Filtering and extracting method for detecting metal elements in water

Abstract

The invention discloses a filtering and extracting method for water quality metal element detection, relates to the technical field of water sample extraction, and judges whether an SPE (Solid Phase Extraction) system is abnormal or not by monitoring key characteristics of the SPE system in real time in a solid phase extraction process; if yes, the corresponding key features in the SPE system are adjusted immediately, and whether the SPE system can continue to be used for subsequent extraction or not is judged again; if yes, the water sample subjected to solid-phase extraction continues to be subjected to metal element extraction in the subsequent step; if not, immediately stopping the solid-phase extraction process, giving an alarm, simultaneously switching to carry out manual solid-phase extraction on the water sample again, and continuing to carry out metal element extraction in the subsequent step; in the filtering and extracting application of actual water quality metal element detection, if the SPE system has a fault, the fault can be found and corrected in time, and the effective purification effect can be ensured, so that the influence on the accuracy and reliability of overall water quality monitoring is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of water sample extraction, and in particular to a filtering and extraction method for detecting metal elements in water quality. Background Art

[0002] In water quality monitoring, the detection of metal elements is of great significance for the assessment of environmental pollution. Because the concentration of metal elements in water is typically low and water samples often contain a large amount of impurities, direct detection faces problems such as poor sensitivity and severe interference. Therefore, the use of filtration extraction methods to improve detection accuracy has become a standard pretreatment step. This method first uses a microporous filter membrane for filtration pretreatment to remove large particulate impurities in the water. Subsequently, solid-phase extraction (SPE) technology is used to enrich the target metal ions in the water using selective adsorbents (such as chelating resins). Finally, the adsorbed metal ions are eluted and concentrated using an eluent to facilitate subsequent quantitative detection. This method has significant advantages in trace metal detection, effectively improving the enrichment efficiency of metal ions and reducing background interference, thereby significantly improving detection sensitivity.

[0003] While solid-phase extraction (SPE) technology is widely used in water metal element testing, its stability and reliability remain key factors affecting detection effectiveness. In practice, if an SPE system malfunctions and is not promptly detected and corrected, purification effectiveness can be significantly reduced. The lack of real-time monitoring and fault warning mechanisms can prevent these issues from being detected in a timely manner, impacting the accuracy and reliability of overall water quality monitoring. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide a filtration and extraction method for detecting metal elements in water quality.

[0005] The present invention proposes a filtration and extraction method for detecting metal elements in water, the method comprising: Multiple sensor modules are set up to monitor the key characteristics of the SPE system that affect the solid phase extraction process in real time, and determine whether the SPE system is abnormal based on the key characteristics; If an abnormality occurs in the SPE system, the corresponding key features in the SPE system are immediately adjusted, and based on the adjusted key features, it is determined whether the SPE system can continue to be used for subsequent extractions; If possible, the water sample after solid phase extraction will continue to the subsequent step of metal element extraction; If not, the solid phase extraction process will be stopped immediately and an alarm will be issued. At the same time, the water sample will be manually re-extracted for solid phase extraction, and the water sample after manual solid phase extraction will be used to continue the subsequent steps of metal element extraction.

[0006] Optionally, the steps of real-time monitoring of key characteristics of the SPE system that affect the solid phase extraction process and determining whether the SPE system is abnormal based on the key characteristics are: By setting up a micro flow sensor to monitor the flow rate of the liquid through the SPE column in real time, and calculating the flow rate abnormality coefficient based on the flow rate, the SPE column flow rate of the SPE system is analyzed to see if it is abnormal; By setting up a pressure sensor to monitor the working pressure of the SPE system in real time, and calculating the pressure abnormality coefficient based on the working pressure, it is analyzed whether the pressure of the SPE system is abnormal; By setting up temperature and humidity sensors to monitor the temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process in real time, the temperature and humidity anomaly coefficient is calculated; and the temperature and humidity of the environment in which the SPE system is located is analyzed to see if it is abnormal. Whether the SPE system is abnormal is determined based on the flow rate abnormality coefficient, pressure abnormality coefficient, and temperature and humidity abnormality coefficient.

[0007] Optionally, the calculation steps of the flow velocity anomaly coefficient are: The flow rate of the SPE column in the SPE system during solid phase extraction is monitored in real time by a micro flow sensor to obtain a flow rate sequence based on time sequence; The initial fluctuation coefficient is obtained by adding the standard deviation and mean of the velocity series and dividing the standard deviation by the mean; Perform linear regression on the flow rate series to extract the trend slope of the flow rate change, compare the absolute value of the slope with the preset standard slope, calculate the difference between the absolute value of the slope and the preset standard slope, and divide the difference by the preset standard slope to obtain the flow rate trend anomaly coefficient; The velocity anomaly coefficient is obtained by weighted summing the initial fluctuation coefficient and the velocity trend anomaly coefficient.

[0008] Optionally, the calculation steps of the pressure anomaly coefficient are: The working pressure of the SPE system is monitored in real time by a pressure sensor to obtain a pressure sequence based on time sequence; Compare the pressure in the pressure sequence with the preset standard pressure range of the SPE system during operation. If the pressure is not within the preset standard pressure range of the SPE system during operation, the corresponding pressure in the pressure sequence is recorded as abnormal pressure. The pressure anomaly coefficient is obtained by dividing the total number of abnormal pressures in the pressure sequence by the total number of pressures in the pressure sequence.

[0009] Optionally, the steps for calculating the temperature and humidity anomaly coefficient are: The temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process are monitored in real time by a temperature and humidity sensor, and the time during which the temperature and humidity are within the preset standard temperature and humidity range is integrated to obtain the temperature anomaly and humidity anomaly of the environment in which the SPE system is located during the solid phase extraction process respectively; The temperature and humidity anomaly coefficients are obtained by weighted summing of the temperature anomaly and the humidity anomaly.

[0010] Optionally, the steps of determining whether an abnormality occurs in the SPE system according to the flow rate abnormality coefficient, the pressure abnormality coefficient, and the temperature and humidity abnormality coefficient are as follows: Comparing the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient with the preset flow rate anomaly coefficient threshold, the preset pressure anomaly coefficient threshold, and the preset temperature and humidity anomaly coefficient threshold, respectively; If the flow rate abnormality coefficient is not less than the preset flow rate abnormality coefficient threshold, or the pressure abnormality coefficient is not less than the preset pressure abnormality coefficient threshold, or the temperature and humidity abnormality coefficient is not less than the preset temperature and humidity abnormality coefficient threshold, the SPE system is immediately judged to be abnormal, an alarm is issued, and the flow rate, pressure and ambient temperature and humidity of the SPE system are immediately adjusted; If the flow rate anomaly coefficient is less than the preset flow rate anomaly coefficient threshold, the pressure anomaly coefficient is less than the preset pressure anomaly coefficient threshold, and the temperature and humidity anomaly coefficient is less than the preset temperature and humidity anomaly coefficient threshold, the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient are weighted and summed to obtain an anomaly value; Compare the abnormal value with the preset abnormal value threshold. If the abnormal value is not less than the preset abnormal value threshold, immediately adjust the flow rate, pressure and ambient temperature and humidity of the SPE system; If the outlier value is less than the preset outlier value threshold, there is no need to adjust the flow rate, pressure, and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample.

[0011] Optionally, the steps of determining whether the SPE system can continue to be used for subsequent extraction based on the adjusted key characteristics are: Calculate the flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient of the adjusted SPE system. If the adjusted flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient are all less than the corresponding preset thresholds, and the anomaly values ​​are less than the preset anomaly value thresholds, then there is no need to adjust the corresponding flow rate, pressure and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample; if not, immediately stop the solid phase extraction process, issue an alarm, and switch to manual solid phase extraction of the water sample again, and continue the metal element extraction steps of the water sample after manual solid phase extraction.

[0012] Beneficial effects of the present invention: The present invention proposes a filtration and extraction method for detecting metal elements in water quality. By setting multiple sensor modules, key features of an SPE system that affect a solid phase extraction process are monitored in real time, and whether the SPE system is abnormal is determined based on the key features. If the SPE system is abnormal, the corresponding key features in the SPE system are immediately adjusted, and whether the SPE system can continue to be used for subsequent extraction is determined based on the adjusted key features. If it can, the water sample after solid phase extraction is used to continue the metal element extraction in the subsequent step. If it cannot, the solid phase extraction process is immediately stopped, an alarm is issued, and manual solid phase extraction is performed on the water sample again, and the water sample after manual solid phase extraction is used to continue the metal element extraction in the subsequent step. In this way, in actual filtration and extraction applications for detecting metal elements in water quality, if a fault occurs in the SPE system, it can be discovered and corrected in time, thereby ensuring an effective purification effect. This real-time monitoring and fault warning mechanism can enable the above-mentioned problem to be discovered in time, thereby reducing the impact on the accuracy and reliability of overall water quality monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention will be further described below with reference to the accompanying drawings.

[0014] Figure 1 The present invention is a flow chart of a filtration and extraction method for detecting metal elements in water quality. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0017] The embodiment of the present invention provides a filtration and extraction method for detecting metal elements in water. Figure 1 , Figure 1 This is a flow chart of a filtration and extraction method for detecting metal elements in water provided by an embodiment of the present invention. The method includes the following steps: Multiple sensor modules are set up to monitor the key characteristics of the SPE system that affect the solid phase extraction process in real time, and determine whether the SPE system is abnormal based on the key characteristics; If an abnormality occurs in the SPE system, the corresponding key features in the SPE system are immediately adjusted, and based on the adjusted key features, it is determined whether the SPE system can continue to be used for subsequent extractions; If possible, the water sample after solid phase extraction will continue to the subsequent step of metal element extraction; If not, the solid phase extraction process will be stopped immediately and an alarm will be issued. At the same time, the water sample will be manually re-extracted for solid phase extraction, and the water sample after manual solid phase extraction will be used to continue the subsequent steps of metal element extraction.

[0018] Based on the filtration and extraction method for metal element detection in water quality provided by an embodiment of the present invention, through the above-mentioned method, in actual filtration and extraction applications for metal element detection in water quality, if a failure occurs in the SPE system, it can be discovered and corrected in a timely manner, thereby ensuring the effectiveness of the purification effect. This real-time monitoring and fault warning mechanism can enable the above-mentioned problems to be discovered in a timely manner, thereby reducing the impact on the accuracy and reliability of the overall water quality monitoring.

[0019] It should be noted that the filtration extraction method used for metal element testing in water generally includes four main steps: filtration pretreatment, metal ion enrichment, elution and concentration, and subsequent testing. The specific process is as follows: First, the collected water sample is filtered through a microporous membrane to remove large impurities such as suspended matter and sediment, minimizing interference with subsequent operations. Next, the filtered water sample is introduced into a solid-phase extraction column filled with a material with selective adsorption for metal ions, such as a chelating resin or functionalized silica gel. As the water sample passes through the column, the target metal ions are adsorbed on the adsorbent surface. After adsorption, the metal ions are eluted from the adsorbent using an appropriate eluent (e.g., an acidic solution) and concentrated in the eluent, achieving concentration. Finally, the eluent is transferred to a subsequent analytical instrument (e.g., atomic absorption spectrometer (AAS) or inductively coupled plasma mass spectrometer (ICP-MS)) for quantitative detection. This process features clear steps, relatively simple operation, and strong adaptability. It is particularly suitable for the extraction and analysis of trace metal ions and has been widely used in fields such as environmental monitoring and drinking water safety assessment.

[0020] It should be noted that an SPE system, or solid phase extraction system, is an automated or semi-automated device used for sample pretreatment. It primarily enriches and purifies target analytes through selective adsorption and elution. SPE systems play a crucial role in water quality metal element testing. Their core purpose is to selectively extract and concentrate target metal ions from complex water samples, thereby improving detection sensitivity and accuracy. Specifically, an SPE system typically consists of a sample introduction unit, a flow control device, a solid phase extraction column, and an elution collection unit. During system operation, a pretreated water sample is loaded into the extraction column. Metal ions selectively bind to an adsorbent (such as a chelating resin) within the column, while other non-target components are washed away. Subsequently, a specific eluent is added to release the metal ions from the adsorbent and collect them. This process not only effectively removes background impurities and reduces interference, but also allows metal elements, originally at very low concentrations, to be concentrated above the detection limit, thus meeting the requirements of subsequent instrumental analysis. Compared with the traditional liquid-liquid extraction method, the SPE system has the advantages of simple operation, low solvent consumption, and high degree of automation. It has become an indispensable key unit in the detection of heavy metals in water quality.

[0021] In one embodiment, multiple sensor modules are provided to monitor in real time the key characteristics of the SPE system that affect the solid phase extraction process, and to determine whether the SPE system is abnormal based on the key characteristics; Specifically, the steps for real-time monitoring of the key characteristics of the SPE system that affect the solid phase extraction process and determining whether the SPE system is abnormal based on the key characteristics are as follows: By setting up a micro flow sensor to monitor the flow rate of the liquid through the SPE column in real time, and calculating the flow rate abnormality coefficient based on the flow rate, the SPE column flow rate of the SPE system is analyzed to see if it is abnormal; By setting up a pressure sensor to monitor the working pressure of the SPE system in real time, and calculating the pressure abnormality coefficient based on the working pressure, it is analyzed whether the pressure of the SPE system is abnormal; By setting up temperature and humidity sensors to monitor the temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process in real time, the temperature and humidity anomaly coefficient is calculated; and the temperature and humidity of the environment in which the SPE system is located is analyzed to see if it is abnormal. Whether the SPE system is abnormal is determined based on the flow rate abnormality coefficient, pressure abnormality coefficient, and temperature and humidity abnormality coefficient.

[0022] It should be noted that to achieve real-time monitoring of the operating status and identify anomalies in the solid-phase extraction (SPE) system, multiple sensor modules are installed to collect key operating parameters and, based on these parameters, determine whether the system is in an abnormal state. Specifically, the method includes the following steps: First, by installing micro-flow sensors before and after the SPE column, the flow rate of the liquid flowing through the SPE column is monitored in real time. The collected real-time flow rate data is compared with a set standard flow rate range to calculate the flow rate anomaly coefficient, thereby determining whether the SPE column has blockage, leakage, or pump control anomalies. Second, a pressure sensor is configured to monitor the operating pressure of the SPE system. By comparing the actual pressure with the normal operating range, the pressure anomaly coefficient is calculated to identify whether the system is experiencing excessive pump load or abnormal changes in column resistance. Finally, a temperature and humidity sensor is used to record the temperature and humidity of the SPE system environment in real time. By comparing the temperature and humidity with the standard environmental values, the temperature and humidity anomaly coefficient is calculated to assess whether there is a risk of system instability caused by environmental changes (such as overheating and humidity). Finally, the above three abnormal coefficients are used as the basis for judgment. If one or more parameters exceed the preset threshold, the system will be judged as an abnormal state, thereby providing decision support for subsequent adjustment and processing.

[0023] Specifically, in one embodiment, the steps for calculating the flow rate anomaly coefficient are: The flow rate of the SPE column in the SPE system during solid phase extraction is monitored in real time by a micro flow sensor to obtain a flow rate sequence based on time sequence; The initial fluctuation coefficient is obtained by adding the standard deviation and mean of the velocity series and dividing the standard deviation by the mean; Perform linear regression on the flow rate series to extract the trend slope of the flow rate change, compare the absolute value of the slope with the preset standard slope, calculate the difference between the absolute value of the slope and the preset standard slope, and divide the difference by the preset standard slope to obtain the flow rate trend anomaly coefficient; The velocity anomaly coefficient is obtained by weighted summing the initial fluctuation coefficient and the velocity trend anomaly coefficient.

[0024] It should be noted that during the calculation of the flow anomaly coefficient, the required data is primarily acquired via microflow sensors installed at the inlet and outlet of the SPE system. These sensors collect instantaneous flow velocity data of the liquid flowing through the SPE column in real time with high temporal resolution (e.g., once per second or higher) and record this data in chronological order to form a flow velocity time series. The sensors are typically connected to a data acquisition module or embedded control system, transmitting the flow velocity data in real time to a host computer or local processing unit for subsequent statistical calculations and trend analysis. To ensure data accuracy and timeliness, the system can also incorporate data caching and outlier rejection mechanisms to perform preliminary processing on the collected raw flow velocity data, thereby providing high-quality, continuous input data for the calculation of the flow anomaly coefficient.

[0025] It should be noted that the flow rate anomaly coefficient is a quantitative indicator that comprehensively assesses the stability and trend of flow rates within an SPE column. It aims to reflect fluctuations and deviations from the expected flow rate trend during operation. A larger flow rate anomaly coefficient indicates more dramatic flow rate fluctuations or deviations from the expected stable state, which generally indicates an abnormality in the SPE system's operating status. This is because the flow rate in an SPE system has a significant impact on the adsorption and elution processes of metal ions. Excessively high or low flow rates can reduce the efficiency of metal ion enrichment and even affect subsequent elution. For example, if the flow rate is too high, the metal ions may not fully contact the adsorbent, preventing adequate adsorption, thereby reducing the purification effect. On the other hand, if the flow rate is too low, the processing time may be prolonged or the adsorbent may be saturated, affecting the system's processing efficiency and stability. If flow rate anomalies are not promptly detected and corrected, they may result in inadequate adsorption of metal ions within the SPE column or incomplete elution of metal ions during elution. This ultimately leads to inaccurate test results or reduced sensitivity. In severe cases, the accuracy and reliability of the entire water quality monitoring process may be significantly compromised. Therefore, real-time monitoring and adjustment of the flow rate anomaly coefficient is crucial to ensure the stable operation of the SPE system and improve the efficiency of metal element purification.

[0026] In one embodiment, the steps for calculating the pressure anomaly coefficient are: The working pressure of the SPE system is monitored in real time by a pressure sensor to obtain a pressure sequence based on time sequence; Compare the pressure in the pressure sequence with the preset standard pressure range of the SPE system during operation. If the pressure is not within the preset standard pressure range of the SPE system during operation, the corresponding pressure in the pressure sequence is recorded as abnormal pressure. The pressure anomaly coefficient is obtained by dividing the total number of abnormal pressures in the pressure sequence by the total number of pressures in the pressure sequence.

[0027] It should be noted that in the calculation process of the pressure anomaly coefficient, the required data is obtained in real time through a pressure sensor installed in the SPE system. The pressure sensor is usually installed at a key position of the SPE system, such as the inlet or outlet of the SPE column, to monitor the working pressure in the system in real time. The pressure sensor can collect pressure data at a high frequency and transmit this data to the data acquisition system or control unit in chronological order. The collected pressure data is then compared with the preset standard pressure range. If the monitored pressure value exceeds the standard range, the system will mark it as abnormal pressure. In addition, the pressure sensor usually has high accuracy and stability to ensure that the collected data reflects the actual operating status of the system. The data acquisition system will process and store the data fed back by the sensor in real time, and use it for subsequent calculation of the pressure anomaly coefficient, providing an important basis for abnormal diagnosis and fault warning of the SPE system.

[0028] It should be noted that the pressure anomaly coefficient quantifies the degree to which the operating pressure in the SPE system deviates from the preset standard pressure range, specifically reflecting whether there are any pressure anomalies during system operation. A larger pressure anomaly coefficient indicates that the pressure values ​​frequently or severely exceed the preset standard range during the monitoring period, which generally indicates a system malfunction or unstable operation. Pressure is crucial to the proper operation of the SPE system as it directly affects the rate and uniformity of liquid flow through the SPE column, and thus the adsorption and elution of metal ions. Excessive system pressure can lead to excessive compaction of the adsorbent, impairing liquid flow, and even damaging system piping or equipment. Excessive pressure can result in insufficient flow, impairing metal ion enrichment efficiency, and even incomplete adsorption, reducing purification effectiveness. Failure to promptly detect and correct pressure anomalies can lead to inadequate metal ion enrichment and incomplete elution within the SPE column, ultimately significantly reducing metal element extraction efficiency and compromising the accuracy and reliability of water quality testing. Therefore, timely monitoring of the pressure anomaly coefficient and implementing corrective measures are key to ensuring stable SPE system operation and improving the accuracy of test results.

[0029] In one embodiment, the steps for calculating the temperature and humidity anomaly coefficient are as follows: The temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process are monitored in real time by a temperature and humidity sensor, and the time during which the temperature and humidity are within the preset standard temperature and humidity range is integrated to obtain the temperature anomaly and humidity anomaly of the environment in which the SPE system is located during the solid phase extraction process respectively; The temperature and humidity anomaly coefficients are obtained by weighted summing of the temperature anomaly and the humidity anomaly.

[0030] It should be noted that in the process of calculating the temperature and humidity anomaly coefficient, the required data is obtained through temperature and humidity sensors installed in the environment surrounding the SPE system. These sensors can monitor the temperature and humidity of the environment in which the SPE system is located in real time and transmit the data to the data acquisition system at a high frequency. Temperature and humidity sensors are usually equipped with high-precision measurement functions and can provide accurate temperature and humidity values ​​under large changes in environmental conditions. The data acquisition system will compare the real-time temperature and humidity data provided by the sensor with the preset standard temperature and humidity range and record the time within the standard range. Based on this data, the system can calculate the temperature and humidity anomaly, reflecting the possible impact of environmental changes on the SPE system. Finally, the temperature anomaly and humidity anomaly are weighted and summed to obtain the temperature and humidity anomaly coefficient, which serves as the basis for judging whether the environment has an impact on the stability of the SPE system.

[0031] It should be noted that the temperature and humidity anomaly coefficient (THA) measures the degree to which the temperature and humidity in the SPE system's operating environment deviate from the preset standard range. It comprehensively accounts for fluctuations in ambient temperature and humidity, reflecting the potential impact of environmental changes on the operational stability of the SPE system. A larger THA indicates that the temperature and humidity in the SPE system's environment frequently or significantly exceed the standard range. This may lead to unstable SPE operating conditions and, in turn, affect the purification effect. Temperature and humidity have a direct impact on the SPE process as they can affect adsorbent properties, liquid fluidity, and chemical reaction rates. For example, excessively high temperatures can increase solubility and reaction rates, resulting in incomplete or excessive contact between metal ions and the adsorbent, thus affecting enrichment efficiency. Excessive humidity can cause the adsorbent to absorb water and swell, affecting its adsorption performance and even causing equipment corrosion and failure. Failure to promptly monitor and adjust for temperature and humidity anomalies can lead to inefficient metal ion purification during the SPE process, or even complete failure, thereby compromising the accuracy and reliability of water quality testing.

[0032] In one embodiment, the steps of determining whether an abnormality occurs in the SPE system based on the flow rate abnormality coefficient, the pressure abnormality coefficient, and the temperature and humidity abnormality coefficient are as follows: Comparing the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient with the preset flow rate anomaly coefficient threshold, the preset pressure anomaly coefficient threshold, and the preset temperature and humidity anomaly coefficient threshold, respectively; If the flow rate abnormality coefficient is not less than the preset flow rate abnormality coefficient threshold, or the pressure abnormality coefficient is not less than the preset pressure abnormality coefficient threshold, or the temperature and humidity abnormality coefficient is not less than the preset temperature and humidity abnormality coefficient threshold, the SPE system is immediately judged to be abnormal, an alarm is issued, and the flow rate, pressure and ambient temperature and humidity of the SPE system are immediately adjusted; If the flow rate anomaly coefficient is less than the preset flow rate anomaly coefficient threshold, the pressure anomaly coefficient is less than the preset pressure anomaly coefficient threshold, and the temperature and humidity anomaly coefficient is less than the preset temperature and humidity anomaly coefficient threshold, the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient are weighted and summed to obtain an anomaly value; Compare the abnormal value with the preset abnormal value threshold. If the abnormal value is not less than the preset abnormal value threshold, immediately adjust the flow rate, pressure and ambient temperature and humidity of the SPE system; If the outlier value is less than the preset outlier value threshold, there is no need to adjust the flow rate, pressure, and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample.

[0033] It should be noted that based on the calculation results of the flow rate anomaly coefficient, pressure anomaly coefficient, and temperature and humidity anomaly coefficient, it is possible to comprehensively judge whether the SPE system has an abnormality and take corresponding adjustment measures. The specific steps are: First, the flow rate anomaly coefficient, pressure anomaly coefficient, and temperature and humidity anomaly coefficient are compared with the preset thresholds respectively. If any of the coefficients exceeds the preset threshold, it indicates that the system has an abnormality. In this case, the system will immediately issue an alarm and adjust the flow rate, pressure, and ambient temperature and humidity according to the abnormal situation to restore the normal working state of the system. For example, if the flow rate anomaly coefficient is too large, it may be because the flow rate is too fast or too slow. At this time, the pump speed or pipeline resistance can be adjusted to correct the flow rate; if the pressure anomaly coefficient is too high, it may be due to pipeline blockage or excessive pump load. The pressure needs to be adjusted or the system needs to be cleaned. If all the anomaly coefficients are below their respective thresholds, they are weighted and summed to obtain a comprehensive anomaly value, which is then compared with the preset anomaly threshold. If the combined abnormality value is not less than the preset threshold, it indicates that the system is still at potential risk and requires immediate adjustment of the flow rate, pressure, and environmental conditions. If the combined abnormality value is less than the threshold, the system is considered to be still within the normal range and no adjustment is required. Solid-phase extraction and subsequent metal element extraction steps can continue. In this process, timely detection and correction of abnormalities can help avoid potential risks in system operation, thereby ensuring the accuracy of purification effects and water quality test results. For example, in the case of high ambient humidity, the system may experience adsorbent expansion or equipment corrosion problems. Timely adjustment of humidity can avoid interference with the purification process and improve the extraction efficiency of metal ions. In one embodiment, the steps of determining whether the SPE system can continue to be used for subsequent extraction based on the adjusted key characteristics are: Calculate the flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient of the adjusted SPE system. If the adjusted flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient are all less than the corresponding preset thresholds, and the anomaly values ​​are less than the preset anomaly value thresholds, then there is no need to adjust the corresponding flow rate, pressure and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample; if not, immediately stop the solid phase extraction process, issue an alarm, and switch to manual solid phase extraction of the water sample again, and continue the metal element extraction steps of the water sample after manual solid phase extraction.

[0034] It should be noted that after adjusting the key characteristics of the SPE system, the key to determining whether the system can continue to be used for subsequent extraction steps lies in evaluating the adjusted flow rate anomaly coefficient, pressure anomaly coefficient, and temperature and humidity anomaly coefficient. The specific steps are: First, recalculate the various anomaly coefficients of the adjusted SPE system, especially the degree of anomaly of flow rate, pressure, and temperature and humidity. If, after adjustment, all flow rate anomaly coefficients, pressure anomaly coefficients, and temperature and humidity anomaly coefficients are less than their respective preset thresholds, and the weighted combined anomaly value is also less than the preset anomaly threshold, it indicates that the system has returned to normal operating conditions, and solid-phase extraction and subsequent metal element extraction steps can then be continued. For example, if the flow rate returns to the set range after adjustment, the pressure returns to normal, and the ambient temperature and humidity return to the standard range, then the SPE system can continue to operate stably, and the metal element enrichment and purification processes are unaffected. However, if the adjusted anomaly coefficients still exceed the thresholds, or the combined anomaly value remains high, this means that the system has not returned to a stable state. In this case, the solid-phase extraction process should be stopped immediately and an alarm should be issued. The system will switch to manual intervention, and the operator will re-perform manual solid-phase extraction on the water sample to ensure that the entire extraction process is not affected by the equipment failure, thereby ensuring the accuracy and effectiveness of the subsequent metal element extraction process. This early warning and automatic adjustment mechanism can promptly detect and resolve potential problems, avoiding reduced purification efficiency or inaccurate test results caused by equipment failure. For example, if the ambient temperature and humidity are too high and the system cannot automatically adjust to the normal range, manual intervention can be used to control the environmental conditions and re-perform solid-phase extraction, thereby ensuring the accuracy of metal ion enrichment.

[0035] The above is a detailed description of an embodiment of the present invention. However, the content is only a preferred embodiment of the present invention and should not be used to artificially limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A filtration and extraction method for detecting metal elements in water, characterized in that: The following steps are involved: Multiple sensor modules are set up to monitor the key characteristics of the SPE system that affect the solid phase extraction process in real time, and determine whether the SPE system is abnormal based on the key characteristics; If an abnormality occurs in the SPE system, the corresponding key features in the SPE system are immediately adjusted, and based on the adjusted key features, it is determined whether the SPE system can continue to be used for subsequent extractions; If possible, the water sample after solid phase extraction will continue to the subsequent step of metal element extraction; If not, the solid phase extraction process will be stopped immediately and an alarm will be issued. At the same time, the water sample will be manually re-extracted for solid phase extraction, and the water sample after manual solid phase extraction will be used to continue the subsequent steps of metal element extraction.

2. A filtration and extraction method for detecting metal elements in water according to claim 1, characterized in that: The steps for real-time monitoring of the key characteristics of the SPE system that affect the solid phase extraction process and determining whether the SPE system is abnormal based on the key characteristics are as follows: By setting up a micro flow sensor to monitor the flow rate of the liquid through the SPE column in real time, and calculating the flow rate abnormality coefficient based on the flow rate, the SPE column flow rate of the SPE system is analyzed to see if it is abnormal; By setting up a pressure sensor to monitor the working pressure of the SPE system in real time, and calculating the pressure abnormality coefficient based on the working pressure, it is analyzed whether the pressure of the SPE system is abnormal; By setting up temperature and humidity sensors to monitor the temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process in real time, the temperature and humidity anomaly coefficient is calculated; and the temperature and humidity of the environment in which the SPE system is located is analyzed to see if it is abnormal. Whether the SPE system is abnormal is determined based on the flow rate abnormality coefficient, pressure abnormality coefficient, and temperature and humidity abnormality coefficient.

3. A filtration and extraction method for detecting metal elements in water according to claim 2, characterized in that: The calculation steps of the velocity anomaly coefficient are: The flow rate of the SPE column in the SPE system during solid phase extraction is monitored in real time by a micro flow sensor to obtain a flow rate sequence based on time sequence; The initial fluctuation coefficient is obtained by adding the standard deviation and mean of the velocity series and dividing the standard deviation by the mean; Perform linear regression on the flow rate series to extract the trend slope of the flow rate change, compare the absolute value of the slope with the preset standard slope, calculate the difference between the absolute value of the slope and the preset standard slope, and divide the difference by the preset standard slope to obtain the flow rate trend anomaly coefficient; The velocity anomaly coefficient is obtained by weighted summing the initial fluctuation coefficient and the velocity trend anomaly coefficient.

4. A filtration and extraction method for detecting metal elements in water according to claim 2, characterized in that: The calculation steps of the pressure anomaly coefficient are: The working pressure of the SPE system is monitored in real time by a pressure sensor to obtain a pressure sequence based on time sequence; Compare the pressure in the pressure sequence with the preset standard pressure range of the SPE system during operation. If the pressure is not within the preset standard pressure range of the SPE system during operation, the corresponding pressure in the pressure sequence is recorded as abnormal pressure. The pressure anomaly coefficient is obtained by dividing the total number of abnormal pressures in the pressure sequence by the total number of pressures in the pressure sequence.

5. A filtration and extraction method for detecting metal elements in water according to claim 2, characterized in that: The calculation steps of the temperature and humidity anomaly coefficient are as follows: The temperature and humidity of the environment in which the SPE system is located during the solid phase extraction process are monitored in real time by a temperature and humidity sensor, and the time during which the temperature and humidity are within the preset standard temperature and humidity range is integrated to obtain the temperature anomaly and humidity anomaly of the environment in which the SPE system is located during the solid phase extraction process respectively; The temperature and humidity anomaly coefficients are obtained by weighted summing of the temperature anomaly and the humidity anomaly.

6. A filtration and extraction method for detecting metal elements in water according to claim 2, characterized in that: The steps to determine whether the SPE system is abnormal based on the flow rate abnormality coefficient, pressure abnormality coefficient, and temperature and humidity abnormality coefficient are as follows: Comparing the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient with the preset flow rate anomaly coefficient threshold, the preset pressure anomaly coefficient threshold, and the preset temperature and humidity anomaly coefficient threshold, respectively; If the flow rate abnormality coefficient is not less than the preset flow rate abnormality coefficient threshold, or the pressure abnormality coefficient is not less than the preset pressure abnormality coefficient threshold, or the temperature and humidity abnormality coefficient is not less than the preset temperature and humidity abnormality coefficient threshold, the SPE system is immediately judged to be abnormal, an alarm is issued, and the flow rate, pressure and ambient temperature and humidity of the SPE system are immediately adjusted; If the flow rate anomaly coefficient is less than the preset flow rate anomaly coefficient threshold, the pressure anomaly coefficient is less than the preset pressure anomaly coefficient threshold, and the temperature and humidity anomaly coefficient is less than the preset temperature and humidity anomaly coefficient threshold, the flow rate anomaly coefficient, the pressure anomaly coefficient, and the temperature and humidity anomaly coefficient are weighted and summed to obtain an anomaly value; Compare the abnormal value with the preset abnormal value threshold. If the abnormal value is not less than the preset abnormal value threshold, immediately adjust the flow rate, pressure and ambient temperature and humidity of the SPE system; If the outlier value is less than the preset outlier value threshold, there is no need to adjust the flow rate, pressure, and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample.

7. A filtration and extraction method for detecting metal elements in water according to claim 6, characterized in that: The steps to determine whether the SPE system can continue to be used for subsequent extraction based on the adjusted key characteristics are as follows: Calculate the flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient of the adjusted SPE system. If the adjusted flow rate anomaly coefficient, pressure anomaly coefficient and temperature and humidity anomaly coefficient are all less than the corresponding preset thresholds, and the anomaly values ​​are less than the preset anomaly value thresholds, then there is no need to adjust the corresponding flow rate, pressure and ambient temperature and humidity of the SPE system; continue to perform solid phase extraction and subsequent metal element extraction steps on the water sample; if not, immediately stop the solid phase extraction process, issue an alarm, and switch to manual solid phase extraction of the water sample again, and continue the metal element extraction steps of the water sample after manual solid phase extraction.

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