Liquid level sensor cleaning method, system, equipment, medium and program product

Abstract

The invention relates to the technical field of sensor cleaning, and discloses a liquid level sensor cleaning method, system and equipment, a medium and a program product, the abnormity caused by attachments on the surface of a sensor can be accurately recognized by combining historical cleaning frequency and a liquid level monitoring data set, and resource waste caused by blind cleaning is avoided. Meanwhile, the influence of the change of the environmental condition of the liquid level sensor on the pollution speed and the cleaning requirement is considered, and long-term stable operation of the liquid level sensor in a complex environment is guaranteed. And furthermore, a target cleaning strategy optimization algorithm is matched according to different pollutant types, so that the cleaning intensity is ensured to be adaptive to pollutant characteristics, and the cleaning efficiency is improved. Furthermore, according to the determined target cleaning time and target cleaning intensity, the ultrasonic oscillation device is controlled to clean the liquid level sensor, timing and quantitative control over cleaning operation is achieved, and it is guaranteed that the liquid level sensor keeps stable measurement precision in long-term operation.

Description

Technical Field

[0001] The present invention relates to the field of sensor cleaning technology, and in particular to a liquid level sensor cleaning method, system, equipment, medium and program product. Background Art

[0002] Traditional liquid level sensors are susceptible to the effects of dirt and sediment in the liquid during long-term use, resulting in reduced measurement accuracy. Traditional self-cleaning solutions typically use a fixed-cycle cleaning method, which has obvious limitations: on the one hand, it is impossible to dynamically adjust the cleaning strategy based on the actual contamination status of the sensor surface (such as the type of attachments and the degree of contamination). This may lead to unnecessary cleaning when the contamination is light, resulting in energy waste and equipment loss, or untimely cleaning when the contamination is severe, affecting measurement accuracy. On the other hand, traditional solutions do not fully consider the impact of changes in the sensor's environmental conditions (such as temperature, humidity, and water characteristics) on the contamination rate and cleaning requirements, resulting in a mismatch between the cleaning timing and intensity and actual needs, making it difficult to ensure the long-term stable operation of the sensor in complex environments. Summary of the Invention

[0003] In view of this, the present invention provides a liquid level sensor cleaning method, system, equipment, medium and program product to solve the problem that traditional self-cleaning solutions cannot dynamically adjust the cleaning strategy according to the actual contamination status of the sensor surface (such as the type of attachments and the degree of contamination) and do not fully consider the impact of changes in the environmental conditions of the sensor (such as temperature and humidity, water characteristics, etc.) on the contamination rate and cleaning requirements.

[0004] In a first aspect, the present invention provides a liquid level sensor cleaning method for an intelligent control module connected to an ultrasonic oscillation device; the method comprises:

[0005] Obtain the historical cleaning frequency and liquid level monitoring data set of the liquid level sensor; determine whether there is an anomaly caused by surface attachments of the liquid level sensor based on the liquid level monitoring data set; when there is an anomaly caused by surface attachments of the liquid level sensor, obtain the anomaly data set and determine the pollution level and pollutant type based on the anomaly data set; determine the target cleaning strategy optimization algorithm based on the pollutant type; based on the pollution level and historical cleaning frequency, obtain the target cleaning time and target cleaning intensity through the target cleaning strategy optimization algorithm, and the target cleaning time is used to represent the start time of cleaning the liquid level sensor; based on the target cleaning time and target cleaning intensity, control the ultrasonic oscillation device to clean the liquid level sensor.

[0006] The liquid level sensor cleaning method provided by the present invention can accurately identify anomalies caused by attachments on the sensor surface by combining historical cleaning frequencies with liquid level monitoring data sets, thereby avoiding waste of resources caused by blind cleaning. At the same time, the impact of changes in the environmental conditions of the liquid level sensor on the pollution rate and cleaning needs is taken into account, so that the cleaning timing and intensity are matched with actual needs, ensuring the long-term stable operation of the liquid level sensor in complex environments. Furthermore, the target cleaning strategy optimization algorithm is matched according to different pollutant types to ensure that the cleaning intensity is adapted to the characteristics of the pollutants and improve the cleaning efficiency. Furthermore, according to the determined target cleaning time and target cleaning intensity, the ultrasonic oscillation device is controlled to clean the liquid level sensor, thereby realizing the timing and quantitative control of the cleaning operation, and ensuring that the liquid level sensor maintains stable measurement accuracy during long-term operation.

[0007] In an optional embodiment, the liquid level monitoring data set includes multiple liquid level data, multiple environmental data, and multiple sensor surface attachment information; and determining whether there is an abnormality caused by the surface attachment of the liquid level sensor based on the liquid level monitoring data set includes:

[0008] Based on multiple liquid level data, multiple target indicators are obtained through sliding window processing; whether there is an abnormality is determined based on the multiple target indicators; when an abnormality exists, it is determined whether the abnormality is caused by surface attachments of the liquid level sensor based on multiple environmental data and multiple sensor surface attachment information.

[0009] The liquid level sensor cleaning method provided by this invention extracts multiple target indicators using a sliding window method based on multiple liquid level data, providing a quantitative basis for abnormality judgment. Furthermore, by combining environmental data and information about sensor surface deposits, it distinguishes whether anomalies are caused by surface deposits or environmental interference, avoiding misjudgments and ensuring that cleaning is triggered only when deposits are confirmed, reducing ineffective operations and saving energy.

[0010] In an optional embodiment, the method further includes:

[0011] Whether the environment in which the liquid level sensor is located is stable is determined based on multiple environmental data; when the environment in which the liquid level sensor is located is stable, the target cleaning time is adjusted to obtain a first cleaning time, and the first cleaning time is greater than the target cleaning time.

[0012] The liquid level sensor cleaning method provided by the present invention determines environmental stability through environmental data, extends the cleaning cycle when the environment is stable, reduces unnecessary cleaning operations, avoids excessive cleaning in scenarios where the environment is stable and pollutants accumulate slowly, reduces equipment operating energy consumption and component loss, extends the service life of the ultrasonic oscillation device, and improves the economy of system operation.

[0013] In an optional embodiment, the method further includes:

[0014] Based on multiple environmental data and multiple sensor surface attachment information, determine whether there is a surge in pollutants; when there is a surge in pollutants, adjust the target cleaning time to obtain a second cleaning time, which is less than the target cleaning time.

[0015] The liquid level sensor cleaning method provided by the present invention can promptly identify a surge in pollutants by combining environmental data and sensor surface information. Furthermore, if a surge in pollutants occurs, cleaning is triggered in advance, avoiding the expansion of measurement errors caused by the rapid accumulation of pollutants and ensuring that the liquid level sensor can still maintain stable measurement performance in complex environments.

[0016] In an optional embodiment, the intelligent control module is further connected to the liquid level measurement module; the method further comprises: performing real-time correction on the ultrasonic measurement data of the liquid level measurement module according to a plurality of environmental data.

[0017] The liquid level sensor cleaning method provided by the present invention uses environmental data to correct ultrasonic measurement data in real time, offsetting the interference of environmental parameters on the ultrasonic measurement data, ensuring that the liquid level data output by the liquid level measurement module is closer to the true value, providing a reliable data basis for subsequent abnormality identification and pollution level judgment, and avoiding misjudgment of cleaning strategies due to environmental interference.

[0018] In an optional embodiment, the method further includes:

[0019] The real-time ultrasonic measurement data value and multiple real-time environmental data of the liquid level measurement module are obtained; a data error value is determined based on the real-time ultrasonic measurement data value and a preset ultrasonic measurement data reference value; a correction value is obtained based on the multiple real-time environmental data and the data error value through a preset correction algorithm; and the real-time ultrasonic measurement data value is dynamically adjusted according to the correction value.

[0020] The liquid level sensor cleaning method provided by this invention quantifies data errors by comparing real-time ultrasonic measurement data with preset baseline values, ensuring that errors remain within a controllable range. Furthermore, by combining real-time environmental data and error values, a preset algorithm generates correction values, dynamically adjusting measurement parameters. This implements a closed-loop control system of "measurement-error monitoring-correction," ensuring long-term measurement parameter accuracy and is particularly suitable for use in highly variable environments.

[0021] In a second aspect, the present invention provides a liquid level sensor cleaning system, the system comprising: a liquid level sensor, a data acquisition module, a liquid level measurement module, an ultrasonic oscillation device, an environmental sensor, and an intelligent control module;

[0022] A data acquisition module is used to obtain information on multiple sensor surface attachments of the liquid level sensor and send the information on multiple sensor surface attachments to the intelligent control module; a liquid level measurement module is used to obtain multiple liquid level data of the liquid level sensor and send the multiple liquid level data to the intelligent control module; an environmental sensor is used to obtain multiple environmental data of the liquid level sensor and send the multiple environmental data to the intelligent control module; the intelligent control module is used to execute the liquid level sensor cleaning method of the first aspect or any corresponding embodiment thereof; and an ultrasonic oscillation device is used to clean the liquid level sensor.

[0023] The liquid level sensor cleaning system provided by the present invention collects multi-dimensional data through the division of labor among the data acquisition module, the liquid level measurement module, and the environmental sensor, providing comprehensive input for the intelligent control module. Furthermore, the liquid level sensor cleaning method is executed by the intelligent control module, realizing full automation from data analysis to cleaning execution. Furthermore, the ultrasonic oscillation device accurately responds to control instructions and completes targeted cleaning. Therefore, by implementing the present invention, dynamic updating and maintenance of the cleaning strategy are realized, ensuring the long-term stable operation of the liquid level sensor in a complex environment and reducing the cost of manual maintenance.

[0024] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the liquid level sensor cleaning method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the liquid level sensor cleaning method of the first aspect or any corresponding embodiment thereof.

[0026] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the liquid level sensor cleaning method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 is a structural block diagram of a liquid level sensor cleaning system according to an embodiment of the present invention;

[0029] Figure 2 is a flow chart of a liquid level sensor cleaning method according to an embodiment of the present invention;

[0030] Figure 3 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0032] An embodiment of the present invention provides a liquid level sensor cleaning method. By combining historical cleaning frequencies with liquid level monitoring data sets and matching target cleaning strategy optimization algorithms according to different pollutant types, the target cleaning time and target cleaning intensity are determined, and then the ultrasonic oscillation device is controlled to clean the liquid level sensor. This achieves timing and quantitative control of the cleaning operation, ensuring that the liquid level sensor maintains stable measurement accuracy during long-term operation.

[0033] According to an embodiment of the present invention, an embodiment of a liquid level sensor cleaning method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] In this embodiment, a liquid level sensor cleaning method is provided for Figure 1 The intelligent control module 16 shown is connected to the data acquisition module 12 , the liquid level measurement module 13 , the ultrasonic oscillation device 14 , and the environmental sensor 15 respectively.

[0035] Figure 2 FIG. 1 is a flow chart of a method for cleaning a liquid level sensor according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0036] Step S201 : Acquire a historical cleaning frequency and liquid level monitoring data set of a liquid level sensor.

[0037] Among them, the historical cleaning frequency indicates the ratio of the number of cleaning operations performed on the liquid level sensor in the past period of time (such as a certain period, which can be set to one month, one year, etc. according to actual needs) to the length of the period, which is used to reflect the frequency of the liquid level sensor's past cleaning operations.

[0038] Optionally, the intelligent control module 16 can call all cleaning records within a preset time period (such as the past 30 days or 90 days) from an internal storage module, count the total number of cleanings within the period, and then calculate the historical cleaning frequency based on the period duration.

[0039] For example, if the device was cleaned 12 times in the past 30 days, the historical cleaning frequency would be "once every 2.5 days on average"; or if calculated based on the number of cleanings per day, the result would be "0.4 times per day on average".

[0040] Furthermore, the liquid level monitoring data set represents a multi-dimensional data set for reflecting the liquid level status, environmental conditions and sensor surface contamination, and may include multiple liquid level data, multiple environmental data and multiple sensor surface attachment information.

[0041] Furthermore, multiple liquid level data can be collected in real time by the liquid level measurement module 13 to reflect the dynamic changes in liquid height, which is the basis for analyzing the fluctuation characteristics of the liquid level signal and identifying measurement anomalies.

[0042] Furthermore, multiple environmental data can be collected in real time by the environmental sensor 15, which may include environmental parameters such as temperature and humidity, water turbidity, and salt concentration in specific scenarios, to reflect the real-time status of the environment in which the liquid level sensor is located.

[0043] Furthermore, information on attachments on the surfaces of multiple sensors can be acquired by the data acquisition module 12 , and may include data such as reflection intensity anomalies, which are used to directly indicate the contamination status of the sensor surface, such as the presence and degree of attachments.

[0044] Step S202: judging whether there is an abnormality caused by surface attachments of the liquid level sensor based on the liquid level monitoring data set.

[0045] Specifically, measurement abnormalities of the liquid level sensor may be caused by a variety of factors, including attachments on the sensor surface (such as dirt and sediment) or external environmental interference (such as temperature and humidity changes).

[0046] Furthermore, if the source of the abnormality is not clear, direct cleaning operations may result in errors: for example, misjudging an abnormality caused by environmental interference as surface contamination will lead to unnecessary cleaning, increased energy consumption and equipment loss; and if an abnormality caused by surface attachments is not handled in a timely manner, it will affect measurement accuracy and stability.

[0047] Furthermore, based on the liquid level monitoring data set, it is determined whether the measurement anomaly of the liquid level sensor is caused by surface attachments, and the anomaly caused by the surface attachments can be accurately located, ensuring that subsequent cleaning strategies are only initiated for real contamination problems, avoiding the waste of resources caused by blind cleaning.

[0048] Step S203 : When there is an abnormality caused by surface attachments of the liquid level sensor, an abnormal data set is acquired and the pollution level and pollutant type are determined according to the abnormal data set.

[0049] Among them, the abnormal data set refers to the subset related to the abnormality extracted from the liquid level monitoring data set when it is determined that the measurement abnormality of the liquid level sensor is caused by its surface attachments. It can include the liquid level data during the abnormal period (such as the liquid level measurement value and signal characteristics in the abnormality identification stage), the corresponding environmental data (such as temperature and humidity, water turbidity, etc. when the abnormality occurs), and the sensor surface attachment information (such as reflection intensity abnormality data during the abnormal period, etc.).

[0050] Specifically, the contamination level can be further quantified by combining the surface attachment information and liquid level signal characteristics in the abnormal data set.

[0051] In some optional embodiments, the pollution level can be quantified as follows:

[0052] (1) Analysis of abnormal reflection intensity: Calculate the deviation rate of the reflection intensity from the normal state (such as the initial stage after cleaning) (such as deviation rate = (normal reflection intensity - current reflection intensity) / normal reflection intensity × 100%). The larger the deviation rate, the thicker or denser the attachment.

[0053] (2) Liquid level signal stability assessment: Combined with the reflection waveform stability and measurement error trend obtained by sliding window analysis, when the stability is lower than the preset threshold (e.g., 80%) and the error trend continues to rise, the degree of interference of contamination on the measurement is determined.

[0054] (3) Classification standard matching: According to the preset rules (such as deviation rate <30% is "light pollution", 30%-60% is "moderate pollution", >60% is "heavy pollution"), combined with the degree of signal interference, the current pollution level is determined.

[0055] Furthermore, the types of pollutants can be distinguished through the multi-dimensional features of abnormal data sets.

[0056] In some optional embodiments, pollutant types can be distinguished based on the following criteria:

[0057] (1) Accumulation rate of attachments: Based on historical data, if the reflection intensity drops rapidly in a short period of time (e.g., within 24 hours) and the water turbidity is high, it may be light silty attachments; if the accumulation rate is slow but the duration is long, it may be algae attachments (algae growth is gradual).

[0058] (2) Environmental relevance: Algal attachments are usually related to environmental parameters such as water temperature and light (e.g., they are more likely to grow in warm seasons), while silty attachments are mostly related to water flow and turbidity (e.g., they are more likely to settle when the water flow is turbulent in the rainy season).

[0059] (3) Differences in signal characteristics: Algae attachments may cause the reflected signal to fluctuate at a specific frequency (due to the irregular shape of the algae), while muddy attachments often show a uniform attenuation of the reflection intensity.

[0060] Furthermore, based on the above characteristics, the specific pollutant type is determined by matching with a preset pollutant type library.

[0061] Step S204: determining a target cleaning strategy optimization algorithm according to the type of pollutant.

[0062] Specifically, different types of pollutants have different characteristics. Therefore, it is necessary to select different target cleaning strategy optimization algorithms that match the determined pollutant types to formulate more effective cleaning strategies.

[0063] For example, the decision tree method is used for algae attachments, and the random forest method is used for light mud attachments to ensure that the cleaning strategy can accurately adapt to the characteristics of the pollutants and improve the cleaning effect.

[0064] Step S205 : Based on the pollution level and historical cleaning frequency, the target cleaning time and target cleaning intensity are obtained through processing by the target cleaning strategy optimization algorithm.

[0065] Among them, the target cleaning time is used to characterize the start time of cleaning the liquid level sensor; the target cleaning intensity is used to determine the working parameters of the ultrasonic oscillation device 14, including the oscillation frequency (such as 50kHz), power (such as 80% rated power), and duration (such as 20 seconds), to ensure that it matches the pollution level and efficiently removes attachments.

[0066] Specifically, the determined pollution levels (such as mild, moderate, and severe) can be converted into quantitative indicators (such as levels 1-5, where the higher the value, the more severe the pollution).

[0067] Furthermore, the quantified pollution level, historical cleaning frequency and preset environmental stability parameters (such as the fluctuation range of recent environmental data) can be standardized to unify the data format and magnitude as algorithm input.

[0068] For example: convert information such as "severe pollution (level 5)", "historical average cleaning interval of 2 days", and "stable environment" into numerical vectors that can be recognized by the algorithm.

[0069] Furthermore, the target cleaning strategy optimization algorithm can analyze the pollution growth rate based on the historical cleaning frequency and dynamically adjust it according to the current pollution level:

[0070] (1) If the current pollution level is higher than the historical average level at the same frequency, shorten the cleaning interval (e.g., one day earlier);

[0071] (2) If the current pollution level is lower than the historical average level at the same frequency, extend the cleaning interval (e.g., by 1 day).

[0072] Furthermore, a specific cleaning start time, ie, a target cleaning time, is output through the above adjustment.

[0073] Furthermore, the targeted cleaning strategy optimization algorithm can also match the cleaning intensity level to the pollution level. For example, light pollution corresponds to 50% power and 10 seconds of oscillation; heavy pollution corresponds to 100% power and 30 seconds of oscillation.

[0074] At the same time, you can also combine historical cleaning effect data (such as "the reflection intensity recovered to 80% after 100% power cleaning during historical severe pollution") to fine-tune the intensity parameters to ensure that the cleaning effect meets the standards.

[0075] Furthermore, the calculated target cleaning time and intensity can be checked for rationality (such as avoiding conflicts between cleaning time and critical periods of liquid level measurement, and ensuring that the cleaning intensity does not exceed the maximum load of the equipment). If the verification passes, the result is output; if not, the adjustment parameters are returned and recalculated.

[0076] In some optional embodiments, taking the decision tree algorithm (applicable to algae attachment scenarios) as an example, the specific process of determining the target cleaning time and target cleaning intensity includes:

[0077] (1) Input parameter loading.

[0078] (a) Pollution level: quantify the algae pollution level (e.g., "moderate") determined in step S203 into a numerical value (e.g., level 3, with levels 1-5 increasing in increments);

[0079] (b) Historical cleaning frequency: extract the average cleaning interval when algae contamination occurred in historical data (e.g., the average cleaning interval for the past six times was 4 days);

[0080] (c) Loading the pre-trained algae pollution decision tree model, which takes pollution level and historical cleaning interval as input features and outputs cleaning time adjustment coefficient and intensity level.

[0081] (2) Decision tree model operation.

[0082] (a) First-level judgment: According to the current pollution level (level 3), the model branch is matched and the path of "moderate pollution" is entered, corresponding to a basic cleaning interval of 4 days (referring to the historical frequency);

[0083] (b) Second-level judgment: Based on historical cleaning effect data (e.g., when the pollution level is level 3, the probability that the pollution has not worsened after a 4-day interval is 80%), the decision tree outputs a time adjustment coefficient of "+0 days" (i.e., maintaining the basic interval);

[0084] (c) Third level judgment: Based on the pollution level (level 3), the model outputs a cleaning intensity level of "medium" (corresponding to ultrasonic power 70% and oscillation time 20 seconds).

[0085] (3) Output target parameters.

[0086] (a) Target cleaning time: Based on the current time (e.g., 2024-08-01 08:00) and the 4-day interval, the cleaning start time is determined to be 2024-08-05 08:00;

[0087] (b) Target cleaning intensity: determined as "70% power, 20 seconds" to ensure effective removal of algae and avoid excessive energy consumption.

[0088] Furthermore, through the hierarchical rule judgment of the decision tree algorithm, accurate cleaning strategy output based on pollution level and historical data is achieved, which adapts to the characteristics of algae attachments.

[0089] Step S206 : Based on the target cleaning time and the target cleaning intensity, the ultrasonic oscillation device is controlled to clean the liquid level sensor.

[0090] Specifically, the intelligent control module 16 monitors the current time in real time, and automatically activates the cleaning instruction trigger program when the target cleaning time determined in step S205 (ie, the preset cleaning start time) is reached.

[0091] Furthermore, the intelligent control module 16 can transmit the parameters corresponding to the target cleaning intensity (such as the operating frequency, power, duration, etc. of the ultrasonic oscillation device) to the driving module of the ultrasonic oscillation device 14 to complete the parameter configuration before cleaning and ensure that the device operates at the set intensity.

[0092] Furthermore, the ultrasonic oscillator 14 can initiate high-frequency oscillation based on the received parameters, removing debris (such as algae and silt) from the surface of the liquid level sensor through mechanical vibration. Simultaneously, during the cleaning process, the intelligent control module 16 can also monitor the operating status of the ultrasonic oscillator 14 in real time (such as whether it is oscillating normally and whether the power is stable).

[0093] Furthermore, when the cleaning time reaches the duration set by the target cleaning intensity, the intelligent control module 16 issues a stop command and the ultrasonic oscillation device 14 stops working; at the same time, the ultrasonic oscillation device 14 feeds back the cleaning completion signal and operating status data (such as actual oscillation duration, power fluctuation, etc.) to the intelligent control module 16 for subsequent cleaning effect evaluation.

[0094] The liquid level sensor cleaning method provided in this embodiment, by combining the historical cleaning frequency with the liquid level monitoring data set, can accurately identify anomalies caused by attachments on the sensor surface, thereby avoiding the waste of resources caused by blind cleaning. At the same time, the impact of changes in the environmental conditions of the liquid level sensor on the pollution rate and cleaning needs is taken into account, so that the cleaning timing and intensity are matched with actual needs, ensuring the long-term stable operation of the liquid level sensor in a complex environment. Furthermore, the target cleaning strategy optimization algorithm is matched according to different pollutant types to ensure that the cleaning intensity is adapted to the characteristics of the pollutants and improve the cleaning efficiency. Furthermore, according to the determined target cleaning time and target cleaning intensity, the ultrasonic oscillation device is controlled to clean the liquid level sensor, thereby realizing the timing and quantitative control of the cleaning operation, and ensuring that the liquid level sensor maintains stable measurement accuracy during long-term operation.

[0095] In some optional implementations, the above step S202 includes:

[0096] Step S2021: Based on the multiple liquid level data, multiple target indicators are obtained through sliding window processing.

[0097] Step S2022: Determine whether there is an abnormality based on multiple target indicators.

[0098] Step S2023: When an abnormality exists, it is determined whether the abnormality is caused by surface attachments of the liquid level sensor based on the plurality of environmental data and the plurality of sensor surface attachment information.

[0099] Specifically, the intelligent control module 16 can set a fixed-length sliding window (such as a window size of 10 data points and a sliding step of 1) for the continuously collected liquid level data (such as collecting one liquid level value every 1 second to form time series data), that is, analyze 10 consecutive liquid level data each time, and then move the window backward by 1 data point and repeat the process.

[0100] Furthermore, for the liquid level data in each sliding window, the following target indicators are calculated:

[0101] (1) Reflection waveform stability: By analyzing the consistency of the liquid level signal waveform in the window (such as the peak value of the waveform and the fluctuation amplitude of the phase), the waveform stability is quantified (the closer the value is to 1, the higher the stability);

[0102] (2) Measurement error trend: Compare the error of each liquid level measurement value in the window with the reference value (such as the initial measurement value after cleaning), and calculate the cumulative change rate of the error (if the error continues to increase, the trend is positive);

[0103] (3) Signal-to-noise ratio (SNR): Separate the effective signal and noise components in the liquid level signal within the window and calculate the power ratio between the two (the lower the SNR, the more serious the noise interference).

[0104] Furthermore, the calculation results of all sliding windows are integrated to form a time series of multiple target indicators.

[0105] Furthermore, the normal range thresholds of various target indicators can be determined based on historical data of the liquid level sensor in a clean state. For example, the reflection waveform stability ≥ 0.8, the absolute value of the measurement error trend ≤ 5% / hour, and the SNR ≥ 20dB.

[0106] Furthermore, compare the target indicator with the threshold window by window:

[0107] (1) If at least one indicator in a single window exceeds the threshold (e.g., reflection waveform stability = 0.6 < 0.8), the window is marked as "suspected abnormality";

[0108] (2) If three or more consecutive windows are marked as "suspected abnormality", it is determined that there is a measurement abnormality (to avoid misjudgment due to accidental fluctuations).

[0109] Furthermore, if it is determined that there is no abnormality, the system returns to continue monitoring the liquid level data. If it is determined that there is an abnormality, the environmental data during the abnormal period (such as temperature and humidity, water turbidity, salt concentration, etc.) can be analyzed to calculate the fluctuation range (such as whether the temperature fluctuation is ≤±2℃, whether the turbidity change is ≤10%):

[0110] (1) If the environmental data fluctuation exceeds the preset stability threshold (e.g., a sudden temperature rise of 5°C), the anomaly may be caused by environmental interference;

[0111] (2) If the environmental data fluctuations are within the stability threshold, the main environmental interference factors are eliminated.

[0112] Furthermore, the sensor surface attachment information (such as reflection intensity abnormality data) during the abnormal period is extracted:

[0113] (1) If the reflection intensity drops by ≥30% compared to the clean state (e.g. the normal reflection intensity is 800mV and the current value is 500mV), and the downward trend coincides with the abnormal window of the liquid level signal, it indicates that there is interference from attachments;

[0114] (2) If there is no significant change in the reflection intensity, the anomaly may be caused by other non-adhesion factors (such as equipment failure).

[0115] Furthermore, when the environment is stable (fluctuation ≤ threshold) and the reflection intensity is abnormal, it can be determined that the abnormality is caused by surface attachments; when the environmental fluctuation exceeds the standard or the reflection intensity is normal, the abnormality is determined to be caused by environmental interference or other factors, and the cleaning operation is not triggered.

[0116] The liquid level sensor cleaning method provided in this embodiment extracts multiple target indicators using a sliding window method based on multiple liquid level data points, providing a quantitative basis for abnormality determination. Furthermore, by combining environmental data with information about surface deposits on the sensor, it distinguishes whether anomalies are caused by surface deposits or environmental interference, avoiding misjudgments and ensuring that cleaning is triggered only when deposits are present, reducing ineffective operations and saving energy.

[0117] In some optional embodiments, the method further comprises:

[0118] Step a1: determining whether the environment in which the liquid level sensor is located is stable based on a plurality of environmental data.

[0119] Step a2: When the environment in which the liquid level sensor is located is stable, the target cleaning time is adjusted to obtain a first cleaning time.

[0120] The first cleaning time is greater than the target cleaning time.

[0121] Specifically, for each piece of environmental data, the fluctuation range within a preset time window (such as 1 hour) can be calculated, which may include:

[0122] (1) Temperature fluctuation: calculate the difference between the highest and lowest temperatures in the window;

[0123] (2) Humidity fluctuation: calculate the maximum rate of change of humidity within the window;

[0124] (3) Fluctuations in water characteristics: such as the standard deviation of turbidity, coefficient of variation of salt concentration, etc.

[0125] Furthermore, the fluctuation amplitude of each data is compared with the preset threshold (such as temperature fluctuation ≤±2°C, turbidity standard deviation ≤5NTU).

[0126] Furthermore, if the fluctuation amplitudes of all environmental parameters do not exceed the corresponding thresholds, the environment is determined to be stable; if the fluctuation of any parameter exceeds the standard, the environment is determined to be unstable.

[0127] Furthermore, since the accumulation rate of pollutants is usually slow when the environment is stable (such as the rate of algae growth and sludge deposition is predictable), the cleaning cycle can be extended according to preset rules, that is, the start time of cleaning the liquid level sensor can be extended.

[0128] The liquid level sensor cleaning method provided in this embodiment determines environmental stability through environmental data, extends the cleaning cycle when the environment is stable, reduces unnecessary cleaning operations, avoids excessive cleaning in scenarios where the environment is stable and pollutants accumulate slowly, reduces equipment operating energy consumption and component loss, extends the service life of the ultrasonic oscillation device, and improves the economy of system operation.

[0129] In some optional embodiments, the method further comprises:

[0130] Step b1: judging whether there is a surge in pollutants based on multiple environmental data and multiple sensor surface attachment information.

[0131] Step b2: When there is a surge in pollutants, the target cleaning time is adjusted to obtain a second cleaning time.

[0132] The second cleaning time is shorter than the target cleaning time.

[0133] Specifically, changes in parameters related to pollutant growth in environmental data can be analyzed, such as water turbidity rising by more than 50% within 1 hour, a sudden drop in liquid flow rate leading to accelerated sedimentation, etc. These environmental changes may indicate the risk of a surge in pollutants.

[0134] Furthermore, the rate of change of the sensor surface deposit information can be calculated using a sliding window method (e.g., a 10-minute window). For example, if the reflection intensity abnormality value increases by more than 30% within a short period of time (e.g., 30 minutes), or if the growth rate of the deposit thickness estimate exceeds twice the historical average value for the same period.

[0135] Furthermore, if the environmental data shows conditions that are conducive to the rapid accumulation of pollutants (such as high turbidity and low flow rate), and the rate of change of the attachment information exceeds a preset threshold (such as the increase rate of the reflection intensity abnormality value is greater than 20% / hour), it can be determined that there is a surge in pollutants; otherwise, it is determined that there is no surge.

[0136] Furthermore, when contaminants surge, deposits quickly accumulate on the sensor surface, necessitating early cleaning to prevent impacts on measurement accuracy. Based on the severity of the surge, the cleaning cycle is shortened and the cleaning operation is triggered earlier, moving the start time (target cleaning time) of the liquid level sensor to the second cleaning time.

[0137] The liquid level sensor cleaning method provided in this embodiment can promptly identify a surge in pollutants by combining environmental data and sensor surface information. Furthermore, if a surge in pollutants occurs, cleaning is triggered in advance, avoiding the expansion of measurement errors caused by the rapid accumulation of pollutants and ensuring that the liquid level sensor can maintain stable measurement performance in complex environments.

[0138] In some optional embodiments, the method further comprises:

[0139] Step c1: correcting the ultrasonic measurement data of the liquid level measurement module in real time according to multiple environmental data.

[0140] Specifically, based on changes in environmental data, factors that have a significant impact on ultrasonic measurement (such as temperature changes that affect the speed of sound) can be identified and a preset correction model can be called.

[0141] Furthermore, the correction model can be used to modify the ultrasonic measurement parameters of the liquid level measurement module (such as time threshold, sensitivity, and transmission frequency) in real time. For example, when the speed of sound changes due to temperature increases, the time threshold can be adjusted to compensate for the measurement error caused by the change in speed of sound.

[0142] Furthermore, the corrected parameters can be applied to the current ultrasonic measurement process to update the liquid level measurement data, thereby ensuring the accuracy of the measurement results when the environment changes.

[0143] The liquid level sensor cleaning method provided in this embodiment uses environmental data to correct ultrasonic measurement data in real time, offsetting the interference of environmental parameters on the ultrasonic measurement data, ensuring that the liquid level data output by the liquid level measurement module is closer to the true value, providing a reliable data basis for subsequent abnormality identification and pollution level judgment, and avoiding misjudgment of cleaning strategies due to environmental interference.

[0144] In some optional embodiments, the method further comprises:

[0145] Step d1: acquiring real-time ultrasonic measurement data values ​​of the liquid level measurement module and a plurality of real-time environmental data.

[0146] Step d2: determining a data error value based on the real-time ultrasonic measurement data value and a preset ultrasonic measurement data reference value.

[0147] In step d3, a correction value is obtained based on a plurality of real-time environmental data and data error values ​​through processing by a preset correction algorithm.

[0148] Step d4: dynamically adjust the real-time ultrasonic measurement data value according to the correction value.

[0149] Specifically, the ultrasonic measurement data reference value can be retrieved from the preset parameter library, where the reference value represents the calibration value of the sensor in a clean state and under standard environmental conditions (such as temperature 20°C and humidity 50%) (such as the liquid level reference value is 1.5m).

[0150] Furthermore, the actual output value (real-time ultrasonic measurement data value) of the current measurement parameters (such as the time threshold, sensitivity, and transmission frequency of ultrasonic measurement) is compared with the calibration reference value in real time, and the data error value is calculated: Error = |(actual output value - calibration reference value) / calibration reference value|×100%.

[0151] Furthermore, when the error exceeds 10%, a feedback calibration mechanism is triggered.

[0152] Furthermore, the correction amount, i.e., the correction value, can be calculated based on the memorized error data and current environmental parameters (such as the impact of temperature changes on the speed of sound) through a preset algorithm (such as proportional-integral-differential control or a historical error correction model).

[0153] Furthermore, the calculated correction values ​​can be used to dynamically adjust measurement parameters (real-time ultrasonic measurement data values) that exceed the specified value. For example, if the time threshold error exceeds 10% due to a change in sound velocity caused by a temperature increase, the time threshold parameter can be recalculated and corrected based on the correlation model between temperature and sound velocity.

[0154] Furthermore, after correction, real-time monitoring is performed to determine whether the error of the adjusted parameters has returned to within 10%.

[0155] Furthermore, if the standard is still exceeded, the "memory-correction" process is repeated until the error meets the requirements; if the standard has been met, the correction parameters and environmental related data are updated and stored to optimize the accuracy of subsequent calibrations and form a closed-loop feedback.

[0156] The liquid level sensor cleaning method provided in this embodiment quantifies data errors by comparing real-time ultrasonic measurement data with preset baseline values, ensuring that errors remain within a controllable range. Furthermore, by combining real-time environmental data and error values, a preset algorithm generates correction values, dynamically adjusting measurement parameters. This implements a closed-loop control system of "measurement-error monitoring-correction," ensuring long-term measurement parameter accuracy and is particularly suitable for use in highly variable environments.

[0157] In this embodiment, a liquid level sensor cleaning system is provided. Figure 1 As shown, the liquid level sensor cleaning system 1 includes a liquid level sensor 11 , a data acquisition module 12 , a liquid level measurement module 13 , an ultrasonic oscillation device 14 , an environmental sensor 15 and an intelligent control module 16 .

[0158] Optionally, the data acquisition module 12 is used to obtain information on multiple sensor surface attachments of the liquid level sensor and send the information to the intelligent control module 16. The specific process can be referred to the description in step S201 above and will not be repeated here.

[0159] Optionally, the liquid level measurement module 13 is configured to obtain a plurality of liquid level data from the liquid level sensor and send the plurality of liquid level data to the intelligent control module 16. The specific process can be referred to the description in the above step S201 and will not be repeated here.

[0160] Optionally, the environmental sensor 15 is used to obtain a plurality of environmental data of the liquid level sensor and send the plurality of environmental data to the intelligent control module 16. The specific process can be referred to the description in the above step S201, which will not be repeated here.

[0161] Optionally, the intelligent control module 16 is configured to execute the liquid level sensor cleaning method provided in the above embodiment of the present invention.

[0162] Optionally, the ultrasonic oscillation device 14 is used to clean the liquid level sensor 11. The specific process can be referred to the description of step S206 above, which will not be repeated here.

[0163] The liquid level sensor cleaning system provided in this embodiment collects multi-dimensional data through the division of labor among the data acquisition module, the liquid level measurement module, and the environmental sensor, providing comprehensive input for the intelligent control module. Furthermore, the liquid level sensor cleaning method is executed by the intelligent control module, realizing full automation from data analysis to cleaning execution. Furthermore, the ultrasonic oscillation device accurately responds to control instructions and completes targeted cleaning. Therefore, by implementing the present invention, dynamic updating and maintenance of the cleaning strategy is realized, ensuring the long-term stable operation of the liquid level sensor in a complex environment and reducing the cost of manual maintenance.

[0164] The embodiment of the present invention also provides a computer device for executing the above Figure 2 How to clean the liquid level sensor.

[0165] See also Figure 3 , Figure 3 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 3 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of a GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0166] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0167] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0168] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0169] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0170] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0171] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0172] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0173] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A liquid level sensor cleaning method, characterized in that: Used in an intelligent control module, the intelligent control module is connected to an ultrasonic oscillation device; the method includes: Acquire a historical cleaning frequency of a liquid level sensor and a liquid level monitoring data set, wherein the liquid level monitoring data set includes a plurality of liquid level data, a plurality of environmental data, and a plurality of sensor surface attachment information; Determining, based on the liquid level monitoring data set, whether there is an abnormality caused by surface attachments of the liquid level sensor; When there is an abnormality caused by surface attachments of the liquid level sensor, obtaining an abnormal data set and determining a pollution level and a pollutant type based on the abnormal data set; Determining a target cleaning strategy optimization algorithm based on the pollutant type; Based on the pollution level and the historical cleaning frequency, a target cleaning time and a target cleaning intensity are obtained through processing by the target cleaning strategy optimization algorithm, wherein the target cleaning time is used to represent the start time of cleaning of the liquid level sensor; Based on the target cleaning time and the target cleaning intensity, the ultrasonic oscillation device is controlled to clean the liquid level sensor.

2. The method according to claim 1, characterized in that Determining, based on the liquid level monitoring data set, whether there is an abnormality caused by surface attachments of the liquid level sensor includes: Based on the multiple liquid level data, multiple target indicators are obtained through sliding window processing; Determining whether there is an abnormality based on the multiple target indicators; When an abnormality occurs, it is determined whether the abnormality is caused by surface attachments of the liquid level sensor based on the plurality of environmental data and the plurality of sensor surface attachment information.

3. The method according to claim 1, characterized in that The method further comprises: determining whether the environment in which the liquid level sensor is located is stable according to the plurality of environmental data; When the environment where the liquid level sensor is located is stable, the target cleaning time is adjusted to obtain a first cleaning time, and the first cleaning time is greater than the target cleaning time.

4. The method according to claim 1, wherein The method further comprises: Determining whether there is a surge in pollutants based on the multiple environmental data and the multiple sensor surface attachment information; When there is a surge in pollutants, the target cleaning time is adjusted to obtain a second cleaning time, which is shorter than the target cleaning time.

5. The method according to claim 1, wherein The intelligent control module is also connected to the liquid level measurement module; the method further includes: The ultrasonic measurement data of the liquid level measurement module is corrected in real time according to the multiple environmental data.

6. The method according to claim 5, characterized in that The method further comprises: Acquiring real-time ultrasonic measurement data values ​​and a plurality of real-time environmental data of the liquid level measurement module; determining a data error value based on the real-time ultrasonic measurement data value and a preset ultrasonic measurement data reference value; Based on the plurality of real-time environmental data and the data error value, a correction value is obtained by processing with a preset correction algorithm; The real-time ultrasonic measurement data value is dynamically adjusted according to the correction value.

7. A liquid level sensor cleaning system, characterized in that: The system includes: a liquid level sensor, a data acquisition module, a liquid level measurement module, an ultrasonic oscillation device, an environmental sensor and an intelligent control module; The data acquisition module is used to obtain information about a plurality of sensor surface attachments of the liquid level sensor and send the information about the plurality of sensor surface attachments to the intelligent control module; The liquid level measurement module is used to obtain multiple liquid level data from the liquid level sensor and send the multiple liquid level data to the intelligent control module; The environmental sensor is used to obtain a plurality of environmental data of the liquid level sensor and send the plurality of environmental data to the intelligent control module; The intelligent control module is used to execute the liquid level sensor cleaning method according to any one of claims 1 to 6; The ultrasonic oscillation device is used to clean the liquid level sensor.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the cleaning method of the liquid level sensor according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for cleaning a liquid level sensor according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for cleaning a liquid level sensor according to any one of claims 1 to 6.

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