovery of filtration load indicator and air supply within a preset evaluation period after the cleaning is ended or terminated in advance, and to count the current cleaning energy consumption to form a cleaning effect evaluation result; when the evaluation result is lower than the cleaning recovery target, the intensity level of the next cleaning action or the number of partitions is increased according to a preset rule; when the unit cleaning energy consumption exceeds the set upper limit, the intensity of the next cleaning action or the number of partitions is reduced according to a preset rule; when the filtration load indicator is lower than the recovery threshold for multiple times, the threshold for the accumulated trigger condition or the minimum cleaning interval is increased.

[0032] Each module is executed by a processor to realize its function by storing program instructions in a memory.

[0033] (Three) beneficial effects

[0034] Compared with the prior art, the present application provides an intelligent air cleaning, filtering and purifying control system and method, which has the following beneficial effects:

[0035] 1. The intelligent air cleaning, filtering and purifying control system and method avoids excessive cleaning and lag caused by fixed cycles or single thresholds at the rule level, generates at least two candidate schemes according to cleaning action types, partition scales and fan speed upper limits after triggering, selects the one with the lowest expected energy consumption as the priority under the premise of meeting the minimum air supply guarantee value and cleaning recovery target, sets the energy consumption upper limit of the current round and real-time checks the air supply and cumulative cleaning energy consumption in the execution stage, converges as soon as the termination condition is met, thereby realizing the cooperation and low-load priority landing of the filtering module, the automatic cleaning module and the fan control, reducing peak energy consumption and downtime, reducing false triggering and delay, maintaining stable air supply, and achieving the purpose of ensuring effective cleaning and continuous air supply under the premise of controlled energy consumption.

[0036] 2. The intelligent air cleaning, filtering and purifying control system and method reduces communication and storage redundancy from the source by using an adaptive collection / upload mechanism driven by an air steady-state index to automatically lengthen the sampling and reporting interval in the steady-state stage and restore high resolution in the fluctuation stage; and uses pressure difference drop rate, air supply recovery degree and unit cleaning energy consumption to form an effect evaluation result after cleaning, automatically writes the next round of threshold, minimum cleaning interval and cleaning intensity or partition number according to the preset rules, forms a closed loop of evaluation, correction and re-execution, makes the parameters gradually converge with the field conditions, avoids long-term conservative or aggressive strategies, prolongs the service life of the filter material and reduces the total cycle energy consumption, thereby achieving the purpose of controllable data side overhead, more reliable judgment and continuous self-optimization of the operation strategy. BRIEF DESCRIPTION OF DRAWINGS

[0037] Figure 1 The intelligent air cleaning, filtering and purifying control method provided by the present application has the step flowchart shown in the figure;

[0038] Figure 2 The operation flowchart of the intelligent air cleaning, filtering and purifying control method provided by the present application is shown in the simplified block diagram;

[0039] Figure 3 The functional module block diagram of the intelligent air cleaning, filtering and purifying control system provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0040] Clearly, the embodiments described are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0041] In order for those skilled in the art to better understand the technical solutions of the present application, the present application will be further described in detail below in combination with the drawings and specific embodiments.

[0042] Please refer to Figure 1 and Figure 2 The present application provides an intelligent air cleaning, filtering and purifying control method, which comprises the following steps:

[0043] S1: Collect and standardize the operating parameters of the intelligent air cleaning, filtering and purifying device; when the air steady-state index in a continuous preset time window is lower than a steady-state threshold, switch the time interval of collection and uploading from a first sampling interval to a second sampling interval, the second sampling interval being greater than the first sampling interval; when the air steady-state index recovers to be higher than the steady-state threshold, switch back to the first sampling interval;

[0044] S2: Filter the load of the standardized operating parameters, and generate a cleaning trigger signal or a delayed cleaning trigger mark according to a preset trigger rule; the trigger rule at least includes an emergency trigger condition, a cumulative trigger condition, a minimum cleaning interval and a low load period condition;

[0045] S3: When the cleaning trigger signal or the delayed cleaning trigger mark meets the low load period condition, form at least two candidate cleaning schemes and execute the optimal one; the candidate cleaning schemes are combined according to a preset rule for cleaning action type, partition number and fan speed upper limit, the optimal execution is to preferentially select the cleaning scheme with the lowest predicted energy consumption under the premise of meeting the preset minimum air supply guarantee value and cleaning recovery target; if the predicted energy consumption is the same, the one with shorter total downtime is selected, and the selected scheme is determined as the target cleaning scheme;

[0046] S4: Execute the cleaning action according to the target cleaning scheme, and monitor the air supply and the cumulative cleaning energy consumption in real time during the execution; continue to execute when the air supply is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the energy consumption upper limit of this round; end the cleaning of this round when the cleaning termination condition is met;

[0047] S5: After the cleaning ends or is terminated in advance, the recovery of the filter load indication quantity and the air supply quantity is monitored in a preset evaluation period, the energy consumption of the current cleaning is counted, and a cleaning effect evaluation result is formed; when the evaluation result is lower than a cleaning recovery target, the intensity level of the next cleaning action or the number of partitions is increased according to a preset rule; when the unit cleaning energy consumption exceeds a set upper limit, the next cleaning action intensity or the number of partitions is reduced according to a preset rule; when the filter load indication quantity is lower than a recovery threshold value for a plurality of consecutive times, the threshold value for accumulating a triggering condition is increased or the minimum cleaning interval is prolonged.

[0048] In this embodiment, reference is made to Figure 1 and Figure 2 , as shown in Figure 1 , a step flow chart of the intelligent air cleaning, filtering and purifying control method provided by the present application is provided. Figure 2 A simplified block diagram of the operation flow of the intelligent air cleaning, filtering and purifying control method provided by the present application is provided. In this embodiment, the intelligent air cleaning, filtering and purifying control method comprises the following steps:

[0049] S1: Collect and standardize the operating parameters of the intelligent air cleaning, filtering and purifying device; when the air steady state index in a continuous preset time window is lower than a steady state threshold value, the time interval of collection and uploading is switched from a first sampling interval to a second sampling interval, the second sampling interval being greater than the first sampling interval; when the air steady state index is restored to be higher than the steady state threshold value, the first sampling interval is switched back;

[0050] In this embodiment of the present application, the operating parameters at least include one or both of the filter screen pressure difference and the air supply quantity. The system performs time alignment, abnormality rejection and unit unification on the original data to form a standardized data sequence. For the calculation of the air steady state index, the system respectively calculates the relative fluctuation degree of each monitored parameter in a preset time window (for example, 15 minutes), that is, the difference between the maximum value and the minimum value in the window relative to the average level of the window, and takes the maximum of the relative fluctuation degrees of the parameters as the air steady state index of the window. When the index of a plurality of consecutive windows (for example, two consecutive windows) is lower than a steady state threshold value (for example, 0.15), the time interval of collection and uploading is switched from a first sampling interval (for example, 30 seconds) to a second sampling interval (for example, 5 minutes); when the index is restored to be higher than the steady state threshold value, the first sampling interval is switched back. When no flow sensor is configured, the fan speed is converted into an equivalent air supply quantity according to a preset linear relationship for the above-mentioned determination. Through the adaptive sampling, the communication and storage burden is reduced in the steady state, and the high resolution is restored in the fluctuation to ensure the monitoring sensitivity.

[0051] S2: filtering load judgment is performed on the normalized operating parameters, and a cleaning trigger signal or a delayed cleaning trigger mark is generated according to a preset trigger rule; the trigger rule at least includes an emergency trigger condition, an accumulated trigger condition, a minimum cleaning interval, and a low load period condition;

[0052] In the embodiment of the present application, the system maintains a baseline level, and the baseline can take the representative value of the stable state after the stable state or the last round of cleaning. The filtered load indication quantity takes the larger one of the percentage of the rising amplitude of the filter screen pressure difference relative to the baseline and the percentage of the falling amplitude of the air supply quantity relative to the baseline. The emergency trigger condition is used to quickly respond to a sudden rise scenario, for example, the indication quantity reaches a first threshold (for example, 40%) within a single time window and lasts for no less than a preset duration (for example, 3 minutes); the accumulated trigger condition is used to identify a slow blocking scenario, for example, the number of times that the indication quantity reaches a second threshold (for example, 25%) reaches a preset number (for example, 3 times / 30 minutes) within adjacent multiple time windows. When either of the two types of conditions is met and the minimum cleaning interval (for example, ≥2 hours) has been reached: if the low load period condition is established (for example, at night or the air supply gear is low), a cleaning trigger signal is directly generated; if the low load period condition is not established, a delayed cleaning trigger mark is generated, and cleaning is automatically triggered when the low load period is subsequently entered. The above-mentioned threshold and time parameters can be preset according to the scale or working condition of the site.

[0053] S3: when the cleaning trigger signal is generated or the delayed cleaning trigger mark meets the low load period condition, at least two candidate cleaning schemes are formed and the optimal one is selected for execution; the candidate cleaning schemes are combined according to a preset rule for cleaning action type, partition number and fan speed upper limit, and the optimal one is selected for execution under the premise of meeting a preset minimum air supply guarantee value and a cleaning recovery target; if the predicted energy consumption is the same, the one with shorter total downtime is selected, and the selected scheme is determined as the target cleaning scheme;

[0054] In the embodiment of the present application, the cleaning action type can include at least two of short pulse back blowing, vibration rapping and partition wheel stop cleaning; the offline proportion of the partition wheel stop cleaning is constrained by a preset upper limit (for example, less than or equal to 30%). The system generates several candidate combinations in the form of “action type × partition number × fan speed upper limit”, and estimates the predicted energy consumption of each combination. The estimation is based on the rated power of the relevant execution unit and the planned action duration, and the additional energy consumption of the fan generated for maintaining air supply (for example, converted according to the time length of the fan power and the limited speed interval) is weighted. At the same time, the minimum air supply guarantee value (for example, not less than 70% of the design fresh air volume) and the cleaning recovery target (for example, pressure difference rollback ≥30%) are checked, and both of them must be met to participate in the sorting. The system is optimized in ascending order of predicted energy consumption; when the energy consumption is the same, the one with shorter total downtime is given priority, and the target cleaning scheme is finally determined and the execution parameters are issued.

[0055] S4: performing cleaning actions according to the target cleaning scheme, and monitoring the air supply amount and the cumulative cleaning energy consumption in real time during the performance; when the air supply amount is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the upper limit of the energy consumption of the current round, the performance is continued; when the cleaning termination condition is met, the cleaning of the current round is ended;

[0056] In the embodiment of the application, the execution coordination and process monitoring module drives the relevant execution units (such as the reverse blowing valve, the vibration mechanism, the partition switching actuator and the fan speed limiting instruction) to implement cleaning according to the step sequence of the target scheme. During the execution, the air supply amount is collected at a first sampling interval and the cleaning energy consumption is accumulated; when the cumulative cleaning energy consumption reaches the upper limit of the energy consumption of the current round (for example, a fixed proportion of the energy consumption budget of the shift) and the air supply amount is still not lower than the minimum air supply guarantee value, the system marks the unexecuted cleaning action as a delayed task and triggers it at the next low load period. The cleaning termination conditions include that the filter load indication amount in the two consecutive time windows is lower than the recovery threshold (for example, ≤10%) or the filter screen pressure difference drop rate reaches the preset target (for example, ≥30%). Any one of the conditions is met to end the cleaning in advance to avoid excessive cleaning. The whole process records the action timing, energy consumption and key measurement to provide a basis for subsequent evaluation.

[0057] S5: after the cleaning is ended or terminated in advance, the recovery of the filter load indication amount and the air supply amount is monitored within a preset evaluation period, the cleaning energy consumption of the current round is counted, and the cleaning effect evaluation result is formed; when the evaluation result is lower than the cleaning recovery target, the intensity level of the next cleaning action or the number of partitions is increased according to a preset rule; when the unit cleaning energy consumption exceeds the set upper limit, the cleaning action intensity or the number of partitions is reduced according to a preset rule; when the filter load indication amount is lower than the recovery threshold for multiple times of evaluation, the threshold for accumulating the triggering condition or the minimum cleaning interval is increased;

[0058] In the embodiment of the application, the evaluation period can be set to 60 minutes. The system calculates the pressure difference drop rate, the air supply recovery degree and the unit cleaning energy consumption, combines them to form the evaluation result and compares it with the target value: if the recovery is insufficient, the cleaning action intensity (such as pulse pressure or vibration frequency) is preferentially increased or the number of partitions is moderately increased in the next round; if the unit cleaning energy consumption is excessive, the action intensity or the number of partitions is reduced to avoid excessive energy consumption; if the filter load indication amount is stably lower than the recovery threshold for multiple times of evaluation, it is indicated that the strategy is conservative, and the threshold for accumulating the triggering condition or the minimum cleaning interval can be moderately increased. The above evaluation and correction closed loop makes the strategy gradually converge with the field working conditions, and takes into account the filter life and the whole cycle energy consumption control.

[0059] Preferably, the operating parameters at least include the filter screen pressure difference or the air supply amount; when no flow sensor is configured, the fan speed is converted into the equivalent air supply amount according to a preset linear conversion relationship, and is used for the calculation of the air steady state index and the switching determination of the time interval;

[0060] In the embodiment of the present application, the operating parameter preferably comprises at least one of the filter screen pressure difference or the air supply amount; when no flow sensor is configured on site, the controller reads the fan speed from the fan frequency converter / speed sensor and converts it into an equivalent air supply amount according to a preset linear conversion relationship, which is used for the calculation of the air steady state index and the switching determination of the collection / upload time interval. The linear conversion relationship is obtained by two-point or multi-point calibration during the debugging stage: for example, the air supply amounts Q1 and Q2 are measured at the low gear n1 and the high gear n2 respectively (which can be temporarily obtained by using a portable air volume cover or a pipe network measurement port), and the conversion parameter is determined and stored in the parameter table; during operation, only the real-time speed needs to be converted into the equivalent air supply amount according to the parameter. In order to reduce the influence of filter resistance change on the equivalent amount, the embodiment can use a rule correction: for example, when the filter screen pressure difference is increased by more than a preset proportion (such as 20%) relative to the baseline, the equivalent air supply amount is adjusted downward (for example, by 5%) according to a fixed correction coefficient; the correction is only used for the determination of the switching of the steady state index and the sampling interval, and does not change the device metering. For a unit with multiple fans in parallel, the equivalent air supply amounts of the fans are calculated according to the above rules respectively and then summed up as the unit air supply amount; for a scene with zoned air supply, the equivalent air supply amounts of the zones can be summed up or the equivalent air supply amount of the key zone can be taken to participate in the steady state index determination (for example, taking the minimum zone air supply amount can better reflect the overall risk). On this basis, the system and the filter screen pressure difference together constitute a monitoring quantity: when the air steady state index calculated by the equivalent air supply amount is lower than the steady state threshold value in a continuous preset time window, the time interval for collection and upload is automatically switched from the first sampling interval to the second sampling interval; when the index recovers to be higher than the threshold value, the first sampling interval is switched back, so that the perception of steady state and fluctuation working conditions and the bandwidth adaptive control are realized without increasing the hardware cost.

[0061] Preferably, the air steady state index is determined by the following method:

[0062] In a preset time window, the relative fluctuation degree of each operating parameter is calculated respectively, and the relative fluctuation degree is the ratio of the difference between the maximum value and the minimum value of the operating parameter in the preset time window to the average level;

[0063] The relative fluctuation degrees of the operating parameters are compared, and the maximum one is taken as the air steady state index of the window;

[0064] In the embodiment of the present application, the determination of the air steady state index adopts a sliding window segmented evaluation method: the system calculates the relative fluctuation degree of each operating parameter in a preset time window (for example, 15 minutes) respectively. In order to ensure robustness, first, the data in the window is subjected to denoising processing (for example, median filtering or removing abnormal points of 5% at the top and bottom), then the difference between the maximum value and the minimum value of the parameter in the window is calculated, and the relative ratio is calculated based on the average level of the window to obtain the relative fluctuation degree of the parameter; when the effective sample number of a certain parameter in the window is insufficient (for example, less than 20) or the average value is too low to cause distortion of the ratio, the parameter is skipped and does not participate in the evaluation of the window. Subsequently, the relative fluctuation degrees of various operating parameters (for example, filter pressure difference, air supply or equivalent air supply) are compared, and the maximum one is taken as the air steady state index of the window to reflect the constraint of the most "unstable" measurement on the overall stability. In order to avoid frequent jitter of the sampling interval, the system can set a hysteresis: for example, the steady state threshold is 0.15, the entering condition for switching to the low frequency uploading is that the index of the two consecutive windows is lower than 0.15, and the exiting condition for restoring to the high frequency uploading is that the index of the consecutive window is higher than 0.17. The above window length, abnormal point removal ratio, minimum sample number and hysteresis band can be preset in the parameter table according to the field working condition or optimized in the operation and maintenance stage. Through the unified measurement of the steady state index, the adaptive switching of the sampling and uploading rhythm can be driven by a single index in the case of multiple parameters coexisting, the bandwidth and storage utilization efficiency are improved, and the sensitivity to abnormal fluctuations is maintained at the same time.

[0065] Preferably, the filter load determination is based on a filter load indication quantity, which is the larger of the following two:

[0066] The percentage of the increase of the filter pressure difference relative to the baseline level, and the percentage of the decrease of the air supply relative to the baseline level;

[0067] In the embodiments of the present application, firstly, the baseline level is determined, and during the steady state stage of the device operation or the period after the completion of the last cleaning and stable operation, the representative values of the filter screen pressure difference and the air supply amount (or equivalent air supply amount) are recorded respectively as the pressure difference baseline and the air supply baseline; in order to avoid accidental fluctuations, the average value or the median value in the stable period is preferably taken as the baseline, and the baseline is slowly corrected by not more than 5% in subsequent low load and stable operation. Subsequently, the relative change percentages of the two are calculated in the current determination window, one of which is the percentage of the rising amplitude of the pressure difference relative to the baseline, that is, when the representative value of the pressure difference in the window is higher than the baseline, it is calculated as the percentage of "(current pressure difference-pressure difference baseline) relative to the pressure difference baseline"; if the current pressure difference is not higher than the baseline, it is recorded as 0%; the other is the percentage of the falling amplitude of the air supply amount relative to the baseline, that is, when the representative value of the air supply in the window is lower than the baseline, it is calculated as the percentage of "(air supply baseline-current air supply) relative to the air supply baseline"; if the current air supply is not lower than the baseline, it is recorded as 0%. The larger one of the two is taken as the filtration load indicator of the current window, which is used to trigger the determination. When the flow sensor is not configured, the equivalent air supply amount can be obtained by the preset linear conversion relationship (obtained by factory calibration or field calibration) between the fan speed and the air supply amount to participate in the above calculation; when the conversion condition is not met or the air supply amount data is missing, the system only takes the percentage of the rising pressure difference as the filtration load indicator. In order to ensure the validity of the value, the baseline value is set with a lower threshold to avoid distortion caused by too small divisor; at the same time, the percentage result is boundary restricted to 0%-100%. For multi-zone structure, the filtration load indicator can be calculated respectively according to the zone, and applied in parallel in the way of single-zone triggering and whole-machine maximum monitoring: when any zone indicator meets the triggering condition, only the zone can be executed for cleaning; when the whole-machine maximum exceeds the threshold and the zone cannot be divided, the whole-machine strategy is executed. For example, if the pressure difference baseline is 120 Pa, the current is 156 Pa, the pressure difference rising amplitude is 30%; the air supply baseline is 3000 m 3 / h, the current is 2550 m 3 / h, the air supply falling amplitude is 15%; the filtration load indicator of the current window takes the larger value of the two, that is, 30%, thereby entering the subsequent emergency / cumulative triggering determination process.

[0068] Preferably, the triggering rule is specifically:

[0069] The emergency triggering condition is that the filtration load indicator reaches the first threshold in a single time window and lasts for not less than a preset duration; the cumulative triggering condition is that the filtration load indicator reaches the second threshold for a preset number of times in adjacent multiple time windows; the minimum cleaning interval is used to limit the shortest time between two cleanings; the low load period condition is determined according to the preset calendar or the air supply gear being in a low gear;

[0070] When the emergency trigger condition or the cumulative trigger condition is met and the minimum cleaning interval is reached, if the low-load period condition is established, a cleaning trigger signal is generated; if the low-load period condition is not established, a delayed cleaning trigger mark is generated, and the cleaning is automatically triggered when the low-load period condition is established;

[0071] In the embodiment of the present application, specifically, the system judges the emergency trigger condition and the cumulative trigger condition for the filtration load indication quantity in each determination window; when either of the conditions is met and the minimum cleaning interval since the last cleaning is reached, the low-load period condition is further checked: if the low-load period condition is established (for example, in a preset night period, or the air supply gear has been continuously kept in a low gear for a preset length of time), a cleaning trigger signal is immediately generated and issued for execution; if the low-load period condition is not established, a delayed cleaning trigger mark is generated, and the target partition / equipment of the mark, the generation time, the earliest executable time (the end time of the last cleaning + the minimum cleaning interval), the dependent low-load determination mode, and the validity period are recorded. The scheduling module polls the low-load state at a fixed period, and when the two rules of “the earliest executable time is reached” and “the low-load period condition is established” are met simultaneously, the delayed mark is automatically converted into a cleaning trigger signal and put into execution. To avoid repeated triggering, the system combines and updates the newly added triggers of the same partition within the validity period of the mark, and the trigger level of the latest trigger and the stricter execution parameters are used as the reference; to avoid excessive cleaning, if the filtration load indication quantity is continuously lower than the recovery threshold for two windows during the waiting period, the delayed mark is automatically cancelled. For a multi-partition structure, the batch execution of the delayed mark is also subject to the constraint of “the simultaneous offline proportion does not exceed the preset upper limit”, and the scheduling is released in turn from high to low according to the load indication quantity, and the remaining marks are postponed to the next low-load period for execution. The above process takes into account the air supply guarantee and energy consumption constraint through explicit time and state gating without changing the trigger criterion.

[0072] Preferably, the cleaning action type of the candidate cleaning scheme includes at least two of short pulse backflushing, vibration rapping and partition wheel stop cleaning; wherein the simultaneous offline proportion of the partition wheel stop cleaning does not exceed a preset upper limit;

[0073] In the embodiment of the present application, the candidate cleaning scheme library is preconfigured with three types of actions: short pulse back blowing, vibration and dust removal, and partition wheel stop cleaning, and combined into "two-type linkage" or "three-type linkage" sequences according to load levels to meet the requirement of "at least two types". For example, "vibration + short pulse back blowing" is used in medium load, and "partition wheel stop + short pulse back blowing + vibration" is used in high load. The parameters of short pulse back blowing mainly include pulse width, interval and number of times (for example, pulse width 0.3-0.8 seconds, interval 3-8 seconds, 5-15 times / round), and the back blowing pressure or reverse air volume is limited to not more than the rated value of the equipment; vibration and dust removal mainly includes frequency and duration (for example, 5-10 Hz, 10-15 seconds, 1-3 rounds); and partition wheel stop cleaning is performed in the order of "high load partition first, staggered peak of adjacent partitions". In order to ensure air supply, the system implements a hard constraint on the "simultaneous offline proportion": assuming that the total number of partitions is N, the upper limit is r max (for example, 30%), the maximum number of partitions allowed to be offline at the same time is The number of offline partitions at any time during scheduling should not exceed M, and adjacent partitions in the same air duct should not be offline at the same time. In terms of execution order, the partition isolation and fan speed limiting instructions are issued first, and then the pulse and vibration actions of the partition are executed in sequence; after the actions are completed, a 5-10 second blow-off delay and dust settling waiting are set, and then the isolation is removed to restore and reconnect. If the pressure difference of a partition falls short of the pre-set recovery target after one round, the action intensity of the partition is automatically increased or upgraded to a "three-type linkage" sequence in the next round; if other partitions are still in an online high load state, only additional cleaning windows are inserted on the premise of not breaking the simultaneous offline proportion. Through the above combination and scheduling rules, at least two types of cleaning actions are ensured to be covered by each candidate scheme, and the minimum air supply guarantee is maintained through the three constraints of upper limit of offline proportion, adjacent staggered peak and fan limiting, avoiding excessive offline causing air supply fluctuation.

[0074] Preferably, the estimated energy consumption is estimated based on the rated power of the relevant execution unit and the planned action duration, and the additional energy consumption of the fan generated during cleaning to maintain air supply is considered by weighting;

[0075] In the embodiment of the present application, the predicted energy consumption is estimated according to the rule of "basic action energy consumption + fan additional energy consumption". The basic action energy consumption is accumulated item by item based on the rated power of the relevant execution unit and the planned action duration: for example, the short pulse back blowing is calculated by multiplying the rated power of the back blowing air source (air compressor or back blowing fan) by the cumulative ventilation duration of all pulses in this round; the rapping and ash removal is calculated by multiplying the rated power of the rapping motor by the rapping duration and the round; the partition round stop cleaning is calculated by multiplying the rated power of the partition switching actuator (motor / magnetic valve) by the action holding duration (for the electromagnetic valve which only consumes energy at the switching moment, the equivalent energy consumption of each action can be converted and accumulated). For the back blowing using compressed air, it is preferred to convert it into electric energy in the form of "gas consumption x equivalent electric energy consumption of unit compressed air", and then add it to the basic action energy consumption. In order to cover the short-time start-stop loss, the action whose planned action duration is lower than the preset threshold (for example, 5 minutes), an additional start-stop loss coefficient calculated based on the rated power of the device is added for conservative calculation. The fan additional energy consumption is calculated based on the "incremental energy consumption compared with the baseline air supply working condition at the same period". First, the average power of the fan during the cleaning period is obtained by combining the upper limit of the fan speed given by the candidate scheme and the simultaneous offline partition ratio, and the fan characteristic table or the empirical rule (the fan power changes approximately according to the cubic relationship with the speed). Then, the difference value is obtained by comparing the baseline power in the same period without cleaning, and the additional energy consumption generated for maintaining the air supply is obtained by integrating the cleaning duration. For example, in the case of reduced effective filtration area caused by partition round stop, the fan may operate in a higher speed range to maintain the minimum air supply guarantee value. The system estimates the average power in this range and calculates the difference with the baseline power. If the scheme limits the upper limit of the fan speed and allows the air supply to be slightly reduced, the additional energy consumption may be zero or negative. The system takes zero to maintain the conservatism of the estimation. Finally, the predicted energy consumption is equal to the sum of the basic action energy consumption and the fan additional energy consumption, which is used as the basis for scheme optimization and upper limit checking of this round energy consumption.

[0076] Preferably, the upper limit of the energy consumption of this round is a fixed proportion of the on-duty energy consumption budget; when the cumulative cleaning energy consumption reaches the upper limit of the energy consumption of this round and the air supply quantity is not lower than the minimum air supply guarantee value, the unexecuted cleaning action is marked as a delayed task, and is triggered to be executed in the next low load period;

[0077] In the embodiment of the present application, the operation and maintenance platform generates energy consumption budget for each shift according to daily / shift energy consumption plan at the beginning of each shift, and sets the upper limit of energy consumption for this round according to a fixed proportion; the proportion is a site parameter, preferably 10%-30%, for example, 20% is used for normal working conditions. The coordination and process monitoring module is executed to accumulate the cleaning energy consumption according to the meter reading or the converted value of "rated power x action duration", and compare it with the upper limit of energy consumption in real time; when the accumulated cleaning energy consumption reaches the upper limit and the air supply volume is not lower than the minimum air supply guarantee value, the system terminates the remaining actions of the current scheme, encapsulates the unexecuted actions as "delayed tasks", and writes them into the task queue, records their target partition, proposed action, expected energy consumption, earliest start period (next low load period) and validity period, etc. After reaching the next low load period, the scheduler automatically wakes up the delayed tasks: if there are multiple delayed tasks in the same partition, the same actions are preferentially combined and deduplicated to reduce repeated energy consumption; the trigger conditions of step S2 and the minimum cleaning interval are verified again before triggering to avoid unnecessary cleaning when the load has naturally recovered; the delayed tasks that have not been executed beyond the validity period are processed or abandoned according to low priority, and the parameter adjustment is prompted in step S5 evaluation. If the accumulated energy consumption reaches the upper limit when the air supply volume is lower than the minimum air supply guarantee value, the delayed logic is not applicable, and the safety strategy and cleaning termination condition of step S4 are preferentially handled to ensure air supply safety. The above mechanism ensures that the cleaning energy consumption is controlled and automatically postponed to the low load period for execution, thereby reducing peak period energy consumption while meeting air supply demand.

[0078] Preferably, the cleaning termination condition specifically refers to that the filter load indication quantity in the two consecutive time windows is lower than the recovery threshold or the falling rate of filter screen pressure difference reaches the preset target.

[0079] In the embodiment of the present application, the cleaning termination determination is performed in cooperation with the process monitoring of step S4. Preferably, the average value of the differential pressure stable segment before the cleaning trigger is taken as the "reference differential pressure before cleaning", and the filter load indicator is calculated in a time window (for example, every 5-10 minutes) consistent with step S2 during the cleaning execution, and the data in the window is denoised and smoothed (for example, removing extreme values and taking the average) to weaken the instantaneous disturbance. Firstly, when the filter load indicator in two consecutive windows is lower than the recovery threshold (for example, 10%), it is recorded as meeting the "stable recovery condition", and to avoid jitter, a confirmation buffer time of 1-2 minutes can be set. Secondly, the differential pressure drop rate is calculated according to the reference differential pressure before cleaning and the current window differential pressure, and when the drop rate reaches a preset target (for example, ≥30% or a project set value), it is recorded as meeting the "target drop condition". When either of the above conditions is met, and the air supply quantity is not lower than the minimum air supply guarantee value, the controller issues a cleaning end instruction: stop the backwashing / vibrating action in turn, remove the partition offline and restore the upper limit of the fan speed, while retaining the short-time exhaust / air sweeping tail (for example, 30-60 seconds) to carry away the residual dust; then freeze the key parameters of this round (the reference differential pressure before cleaning, the differential pressure at the end, the air supply quantity, the cumulative cleaning energy consumption and the action list) and write them into step S5 evaluation. If neither of the two conditions is met and the cumulative cleaning energy consumption has approached the upper limit of the energy consumption of this round, the air supply guarantee value is prioritized: without affecting the air supply safety, a window can be extended for reevaluation; if the air supply quantity has approached the lower limit of the guarantee, the air supply safety is prioritized to terminate early. This embodiment avoids false judgments due to short-term disturbances through the dual conditions of "consecutive windows + target drop" and confirmation buffer, ensures timely termination of cleaning when the expected recovery effect is achieved, and thus reduces excessive cleaning and unnecessary energy consumption.

[0080] Preferably, the present application also provides an intelligent air cleaning, filtering and purifying control system, which comprises:

[0081] An operation parameter acquisition and standardization module is used to acquire and standardize the operation parameters of the intelligent air cleaning, filtering and purifying device; when the air steady-state index in a continuous preset time window is lower than a steady-state threshold, the time interval of acquisition and uploading is switched from a first sampling interval to a second sampling interval, the second sampling interval being greater than the first sampling interval; when the air steady-state index recovers to be higher than the steady-state threshold, the first sampling interval is switched back;

[0082] A filter load determination and trigger decision module is used to determine the filter load of the standardized operation parameters, and generate a cleaning trigger signal or a delayed cleaning trigger mark according to a preset trigger rule; the trigger rule at least includes an emergency trigger condition, a cumulative trigger condition, a minimum cleaning interval and a low load period condition;

[0083] The cleaning scheme generation and optimal execution module is used to form at least two candidate cleaning schemes and to optimally execute them when the cleaning trigger signal generation or the delayed cleaning trigger mark meets the low load period condition; the candidate cleaning schemes are combined according to a preset rule on the cleaning action type, the number of partitions and the upper limit of the fan speed, and the optimal execution is to preferentially select the cleaning scheme with the lowest predicted energy consumption under the premise of meeting the preset minimum air supply guarantee value and the cleaning recovery target; if the predicted energy consumption is the same, the one with the shorter total downtime is selected, and the selected scheme is determined as the target cleaning scheme;

[0084] The execution coordination and process monitoring module is used to execute the cleaning action according to the target cleaning scheme, and to monitor the air supply and the cumulative cleaning energy consumption in real time during the execution; the execution continues when the air supply is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the upper limit of the energy consumption of the current round; the current round of cleaning is ended when the cleaning termination condition is met;

[0085] The cleaning effect evaluation and self-correction module is used to monitor the recovery of the filter load indication and the air supply within a preset evaluation period after the cleaning is ended or terminated in advance, to count the energy consumption of the current round of cleaning, and to form a cleaning effect evaluation result; when the evaluation result is lower than the cleaning recovery target, the intensity level of the next cleaning action or the number of partitions is increased according to a preset rule; when the unit cleaning energy consumption exceeds the set upper limit, the intensity of the next cleaning action or the number of partitions is reduced according to a preset rule; when the filter load indication is lower than the recovery threshold for a plurality of consecutive times, the threshold for the cumulative trigger condition is increased or the minimum cleaning interval is extended;

[0086] Each module is executed by a processor to realize its function.

[0087] It should be noted that, in this text, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between the entities or operations. Moreover, the term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "includes a" does not exclude the presence of another identical element in the process, method, article or equipment including the element.

[0088] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. A method of intelligent air cleaning filtration purification control, characterized in that, The method includes: S1: Collect and standardize the operating parameters of the intelligent air cleaning and filtration purification device; when the air steady-state index is lower than the steady-state threshold within a continuous preset time window, switch the time interval between collection and upload from the first sampling interval to the second sampling interval, where the second sampling interval is greater than the first sampling interval; when the air steady-state index recovers to be higher than the steady-state threshold, switch back to the first sampling interval; S2: Filter the load of the standardized operating parameters and generate a cleaning trigger signal or a delayed cleaning trigger mark according to the preset trigger rules; the trigger rules include at least emergency trigger conditions, cumulative trigger conditions, minimum cleaning interval and low load period conditions; S3: When the cleaning trigger signal is generated or the delayed cleaning trigger flag meets the low load period conditions, at least two candidate cleaning schemes are formed and the optimal one is selected for execution. The candidate cleaning schemes are combined according to preset rules based on the cleaning action type, number of zones, and upper limit of fan speed. The optimal execution means that, under the premise of meeting the preset minimum air supply guarantee value and cleaning recovery target, the cleaning scheme with the lowest expected energy consumption is selected first. If the expected energy consumption is the same, the one with the shorter total downtime is selected, and the selected scheme is determined as the target cleaning scheme. S4: Perform cleaning actions according to the target cleaning plan, and monitor the air supply volume and cumulative cleaning energy consumption in real time during the execution process; continue execution when the air supply volume is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the energy consumption limit of this round; end this round of cleaning when the cleaning termination conditions are met; S5: After cleaning is completed or terminated early, monitor the recovery of filter load indication and air volume within a preset evaluation period, and calculate the energy consumption of this round of cleaning to form a cleaning effect evaluation result; when the evaluation result is lower than the cleaning recovery target, increase the intensity level of the next cleaning action or expand the number of zones according to preset rules; when the unit cleaning energy consumption exceeds the set upper limit, reduce the intensity of the next cleaning action or shrink the number of zones according to preset rules; when multiple consecutive evaluations show that the filter load indication is lower than the recovery threshold, increase the threshold used for cumulative triggering conditions or extend the minimum cleaning interval.

2. The intelligent air wash filtration purification control method of claim 1, wherein: The operating parameters include at least the filter pressure difference or the air volume; when no flow sensor is configured, the fan speed is converted into the equivalent air volume according to a preset linear conversion relationship, and used for the calculation of the air steady state index and the determination of the time interval switching.

3. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that, The air stability index is determined in the following way: Within a preset time window, the relative volatility of each operating parameter is calculated. The relative volatility is the ratio of the difference between the maximum and minimum values ​​of the operating parameter within the preset time window to its average level. The relative fluctuations of each operating parameter are compared, and the largest one is taken as the air steady-state index for that window.

4. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that, The filter load determination is based on a filter load indication, which is the larger of the following two: The percentage increase in filter pressure differential relative to the baseline level, and the percentage decrease in air volume relative to the baseline level.

5. The intelligent air cleaning, filtration, and purification control method according to claim 4, characterized in that, The triggering rule is specifically as follows: The emergency trigger condition is that the filtered load indicator reaches the first threshold and continues for no less than the preset duration within a single time window. The cumulative trigger condition is the number of times the filter load indicator reaches the second threshold within multiple adjacent time windows reaches a preset number; the minimum cleaning interval is used to limit the shortest time between two cleaning cycles. Low-load periods are determined based on the preset calendar or when the air supply speed is at a low setting. When the emergency triggering condition or the cumulative triggering condition is met and the minimum cleaning interval is reached, a cleaning triggering signal is generated if the low load period condition is met. If the low-load period conditions are not met, a delayed cleaning trigger flag is generated, and cleaning is automatically triggered when the low-load period conditions are met.

6. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that: The candidate cleaning scheme includes at least two of the following cleaning action types: short pulse backflushing, rapping cleaning, and zoned rotation cleaning; wherein, the offline ratio of the zoned rotation cleaning does not exceed a preset upper limit.

7. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that: The estimated energy consumption is based on the rated power of the relevant execution unit and the planned operation duration, and the additional energy consumption of the fan generated during the cleaning period to maintain air supply is weighted and taken into account.

8. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that: The current energy consumption limit is a fixed percentage of the shift's energy consumption budget. When the cumulative cleaning energy consumption reaches the current energy consumption limit and the air supply volume is not lower than the minimum air supply guarantee value, the unexecuted cleaning actions will be marked as delayed tasks and triggered for execution in the next low-load period.

9. The intelligent air cleaning, filtration, and purification control method according to claim 1, characterized in that: The cleaning termination condition is specifically defined as the filter load indication being lower than the recovery threshold or the filter pressure difference falling back to a preset target within two consecutive time windows.

10. An intelligent air cleaning, filtration, and purification control system, characterized in that, The system includes: The operating parameter acquisition and standardization module is used to collect and standardize the operating parameters of the intelligent air cleaning and filtration purification device; when the air steady-state index is lower than the steady-state threshold within a continuous preset time window, the time interval between acquisition and upload is switched from the first sampling interval to the second sampling interval, which is greater than the first sampling interval; when the air steady-state index recovers to be higher than the steady-state threshold, it switches back to the first sampling interval; The filter load determination and trigger decision module is used to determine the filter load based on the standardized operating parameters and generate a cleaning trigger signal or a delayed cleaning trigger mark according to the preset trigger rules; the trigger rules include at least emergency trigger conditions, cumulative trigger conditions, minimum cleaning interval, and low load period conditions. The cleaning scheme generation and optimal execution module is used to generate at least two candidate cleaning schemes and select the optimal one after the cleaning trigger signal is generated or the delayed cleaning trigger flag meets the low load period conditions. The candidate cleaning schemes are combined according to preset rules based on the cleaning action type, number of zones, and upper limit of fan speed. The optimal execution is to prioritize the cleaning scheme with the lowest expected energy consumption under the premise of meeting the preset minimum air supply guarantee value and cleaning recovery target. If the expected energy consumption is the same, the one with the shorter total downtime is selected and the selected scheme is determined as the target cleaning scheme. The execution coordination and process monitoring module is used to execute cleaning actions according to the target cleaning plan, and monitor the air supply volume and cumulative cleaning energy consumption in real time during the execution process; execution continues when the air supply volume is not lower than the minimum air supply guarantee value and the cumulative cleaning energy consumption does not exceed the energy consumption limit of this round; the cleaning round ends when the cleaning termination conditions are met. The cleaning effect evaluation and self-calibration module is used to monitor the recovery of filter load indication and air volume within a preset evaluation period after cleaning is completed or terminated early, and to calculate the energy consumption of this round of cleaning to form a cleaning effect evaluation result. When the evaluation result is lower than the cleaning recovery target, the intensity level of the next cleaning action is increased or the number of zones is expanded according to preset rules. When the unit cleaning energy consumption exceeds the set upper limit, the intensity of the next cleaning action is reduced or the number of zones is reduced according to preset rules. When multiple consecutive evaluations show that the filter load indication is lower than the recovery threshold, the threshold used for cumulative triggering conditions is increased or the minimum cleaning interval is extended. Each module is executed by the processor using program instructions stored in memory to perform its function.

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