Intelligent acquisition system for rainfall isotope sample

Abstract

The invention relates to the technical field of intelligent collection of rainfall samples, in particular to an intelligent collection system for rainfall isotope samples, which comprises an environment monitoring module, a sampling equipment control module, a sampling data acquisition module and a sampling data verification module, the wind direction and meteorological data of a deployment area are obtained, the opening and closing speed of a cover body of a sampling device is dynamically calculated, synchronous control is executed, and a chromaticity response curve and a flow response curve are constructed by combining high-frequency collection and delay correction of filtrate flow and chromaticity; extracting chromaticity mutation points through sliding window extreme value detection and threshold value comparison, and judging that the quality of the filtrate is abnormal; and on the basis of symmetric compensation and curve similarity evaluation, cover body opening and closing faults are identified, and dual verification of physical structure abnormity and sampling data validity in the sampling process is realized. The system can improve the representativeness and accuracy of the rainfall sample in a complex meteorological environment so as to ensure the stability and traceability of a subsequent isotope analysis result.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent collection of precipitation samples, and in particular to an intelligent collection system for precipitation isotope samples. Background Art

[0002] The accurate collection of precipitation isotope samples is of great significance to hydrometeorology, environmental monitoring and climate change research. Existing precipitation sampling devices usually use a mechanical cover opening and closing structure, and its opening and closing actions are mostly fixed cycles or manually controlled. They lack dynamic adaptation to real-time meteorological conditions and are easily affected by environmental factors such as wind direction and wind speed, resulting in frequent sample contamination, mis-collection and missed collection during the sampling process. In addition, traditional systems lack effective hysteresis correction and abnormal data identification methods in the sampling data processing link, making it difficult to distinguish between physical failures and external pollution interference during the sampling process, resulting in reduced stability and representativeness of subsequent isotope analysis results. In the existing technology, the monitoring and control modules of the relevant sampling equipment are independent of each other, lacking a unified intelligent management system, and cannot achieve all-round monitoring of the sampling process and automatic response to abnormalities, which limits the further development and application of intelligent collection technology for precipitation samples.

[0003] Chinese patent publication number: CN113689054A discloses an intelligent prediction method based on climate precipitation data collection. The method integrates numerical models, statistical models, result analysis output and result evaluation, and predicts through a downscaling prediction system that combines dynamics and statistics of flood season precipitation in the middle and lower reaches of the river.

[0004] However, at the same time, each subsystem of the invention needs to be independently modeled, parameterized and maintained, the overall system integration is complex and the threshold for promotion and application is high; the surface floating mechanism and parachute assembly both rely on airbag inflation and deployment, and may fail to inflate or deploy abnormally in strong winds, high humidity or high temperature environments, affecting the positioning and deployment accuracy of the device; the current nodes rely on parachute assemblies or hooks for fixation, and the automatic deployment efficiency is low, which is not suitable for large-scale and rapid deployment needs. Summary of the Invention

[0005] To this end, the present invention provides an intelligent collection system for precipitation isotope samples to overcome the problem in the prior art that the opening and closing of the cover cannot adapt to the real-time detection environment, external pollution and device fault identification are independent of each other.

[0006] To achieve the above object, the present invention provides an intelligent collection system for precipitation isotope samples, comprising:

[0007] Environmental monitoring module, which is used to obtain wind direction data and meteorological data in the area where precipitation sampling equipment is deployed during each unit pre-detection cycle;

[0008] a sampling device control module connected to the environmental monitoring module, configured to calculate the cover opening and closing speeds based on environmental parameters and execute corresponding opening and closing actions to collect precipitation samples;

[0009] A sampling data acquisition module, which is connected to the sampling device control module and is used to collect sampling data of precipitation samples, including color detection data and flow data;

[0010] A sampling data verification module, connected to the sampling data acquisition module, is used to perform time sequence unification and hysteresis correction on the sampling data, construct a numerical response curve of chromaticity and flow rate, and compare and analyze the peak value of the chromaticity mutation point and evaluate the symmetry similarity of the flow rate curve within the lid opening and closing interval to verify whether there are any anomalies in the sampling data;

[0011] An autonomous response module is connected to the sampling device control module, the sampling data acquisition module and the sampling data verification module respectively, and is used to issue an alarm when a fault corresponding to each abnormal sampling data is obtained and send it to the monitoring main control end, so as to correct the next precipitation sampling device based on the fault.

[0012] Furthermore, the intelligent collection system for precipitation isotope samples according to claim 1 is characterized in that the environmental monitoring module includes a wind parameter capture unit and a weather data acquisition unit, wherein:

[0013] The wind parameter capture unit is used to obtain wind direction data within the deployment area of the precipitation sampling equipment, including the average wind direction angle and median wind speed;

[0014] The weather data acquisition unit is used to collect meteorological data in the area where the precipitation sampling equipment is deployed, including precipitation probability and precipitation intensity.

[0015] Furthermore, the wind parameter capturing unit includes a wind direction capturing subunit and a wind speed measuring subunit, wherein:

[0016] The wind direction capturing subunit is used to obtain the average wind direction angle within the precipitation sampling device deployment area within a unit pre-detection period;

[0017] The wind speed calculation subunit is used to obtain the median wind speed of the wind speed change value within a unit pre-detection period.

[0018] Furthermore, the sampling device control module includes a cover opening and closing speed calculation unit and a cover opening and closing execution unit, wherein:

[0019] The cover opening and closing speed calculation unit is used to calculate the ideal opening and closing speed of the cover within the collection period based on the wind direction data and the meteorological data;

[0020] The cover opening and closing execution unit is used to take the ideal opening and closing speed as the actual opening and closing speed, and open or close the cover at the actual opening and closing speed.

[0021] Furthermore, the sampling data verification module includes a sampling data processing unit, a peak value analysis unit and an opening and closing symmetry analysis unit, wherein:

[0022] The sampling data processing unit is used to perform time sequence unification and hysteresis correction processing on the sampling data, and after obtaining each corrected sampling data, construct a numerical response curve of chromaticity and flow according to the time series;

[0023] The peak analysis unit is used to obtain a peak analysis result based on a comparison result of the obtained chroma detection difference value and a standard peak chroma detection difference threshold;

[0024] Among them, the chromaticity detection difference is the chromaticity detection difference between the chromaticity mutation point and the left and right adjacent sampling points;

[0025] The opening and closing symmetry analysis unit is used to perform symmetrical compensation processing on the correction flow curve within the opening and closing range of the cover body, and obtain a similarity evaluation result by comparing the point-by-point difference between the two standard flow curves with the tolerance threshold, thereby obtaining an opening and closing symmetry analysis result.

[0026] Furthermore, the sampling data processing unit includes a time parameter correction subunit and a curve fitting unit, wherein:

[0027] The time parameter correction subunit is used to perform time sequence uniform processing and hysteresis correction processing on each sampling data to obtain each corrected sampling data;

[0028] The curve fitting unit is used to obtain each corrected sampling data, sort the chromaticity detection data and the flow detection data according to the timestamp, and then obtain the change curve of each corrected sampling data through smooth interpolation fitting.

[0029] Furthermore, the time parameter correction subunit performs time sequence uniform processing and hysteresis correction processing on each sampling data, including:

[0030] Get the timestamp of each sampling data;

[0031] Establish a unified time axis and perform interpolation alignment on each sampling data;

[0032] The average response delay time of the filter layer water absorption process is obtained, and hysteresis correction processing is performed based on the average response delay time to obtain corrected sampling data.

[0033] Furthermore, the peak analysis unit includes an image disturbance extraction subunit, a peak threshold comparison subunit and a flow exclusion subunit, wherein:

[0034] The image disturbance extraction subunit is used to divide the unit positive detection period into a number of sub-periods, and extract the chromaticity mutation points corresponding to the local maximum values of the correction chromaticity detection data change curve in each sub-period as the points to be compared;

[0035] The peak threshold comparison subunit is used to calculate the chroma detection value at any point to be compared and the two chroma detection differences of adjacent sampling points, and compare the two chroma detection differences with the standard peak chroma detection difference threshold to obtain the peak threshold comparison result;

[0036] The two chromaticity detection differences include a left chromaticity detection difference between the chromaticity detection value at the point to be compared and the left adjacent sampling point, and a right chromaticity detection difference between the chromaticity detection value at the point to be compared and the right adjacent sampling point.

[0037] The flow exclusion subunit is used to exclude the funnel filter layer rupture fault through flow verification when the first peak threshold comparison result is obtained.

[0038] Furthermore, the opening and closing symmetry analysis unit includes a symmetry compensation subunit and a similarity evaluation subunit, wherein:

[0039] The symmetrical compensation subunit is used to perform symmetrical compensation processing on the correction flow curves in the cover body opening interval and the cover body closing interval to obtain two standard flow curves;

[0040] The similarity evaluation subunit is used to calculate point by point whether the flow difference between each sampling point of the two standard flow curves is within the set tolerance threshold range, and compare the ratio of the number of sampling points whose flow difference is within the set tolerance threshold range to the total number of sampling points with the standard similarity threshold to obtain a similarity evaluation result.

[0041] Furthermore, the symmetrical compensation processing of the correction flow curves in the cover opening interval and the cover closing interval includes:

[0042] Unifying the calibrated sampling data in the cover-open interval and the cover-closed interval under the same cumulative rainfall environment, obtaining a first standard flow curve in the cover-open interval and a second standard flow curve in the cover-closed interval;

[0043] Flip the second standard flow curve left and right;

[0044] Align the timestamps of the first standard flow curve and the second standard flow curve that has been flipped left and right, so that the last timestamp of the flipped second standard flow curve is consistent with the first timestamp of the first standard flow curve, and the first timestamp of the flipped second standard flow curve is consistent with the last timestamp of the first standard flow curve.

[0045] Compared with the existing technology, the beneficial effect of the present invention is that by introducing five modules, namely multi-source environmental monitoring, precise opening and closing control, sampling data correction, anomaly discrimination and feedback response, the whole process of precipitation isotope sample collection can be intelligently managed; the cover opening and closing speed calculation mechanism driven by wind direction and meteorological data can significantly reduce the risk of action; the synchronization of chromaticity and flow curves and the authenticity of physical response can be improved through time sequence unification and hysteresis correction; the peak analysis algorithm combining sliding window extreme value recognition and difference comparison can achieve accurate identification of filtrate mutations; the consistency and mechanical stability of the cover opening and closing action can be quantitatively evaluated through symmetry similarity analysis of the flow curves before and after sampling; and finally, the response module is triggered by the empirical characteristics of the sampling data to ensure that the system quickly alarms and intervenes in the event of a fault. This system can significantly improve the effectiveness and representativeness of precipitation samples, ensure data quality, and improve sampling reliability under extreme weather conditions. It is suitable for long-term precipitation isotope collection scenarios under various complex meteorological conditions.

[0046] Furthermore, through the coordinated operation of the wind direction capture subunit and the wind speed measurement subunit, high-frequency and accurate acquisition of wind direction and wind speed characteristics within the unit pre-detection period can be achieved, effectively improving the response capability to the influence of precipitation direction and wind disturbance under complex meteorological conditions; the opening and closing speed is calculated by combining the average wind direction angle and the median wind speed, which can avoid malfunction of the cover caused by wind deviation interference, ensure that the sampling behavior is stably executed within the wind speed disturbance tolerance range, and improve the representativeness and reliability of the sampling data.

[0047] Furthermore, through unified time axis interpolation alignment and forward compensation correction based on the filter layer response characteristics, the timing synchronization of sampling data from different sources and the compensation of physical hysteresis effects are achieved, which can accurately reconstruct the dynamic response process of chromaticity and flow, effectively avoid abnormal misjudgments caused by data time dislocation or filter membrane delay, and significantly improve the accuracy of sampling data and analysis stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic diagram of the structure of an intelligent collection system for precipitation isotope samples according to an embodiment of the present invention;

[0049] Figure 2 This is a connection diagram of a sampling device control module according to an embodiment of the present invention;

[0050] Figure 3 This is a connection diagram of a sampling data verification module according to an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of the structure of an intelligent collection device for precipitation isotope samples according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below with reference to embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0054] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0055] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0056] See also Figure 1 As shown, it is a structural diagram of an intelligent collection system for precipitation isotope samples according to an embodiment of the present invention. The present invention provides an intelligent collection system for precipitation isotope samples, comprising:

[0057] Environmental monitoring module, which is used to obtain wind direction data and meteorological data in the area where precipitation sampling equipment is deployed during each unit pre-detection cycle;

[0058] a sampling device control module connected to the environmental monitoring module, configured to calculate the cover opening and closing speeds based on environmental parameters and execute corresponding opening and closing actions to collect precipitation samples;

[0059] A sampling data acquisition module, which is connected to the sampling device control module and is used to collect sampling data of precipitation samples, including color detection data and flow data;

[0060] A sampling data verification module, connected to the sampling data acquisition module, is used to perform time sequence unification and hysteresis correction on the sampling data, construct a numerical response curve of chromaticity and flow rate, and compare and analyze the peak value of the chromaticity mutation point and evaluate the symmetry similarity of the flow rate curve within the lid opening and closing interval to verify whether there are any anomalies in the sampling data;

[0061] The autonomous response module is connected to the sampling device control module, the sampling data acquisition module and the sampling data verification module respectively, and is used to issue an alarm when a fault corresponding to each abnormal sampling data is obtained and send the alarm to the monitoring main control end.

[0062] In this embodiment, the environmental monitoring module is used to obtain wind direction data and meteorological data in the precipitation sampling device deployment area during the unit pre-detection period, which includes:

[0063] The raindrop infrared sensor plate uses a raindrop detection device with an infrared light curtain structure and is installed on the side of the sampling system at an angle of 40° to the horizontal plane;

[0064] Ultrasonic wind direction and anemometer: Use an ultrasonic wind direction and anemometer without mechanical parts, with a wind speed detection range of 0 to 30 m / s and a wind direction resolution of 1°. Install it at the highest point of the support pole at the top of the system, and the installation height should be greater than or equal to 1.5 m.

[0065] The sampling device control module includes a cover body, which is a rotating opening and closing structure driven by a servo motor and is arranged on the upper part of the sampling device to receive control instructions to open and close the sampling port;

[0066] The control logic is calculated by the system's built-in control circuit based on the parameters provided by the environmental monitoring module.

[0067] The sampling data acquisition module is used to collect precipitation samples and detect color and flow parameters, including:

[0068] Rain gauge collection tube, the shell is made of polycarbonate material, the top opening diameter is 200mm, used to collect natural precipitation, and is fixed vertically on the upper part of the device;

[0069] The rain collection funnel is located below the rain collection tube and is made of polytetrafluoroethylene. The cone collects rainwater and directly introduces it into the water storage device. The top of the funnel is equipped with a multi-layer filter structure, including a 200μm primary filter layer and a 50μm fine filter layer to intercept particulate impurities.

[0070] The water storage device, located below the rainfall collection funnel, uses a 500 mL glass bottle equipped with a silicone seal stopper to store filtered precipitation samples for subsequent stability analysis or laboratory testing;

[0071] A micro flow meter is installed in the passage between the bottom of the rainfall collection funnel and the water storage device to collect flow data of filtered precipitation samples. The flow detection range is 0~200mL / min, and the error is no more than ±1mL / min.

[0072] The colorimetric sensor is located on the side of the water storage device and adopts a 16-bit photosensitive array structure. The detection point is the precipitation sample inside the water storage device to synchronously obtain the filtrate colorimetric information.

[0073] By introducing five modules—multi-source environmental monitoring, precise opening and closing control, sampling data correction, anomaly identification, and feedback response—the system achieves intelligent management of the entire precipitation isotope sampling process. Through a wind direction and meteorological data-driven lid opening and closing speed calculation mechanism, the system improves the synchronization of chromaticity and flow curves and the authenticity of physical responses through timing unification and hysteresis correction. Accurately identify sudden changes in filtrate through a peak analysis algorithm that combines sliding window extreme value recognition with difference comparison. Through symmetry similarity analysis of flow curves before and after sampling, the consistency and mechanical stability of lid opening and closing actions are quantitatively evaluated. Finally, the empirical characteristics of the sampling data trigger the response module, ensuring rapid alarm and intervention in the event of a fault. This system can significantly improve the effectiveness and representativeness of precipitation samples, ensure data quality, and enhance sampling reliability in extreme weather conditions. It is suitable for long-term precipitation isotope collection scenarios under a variety of complex meteorological conditions.

[0074] Specifically, the environmental monitoring module includes a wind parameter capture unit and a weather data acquisition unit, wherein:

[0075] The wind parameter capture unit is used to obtain wind direction data within the deployment area of the precipitation sampling equipment, including the average wind direction angle and median wind speed;

[0076] The weather data acquisition unit is used to collect meteorological data in the area where the precipitation sampling equipment is deployed, including precipitation probability and precipitation intensity.

[0077] Specifically, the wind parameter capturing unit includes a wind direction capturing subunit and a wind speed measuring subunit, wherein:

[0078] The wind direction capturing subunit is used to obtain the average wind direction angle within the precipitation sampling device deployment area within a unit pre-detection period;

[0079] The wind speed calculation subunit is used to obtain the median wind speed of the wind speed change value within a unit pre-detection period.

[0080] In this embodiment, the wind direction capture subunit is a GillWindSonic2 ultrasonic wind direction sensor, which has 360° omnidirectional detection capability, a response time of no more than 0.25s, a resolution better than 1°, and rain and snow resistance and self-cleaning capabilities;

[0081] The wind direction sensor is installed on the main pole at the top of the system, with a fixed height of 2.8m;

[0082] The wind direction capture subunit collects the original wind direction data within the unit pre-detection period at a frequency of 10 Hz, and performs arithmetic averaging on all the original wind direction data within the interval to obtain the average wind direction angle of the current period;

[0083] The wind speed calculation subunit shares the wind speed output channel of the ultrasonic wind speed sensor. It collects the wind speed sequence within the unit pre-detection period and filters out the instantaneous abnormal wind speed interference through the median algorithm to obtain the median wind speed within the period as the wind speed representative.

[0084] Through the coordinated operation of the wind direction capture subunit and the wind speed measurement subunit, high-frequency and accurate acquisition of wind direction and wind speed characteristics within the unit pre-detection period is achieved, effectively improving the response capability to the influence of precipitation direction and wind disturbance under complex meteorological conditions; the opening and closing speeds are calculated by combining the average wind direction angle and the median wind speed to ensure that the sampling behavior is stably executed within the wind speed disturbance tolerance range, thereby improving the representativeness and reliability of the sampling data.

[0085] See Figure 2 As shown, it is a connection diagram of the sampling device control module according to an embodiment of the present invention;

[0086] Specifically, the sampling device control module includes a cover opening and closing speed calculation unit and a cover opening and closing execution unit, wherein:

[0087] The cover opening and closing speed calculation unit is used to calculate the ideal opening and closing speed of the cover within the collection period based on the wind direction data and the meteorological data;

[0088] The cover opening and closing execution unit is used to take the ideal opening and closing speed as the actual opening and closing speed, and open or close the cover at the actual opening and closing speed.

[0089] In this embodiment, the calculation formula of the cover opening and closing speed calculation unit is:

[0090]

[0091] in, The ideal opening and closing speed of the cover;

[0092] is the real-time wind direction;

[0093] The reference wind direction for the sampler is set to due south by default;

[0094] is the real-time wind speed;

[0095] The maximum allowable wind speed set for the system is 15m / s;

[0096] The probability of precipitation is obtained from the weather forecast, ranging from 0 to 100%, and is used to assess whether there is a possibility of precipitation occurring at the moment;

[0097] To express the forecasted precipitation intensity, combined with the probability of precipitation;

[0098] 、 as well as is the experience weighting coefficient, satisfying ,Pick , , ;

[0099] The above calculation results will be transmitted to the cover opening and closing execution unit as the opening and closing instruction speed parameter;

[0100] The cover opening and closing actuator is composed of an electric push rod drive mechanism. The push rod model is LINAK LA36, with a stroke of 300mm, a rated thrust of 500N, and supports PWM speed control.

[0101] The cover opening and closing execution unit controls the opening and closing speed through the PWM duty cycle output by the central control unit, and is equipped with a position encoder to feedback the current displacement state;

[0102] During execution, the central control unit generates a PWM signal based on the target speed and controls the push rod motor to complete the opening and closing action at a specified rate.

[0103] Through the coordinated design of the cover opening and closing speed calculation unit and the execution unit in the sampling equipment control module, the cover opening and closing speed can be dynamically adjusted under different wind direction and wind speed conditions, realizing response regulation that is highly matched with the meteorological environment; a multi-factor weighting model is used to comprehensively consider the wind participation precipitation parameters, combined with an adjustable speed electric push rod and a PWM fine control mechanism to improve the smoothness and accuracy of the cover movement process, and ensure interference with precipitation samples during the collection process.

[0104] See Figure 3 , which is a connection diagram of the sampling data verification module according to an embodiment of the present invention;

[0105] Specifically, the sampling data verification module includes a sampling data processing unit, a peak value analysis unit and an opening and closing symmetry analysis unit, wherein:

[0106] The sampling data processing unit is used to perform time sequence unification and hysteresis correction processing on the sampling data, and after obtaining each corrected sampling data, construct a numerical response curve of chromaticity and flow according to the time series;

[0107] The peak analysis unit is used to obtain a peak analysis result based on a comparison result of the obtained chroma detection difference value and a standard peak chroma detection difference threshold;

[0108] Among them, the chromaticity detection difference is the chromaticity detection difference between the chromaticity mutation point and the left and right adjacent sampling points;

[0109] The opening and closing symmetry analysis unit is used to perform symmetrical compensation processing on the correction flow curve within the opening and closing range of the cover body, and obtain a similarity evaluation result by comparing the point-by-point difference between the two standard flow curves with the tolerance threshold, thereby obtaining an opening and closing symmetry analysis result.

[0110] In this embodiment, the chromaticity mutation point is a point at which the chromaticity detection value changes significantly at a certain sampling moment during the sampling process, specifically, the chromaticity value of the point is significantly different from that of the adjacent sampling points on the left and right.

[0111] Among them, the chromaticity mutation point = the maximum difference point between the chromaticity value of the current sampling point and the chromaticity detection values of its two adjacent sampling points on the left and right, that is, the chromaticity detection difference = |C(i)-C(i-1)|+|C(i)-C(i+1|;

[0112] Where C(i) represents the chromaticity value of the i-th sampling point;

[0113] If the difference is greater than the average chroma detection difference threshold, the point is determined to be a chroma mutation point;

[0114] In this embodiment, the average chroma detection difference threshold is set to 2.0 CU, that is, 2 chroma measurement units.

[0115] Specifically, the sampling data processing unit includes a time parameter correction subunit and a curve fitting unit, wherein:

[0116] The time parameter correction subunit is used to perform time sequence uniform processing and hysteresis correction processing on each sampling data to obtain corresponding corrected sampling data;

[0117] The curve fitting unit is used to obtain each corrected sampling data, sort the chromaticity detection data and the flow detection data according to the timestamp, and then obtain the change curve of each corrected sampling data through smooth interpolation fitting.

[0118] Specifically, the time parameter correction subunit performs time sequence uniform processing and hysteresis correction processing on each sampling data, including:

[0119] Get the timestamp of each sampling data;

[0120] Establish a unified time axis and perform interpolation alignment on each sampling data;

[0121] The average response delay time of the filter layer water absorption process is obtained, and the sampling data is subjected to hysteresis correction processing based on the average response delay time to obtain corrected sampling data.

[0122] In this embodiment, the system extracts the timestamp of each data point from the micro flow meter and the colorimetric sensor, with a unit accuracy of 1s;

[0123] Set the current detection period to 10 minutes. Within the current detection period, establish a unified time axis with a step size of 1 second, for a total of 300 time points.

[0124] The following interpolation formula is used:

[0125]

[0126] in, ,x is the corresponding detection value, i.e., sampling data;

[0127] At the target time The interpolation result on ;

[0128] Linear interpolation is performed on the flow data and chromaticity data respectively, and the sampling points at different time intervals are mapped to the unified time axis;

[0129] After completing the interpolation alignment, apply the hysteresis correction function to compensate the forward time. The formula is:

[0130]

[0131] in, is the sample data after interpolation alignment;

[0132] is the average response delay time of the filter layer water absorption process;

[0133] is the sampling data after hysteresis correction, that is, the corrected sampling data.

[0134] Through unified time axis interpolation alignment and forward compensation correction based on filter layer response characteristics, the timing synchronization of sampling data from different sources and compensation for physical hysteresis effects are achieved. The dynamic response process of chromaticity and flow can be accurately reconstructed, effectively avoiding abnormal misjudgments caused by data time misalignment or filter membrane delay, and significantly improving the accuracy of sampling data and analysis stability.

[0135] Specifically, the peak analysis unit includes an image disturbance extraction subunit, a peak threshold comparison subunit, and a flow exclusion subunit, wherein:

[0136] The image disturbance extraction subunit is used to divide the unit positive detection period into a number of sub-periods, and extract the chromaticity mutation points corresponding to the local maximum values of the correction chromaticity detection data change curve in each sub-period as the points to be compared;

[0137] The peak threshold comparison subunit is used to calculate the chroma detection value at any point to be compared and the two chroma detection differences of adjacent sampling points, and compare the two chroma detection differences with the standard peak chroma detection difference threshold to obtain the peak threshold comparison result;

[0138] The two chromaticity detection differences include a left chromaticity detection difference between the chromaticity detection value at the point to be compared and the left adjacent sampling point, and a right chromaticity detection difference between the chromaticity detection value at the point to be compared and the right adjacent sampling point.

[0139] The flow exclusion subunit is used to exclude the funnel filter layer rupture fault through flow verification when the first peak threshold comparison result is obtained.

[0140] In this embodiment, the system sets the unit positive detection cycle to 640 seconds, the non-cover opening and closing time to 600 seconds, and divides the cycle into 6 sub-cycles, each sub-cycle is 100 seconds long;

[0141] In each sub-period, the sampled data is time-series unified and hysteresis-corrected to construct a corrected chromaticity detection data curve. The image disturbance extraction sub-unit extracts the local maximum points in each sub-period using a sliding window local extreme value detection algorithm.

[0142] The sliding window is set to 5 seconds, that is, every 5 consecutive sampling points are grouped as a group for sliding processing;

[0143] The maximum value judgment condition is:

[0144] If the chromaticity value of a certain point is corrected satisfy and , then the point is marked as a local maximum;

[0145] Identify the corrected chromaticity mutation point After that, the peak threshold comparison subunit corrects the chromaticity value The sampling point on its left , right sampling point The difference calculation is performed respectively, where

[0146] The left direction corrected chromaticity difference is

[0147] The chromaticity difference corrected in the right direction is

[0148] Take the standard peak chromaticity detection difference threshold as δ=12 AU (absorbance unit), and compare the left direction corrected chromaticity difference and the right direction corrected chromaticity difference with the standard peak chromaticity detection difference threshold respectively.

[0149] If the corrected chromaticity difference in any direction is greater than the standard peak chromaticity detection difference threshold, and the first peak threshold comparison result is obtained, then the corrected chromaticity mutation point is abnormal, and the filtrate turbidity exceeds the standard. Further flow calibration is performed to rule out the funnel filter layer rupture fault;

[0150] Obtain the corrected flow rate value and determine the standard flow rate interval as [60,80] based on the properties of the filter layer, in mL / min;

[0151] Compare the corrected flow value with the standard flow range.

[0152] If the corrected flow rate value is greater than or equal to the maximum value of the standard flow rate range, the funnel filter layer has structural ruptures, and rainwater flows directly into the sample bottle without being fully filtered. This is a chromaticity increase caused by insufficient filtration.

[0153] If the corrected flow rate value is within the closed range of the standard flow rate interval, the funnel filter layer has no faults and further analysis of the opening and closing symmetry is conducted;

[0154] If the corrected flow rate value is less than or equal to the minimum value of the standard flow rate range, the pores of the funnel filter layer are blocked, and rainwater retention causes the sample to be soaked for a long time, which is a chromaticity increase caused by liquid accumulation;

[0155] If the corrected chromaticity differences in each direction are less than or equal to the standard peak chromaticity detection difference threshold, and the second peak threshold comparison result is obtained, then the chromaticity mutation point mutation is normal, the filtrate turbidity does not exceed the standard, and the opening and closing symmetry is further analyzed.

[0156] By dividing a unit positive detection cycle into several sub-cycles and combining a sliding window maximum value recognition strategy with a difference threshold comparison strategy, high-precision identification of localized sudden changes in chromaticity is achieved. This mechanism can promptly distinguish abnormal chromaticity changes caused by filter blockage, damage, or short-term contamination from normal background disturbances, effectively avoiding false positives and missed detections. The system uses significant sudden change points as key judgment criteria, triggering abnormal responses or transitioning to the next analysis step, significantly improving the sensitivity of filtrate quality anomaly identification and the rationality of the decision-making process.

[0157] Specifically, the opening and closing symmetry analysis unit includes a symmetry compensation subunit and a similarity evaluation subunit, wherein:

[0158] The symmetrical compensation subunit is used to perform symmetrical compensation processing on the correction flow curves in the cover body opening interval and the cover body closing interval to obtain two standard flow curves;

[0159] The similarity evaluation subunit is used to calculate point by point whether the flow difference between each sampling point of the two standard flow curves is within the set tolerance threshold range, and compare the ratio of the number of sampling points whose flow difference is within the set tolerance threshold range to the total number of sampling points with the standard similarity threshold to obtain a similarity evaluation result.

[0160] In this embodiment, the system compares the flow values at corresponding time points one by one based on the aligned first standard flow curve and the second standard flow curve, and calculates their absolute difference;

[0161] The tolerance threshold ε is set to 1.5 mL / min, which is calibrated through long-term actual measurement;

[0162] There are N = 40 sampling points in the two aligned curves;

[0163] Calculate the flow difference between each sampling point of the two standard flow curves point by point, that is, ;

[0164] Get The number of sampling points n is used to calculate the similarity ratio. The formula is:

[0165]

[0166] in, and are the flow values of the opening and closing intervals at the i-th moment respectively;

[0167] Take the standard similarity threshold as 0.85, and compare the similarity ratio with the standard similarity threshold.

[0168] If the similarity ratio is greater than the standard similarity threshold, a first similarity evaluation result is obtained, that is, the two standard flow curves are similar and there is no mechanical fault in the opening and closing of the cover;

[0169] If the similarity ratio is less than or equal to the standard similarity threshold, a second similarity evaluation result is obtained, that is, the two standard flow curves are not similar, and there is a mechanical failure in the opening and closing of the cover;

[0170] By comparing the similarity between the current opening and closing flow curve and the standard opening and closing flow curve preset by the system, the system can identify mechanical anomalies during the opening and closing process of the cover, and at the same time ensure the accurate execution of the sampling action.

[0171] By introducing the dual mechanisms of symmetrical compensation and similarity ratio, the ability to judge the consistency of the cover opening and closing behavior during the sampling stage is significantly enhanced; the point-by-point error evaluation combined with the tolerance threshold and similarity threshold criteria enables the system to accurately identify sampling flow response deviations caused by factors such as opening and closing mechanical jams and structural deformation, maintain the consistency of evaluation results under different precipitation intensities, and provide a quantitative basis for judging whether there are potential faults in the sampling mechanism.

[0172] Specifically, the symmetrical compensation processing of the correction flow curve in the cover opening interval and the cover closing interval includes:

[0173] Unifying the calibrated sampling data in the cover-open interval and the cover-closed interval under the same cumulative rainfall environment, obtaining a first standard flow curve in the cover-open interval and a second standard flow curve in the cover-closed interval;

[0174] Flip the second standard flow curve left and right;

[0175] Align the timestamps of the first standard flow curve and the second standard flow curve that has been flipped left and right, so that the last timestamp of the flipped second standard flow curve is consistent with the first timestamp of the first standard flow curve, and the first timestamp of the flipped second standard flow curve is consistent with the last timestamp of the first standard flow curve.

[0176] In this embodiment, the cover opening interval is the continuous time interval from the beginning of the sampler cover opening to the complete opening, from the cover completely covering the rainfall collection tube to the complete exposure to the natural environment;

[0177] The cover closing interval is the continuous time interval from the beginning of the sampler cover closing to the complete closing process, when the cover is completely exposed to the natural environment and the rain gauge collection tube is completely blocked;

[0178] During the detection period, the sampling data within the cover opening interval (0-20 seconds) and the cover closing interval (600-640 seconds) are identified;

[0179] In order to eliminate the sampling amplitude deviation caused by the difference in rainfall intensity between the two intervals, the system normalizes the corrected flow value in the cover closed interval to the corrected flow value in the cover open interval. The calculation formula is:

[0180]

[0181] in, Normalized flow value of the closed interval of the cover;

[0182] is the corrected flow value within the cover closed interval;

[0183] It is the minimum value of the corrected flow value within the cover closed interval;

[0184] It is the maximum value of the calibrated flow rate within the closed interval of the cover;

[0185] It is the minimum value of the calibrated flow rate within the cover opening interval;

[0186] It is the maximum value of the calibrated flow value within the cover opening interval;

[0187] The left-right flipping process is to mirror-flip the normalized flow curve of the closed interval of the cover along the time axis, so that the time series in the closed interval is in the opposite order to that in the open interval;

[0188] Adjust the timestamp of the closed interval after flipping so that its start and end times correspond to the start and end times of the open interval respectively, so as to achieve complete overlap of the two standard flow curves on the time axis, that is, align the timestamps of the first standard flow curve and the second standard flow curve that has been flipped left and right, so that the last timestamp of the flipped second standard flow curve is consistent with the first timestamp of the first standard flow curve, and the first timestamp of the flipped second standard flow curve is consistent with the last timestamp of the first standard flow curve.

[0189] By unifying the corrected flow data of the opening and closing intervals to the same cumulative rainfall environment and normalizing and mirror-flipping the curve of the cover closing interval, the interference of rainfall intensity changes on the flow curve shape can be effectively eliminated, ensuring the comparability of the data of the two opening and closing intervals; and then through the timestamp alignment operation, the symmetry analysis is completed based on point-to-point comparison with strict time axis matching, which helps to accurately evaluate the response consistency and mechanical stability of the sampling system during the execution of the opening and closing action, and improve the accuracy and reliability of anomaly detection.

[0190] See Figure 4 , which is a schematic structural diagram of an intelligent precipitation isotope sample collection device according to an embodiment of the present invention. The present invention further provides an intelligent precipitation isotope sample collection device for use in the intelligent precipitation isotope sample collection system according to this embodiment, comprising an environmental monitoring module 1, a raindrop infrared sensor plate 101, an ultrasonic wind direction and anemometer 102 (not shown in the figure), a cover 2, a sampling data acquisition module 3, a rainfall collection tube 301, a rainfall collection funnel 302, a water storage device 303, a micro flowmeter 304, a colorimetric sensor 305, and a control mechanism (not shown in the figure), wherein:

[0191] Environmental monitoring module 1, including a raindrop infrared sensor plate arranged outside the collection device for collecting meteorological data and an ultrasonic wind direction and anemometer arranged outside the collection device for collecting wind direction data;

[0192] The cover 2 is provided on the upper part of the sampling device and is used to receive control instructions to open and close the sampling port;

[0193] A rain collection tube 301 is provided inside the collection device to collect precipitation samples;

[0194] A rain collection funnel 302 is provided below the rain collection tube 301 and is used to filter the collected precipitation samples;

[0195] A water storage device 303 is provided below the rainfall collection funnel 302 to store filtered precipitation samples;

[0196] A micro flow meter 304 is provided below the rainfall collection funnel 302 to collect flow data of the filtered precipitation sample;

[0197] a chromaticity sensor 305 , which is disposed on the side of the water storage device 303 and is used to collect chromaticity detection data of the filtered precipitation sample;

[0198] The control mechanism is connected to the environmental monitoring module 1, the sampling device control module 2 and the sampling data acquisition module 3 respectively, and is used to control each component to collect precipitation samples.

[0199] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0200] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An intelligent collection system for precipitation isotope samples, characterized in that: include, Environmental monitoring module, which is used to obtain wind direction data and meteorological data in the area where precipitation sampling equipment is deployed during each unit pre-detection cycle; a sampling device control module connected to the environmental monitoring module, configured to calculate the cover opening and closing speeds based on environmental parameters and execute corresponding opening and closing actions to collect precipitation samples; A sampling data acquisition module, which is connected to the sampling device control module and is used to collect sampling data of precipitation samples, including color detection data and flow data; A sampling data verification module, connected to the sampling data acquisition module, is used to perform time sequence unification and hysteresis correction on the sampling data, construct a numerical response curve of chromaticity and flow rate, and compare and analyze the peak value of the chromaticity mutation point and evaluate the symmetry similarity of the flow rate curve within the lid opening and closing interval to verify whether there are any anomalies in the sampling data; The autonomous response module is connected to the sampling device control module, the sampling data acquisition module and the sampling data verification module respectively, and is used to issue an alarm when a fault corresponding to each abnormal sampling data is obtained and send the alarm to the monitoring main control end.

2. The intelligent collection system for precipitation isotope samples according to claim 1, characterized in that: The environmental monitoring module includes a wind parameter capture unit and a weather data acquisition unit, wherein: The wind parameter capture unit is used to obtain wind direction data within the deployment area of the precipitation sampling equipment, including the average wind direction angle and median wind speed; The weather data acquisition unit is used to collect meteorological data in the area where the precipitation sampling equipment is deployed, including precipitation probability and precipitation intensity.

3. The intelligent collection system for precipitation isotope samples according to claim 2, characterized in that: The wind parameter capturing unit includes a wind direction capturing subunit and a wind speed measuring subunit, wherein: The wind direction capturing subunit is used to obtain the average wind direction angle within the precipitation sampling device deployment area within a unit pre-detection period; The wind speed calculation subunit is used to obtain the median wind speed of the wind speed change value within a unit pre-detection period.

4. The intelligent collection system for precipitation isotope samples according to claim 1, characterized in that: The sampling device control module includes a cover opening and closing speed calculation unit and a cover opening and closing execution unit, wherein: The cover opening and closing speed calculation unit is used to calculate the ideal opening and closing speed of the cover within the collection period based on the wind direction data and the meteorological data; The cover opening and closing execution unit is used to take the ideal opening and closing speed as the actual opening and closing speed, and open or close the cover at the actual opening and closing speed.

5. The intelligent collection system for precipitation isotope samples according to claim 1, characterized in that: The sampling data verification module includes a sampling data processing unit, a peak value analysis unit and an opening and closing symmetry analysis unit, wherein: The sampling data processing unit is used to perform time sequence unification and hysteresis correction processing on the sampling data, and after obtaining each corrected sampling data, construct a numerical response curve of chromaticity and flow according to the time series; The peak analysis unit is used to obtain a peak analysis result based on a comparison result of the obtained chroma detection difference value and a standard peak chroma detection difference threshold; Among them, the chromaticity detection difference is the chromaticity detection difference between the chromaticity mutation point and the left and right adjacent sampling points; The opening and closing symmetry analysis unit is used to perform symmetrical compensation processing on the correction flow curve within the opening and closing range of the cover body, and obtain a similarity evaluation result by comparing the point-by-point difference between the two standard flow curves with the tolerance threshold, thereby obtaining an opening and closing symmetry analysis result.

6. The intelligent collection system for precipitation isotope samples according to claim 5, characterized in that: The sampling data processing unit includes a time parameter correction subunit and a curve fitting unit, wherein: The time parameter correction subunit is used to perform time sequence uniform processing and hysteresis correction processing on each sampling data to obtain corresponding corrected sampling data; The curve fitting unit is used to obtain each corrected sampling data, sort the chromaticity detection data and the flow detection data according to the timestamp, and then obtain the change curve of each corrected sampling data through smooth interpolation fitting.

7. The intelligent collection system for precipitation isotope samples according to claim 6, characterized in that: The time parameter correction subunit performs time sequence uniform processing and hysteresis correction processing on each sampling data, including: Get the timestamp of each sampling data; Establish a unified time axis and perform interpolation alignment on each sampling data; The average response delay time of the filter layer water absorption process is obtained, and hysteresis correction processing is performed based on the average response delay time to obtain corrected sampling data.

8. The intelligent collection system for precipitation isotope samples according to claim 5, characterized in that: The peak analysis unit includes an image disturbance extraction subunit, a peak threshold comparison subunit and a flow exclusion subunit, wherein: The image disturbance extraction subunit is used to divide the unit positive detection period into a number of sub-periods, and extract the chromaticity mutation points corresponding to the local maximum values of the correction chromaticity detection data change curve in each sub-period as the points to be compared; The peak threshold comparison subunit is used to calculate the chroma detection value at any point to be compared and the two chroma detection differences of adjacent sampling points, and compare the two chroma detection differences with the standard peak chroma detection difference threshold to obtain the peak threshold comparison result; The two chromaticity detection differences include a left chromaticity detection difference between the chromaticity detection value at the point to be compared and the left adjacent sampling point, and a right chromaticity detection difference between the chromaticity detection value at the point to be compared and the right adjacent sampling point. The flow exclusion subunit is used to exclude the funnel filter layer rupture fault through flow verification when the first peak threshold comparison result is obtained.

9. The intelligent collection system for precipitation isotope samples according to claim 5, characterized in that: The opening and closing symmetry analysis unit includes a symmetry compensation subunit and a similarity evaluation subunit, wherein: The symmetrical compensation subunit is used to perform symmetrical compensation processing on the correction flow curves in the cover body opening interval and the cover body closing interval to obtain two standard flow curves; The similarity evaluation subunit is used to calculate point by point whether the flow difference between each sampling point of the two standard flow curves is within the set tolerance threshold range, and compare the ratio of the number of sampling points whose flow difference is within the set tolerance threshold range to the total number of sampling points with the standard similarity threshold to obtain a similarity evaluation result.

10. The intelligent collection system for precipitation isotope samples according to claim 9, characterized in that: The symmetrical compensation processing of the correction flow curves in the cover opening interval and the cover closing interval includes: Unifying the calibrated sampling data in the cover-open interval and the cover-closed interval under the same cumulative rainfall environment, obtaining a first standard flow curve in the cover-open interval and a second standard flow curve in the cover-closed interval; Flip the second standard flow curve left and right; Align the timestamps of the first standard flow curve and the second standard flow curve that has been flipped left and right, so that the last timestamp of the flipped second standard flow curve is consistent with the first timestamp of the first standard flow curve, and the first timestamp of the flipped second standard flow curve is consistent with the last timestamp of the first standard flow curve.

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