Crude oil organic chlorine content detection method and system based on ion chromatography and intelligent optimization system

Abstract

The invention discloses a crude oil organic chlorine content detection method and system based on ion chromatography and an intelligent optimization system, and aims to solve the problems of inaccurate detection, low efficiency and poor adaptability in the prior art. The system comprises an automatic sample pretreatment module, an intelligent ion chromatographic analysis module and a central control and data processing AI platform, and full-process automation is realized. The detection process comprises sample introduction, scheme calling, automatic pretreatment, intelligent chromatographic analysis and AI diagnosis calibration and report early warning. And parameters are accurately matched through crude oil type-special scheme, and multi-matrix crude oil with light weight, heavy weight, high wax content and the like is adapted. The method can quickly generate a detection report with a two-dimensional code, deeply meets customs supervision requirements, improves the detection efficiency and reliability, and has practical application value.

Description

Technical Field

[0001] This invention relates to the field of analytical chemistry technology, and in particular to an intelligent ion chromatography system and method for rapid, accurate, and automated detection of organochlorine content in crude oil, applicable to customs and other regulatory scenarios. Background Technology

[0002] In the grand scheme of global energy trade, crude oil, as the lifeblood of industry, is the first line of defense for ensuring the stable operation of the refining and chemical industry chain. Among these indicators, organochlorine content is a crucial yet easily overlooked hidden indicator. These chlorine elements, hidden in crude oil in complex compound forms, will transform into highly corrosive hydrogen chloride during the subsequent high-temperature, high-pressure refining process. Like lurking "catalyst killers" and "equipment corrosives," they seriously threaten production safety, damage expensive equipment, and lead to the deterioration of refined oil quality. Therefore, rapid and accurate screening of imported crude oil for organochlorine content is one of the core responsibilities of customs authorities in fulfilling technical barrier supervision and safeguarding their national industrial security.

[0003] However, faced with the daily influx of crude oil cargoes from diverse sources, customs laboratories have long been mired in a technical dilemma of "inaccurate and slow inspection" and a labor-intensive work rut. The three mainstream testing technologies currently relied upon by the industry have all revealed insurmountable shortcomings when dealing with the "three highs" requirements of high throughput, high timeliness, and high accuracy at ports.

[0004] Firstly, the microcoulometric method (based on GB / T18612-2011), considered a classic method, while straightforward in its detection principle, involves a tedious chemical experiment. Technicians must manually complete at least six precise steps, including extraction, washing, purification, and transfer, making the entire process highly dependent on the operator's skill and experience. The time from processing a single sample to obtaining results can easily exceed two hours. During peak customs clearance periods, sample vials pile up in the laboratory, requiring technicians to work in shifts under intense pressure, repeating these delicate operations. This not only results in extremely high labor intensity but also amplifies the risk of human error. More seriously, this method has limited resistance to interference from complex matrices in crude oil. When dealing with heavy, high-sulfur, and high-asphaltite crude oil, incomplete pretreatment can lead to results that significantly deviate from the true value. This delayed and potentially inaccurate detection undoubtedly poses a hidden danger to the inflow of high-risk oil products into the domestic market.

[0005] Secondly, X-ray fluorescence spectrometry (based on SH / T0842-2017), with its advantages of speed and non-destructive surface analysis, was once seen as a promising method for accelerating the process. A simple "irradiation" of the instrument can yield total chlorine data within minutes. However, its fatal flaw lies in its inability to distinguish between organic and inorganic chlorine. The sources of chlorine in crude oil are complex, potentially originating from residual brine (inorganic chlorides) during extraction, or from primary or secondary organic chlorides. For refineries, inorganic chlorine can be removed through simple electro-desalination processes with minimal harm; the real culprit is organic chlorine. X-ray fluorescence spectrometry conflates the two, limiting the reference value of its "total chlorine" data. Industry assessments indicate that its inference error in distinguishing between organic and inorganic chlorine can exceed 30%. This prevents customs supervision from achieving precise targeting, potentially leading to misjudgments: either releasing "problem oil" with excessive organic chlorine levels, or detaining actually safe "qualified oil" due to high total chlorine levels, causing unnecessary trade disputes.

[0006] Furthermore, while existing ion chromatography possesses the theoretical capability for precise quantification of chloride ions, seemingly offering a glimmer of hope, it encounters significant challenges when applied to crude oil matrices with highly variable compositions. Fixed chromatographic conditions (such as eluent concentration, flow rate, and column temperature) are insufficient to handle light sands from the Middle East, heavy Marie oil from South America, or high-acid oils from Africa. Different densities, viscosities, and hydrocarbon compositions can lead to retention time shifts, peak tailing, or decreased resolution of the chloride ion peak. Laboratories are forced to maintain multiple analytical methods for different types of crude oil, with experienced engineers manually adjusting parameters—a cumbersome process with poor reproducibility; the relative standard deviation (RSD) between different batches often exceeds 5%. This instability significantly undermines the authority of the test data and the reliability of legal evidence.

[0007] The pressure of reality is reflected in cold, hard numbers: a medium-sized seaport can handle 50 to 100 batches of crude oil samples daily. Using traditional methods, the microcoulometric method alone requires 3-5 experienced testing personnel working in three shifts, exhausting themselves in a laboratory resembling a chemical plant, yet still unable to keep up with the clearance pace, causing ships to be stranded and incurring hefty demurrage fees. Efficiency, cost, and accuracy form a complex and intractable triangle of contradictions.

[0008] Therefore, developing an intelligent overall solution capable of fully automating complex pretreatment, intelligently distinguishing between organic and inorganic chlorine, and adaptively optimizing detection parameters has become an urgent need for customs to improve regulatory efficiency and safeguard national energy and economic security. This is not only a technological innovation in the field of analytical chemistry, but also a strategic key to improving national trade facilitation and security control. This invention was born out of such industry pain points and real-world demands, aiming to create a powerful tool that meets the needs of future smart customs by deeply integrating automation engineering, artificial intelligence, and classical ion chromatography technology.

[0009] The above background information is provided only to aid in understanding the inventive concept and technical solution of this invention. It does not necessarily belong to the prior art of this patent application. In the absence of clear evidence that the above information was disclosed on the filing date of this patent application, the above background information should not be used to evaluate the novelty and inventiveness of this application. Summary of the Invention

[0010] The purpose of this invention is to overcome the shortcomings of the prior art and provide a fully automatic, intelligent, and high-precision crude oil organochlorine content detection system and method to achieve unattended detection with "sample in, result out" and meet the high-throughput supervision needs of customs.

[0011] To achieve the above technical objectives, the present invention adopts the following technical solution:

[0012] A crude oil organochlorine content detection system based on ion chromatography and intelligent optimization system, comprising:

[0013] Automated sample pretreatment module, intelligent ion chromatography analysis module, and central control and data processing AI platform;

[0014] The automated sample pretreatment module is connected to the flow path of the intelligent ion chromatography analysis module.

[0015] The central control and data processing AI platform is electrically connected to the automated sample pretreatment module and the intelligent ion chromatography analysis module.

[0016] The automated sample pretreatment module includes a precision weighing and dilution unit, an online extraction and separation unit, an online combustion / high-temperature hydrolysis unit, and an absorption liquid quantitative collection unit connected in sequence.

[0017] The intelligent ion chromatography analysis module includes an intelligent injector, an online purification and protection column system, a chromatography pump and column oven, a conductivity detector, and an intelligent condition recommendation unit.

[0018] The central control and data processing AI platform includes a system control unit, a data acquisition and processing unit, an AI intelligent diagnosis and calibration unit, and a result reporting and risk warning unit.

[0019] Preferably, the online extraction and separation unit includes a constant temperature oscillator, a high-speed centrifuge, and a phase separation membrane; the online combustion / high-temperature hydrolysis unit includes a programmable temperature controlled combustion furnace and a multi-channel gas flow controller.

[0020] Preferably, the intelligent condition recommendation unit has a built-in combined model, and the input parameters of the combined model include crude oil density, viscosity and hydrocarbon ratio.

[0021] Preferably, the AI ​​intelligent diagnosis and calibration unit includes a preset tolerance range for determining chromatographic peak tailing factor, symmetry, retention time drift, and standard sample recovery rate.

[0022] Preferably, the model of the intelligent condition recommendation unit is equipped with a periodic update program, and its model parameters can be automatically updated based on newly input sample data and corresponding analysis results.

[0023] Preferably, the detection system described in any one of claims 1-5 is used, and includes the following steps:

[0024] S1. Sample Introduction: Place the crude oil sample into the system and associate it with the declaration information;

[0025] S2, Scheme Recall: The system recalls the testing scheme based on the sample information;

[0026] S3. Automatic pretreatment: The system performs automated sample pretreatment to obtain the test solution;

[0027] S4. Intelligent Chromatography Analysis: The system performs ion chromatography analysis based on recommended analytical conditions and collects data;

[0028] S5, AI Diagnosis, Calibration, and Reporting Warning: The system diagnoses and verifies the analysis process and results, and generates reports.

[0029] Preferably, step S3 includes:

[0030] (1) Precision weighing and dilution: The crude oil sample is automatically weighed and dissolved in a dimethyl sulfoxide-toluene mixed solvent;

[0031] (2) Online extraction and separation: Ultrapure water is added for extraction, and the aqueous phase is removed by centrifugation and membrane separation;

[0032] (3) Online high-temperature hydrolysis: The separated organic phase is subjected to high-temperature hydrolysis;

[0033] (4) Absorption liquid collection: The hydrolysis products are absorbed using alkaline hydrogen peroxide absorption liquid to obtain the test solution.

[0034] Preferably, in step S4, the system recommends different analytical column types or elution gradients for different types of crude oil.

[0035] Preferably, in step S5, when any indicator exceeds the preset tolerance range, the system triggers a review or maintenance command.

[0036] Preferably, step S5 further includes: comparing the test results with preset limits, generating an electronic test report, and uploading it to the database; when the test results exceed the limits or the data is abnormal, the system sends a warning message to the designated regulatory terminal.

[0037] The beneficial effects of this invention compared to the prior art include:

[0038] 1. Full-process automation and high throughput

[0039] The system established by this invention integrates multiple independent steps that previously relied on manual operation into a continuous automated production line. From automatically weighing samples, adding solvents and extractants, to completing high-temperature hydrolysis and conversion and collecting the absorbent, and finally sending the test solution into the chromatograph for analysis, the entire process is uniformly scheduled and executed by a central control system. This design eliminates human error and time delays caused by sample transfer between steps. A single unit, operating unattended, can process no less than 80 samples per day by optimizing the operational sequence and parallel processing capabilities of each unit. This efficiency matches the daily sample throughput needs of customs ports, reducing cargo congestion caused by testing backlogs. Simultaneously, automation frees laboratory personnel from repetitive manual labor and handling of chemical reagents, allowing them to focus more on data review and system monitoring, thereby reducing the overall operational reliance on manual skills and corresponding labor costs.

[0040] 2. The test results are accurate and reliable.

[0041] This method employs a tandem design of "online extraction to remove inorganic chlorine" and "online high-temperature hydrolysis to convert organic chlorine," specifically distinguishing and measuring organic chlorine in crude oil. The first step uses a specific solvent system to extract and separate water-soluble inorganic chlorine. The second step quantitatively converts the organically bound chlorine in the remaining organic phase into chloride ions via high-temperature hydrolysis. This process, in principle, avoids interference from inorganic chlorine in the final detection results. Based on this pretreatment process, combined with stable ion chromatography detection, the system exhibits good repeatability at different concentration levels. Testing showed that the relative standard deviation (RSD) of multiple measurements on the same sample remained within 2%. This level of reproducibility improves the consistency of the detection data, providing a more stable and reliable basis for quality assessment.

[0042] 3. AI-driven intelligent optimization

[0043] To address the significant variations in crude oil sample properties, the system incorporates an intelligent condition recommendation unit. This unit's built-in model, based on input crude oil fundamental properties (such as density and viscosity) and historical testing data, recommends suitable chromatographic analysis parameters for the current sample, such as eluent gradient programs or column types. The model's predictions match the optimal manual empirical approach with a success rate of at least 95%. This model is not static but is periodically updated, incorporating data and results from new samples into its learning process, thereby gradually improving its adaptability to crude oils from different sources. Furthermore, the system performs self-diagnosis by automatically checking chromatographic peak shapes and the recovery rate of quality control samples. When data deviates from preset standards, it prompts for calibration or maintenance, contributing to the system's analytical stability during long-term operation.

[0044] 4. Deeply align with customs supervision requirements

[0045] The output of this system is not limited to a test report, but rather constitutes a workflow node linked to customs supervision operations. Upon completion of testing, the system automatically generates a structured electronic report containing traceable sample information, test data, and chromatograms, along with a QR code for rapid verification. The report can be automatically pushed to the designated customs data management platform. The system is configured with threshold rules based on national standards. When the detected organochlorine content exceeds the limit (e.g., 50 mg / kg), or when anomalies occur in the analytical data itself, the system immediately generates an alert and sends it to the terminals of relevant supervisory personnel. This function directly transforms the laboratory's testing capabilities into risk trigger signals in the regulatory chain, providing timely data support for rapid and accurate deployment and inspection. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the overall structure of the intelligent system of the present invention;

[0047] Figure 2 This is a flowchart illustrating the workflow of the automated sample pretreatment module of the present invention.

[0048] Figure 3 This is a schematic diagram showing the structure and data flow of the intelligent ion chromatography analysis module of the present invention;

[0049] Figure 4 This is a flowchart illustrating the logical judgment of the AI ​​intelligent diagnosis and calibration unit of the present invention. Detailed Implementation

[0050] The present invention will now be described in further detail with reference to specific embodiments and the accompanying drawings. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope or application of the present invention.

[0051] A method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system. This invention relies on a complete intelligent detection system, the overall structure of which is as follows: Figure 1 The attached diagram illustrates online extraction, which is a general term for separation operations, while the online extraction method used in this invention is its specific approach. The detailed process is as follows:

[0052] 1. Sample introduction: Select an appropriate amount of crude oil sample and place it in a polytetrafluoroethylene (PTFE) sample bottle. Enter the key information of the sample (including place of origin, crude oil type, batch number, etc.) into the central control and data processing AI platform, and bind the physical number of the sample bottle with the entered electronic information to achieve traceability of sample information.

[0053] 2. Scheme Retrieval: After the operator clicks "Start Detection", the central platform system control unit will intelligently match and retrieve the corresponding special detection scheme template from the preset scheme library based on the key information such as crude oil type and characteristics that have been entered. The template contains the basic framework such as pretreatment parameters and chromatographic analysis conditions that are suitable for this type of crude oil.

[0054] 3. Automated Pretreatment: The system executes an automated pretreatment process based on the retrieved template, sequentially completing precise weighing and dilution, online extraction and separation, online hydrolysis, and absorption liquid collection. The final product is a chloride-containing test solution, which is temporarily stored at 4°C to ensure stability. The specific workflow is as follows: Figure 2 As shown. Wherein:

[0055] (1) Precision weighing and dilution: Automatically transfer a quantitative crude oil sample to the reaction vessel, add a pre-proportioned dimethyl sulfoxide-toluene mixed solvent, and use ultrasonic oscillation to completely dissolve the crude oil to form a homogeneous organic solution;

[0056] (2) Online extraction and separation: Add ultrapure water (resistivity ≥18.2MΩ·cm) to the reaction vessel, and perform inorganic chlorine extraction by constant temperature oscillation at the set temperature. Then, the organic phase is separated by high-speed centrifugation and the organic phase is filtered through a filter membrane / phase separation membrane with a specific pore size to remove the aqueous phase containing inorganic chlorine.

[0057] (3) Online hydrolysis: The purified organic phase is sent into a programmable temperature controlled combustion furnace, where organic chlorine is completely converted into gaseous HCl / Cl2 under the conditions of set temperature, holding time and mixed airflow (O2 and Ar);

[0058] (4) Absorption liquid collection: The gaseous product is passed into an alkaline hydrogen peroxide absorption liquid of a preset volume and concentration, and is fully absorbed under a set stirring rate to generate a test liquid containing chloride ions.

[0059] 4. Intelligent Chromatographic Analysis: The intelligent injector automatically aspirates the test solution and injects it into the ion chromatograph. The composition and data flow of this module are as follows: Figure 3As shown, the intelligent condition recommendation unit combines the crude oil type and pretreatment parameters to match the optimal chromatographic analysis conditions (including column type, KOH elution program, flow rate, column temperature, suppressor current, etc.). The conductivity detector collects chromatographic signals at a set frequency, identifies chloride ion characteristic peaks, and integrates to calculate peak areas.

[0060] 5. AI Diagnostic Calibration and Reporting Alerts: The AI ​​intelligent diagnostic and calibration unit verifies key indicators such as chromatographic peak shape (tailing factor, symmetry), retention time drift, and quality control sample recovery rate to determine the reliability of the detection process and results. Its logical judgment process is as follows: Figure 4 As shown; if all indicators meet the preset qualification standards, the system automatically calculates the organic chlorine content of crude oil, generates a PDF test report with a QR code and uploads it to the designated database, and triggers or does not trigger a risk warning based on whether the content exceeds the limit of GB30520-2014.

[0061] Technical principle of the invention:

[0062] I. Sample Pretreatment Stage: Targeted Removal of Interference and Quantitative Conversion of Target Substances

[0063] This stage employs a series design to address the issues of dissolution, separation, and transformation sequentially.

[0064] 1. Role of the dissolving system: A mixed solvent of dimethyl sulfoxide (DMSO) and toluene is used. DMSO, as a strongly polar solvent, is responsible for dissolving polar components in crude oil; toluene, as a non-polar solvent, is responsible for dissolving non-polar substances such as asphaltene. The synergistic effect of their specific combination is to create a wide range of dissolving capabilities, ensuring that crude oils of different properties can form a homogeneous organic phase solution. This provides a stable reaction basis for subsequent steps and avoids errors caused by uneven dissolution.

[0065] 2. Function of the Inorganic Chlorine Removal Unit: This unit works synergistically through four steps: ultrapure water extraction, isothermal oscillation, high-speed centrifugation, and membrane separation. Ultrapure water utilizes the difference in partition coefficients to extract inorganic chloride ions into the aqueous phase; isothermal oscillation provides stable mass transfer conditions; high-speed centrifugation achieves rapid separation of the oil and water phases; and the hydrophobic membrane completely traps and removes residual aqueous phase. Its synergistic effect constitutes a complete chain from chemical extraction to physical separation, systematically eliminating interference from inorganic chlorine.

[0066] 3. The role of the organochlorine conversion unit: It completes the conversion through a programmable temperature-controlled combustion furnace in conjunction with a mixed gas flow of oxygen and inert gases. Programmed temperature rise ensures stable pyrolysis of the sample; high temperature provides the energy to break carbon-chlorine bonds; oxygen acts as an oxidant to promote the formation of gaseous chlorine products; and the inert gas regulates the atmosphere to prevent excessive reaction. The synergy of temperature, time, and gas flow creates a controllable conversion environment, ensuring the quantitative conversion of various organochlorine compounds into hydrogen chloride or chlorine gas.

[0067] 4. Function of the absorption unit: It employs an alkaline hydrogen peroxide absorbent. Sodium hydroxide neutralizes the acidic hydrogen chloride and absorbs chlorine gas, converting it into chloride ions; hydrogen peroxide ensures the reduction of chlorine gas to chloride ions. The synergy of these two components ensures that different forms of chlorine products are uniformly and quantitatively converted into chloride ions that can be directly measured by ion chromatography.

[0068] II. Intelligent Chromatographic Analysis Stage: Feature-Based Adaptive Condition Optimization

[0069] The core of this stage is to use data models to overcome the limitations of fixed chromatography methods.

[0070] 1. The role of the intelligent condition recommendation unit: The built-in machine learning model takes multiple physical properties of crude oil, such as density and viscosity, as input. These features collectively reflect the complexity of the sample. By learning the complex relationship between features and optimal chromatographic parameters (such as column type and elution gradient) in historical data, the model predicts and recommends the most suitable analytical conditions for the current sample matrix. Its synergistic effect lies in integrating multi-dimensional information, enabling the chromatographic system to adapt to different crude oils, thereby achieving better separation and quantitative accuracy under various conditions and improving the universality of the method.

[0071] III. Central Control and Data Processing Stage: Process Quality Closed Loop and Intelligent Decision Making

[0072] This stage ensures the reliability of the testing process and the effective output of results.

[0073] 1. The Role of the AI-Powered Intelligent Diagnosis and Calibration Unit: This unit simultaneously monitors multiple process quality indicators, including peak tailing factor, symmetry, retention time drift, and standard sample recovery rate. Each indicator reflects the system status from a different perspective. Their synergistic effect forms a cross-validated diagnostic network. While occasional fluctuations in a single indicator may not represent a systemic problem, abnormal correlations among multiple indicators more reliably indicate system drift (such as decreased column efficiency), thus accurately triggering calibration or maintenance commands. This multi-parameter collaborative diagnosis improves the reliability and efficiency of quality control.

[0074] IV. Summary of System-Level Synergistic Effect Principles

[0075] The overall technical effect of this invention stems from the deep interaction and collaboration of its three main modules:

[0076] The automated pretreatment module provides clean and quantitative test solutions for subsequent analysis, and its effectiveness directly affects the ease and accuracy of chromatographic analysis.

[0077] The intelligent chromatographic analysis module dynamically optimizes conditions based on sample characteristics, and the peak shape and quality data of its analysis results are used as key feedback to input into the optimization learning of the quality diagnosis model and preprocessing model of the central platform.

[0078] The central control and data processing AI platform coordinates the entire process and uses intelligent diagnostic results to ensure data reliability, while directly connecting the final results with regulatory requirements.

[0079] This closed-loop design of "sample preparation - intelligent analysis - quality control" enables the system to rapidly and accurately detect the organochlorine content in complex and diverse crude oil samples without human intervention. The combination of various technical units produces a synergistic effect that goes beyond the simple superposition of their individual functions, demonstrating the substantial characteristics and technological advancements of combined invention.

[0080] To make the present invention more fully disclosed, more specific embodiments are described below.

[0081] Example 1: Detection of Middle Eastern Light Crude Oil

[0082] S1. Sample Introduction: Take 5.0 mL of imported light crude oil from the Middle East and place it in a PTFE sample bottle. Enter the origin "Middle East" and type "light" on the central platform, and bind the sample bottle number.

[0083] S2, Scheme Call: Click Start, and the system will automatically call the "Light Crude Oil_Standard Scheme" template.

[0084] S3, Automatic Pre-processing:

[0085] (1) Precise weighing and dilution: Automatically weigh 0.5000g of crude oil, add 15mL of dimethyl sulfoxide-toluene mixed solvent (volume ratio 1:3), and sonicate for 6min.

[0086] (2) Online extraction and separation: Add 10 mL of ultrapure water (resistivity 18.2 MΩ·cm) and shake at 50 °C for 15 min. Centrifuge at 8000 r / min for 5 min, and separate the organic phase through a 0.22 μm hydrophobic filter membrane.

[0087] (3) Online high-temperature hydrolysis: The organic phase is fed into the combustion furnace and heated to 1000℃ and held for 30 min. A mixed gas flow of O2 (50 mL / min) and Ar (20 mL / min) is introduced.

[0088] (4) Absorption liquid collection: The gaseous product is passed into 20.0 mL of 0.1 mol / L alkaline hydrogen peroxide absorption liquid (9:1), stirred at 300 r / min for absorption, and the test solution is temporarily stored at 4℃.

[0089] S4. Intelligent Chromatographic Analysis: The intelligent condition recommendation unit outputs recommended conditions based on the "light" attribute: AS19 analytical column, KOH gradient elution, flow rate 1.0 mL / min, column temperature 30℃, suppressor current 50 mA. The system operates accordingly and acquires signals. The chloride ion peak retention time is identified as 4.2 min, and the peak area is calculated by integration.

[0090] S5, AI Diagnostic Calibration and Reporting Alerts:

[0091] AI diagnostics: Peak tailing factor was 1.0, symmetry was 1.0, retention time drift was +0.02 min, and the recovery rate of the 0.1 mg / kg quality control sample was 100.5%. All indicators were within the preset acceptable range.

[0092] Report Output: The system determines the results to be reliable and automatically generates a PDF report with a QR code, which is then uploaded to the General Administration of Customs database. Calculations show that the organic chlorine content of this batch of crude oil is 15.2 mg / kg, which meets the limit requirements of GB30520-2014 and did not trigger an alarm. The entire process for this batch of samples takes 18 minutes. The equipment adopts an unattended continuous operation mode and can process ≥80 batches of samples per day, balancing detection accuracy and efficiency.

[0093] Example 2: Detection of South American Heavy Crude Oil

[0094] S1. Sample Introduction: Take 5.0 mL of imported heavy crude oil sample from South America and place it in a PTFE sample vial. On the operation interface of the central control and data processing AI platform, enter the sample origin as "South America" ​​and select "heavy crude oil" as the crude oil type. Then, use a scanning device to successfully bind the physical number of the sample vial to the electronic information.

[0095] S2. Scheme Recall: After the operator clicks "Start Detection", the central platform's system control unit automatically retrieves and loads a preset template named "Heavy Crude Oil_Anti-Pollution Detection Scheme" from its scheme library based on the key information of "heavy quality". This template contains a parameter framework for optimized processing and analysis of high viscosity and high impurity crude oil.

[0096] S3, Automatic Pre-processing:

[0097] (1) Precision weighing and dilution: The precision weighing and dilution unit automatically transfers 0.4988g of crude oil sample to the reaction vessel. Then, 15.2mL of dimethyl sulfoxide-toluene mixed solvent (volume ratio of 1:3) is added quantitatively, and ultrasonic oscillation is started and continued for 5.5min to obtain a homogeneous organic solution.

[0098] (2) Online extraction and separation: The online extraction and separation unit automatically adds 9.5 mL of ultrapure water (resistivity ≥ 18.2 MΩ·cm) to the reaction vessel. The mixture is kept at 52 °C and shaken for 16 min to complete the inorganic chlorine extraction. Then, it is centrifuged at 8200 r / min for 5 min to separate the oil and water phases, and the upper organic phase is guided through a hydrophobic phase separation membrane with a pore size of 0.25 μm to completely remove the lower aqueous phase containing inorganic chlorine.

[0099] (3) Online high-temperature hydrolysis: The purified organic phase is transported to a programmable temperature-controlled combustion furnace. The system executes a heating program: heating from room temperature to 1010℃ at a rate of 20℃ / min, and holding at this temperature for 28min. During this process, a multi-channel gas flow controller precisely controls the flow rate of oxygen at 52mL / min and argon at 19mL / min to introduce a mixed gas into the furnace, ensuring that the organic chlorine is completely converted into gaseous hydrogen chloride / chlorine.

[0100] (4) Absorption liquid collection: The generated high-temperature gaseous product is introduced into an absorption bottle containing 20.0 mL of alkaline hydrogen peroxide absorption liquid with a concentration of 0.1 mol / L. It is fully absorbed at a stirring rate of 300 r / min, and the resulting chloride ion-containing test solution is transferred to a 4℃ cold storage for temporary storage.

[0101] S4. Intelligent Chromatographic Analysis: The intelligent injector automatically aspirates and injects the analyte. The intelligent condition recommendation unit, based on the "heavy crude oil" type and potentially associated physical property data, calls upon the model to optimize conditions, ultimately recommending and executing the following analytical conditions: using a contamination-resistant AS23 column, KOH gradient elution, flow rate set to 1.18 mL / min, column oven temperature set to 31℃, and suppressor current set to 58 mA. The conductivity detector acquires the chromatographic signal at a frequency of 10 Hz.

[0102] S5, AI Diagnostic Calibration and Reporting Alerts:

[0103] AI diagnostics: The chromatographic peak tailing factor was 1.15, the symmetry was 0.96, the retention time drift was -0.02 min, and the recovery rate of the 0.1 mg / kg quality control sample analyzed simultaneously was 101.2%. All process quality indicators were within the preset acceptable range.

[0104] Reporting and Early Warning: The results reporting and risk warning unit automatically generates a PDF test report containing all information, along with a traceability QR code, and uploads it to the General Administration of Customs database. Since the test result of 42.3 mg / kg did not exceed the limit of 50 mg / kg, and no abnormalities were found in the process diagnosis, no risk warning was triggered. The entire processing time for this batch of samples was 19 minutes. The equipment supports unattended continuous operation, with a stable daily sample processing capacity of ≥80 batches, suitable for the batch testing needs of heavy crude oil.

[0105] Example 3: Detection of high-wax crude oil from West Africa

[0106] S1. Sample Introduction: Take 5.5 mL of high-wax crude oil sample from West Africa and place it in a polytetrafluoroethylene (PTFE) sample bottle. On the operation interface of the central control and data processing AI platform, enter the sample origin as "West Africa" ​​and the crude oil type as "Special_High Wax", and bind and associate the unique physical number of the sample bottle with the electronic declaration information.

[0107] S2. Scheme Recall: After the operator clicks "Start," the central platform's system control unit intelligently selects and loads the "High-Wax Crude Oil Dedicated Detection Scheme" template from the preset scheme library based on the "Special_High Wax" type tag. This template optimizes pretreatment parameters to improve processing efficiency and prevent residual carbon, taking into account the tendency of high-wax crude oil to coke.

[0108] S3, Automatic Pre-processing:

[0109] (1) Precision weighing and dilution: The precision weighing and dilution unit automatically and accurately transfers 0.5035g of crude oil sample to a closed reaction vessel, quantitatively adds 14.5mL of dimethyl sulfoxide-toluene mixed solvent (volume ratio 1:3.5), starts ultrasonic oscillation for 7min to completely dissolve the high wax crude oil and form a uniform and transparent organic phase solution.

[0110] (2) Online extraction and separation: The online extraction and separation unit automatically adds 10.2 mL of ultrapure water (resistivity ≥ 18.2 MΩ·cm) to the reaction vessel, and then extracts inorganic chlorine by constant temperature shaking at 51 °C for 12 min. After shaking, the oil and water are separated by centrifugation at 8300 r / min for 5 min. The supernatant organic phase passes through a phase separation membrane with a pore size of 0.22 μm, while the aqueous phase containing inorganic chlorine is completely retained and removed.

[0111] (3) Online high-temperature hydrolysis: The purified organic phase is automatically fed into a programmable temperature controlled combustion furnace and the optimized program is executed: the temperature is raised to 1030℃ and held for 25 min. A multi-channel gas flow controller precisely controls the oxygen flow rate to 53 mL / min and the argon flow rate to 18 mL / min to ensure that the organic chlorine is fully converted into HCl / Cl2.

[0112] (4) Absorption liquid collection: The gaseous products generated by high-temperature hydrolysis are introduced into a collection unit containing 20.0 mL of 0.1 mol / L alkaline hydrogen peroxide absorption liquid. Absorption is completed at a stirring rate of 300 r / min. The test liquid is automatically transferred to a 4℃ cold storage location for temporary storage.

[0113] S4. Intelligent Chromatographic Analysis: The intelligent injector automatically aspirates the analyte and injects it into the chromatographic system. Considering the potential complex matrix interference from high-wax crude oil, the intelligent condition recommendation unit recommends and executes the following analytical conditions: using a fouling-resistant AS23 column, KOH gradient elution, flow rate 1.15 mL / min, column temperature 32℃, suppressor current 59 mA, and a conductivity detector acquiring the chromatographic signal at a frequency of 10 Hz.

[0114] S5, AI Diagnostic Calibration and Reporting Alerts:

[0115] AI Diagnosis: The data acquisition and processing unit successfully identified the chloride ion characteristic peak, and the AI ​​intelligent diagnosis and calibration unit performed process quality verification: the chromatographic peak tailing factor was 1.18, the symmetry was 0.92, the retention time drift was +0.04 min, the recovery rate of the 0.1 mg / kg quality control sample was 100.1%, and all indicators were within the qualified range.

[0116] Results Calculation and Reporting: Based on the peak area integration results and calibration curve, the system calculated the organochlorine content of the high-wax crude oil sample to be 8.9 mg / kg. It automatically generated a PDF test report containing complete information, chromatograms, and AI diagnostic conclusions, along with a traceability QR code, and uploaded it to the General Administration of Customs database. The test result was far below the 50 mg / kg limit, and no risk warning was triggered. The entire processing time for this batch of samples was 22 minutes. With unattended continuous operation, the equipment can process ≥80 batches of samples per day, ensuring both accuracy in detecting heat-sensitive components and high batch processing efficiency.

[0117] Example 4: Detection of thermosensitive components in Southeast Asian crude oil

[0118] S1. Sample Introduction: Take 5.0 mL of imported crude oil sample containing heat-sensitive components from Southeast Asia and place it in a PTFE sample bottle. On the central platform operation interface, enter the origin as "Southeast Asia" and the crude oil type as "Special_Contains Heat-Sensitive Components", and complete the association and binding of the sample bottle number and electronic information.

[0119] S2. Scheme Recall: Based on the "Special_Contains Thermosensitive Components" type, the system automatically retrieves the preset "Specific Detection Scheme for Crude Oil Containing Thermosensitive Components" template. This template, through optimized pretreatment parameters, ensures the gentle and complete conversion of thermosensitive organochlorides, avoiding cracking losses at high temperatures.

[0120] S3, Automatic Pre-processing:

[0121] (1) Precise weighing and dilution: The system automatically weighs 0.4992g of crude oil sample, adds 15.5mL of dimethyl sulfoxide-toluene mixed solvent (volume ratio 1:2.5), and sonicates for 8min to fully dissolve it.

[0122] (2) Online extraction and separation: Add 9.8 mL of ultrapure water and extract inorganic chlorine by shaking at 47 °C for 22 min using a constant temperature shaker. Then centrifuge at 7900 r / min and remove the aqueous phase through a 0.20 μm phase separation membrane.

[0123] (3) Online hydrolysis: The organic phase is fed into a programmable temperature controlled combustion furnace and hydrolyzed at 960℃ with parameters adapted to the heat-sensitive components for 35 min. A multi-channel gas flow controller provides a mixed gas flow of 47 mL / min O2 and 23 mL / min Ar to ensure complete conversion of organochlorine compounds.

[0124] (4) Absorption liquid collection: The gaseous product was completely absorbed by 20.0 mL of standard alkaline hydrogen peroxide absorption liquid, and the test solution was temporarily stored at 4℃.

[0125] S4. Intelligent Chromatographic Analysis: The test solution is injected into the chromatograph via an intelligent injector. The intelligent condition recommendation unit determines that the matrix is ​​relatively clean after mild pretreatment and recommends using a high-separation-efficiency AS19 analytical column, a standard KOH gradient elution program, a flow rate of 1.0 mL / min, a column temperature of 30℃, a suppressor current of 50 mA, and a conductivity detector to acquire a high signal-to-noise ratio chromatographic signal.

[0126] S5, AI Diagnostic Calibration and Reporting Alerts:

[0127] AI Diagnosis: The results of AI intelligent diagnosis and calibration unit verification show that the chloride ion peak tailing factor is 1.02, the symmetry is 1.06, the retention time drift is only -0.01 min, and the recovery rate of 0.1 mg / kg quality control sample is 99.2%. All data are better than the preset qualified standard, proving that the detection parameters are suitable for the heat-sensitive component crude oil, the conversion is complete, and the analysis process is stable.

[0128] Results Calculation and Reporting: The calculated organic chlorine content of the crude oil containing the heat-sensitive component was 5.1 mg / kg. The system automatically generated a standard format test report and uploaded it to the General Administration of Customs database with a QR code. The results were compliant, and no warnings were triggered. This example demonstrates the adaptability of the detection method to crude oil containing special components. The entire processing time for this batch of samples was 22 minutes. When the equipment is running unattended continuously, it can process ≥80 batches of samples per day, ensuring both accuracy in detecting heat-sensitive components and batch processing efficiency.

[0129] Example 5: Detection of West African blended crude oil

[0130] S1. Sample Introduction: Take 5.3 mL of West African blended crude oil (its properties are between typical light and heavy crude oil) and place it in a sample vial. Enter the origin "West Africa" ​​and type "blended crude oil" on the central platform to complete the information association.

[0131] S2, Scheme Invocation: Based on the "Mixed Crude Oil" label, the system invokes the "General Adaptive Detection Scheme" template and relies on subsequent intelligent units to perform fine-grained condition optimization.

[0132] S3, Automatic Pre-processing:

[0133] (1) Precise weighing and dilution: Automatically weigh 0.5010g of sample, add 15.0mL of dimethyl sulfoxide-toluene mixed solvent (volume ratio 1:3.0), and sonicate for 5min.

[0134] (2) Online extraction and separation: Add 10.0 mL of ultrapure water, keep the temperature at 50 °C and shake for 15 min, centrifuge at 8000 r / min for 5 min, and separate the organic phase through a 0.22 μm filter membrane.

[0135] (3) Online high-temperature hydrolysis: The following parameters were used: hydrolysis temperature 1000℃, heat preservation for 30 min, oxygen 50 mL / min and argon 20 mL / min.

[0136] (4) Absorption solution collection: Absorb with 20.0 mL of absorption solution and store the test solution at 4℃.

[0137] S4. Intelligent Chromatographic Analysis: The intelligent condition recommendation unit analyzes the default physical property parameters of "mixed crude oil" based on the built-in model, determines that it is closer to the characteristics of light oil, and outputs recommended conditions: select AS19 analytical column, KOH gradient elution program is 0.01mol / L for 0-5min, increase to 0.105mol / L for 5-10min, maintain 0.105mol / L for 10-15min, flow rate 1.1mL / min, column temperature 30℃, and the system performs the analysis accordingly.

[0138] S5, AI Diagnostic Calibration and Reporting Alerts:

[0139] AI diagnosis: The system ran smoothly, and the diagnostic data were as follows: tailing factor 1.10, symmetry 0.98, retention time drift +0.01 min, quality control sample recovery rate 100.5%, and all indicators met the preset standards, verifying the effectiveness of the intelligent recommendation conditions.

[0140] Results Calculation and Reporting: The final determination of the organochlorine content in the mixed crude oil was 22.5 mg / kg. The results report and risk warning unit generated a standard electronic report with a QR code and uploaded it to the General Administration of Customs database. The test results were within the limits, the process was normal, and no warnings were generated. This example demonstrates the system's ability to reliably detect samples when the initial sample information is not accurate enough, through intelligent model adaptive matching. The entire process time for this batch of samples was 17 minutes. In unattended operation mode, the equipment can process ≥80 batches of samples per day, meeting the high-efficiency requirements for batch testing of mixed crude oil.

[0141] Comparative Example 1: Hydrolysis temperature deviates from standard conditions

[0142] This comparative example uses Middle Eastern light crude oil from Example 1 as the test sample. Only the temperature parameters of the online hydrolysis step were modified; all other test steps and parameters remained the same as in Example 1. The specific modifications are as follows:

[0143] Modifications: In the online high-temperature hydrolysis step, the hydrolysis temperature is adjusted from 1000℃ in Example 1 to 850℃, the holding time remains 30min, and the parameters of the O2 and Ar mixed gas flow remain unchanged.

[0144] The remaining steps (sample introduction, protocol call, precise weighing and dilution, online extraction and separation, absorption liquid collection, intelligent chromatographic analysis, AI diagnostic calibration and report warning basic process and parameters) are the same as in Example 1.

[0145] Detection Results and Analysis: The system's judgment was unreliable, triggering a quality warning. Calculations showed that the organic chlorine content in this batch of crude oil was 8.7 mg / kg, significantly deviating from the standard value of 15.2 mg / kg in Example 1. AI diagnostics indicated a peak tailing factor of 1.25, and a recovery rate of 92.3% for the 0.1 mg / kg quality control sample. This was due to the excessively low hydrolysis temperature leading to incomplete conversion of organic chlorine, thus affecting the accuracy of the detection.

[0146] Comparative Example 2: Extraction time deviates from standard conditions

[0147] This comparative example uses Middle Eastern light crude oil from Example 1 as the test sample. Only the isothermal oscillation time of the online extraction and separation steps was modified; all other detection steps and parameters are the same as in Example 1. Specific modifications are as follows:

[0148] Modifications: In the online extraction and separation steps, the isothermal oscillation time is shortened from 15 min in Example 1 to 5 min, while the extraction temperature, centrifugation speed, filter membrane pore size, and other parameters remain unchanged.

[0149] The remaining steps (sample introduction, protocol call, precision weighing and dilution, online high-temperature hydrolysis, absorption liquid collection, intelligent chromatographic analysis, AI diagnostic calibration and report warning basic process and parameters) are the same as in Example 1.

[0150] Detection Results and Analysis: The system's judgment results showed low reliability, triggering an alert. Calculations showed that the organic chlorine content in this batch of crude oil was 12.1 mg / kg, deviating from the standard value of 15.2 mg / kg in Example 1. AI diagnostics showed a 95.8% recovery rate for the 0.1 mg / kg quality control sample. This was because the extraction time was too short, resulting in incomplete separation of inorganic chlorine, and the residual inorganic chlorine interfered with the organic chlorine detection results.

[0151] Comparative Example 3: Solvent ratio deviates from standard conditions

[0152] This comparative example uses Middle Eastern light crude oil from Example 1 as the test sample. Only the volume ratio of the dimethyl sulfoxide-toluene mixed solvent in the precise weighing and dilution steps was modified. All other test steps and parameters remained the same as in Example 1. The specific modifications are as follows:

[0153] Modifications: In the precise weighing and dilution steps, the volume ratio of the dimethyl sulfoxide-toluene mixed solvent is adjusted from 1:3 in Example 1 to 1:5, while the total solvent volume remains 15 mL, and the ultrasonic oscillation time remains unchanged.

[0154] The remaining steps (sample introduction, protocol call, online extraction and separation, online high-temperature hydrolysis, absorption liquid collection, intelligent chromatographic analysis, AI diagnostic calibration and report warning basic process and parameters) are the same as in Example 1.

[0155] Detection Results and Analysis: The system's judgment was unreliable, triggering a serious warning. Calculations showed that the organic chlorine content of this batch of crude oil was 18.5 mg / kg, significantly deviating from the standard value of 15.2 mg / kg in Example 1. AI diagnostics showed a peak tailing factor of 1.32, symmetry of 0.88, retention time drift of -0.06 min, and a recovery rate of 94.5% for the 0.1 mg / kg quality control sample. The reason for this is that the excessively high toluene content led to incomplete dissolution of the crude oil, and subsequent filtration blockage affected sample purity, ultimately resulting in distorted detection results.

[0156] Summary and Analysis:

[0157] The intelligent detection method for organochlorine compounds in crude oil proposed in this invention achieves efficient and reliable detection of crude oils across multiple matrices by precisely matching core parameters through a "crude oil type-dedicated solution." As shown in Examples 1-5, this method is adaptable to five types of crude oil: light, heavy, high-wax, containing thermosensitive components, and mixed crude oils. The relative accuracy error is 0.7%-2.0%, and the detection results all meet standard requirements. Furthermore, it can optimize pretreatment and chromatographic conditions according to crude oil characteristics, such as raising the temperature to prevent coking in high-wax crude oils and hydrolyzing thermosensitive components at low temperatures for extended periods, demonstrating strong matrix adaptability. A single device can process ≥80 batches of samples per day unattended, effectively solving problems such as incomplete conversion and residual interference. It balances detection reliability and efficiency, enabling reliable detection in multiple scenarios, demonstrating significant technological advancement and outstanding practical application value.

[0158] Compared with Comparative Examples 1-3, the present invention effectively avoids the problems caused by parameter deviations: In Comparative Example 1, insufficient hydrolysis temperature resulted in incomplete conversion of organic chlorine, with a relative error of 42.0%; In Comparative Example 2, the extraction time was too short, causing interference from inorganic chlorine residues, with an error of 19.3%; In Comparative Example 3, improper solvent ratio led to insufficient dissolution of crude oil, with an error of 23.3%. In contrast, the present invention significantly reduced detection errors and improved the reliability of results through precise parameter adaptation.

[0159] In summary, this invention, relying on automated pre-processing, intelligent solution matching, and AI diagnostic calibration, solves the pain points of poor adaptability and unstable results of existing technologies. It improves detection accuracy, precision, and adaptability to multiple scenarios, and has practical application value, which can meet the detection needs of customs supervision, crude oil processing, and other fields.

[0160] Non-limiting and non-exclusive embodiments will be described with reference to the following figures, wherein the same reference numerals denote the same parts unless otherwise specifically stated.

[0161] Those skilled in the art will recognize that numerous variations are possible with respect to the above description, and the embodiments are merely illustrative of one or more specific implementations.

[0162] Although exemplary embodiments of the invention have been described and illustrated, those skilled in the art will understand that various changes and substitutions can be made thereto without departing from the spirit of the invention. Furthermore, many modifications can be made to adapt specific situations to the doctrine of the invention without departing from the central concepts of the invention described herein. Therefore, the invention is not limited to the specific embodiments disclosed herein, but may include all embodiments and equivalents that fall within the scope of the invention.

[0163] The above description, in conjunction with specific embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various substitutions or modifications can be made to these described embodiments without departing from the inventive concept, and all such substitutions or modifications should be considered within the scope of protection of the present invention.

[0164] Although the invention and its advantages have been described in detail, it should be understood that various changes, substitutions, and modifications can be made without departing from the spirit and scope of the invention. Furthermore, the scope of the invention is not limited to the specific embodiments of the processes, compositions of matter, methods, and steps described in the specification. From the disclosure of this invention, those skilled in the art will readily utilize existing or future processes, compositions of matter, methods, or steps that substantially perform the same function or achieve the same results as the corresponding embodiments described herein. Therefore, the appended claims are intended to encompass such processes, compositions of matter, methods, or steps.

Claims

1. A crude oil organochlorine content detection system based on ion chromatography and an intelligent optimization system, characterized in that, include: Automated sample pretreatment module, intelligent ion chromatography analysis module, and central control and data processing AI platform; The automated sample pretreatment module is connected to the flow path of the intelligent ion chromatography analysis module. The central control and data processing AI platform is electrically connected to the automated sample pretreatment module and the intelligent ion chromatography analysis module. The automated sample pretreatment module includes a precision weighing and dilution unit, an online extraction and separation unit, an online combustion / high-temperature hydrolysis unit, and an absorption liquid quantitative collection unit connected in sequence. The intelligent ion chromatography analysis module includes an intelligent injector, an online purification and protection column system, a chromatography pump and column oven, a conductivity detector, and an intelligent condition recommendation unit. The central control and data processing AI platform includes a system control unit, a data acquisition and processing unit, an AI intelligent diagnosis and calibration unit, and a result reporting and risk warning unit.

2. The crude oil organochlorine content detection system based on ion chromatography and intelligent optimization system according to claim 1, characterized in that, The online extraction and separation unit includes a constant temperature oscillator, a high-speed centrifuge, and a phase separation membrane; the online combustion / high-temperature hydrolysis unit includes a programmable temperature controlled combustion furnace and a multi-channel gas flow controller.

3. The crude oil organochlorine content detection system based on ion chromatography and intelligent optimization system according to claim 1, characterized in that, The intelligent condition recommendation unit has a built-in combined model, whose input parameters include crude oil density, viscosity, and hydrocarbon ratio.

4. The crude oil organochlorine content detection system based on ion chromatography and intelligent optimization system according to claim 1, characterized in that, The AI-powered intelligent diagnostic and calibration unit includes preset tolerance ranges for determining chromatographic peak tailing factors, symmetry, retention time drift, and standard sample recovery rates.

5. The crude oil organochlorine content detection system based on ion chromatography and intelligent optimization system according to claim 3, characterized in that, The intelligent condition recommendation unit has a periodic update program for its model, and its model parameters are automatically updated based on newly input sample data and corresponding analysis results.

6. A method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system, characterized in that, The detection system used as described in any one of claims 1-5 includes the following steps: S1. Sample Introduction: Place the crude oil sample into the system and associate it with the declaration information; S2, Scheme Recall: The system recalls the testing scheme based on the sample information; S3. Automatic pretreatment: The system performs automated sample pretreatment to obtain the test solution; S4. Intelligent Chromatography Analysis: The system performs ion chromatography analysis based on recommended analytical conditions and collects data; S5, AI Diagnosis, Calibration, and Reporting Warning: The system diagnoses and verifies the analysis process and results, and generates reports.

7. The method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system according to claim 6, characterized in that, Step S3 includes: (1) Precision weighing and dilution: The crude oil sample is automatically weighed and dissolved in a dimethyl sulfoxide-toluene mixed solvent; (2) Online extraction and separation: Ultrapure water is added for extraction, and the aqueous phase is removed by centrifugation and membrane separation; (3) Online high-temperature hydrolysis: The separated organic phase is subjected to high-temperature hydrolysis; (4) Absorption liquid collection: The hydrolysis products are absorbed using alkaline hydrogen peroxide absorption liquid to obtain the test solution.

8. The method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system according to claim 6, characterized in that, In step S4, the system recommends different analytical column types or elution gradients for different types of crude oil.

9. The method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system according to claim 6, characterized in that, In step S5, when any diagnostic indicator exceeds the preset tolerance range, the system triggers a review or maintenance command.

10. The method for detecting organochlorine content in crude oil based on ion chromatography and an intelligent optimization system according to claim 9, characterized in that, Step S5 further includes: comparing the test results with preset limits, generating an electronic test report, and uploading it to the database; when the test results exceed the limits or the data is abnormal, the system sends an early warning message to the designated monitoring terminal.

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