Online residual chlorine sampling and analyzing system at sea discharge port

Abstract

The invention discloses an online residual chlorine sampling and analyzing system for a discharge port. The system comprises the following units: a seawater sample acquisition and pretreatment unit, a water quality parameter and residual chlorine signal acquisition unit, a residual chlorine signal self-adaptive correction unit and a result output unit, the seawater sample acquisition and pretreatment unit is used for acquiring and pretreating a seawater sample at a sea discharge port; the water quality parameter and residual chlorine signal acquisition unit is used for acquiring water quality parameters and residual chlorine detection signals of seawater samples. According to the online residual chlorine sampling and analyzing system for the discharge port, a water quality self-adaptive compensation algorithm built in the system can dynamically correct residual chlorine signals, and a calculation model for correcting and optimizing residual chlorine concentration based on water quality parameters collected in real time is achieved, so that the system can cope with changes under different water quality conditions; the accuracy and the stability of residual chlorine concentration monitoring are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of water quality monitoring, and more specifically, to an online residual chlorine sampling and analysis system for ocean outlets. Background Technology

[0002] In numerous industrial production and wastewater treatment scenarios involving seawater discharge, accurate monitoring of residual chlorine levels in seawater is crucial to ensure compliance with relevant environmental standards. Residual chlorine refers to the effective chlorine component remaining after chlorine-containing disinfectants have been used in the disinfection process. Excessive levels can severely damage the marine ecosystem, impacting the survival and reproduction of marine life; conversely, insufficient levels may fail to achieve effective disinfection, leading to water quality safety issues. Traditional residual chlorine monitoring methods typically rely on manual sampling and offline experimental analysis, which not only suffers from long detection cycles and significant human error but also presents particular challenges in real-time monitoring of residual chlorine concentrations in complex and rapidly changing marine outfall areas.

[0003] Currently, existing residual chlorine detection methods and equipment have many limitations. On the one hand, traditional residual chlorine detection equipment can typically only collect residual chlorine detection signals, without fully considering various water quality parameters that affect the accuracy of residual chlorine detection, such as salinity, temperature, and pH. Changes in these water quality parameters can significantly interfere with the accuracy of residual chlorine detection signals, leading to large deviations between the detection results and the actual residual chlorine concentration, thus failing to provide a reliable basis for environmental protection decisions. On the other hand, some detection equipment lacks effective signal correction and model optimization mechanisms, and cannot dynamically correct residual chlorine detection signals based on real-time water quality conditions, making it difficult to meet the requirements of high precision and high stability. In addition, existing equipment also has shortcomings in data storage and management, making it difficult to achieve comprehensive and orderly storage of real-time analysis results and historical data, which is not conducive to subsequent data traceability and analysis, and cannot provide strong support for further optimization of detection models and improvement of detection performance. Therefore, developing an online sampling and analysis system that can accurately, stably, and comprehensively monitor the residual chlorine content of seawater at estuaries is of significant practical importance. Summary of the Invention

[0004] The purpose of this invention is to provide an online residual chlorine sampling and analysis system for sea outlets. This system solves the problem that existing residual chlorine detection equipment can only collect residual chlorine detection signals and does not fully consider various water quality parameters that affect the accuracy of residual chlorine detection. This can interfere with the accuracy of residual chlorine detection signals, resulting in a large deviation between the detection results and the actual residual chlorine concentration, and thus failing to provide a reliable basis for environmental protection decisions.

[0005] This invention achieves the above objective through the following technical solution: an online residual chlorine sampling and analysis system for sea outlets, the system comprising the following units: The system includes a seawater sample acquisition and pretreatment unit, a water quality parameter and residual chlorine signal acquisition unit, a residual chlorine signal adaptive correction unit, and a result output unit. The seawater sample acquisition and preprocessing unit is used to acquire seawater samples from the discharge outlet and preprocess them. The water quality parameter and residual chlorine signal acquisition unit is used to collect water quality parameters and residual chlorine detection signals from seawater samples. The residual chlorine signal adaptive correction unit is used to correct the residual chlorine detection signal based on water quality parameters and optimize the residual chlorine concentration calculation model. The result output unit is used to calculate and output the residual chlorine analysis results.

[0006] Furthermore, the seawater sample acquisition and preprocessing unit includes: Sampling components and preprocessing components; The sampling component is used to continuously acquire seawater samples from the discharge outlet. The pretreatment component is used to filter seawater samples to remove impurities and maintain the sample temperature within a preset fluctuation range through a temperature control structure.

[0007] Furthermore, the water quality parameters and residual chlorine signal acquisition unit: A multi-parameter sensing device is used to simultaneously collect the raw residual chlorine detection signal of seawater samples and at least one water quality parameter that affects the accuracy of residual chlorine detection, and all signals and parameters are collected at the same frequency.

[0008] Furthermore, the water quality parameters affecting the accuracy of residual chlorine detection include one or more of salinity, temperature, and pH value. Each parameter is collected by a corresponding sensing unit, and the collected data has a unified timestamp.

[0009] Furthermore, the residual chlorine signal adaptive correction unit: The built-in water quality adaptive compensation algorithm dynamically corrects the original residual chlorine detection signal based on the water quality parameters and the water quality parameters acquired in real time by the residual chlorine signal acquisition unit, and adjusts the parameters of the residual chlorine concentration calculation model.

[0010] Furthermore, the execution process of the water quality adaptive compensation algorithm includes: Construct a basic residual chlorine concentration calculation model; Establish separate influencing factor calculation models for each water quality parameter; A comprehensive compensation coefficient is constructed based on each influencing factor; The basic residual chlorine concentration calculation model was adjusted using a comprehensive compensation coefficient to obtain a corrected residual chlorine concentration calculation model.

[0011] Furthermore, the result output unit: The residual chlorine concentration of seawater samples is calculated using the corrected residual chlorine concentration calculation model. The validity of the calculation results is judged, and the results that meet the preset valid range are output. If the result exceeds the valid range, an abnormal warning mechanism will be triggered and a prompt message will be output.

[0012] Furthermore, the pretreatment component employs a multi-stage filtration structure, with the filtration accuracy of each stage increasing sequentially. The filtration structure is also equipped with a differential pressure monitoring unit, which automatically activates the backwashing function to restore filtration performance when the detected differential pressure exceeds a set threshold.

[0013] Furthermore, the water quality adaptive compensation algorithm also includes a coefficient update mechanism. This mechanism periodically collects standard residual chlorine solution samples of known concentrations, combines the sample detection signals with water quality parameters, and iteratively updates the key coefficients in the water quality adaptive compensation algorithm.

[0014] Furthermore, the system also includes a data storage unit that synchronously stores real-time analysis results and historical collected data. The data storage frequency matches the parameter collection frequency, and the stored data can be used for subsequent traceability and analysis.

[0015] The beneficial effects of this invention are as follows: 1. By combining multi-parameter sensing devices, the system can simultaneously collect water quality parameters and residual chlorine signals, and mark the data with a unified timestamp to ensure the accurate correlation between water quality parameters and residual chlorine concentration, and reduce measurement errors caused by changes in water quality.

[0016] 2. The system's built-in water quality adaptive compensation algorithm can dynamically correct the residual chlorine signal. It is based on real-time collected water quality parameters to optimize the calculation model of residual chlorine concentration, enabling the system to cope with changes under different water quality conditions and significantly improving the accuracy and stability of residual chlorine concentration monitoring.

[0017] 3. The system outputs the residual chlorine concentration using the corrected residual chlorine concentration calculation model and judges the validity of the calculation results. If abnormal data is detected that exceeds the valid range, the system will automatically trigger the abnormal warning mechanism, output prompt information in a timely manner, and help relevant personnel take measures to ensure the safety of the water quality at the discharge estuary.

[0018] 4. The pretreatment component adopts a multi-stage filtration structure, which can effectively remove impurities in seawater and ensure the accuracy of sampling data. When the filtration system experiences excessive pressure difference, the system will automatically start the backwashing function to restore filtration performance and ensure long-term stable operation of the system.

[0019] 5. The system includes a data storage unit that can synchronously store real-time analysis results and historical data, supporting subsequent data traceability and analysis, and meeting the needs of long-term data monitoring and environmental supervision. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating the overall system workflow of the present invention; Figure 2 This is a flowchart of the adaptive correction algorithm of the present invention. Detailed Implementation

[0021] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0022] Example 1: Please see Figure 1-2 This invention provides a technical solution: an online residual chlorine sampling and analysis system for sea outlets, the system comprising the following units: Seawater sample acquisition and pretreatment unit, water quality parameter and residual chlorine signal acquisition unit, residual chlorine signal adaptive correction unit and result output unit; The seawater sample acquisition and preprocessing unit is used to acquire and preprocess seawater samples from the discharge outlet. This unit is responsible for collecting seawater samples from the outlet and performing a series of preprocessing operations on the collected samples. The purpose of preprocessing is usually to remove impurities, suspended solids, etc. from the samples so that the seawater samples are in a state suitable for subsequent analysis and testing, and to ensure the accuracy of the test results. The water quality parameter and residual chlorine signal acquisition unit is used to acquire the original detection signals of water quality parameters and residual chlorine of seawater samples in real time through multi-parameter sensors. The water quality parameters include salinity, temperature, and pH value. The water quality parameter and residual chlorine signal acquisition unit utilizes a multi-parameter sensor to acquire real-time data from pretreated seawater samples. It can simultaneously acquire water quality parameters and raw residual chlorine detection signals. A multi-parameter sensor is a sensor device capable of simultaneously measuring multiple different parameters. In this system, it can simultaneously measure water quality parameters such as salinity, temperature, and pH value, as well as raw residual chlorine detection signals, achieving synchronous acquisition of multi-dimensional information from seawater samples. Water quality parameters reflect various physical, chemical, and biological indicators of seawater quality. In this system, these specifically include salinity, the ratio of dissolved salt mass to seawater mass, reflecting the salinity of the seawater; temperature, indicating the temperature of the seawater, affecting chemical reaction rates and biological activity; and pH value, an indicator of seawater acidity and alkalinity, which significantly impacts the survival of organisms and chemical reactions in seawater. The raw residual chlorine detection signal is an initial electrical signal or other form of signal directly acquired through a specific detection method or sensor regarding the residual chlorine content in seawater. This signal has not undergone calibration and may contain errors due to factors such as changes in water quality. The residual chlorine signal adaptive correction unit is used to dynamically correct the original residual chlorine detection signal based on real-time collected water quality parameters using an adaptive compensation algorithm for water quality changes, and to adjust the residual chlorine concentration calculation model. Among them, the water quality change adaptive compensation algorithm is an algorithm that can automatically adjust the calculation model or parameters according to changes in water quality parameters such as salinity, temperature, and pH value. In this system, it can compensate and correct the original residual chlorine detection signal based on the real-time collected water quality parameters, eliminate the influence of water quality changes on the residual chlorine detection results, and make the calculated residual chlorine concentration closer to the true value. The residual chlorine concentration calculation model is a mathematical model used to calculate the residual chlorine concentration in seawater based on the collected signals, such as the original residual chlorine detection signal and related water quality parameters. This model will convert the input signal into a specific residual chlorine concentration value according to different algorithms and parameter settings. Before correction, there may be some error. After adjustment by the adaptive correction unit, it can more accurately reflect the residual chlorine concentration in seawater. The results output unit is used to calculate the residual chlorine concentration of seawater samples using the corrected residual chlorine concentration calculation model and output the online residual chlorine analysis results. Among them, the online residual chlorine analysis results are the final data results on the residual chlorine concentration in the seawater at the discharge outlet, obtained in real time through the online residual chlorine sampling and analysis system at the discharge outlet. These results can reflect the residual chlorine pollution status of the seawater at the discharge outlet in a timely manner, which is of great significance for ensuring the safety of the marine ecological environment.

[0023] It should be noted that during use, the seawater sample acquisition and pretreatment unit ensures the acquisition of representative samples, laying the foundation for accurate analysis. The water quality parameter and residual chlorine signal acquisition unit, with the help of multi-parameter sensors, can simultaneously acquire water quality parameters such as salinity, temperature, and pH value, as well as raw residual chlorine signals, providing comprehensive and real-time information. The residual chlorine signal adaptive correction unit adopts a water quality change adaptive compensation algorithm, dynamically correcting the raw residual chlorine signal and adjusting the calculation model based on real-time water quality parameters, effectively eliminating the interference of water quality fluctuations on the detection results and improving accuracy. The result output unit uses the corrected model to calculate and output online residual chlorine analysis results, which can reflect the residual chlorine status of seawater at the discharge outlet in a timely and accurate manner, providing a reliable basis for environmental monitoring and pollution control, and helping to ensure the safety of the marine ecological environment.

[0024] In one embodiment, obtaining seawater samples from the discharge outlet and preprocessing them includes: Seawater samples were continuously collected from the outlet using an online sampling device, with the sampling flow rate controlled between 0.5 and 2 L / min. Seawater samples were filtered to remove particles larger than [the specified size]. Suspended particulate matter; The filtered seawater sample was introduced into a constant temperature flow cell, and the water temperature fluctuation range in the flow cell was maintained within ±0.5℃ to obtain a pretreated seawater sample.

[0025] This design, using an online sampling device for continuous data acquisition and controlling the flow rate between 0.5 and 2 L / min, can stably obtain representative samples and filter out particles larger than [a certain size]. The filtered sample contains suspended particulate matter, preventing impurities from interfering with subsequent testing. The filtered sample is then introduced into a constant-temperature flow cell, maintaining water temperature fluctuations within ±0.5℃. This eliminates the impact of water temperature changes on testing, ensuring the quality and stability of the seawater sample. This provides a reliable basis for the accurate collection of water quality parameters and residual chlorine signals, enabling the test results to more accurately reflect the actual situation of the seawater at the discharge outlet, and improving the accuracy and reliability of the entire online residual chlorine sampling and analysis system.

[0026] In one embodiment, water quality parameters and residual chlorine raw detection signals of seawater samples are acquired in real time using a multi-parameter sensor, including: The raw residual chlorine detection signal of seawater samples was collected using a residual chlorine sensor to obtain the raw detection value. The unit is mg / L; Salinity values ​​of seawater samples were collected using a salinity sensor. The unit is ‰; Temperature values ​​of seawater samples were collected using a temperature sensor. The unit is ℃; pH values ​​of seawater samples were collected using a pH sensor. ; The acquisition frequency of all parameters is synchronously set to 1 time / second to ensure consistent data timestamps.

[0027] This design employs sensors for residual chlorine, salinity, temperature, and pH to collect corresponding data. The acquisition frequency for each parameter is synchronized at 1 time per second, ensuring consistent timestamps. This allows for comprehensive and real-time acquisition of multi-dimensional information from seawater samples. Synchronized acquisition and consistent timestamps guarantee the synchronicity and correlation of the data, making subsequent residual chlorine signal correction and analysis based on these parameters more accurate and scientific. It can promptly detect the impact of changes in water quality parameters on residual chlorine detection, providing a reliable basis for accurately adjusting the residual chlorine concentration calculation model, thereby improving the accuracy of online residual chlorine analysis results.

[0028] In one embodiment, an adaptive compensation algorithm for water quality changes is employed to dynamically correct the original residual chlorine detection signal based on real-time collected water quality parameters, adjusting the residual chlorine concentration calculation model, including: A basic residual chlorine concentration calculation model is constructed, and the basic model expression is as follows:

[0029] in, This is the initial calculated value of the uncompensated residual chlorine concentration, in mg / L. The scaling factor of the basic model, The intercept term of the basic model was calibrated using a standard residual chlorine solution to obtain its initial value. =1.02, =0.01; Establish a calculation model for water quality parameter influencing factors, and calculate the salinity influencing factor separately. Temperature Influence Factors pH influencing factors : Formula for calculating salinity impact factor:

[0030] in, The standard salinity reference value is set at 35‰. The salinity influence coefficient is 0.032. Formula for calculating temperature influence factor:

[0031] in, The standard temperature reference value is set to 25℃. This is the coefficient for the first-order temperature term, with a value of -0.021. This is the coefficient of the quadratic term of temperature, with a value of 0.0003; Formula for calculating pH influence factor:

[0032] in, The standard pH reference value is set to 7.8. The pH influence coefficient is set to 0.045. A comprehensive compensation coefficient was constructed based on the influencing factors of various water quality parameters. The formula is:

[0033] The basic residual chlorine concentration calculation model is dynamically adjusted by a comprehensive compensation coefficient to obtain the corrected residual chlorine concentration calculation model:

[0034] in, The residual chlorine concentration is the corrected value after adaptive compensation for water quality changes, in mg / L.

[0035] This design constructs a basic residual chlorine concentration calculation model and establishes calculation models for salinity, temperature, and pH influencing factors. Furthermore, a comprehensive compensation coefficient is constructed to dynamically adjust the basic model. This fully considers the impact of water quality parameters such as salinity, temperature, and pH on residual chlorine detection. By establishing accurate influencing factor models and comprehensive compensation coefficients, the original residual chlorine detection signal can be dynamically and accurately corrected based on real-time collected water quality parameters. This adjusts the residual chlorine concentration calculation model, effectively eliminating interference from water quality changes and making the calculated residual chlorine concentration closer to the true value, greatly improving the accuracy and reliability of online residual chlorine analysis.

[0036] In one embodiment, the residual chlorine concentration of a seawater sample is calculated using a corrected residual chlorine concentration calculation model, and online residual chlorine analysis results are output, including: The effective range for residual chlorine concentration is set as 0-10 mg / L, and the calculated residual chlorine concentration correction value is... Perform validity verification; like If it is within the effective range, the value will be directly output as the result of the online residual chlorine analysis; like If the value exceeds the valid range, an anomaly warning will be activated, and the most recent valid correction value and anomaly message will be output. Real-time analysis results are synchronized with historical data and stored in the database, with the storage frequency matching the acquisition frequency.

[0037] This design sets an effective range for residual chlorine concentration, verifies the effectiveness of the corrected residual chlorine concentration value, outputs the result directly within the range, and triggers an anomaly warning and outputs relevant information if the result exceeds the range. It also stores real-time results and historical data synchronously. On the one hand, this ensures that the output residual chlorine analysis results are accurate and reliable, and provides timely warnings for abnormal situations, facilitating timely handling by staff. On the other hand, the synchronously stored data provides rich information for subsequent data analysis and trend research, which helps to gain a deeper understanding of the changes in residual chlorine in seawater at the discharge outlet, and provides stronger support for environmental management and decision-making.

[0038] In one embodiment, filtering a seawater sample includes: A two-stage filtration mechanism is adopted. The first stage uses a stainless steel filter screen for coarse filtration with a pore size of 50 mm. ; The second stage uses a ceramic filter element for fine filtration, with a filter element pore size of 5 mm. ; During the filtration process, the pressure difference across the filter screen is monitored in real time. When the pressure difference exceeds 0.1 MPa, the backwashing program is automatically started to ensure continuous filtration.

[0039] This design employs a two-stage filtration mechanism: a first-stage stainless steel filter for coarse filtration and a second-stage ceramic filter for fine filtration. The pressure difference across the filter is monitored in real time during filtration, and a backwashing process is automatically initiated when the pressure exceeds 0.1 MPa. This two-stage filtration effectively removes impurities of different particle sizes, improving the purity of seawater samples and reducing interference from impurities in subsequent testing. Real-time pressure monitoring and automatic backwashing ensure the continuity and stability of the filtration system, preventing a decline in filtration efficiency due to filter clogging. This guarantees that the quality of the acquired seawater samples consistently meets requirements, laying a solid foundation for accurate subsequent testing and analysis.

[0040] In one embodiment, the water quality change adaptive compensation algorithm further includes a coefficient dynamic update step: A set of standard residual chlorine solution samples were collected every 24 hours. The concentrations of the standard residual chlorine solutions were known and covered four gradients: 0.5 mg / L, 2 mg / L, 5 mg / L, and 8 mg / L. Under the current water quality conditions, the detection signals of standard residual chlorine solution and water quality parameters are collected by sensors, and then substituted into the corrected residual chlorine concentration calculation model to calculate the predicted values ​​at each gradient. ; Based on predicted values ​​and standard values The deviation is updated using the least squares method. , , , The updated formula is:

[0041] in, This represents the coefficients to be updated, specifically... , , , , The coefficient values ​​before the update. For the updated coefficient values, Let L be the learning rate, with a value of 0.001, and L be the loss function, calculated using the following formula:

[0042] This represents the number of standard solution gradients.

[0043] This design involves collecting standard residual chlorine solution samples every 24 hours, acquiring detection signals and water quality parameters under the current water quality environment, substituting them into the model to calculate predicted values, and updating the coefficients using the least squares method based on the deviation between the predicted values ​​and the standard values. As time and water quality conditions change, the coefficients can be automatically adjusted and optimized. By periodically verifying and updating using standard solutions, the adaptive compensation algorithm for water quality changes can be ensured to always be in the best state, better adapting to actual water quality changes, further improving the accuracy of residual chlorine concentration calculation, and enabling the online residual chlorine sampling and analysis system to operate stably and accurately for a long time.

[0044] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0045] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. An online residual chlorine sampling and analysis system for sea outlets, characterized in that, The system includes the following units: The system includes a seawater sample acquisition and pretreatment unit, a water quality parameter and residual chlorine signal acquisition unit, a residual chlorine signal adaptive correction unit, and a result output unit. The seawater sample acquisition and preprocessing unit is used to acquire seawater samples from the discharge outlet and preprocess them. The water quality parameter and residual chlorine signal acquisition unit is used to collect water quality parameters and residual chlorine detection signals from seawater samples. The residual chlorine signal adaptive correction unit is used to correct the residual chlorine detection signal based on water quality parameters and optimize the residual chlorine concentration calculation model. The result output unit is used to calculate and output the residual chlorine analysis results.

2. The online residual chlorine sampling and analysis system for sea outlets according to claim 1, characterized in that, The seawater sample acquisition and preprocessing unit includes: Sampling components and preprocessing components; The sampling component is used to continuously acquire seawater samples from the discharge outlet. The pretreatment component is used to filter seawater samples to remove impurities and maintain the sample temperature within a preset fluctuation range through a temperature control structure.

3. The online residual chlorine sampling and analysis system for sea outlets according to claim 1, characterized in that, The water quality parameters and residual chlorine signal acquisition unit: A multi-parameter sensing device is used to simultaneously collect the raw residual chlorine detection signal of seawater samples and at least one water quality parameter that affects the accuracy of residual chlorine detection, and all signals and parameters are collected at the same frequency.

4. The online residual chlorine sampling and analysis system for sea outlets according to claim 3, characterized in that: The water quality parameters that affect the accuracy of residual chlorine detection include one or more of salinity, temperature, and pH value. Each parameter is collected by a corresponding sensing unit, and the collected data has a unified timestamp.

5. The online residual chlorine sampling and analysis system for sea outlets according to claim 1, characterized in that, The residual chlorine signal adaptive correction unit: The built-in water quality adaptive compensation algorithm dynamically corrects the original residual chlorine detection signal based on the water quality parameters and the water quality parameters acquired in real time by the residual chlorine signal acquisition unit, and adjusts the parameters of the residual chlorine concentration calculation model.

6. The online residual chlorine sampling and analysis system for sea outlets according to claim 5, characterized in that, The execution process of the water quality adaptive compensation algorithm includes: Construct a basic residual chlorine concentration calculation model; Establish separate influencing factor calculation models for each water quality parameter; A comprehensive compensation coefficient is constructed based on each influencing factor; The basic residual chlorine concentration calculation model was adjusted using a comprehensive compensation coefficient to obtain a corrected residual chlorine concentration calculation model.

7. The online residual chlorine sampling and analysis system for sea outlets according to claim 1, characterized in that, The result output unit: The residual chlorine concentration of seawater samples is calculated using the corrected residual chlorine concentration calculation model. The validity of the calculation results is judged, and the results that meet the preset valid range are output. If the result exceeds the valid range, an abnormal warning mechanism will be triggered and a prompt message will be output.

8. The online residual chlorine sampling and analysis system for sea outlets according to claim 2, characterized in that: The pretreatment component employs a multi-stage filtration structure, with each stage increasing in filtration precision. The filtration structure is also equipped with a differential pressure monitoring unit, which automatically activates backwashing to restore filtration performance when the detected differential pressure exceeds a set threshold.

9. The online residual chlorine sampling and analysis system for sea outlets according to claim 5, characterized in that: The water quality adaptive compensation algorithm also includes a coefficient update mechanism. This mechanism periodically collects standard residual chlorine solution samples of known concentrations, combines the sample detection signals with water quality parameters, and iteratively updates the key coefficients in the water quality adaptive compensation algorithm.

10. The online residual chlorine sampling and analysis system for sea outlets according to any one of claims 1-9, characterized in that: The system also includes a data storage unit that synchronously stores real-time analysis results and historical collected data. The data storage frequency matches the parameter collection frequency, and the stored data can be used for subsequent traceability and analysis.

Images