Chromatographic detection correction method and system

Abstract

The invention provides a chromatographic detection correction method and system, and the method comprises the steps: obtaining a first detection result of each component of chromatographic detection of a prepared detection comparison oil sample by an evaluation instrument of each evaluation unit, carrying out initial evaluation, and removing the first detection result which does not meet a preset requirement; analyzing the remaining first detection results, and screening out the evaluated instruments with qualified first detection results and unqualified evaluated instruments; selecting a reference evaluation instrument from the qualified evaluation instruments, obtaining a second detection result of the reference evaluation instrument on the reconfigured correction comparison oil samples with the at least two concentrations and a third detection result of the unqualified evaluation instruments on the correction comparison oil samples, and performing iterative correction to obtain a correction result of the reconfigured correction comparison oil samples with the at least two concentrations; according to the method, the objective and quantitative evaluation of the detection level of each unit is realized, the overall accuracy and reliability of the chromatographic detection result are comprehensively improved, and the safe operation of a power grid is ensured.

Description

Technical Field

[0001] This invention relates to the field of chromatographic analysis technology for electrically filled oil equipment, and in particular to a chromatographic detection correction method and system. Background Technology

[0002] Insulating oil, as one of the core insulating media in oil-filled electrical equipment such as oil-immersed transformers, reactors, current transformers, and bushings, directly reflects the health level of these devices through performance testing. Chromatographic testing, as one of the most sensitive methods for detecting early faults in oil-filled electrical equipment, is widely used. Industry requirements stipulate that chromatographic analysis should be performed monthly for 1000kV oil-immersed power transformers and reactors; every three months for 330kV~750kV equipment; every six months for 220kV equipment; and once a year for 35kV~110kV equipment. Therefore, the accuracy of chromatographic test results directly affects the accuracy of the health level assessment of all operating oil-filled electrical equipment in the company. Given that chromatography is one of the most sensitive methods for detecting early faults in oil-filled electrical equipment, inaccurate testing can easily lead to misdiagnosis or missed diagnosis of equipment faults, posing a significant threat to the safe and stable operation of the power grid.

[0003] However, the chromatographic detection process is complex, and many factors affect the accuracy of the results. The skill levels of personnel and the condition of instruments vary among different units. In addition, there are currently no national standard material production units on the market that can produce chromatographic analysis standards. How to evaluate the chromatographic detection of various units and correct the chromatographic detection results of unqualified units has become a major problem for chromatographic detection personnel in various units.

[0004] While some methods exist for evaluating chromatographic detection results, they generally suffer from inconsistent evaluation standards and imperfect correction methods. In particular, the lack of effective correction mechanisms to ensure the accuracy of the final results when deviations occur can easily lead to misdiagnosis or missed diagnosis of equipment malfunctions, thus reducing the safety of the power grid. Summary of the Invention

[0005] This invention provides a chromatographic detection correction method and system for objectively and quantitatively evaluating the detection level of each unit and effectively and quickly correcting problematic detection results online, thereby comprehensively improving the overall accuracy and reliability of chromatographic detection results and providing a solid guarantee for accurate diagnosis of the status of power equipment and safe operation of the power grid.

[0006] On one hand, the present invention provides a chromatographic detection correction method, which includes: Obtain the first detection results of various components of the oil sample by the chromatographic analysis of the prepared test ratio using the instruments of each participating unit; An initial evaluation is performed on the first test results of each participating instrument, and the first test results that do not meet the preset requirements are eliminated. The remaining first test results are analyzed to screen out the qualified and unqualified instruments for evaluation. Select a benchmark instrument from the qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two corrected comparison oil samples of the reconstituted concentration. Obtain the third test results of each corrected comparison oil sample from the unqualified participating instruments, and iteratively correct the third test results based on the second test results until the deviation between the corrected results and the second test results is less than the first preset deviation threshold.

[0007] On the other hand, the present invention also provides a chromatographic detection correction system, comprising: The acquisition module is used to acquire the first detection results of various components of the prepared test ratio oil sample by the participating instruments of each participating unit through chromatographic detection; The elimination module is used to perform an initial evaluation of the first test results of each participating instrument and eliminate the first test results that do not meet the preset requirements. The screening module is used to analyze the remaining first test results and screen out the participating instruments that have passed the first test and those that have failed. The selection module is used to select a benchmark instrument from qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two reconstituted comparison oil samples with corrected concentrations. The correction module is used to obtain the third test results of each correction comparison oil sample from the unqualified evaluation instrument, and to iteratively correct the third test results based on the second test results until the deviation between the correction results and the second test results is less than the first preset deviation threshold.

[0008] The chromatographic detection correction method and system provided by this invention first eliminates unstable data through initial evaluation, analyzes the remaining first detection results, and screens out unqualified evaluation instruments with systematic biases in their detection results. Then, a benchmark evaluation instrument comparison and iterative correction algorithm is introduced. Using the detection value of the benchmark evaluation instrument as the standard, the correction parameters of the unqualified evaluation instruments are dynamically calculated, and through multiple iterative calculations, the detection results are gradually made to approach the benchmark average value. This achieves an objective and quantitative evaluation of the detection level of each unit, and effectively and quickly corrects the problematic detection results, thereby comprehensively improving the overall accuracy and reliability of chromatographic detection results and providing a solid guarantee for the accurate diagnosis of the status of power equipment and the safe operation of the power grid. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0010] Figure 1 This is a schematic flowchart of the chromatographic detection correction method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the chromatographic detection correction system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0011] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0012] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0013] Figure 1 This is a schematic flowchart of the chromatographic detection correction method provided in an embodiment of the present invention.

[0014] like Figure 1 As shown, the chromatographic detection correction method provided in this embodiment of the invention can be executed by an electronic device, and the method mainly includes the following steps: 101. Obtain the first detection results of various components of the oil sample by the chromatographic detection of the prepared detection ratio by the instruments of each participating unit; 102. Conduct an initial evaluation of the first test results of each participating instrument and eliminate the first test results that do not meet the preset requirements; 103. Analyze the remaining first test results and screen out the participating instruments that have qualified first test results and those that have not. 104. Select a benchmark instrument from the qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two corrected comparison oil samples of reconstituted concentrations. 105. Obtain the third test results of each corrected comparison oil sample from the unqualified participating instruments, and iteratively correct the third test results based on the second test results until the deviation between the corrected results and the second test results is less than the first preset deviation threshold.

[0015] In a specific implementation process, the participating units refer to the various laboratories or testing institutions involved in the chromatographic detection evaluation. The participating instruments refer to the gas chromatographs used by each unit for chromatographic detection. The test comparison oil sample refers to a pre-prepared insulating oil sample containing known concentrations of multiple gaseous components (such as hydrogen (H2), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), ethane (C2H6), ethylene (C2H4), and acetylene (C2H2), used to evaluate the instrument's detection performance. The first detection result refers to the gas concentration data obtained by the participating instrument performing two repeated tests on the test comparison oil sample. The initial evaluation refers to judging whether the detection process is stable and reliable based on the difference between the two detection results of the same instrument. The benchmark participating instrument refers to an instrument arbitrarily selected from those with qualified detection results; its detection result serves as a reference benchmark for correction. The correction comparison oil sample refers to a newly prepared oil sample containing at least two different concentrations, used for corrective training of unqualified participating instruments. The second detection result refers to the detection data of the benchmark participating instrument on the correction comparison oil sample. The third test result refers to the test data of the unqualified evaluation instrument for the same corrected comparison oil sample. Iterative correction refers to the process of gradually bringing the test results of the unqualified evaluation instrument closer to the benchmark value through multiple calculations and adjustments. The first preset deviation threshold refers to the maximum acceptable deviation between the corrected result and the benchmark value, which is set in advance.

[0016] In detail, in this embodiment, the organizer first prepares a test comparison oil sample containing seven characteristic gas components and distributes it to each participating unit. During this process, appropriate measures are taken to ensure that the test comparison oil sample does not undergo significant changes during transportation compared to when it was freshly prepared. Each unit uses its own testing instrument to perform two repeated tests on the oil sample and reports the first test result.

[0017] In a specific implementation process, to ensure the comparability of test data from all participating units, the mechanical oscillation method was uniformly adopted for this comparison. After the gas was extracted from the oil, it was immediately and rapidly transferred to a glass syringe of a specified volume to avoid selective re-dissolution of gas components when the gas came into contact with the degassed oil. The extracted gas sample was analyzed as soon as possible to avoid gas escape due to prolonged storage.

[0018] It should be noted that when the instrument being evaluated performs two repeated tests on the oil sample, the various components being tested can be individual gaseous components or mixtures of multiple gaseous components. For example, in this embodiment, in addition to testing the aforementioned seven individual components, it is also necessary to test the total hydrocarbon component formed by the mixture of methane (CH4), ethane (C2H6), ethylene (C2H4), and acetylene (C2H2), which is equivalent to a total of eight components.

[0019] In this embodiment, for each participating instrument, two first detection results can be obtained; the average value of the two first detection results can be calculated; if the average value of the first detection results is greater than a preset concentration threshold, it is determined whether the difference between the two detection results is less than a second preset deviation threshold; the second preset deviation threshold is a first proportion of the average value of the first detection results; if the difference between the two first detection results is less than the second preset deviation threshold, it is determined that the preset requirements are met; if the difference between the two first detection results is greater than or equal to the second preset deviation threshold, it is determined that the preset requirements are not met. If the average value of the first detection results is less than or equal to the preset concentration threshold, it is determined whether the difference between the two first detection results is less than a third preset deviation threshold; the third preset deviation threshold is the sum of a second proportion of the average value of the first detection results and a preset multiple of the minimum detection concentration of the component corresponding to the first detection result; if the difference between the two first detection results is less than the third preset deviation threshold, it is determined that the preset requirements are met; if the difference between the two first detection results is greater than or equal to the third preset deviation threshold, it is determined that the preset requirements are not met.

[0020] For example, when calculating the average of two initial detection results, if the average is greater than 10 μL / L, the difference between the two initial detection results must not exceed 10% of the average; if the average is not greater than 10 μL / L, the difference between the two initial detection results must not exceed the sum of 15% of the average and twice the minimum detection concentration of the component. Both of these conditions indicate that the data is reliable and qualify the instrument as an initial qualified evaluation instrument. Instruments that do not meet the above requirements are considered unqualified evaluation instruments, and their detection data will be discarded.

[0021] For the remaining first detection results that passed the initial evaluation, an iterative robust statistical algorithm is used for analysis. Specifically, the robust mean and robust standard deviation for each component can be calculated; for each value corresponding to the first detection result, the difference between the value corresponding to the first detection result and the robust mean is calculated, and the absolute value of the quotient of the first detection result and the robust standard deviation is used as the Z-score for each component; instruments with a Z-score greater than a preset pass threshold are considered unqualified instruments, and instruments with a Z-score less than or equal to the preset pass threshold are considered qualified instruments.

[0022] The robust average is a central tendency value calculated using an iterative algorithm that resists the influence of outliers. The robust standard deviation is a measure of data dispersion calculated based on robust statistical principles that resists the influence of outliers. The Z-score is a standardized score representing the degree to which a single test value deviates from the central tendency of the dataset, expressed as a multiple of the standard deviation. The formula is: |Z| = |(single value - robust average) / robust standard deviation|.

[0023] The preset acceptable threshold is the Z-score limit for determining whether the instrument's test results are acceptable, and can be set to 2.

[0024] In this embodiment, for a given component, the first test results reported by all qualified participating instruments are collected, and an iterative robust statistical algorithm is used to calculate the robust mean and robust standard deviation of the data set. These two statistics are insensitive to any possible outliers and better represent the detection level of most normal instruments.

[0025] Subsequently, for each instrument's detection value of that component, the deviation is first obtained by subtracting the robust average value from the component detection value. Then, this deviation is divided by the robust standard deviation, and finally, the absolute value is taken. This score represents how many standard deviation units the instrument's result deviates from the "mainstream consensus."

[0026] In a specific implementation process, a preset pass / fail threshold, such as 2, can be set in advance. The |Z| value of each instrument is compared with 2: if |Z|≤2, it means that the instrument's test result is consistent with the mainstream result and is judged as pass; if |Z|>2, it means that the instrument's test result deviates significantly from the mainstream, indicating a systematic error, and is judged as fail, and marked as a "problem device" requiring further correction. This method can objectively and quantitatively identify instruments with accuracy problems.

[0027] In one specific implementation process, one qualified instrument is selected as the benchmark instrument. The organizer prepares two corrected comparison oil samples with different concentrations, which are then tested by the benchmark instrument to obtain a second test result as a true reference. Subsequently, each unqualified instrument tests the same two oil samples to obtain a third test result.

[0028] Then, the third detection result is iteratively corrected based on the second detection result until the deviation between the corrected result and the second detection result is less than a first preset deviation threshold. The iterative process includes: determining the baseline average value corresponding to the second detection result and the detection average value corresponding to the third detection result; determining the correction degree for unqualified evaluation instruments based on the baseline average value and the detection average value; if the correction degree is greater than a preset correction degree, correcting the third detection result to obtain the current correction value; calculating the deviation between the current correction value and the baseline average value; if the deviation value is less than or equal to the first preset deviation threshold, stopping the iteration; if the deviation value is greater than the first preset deviation threshold, updating the detection average value using the current correction value and performing the next iteration.

[0029] In this embodiment, the benchmark average value refers to the arithmetic mean of the detection results of multiple corrected comparison oil samples (at least two concentrations) by the benchmark evaluation instrument.

[0030] The average test result refers to the arithmetic mean of the test results of multiple corrected comparison oil samples by the unqualified test instruments.

[0031] Correction degree refers to an indicator used to quantify the overall deviation between the test results of non-compliant participating instruments and the benchmark, and to determine whether correction is required.

[0032] The preset correction level refers to the correction threshold value that triggers the correction procedure.

[0033] The current correction value refers to the adjusted value of the test results of the unqualified participating instruments obtained after one iterative correction calculation.

[0034] In detail, after selecting the second test result of the benchmark instrument and obtaining the third test result of the unqualified instrument, the benchmark average value of the second test results of the benchmark instrument for the two concentration oil samples is calculated first, and the average value of the third test results of the unqualified instrument for the same batch of oil samples is calculated.

[0035] Next, the correction degree for the non-compliant instruments is calculated based on these two average values. This correction degree reflects the overall proportion or degree of deviation of the non-compliant instrument's test results relative to the benchmark. The calculated correction degree is compared with the preset correction degree. If the correction degree is not greater than the preset correction degree, it indicates that the deviation is within the unacceptable inherent error range, and the data cannot be used through correction and is discarded directly. Only when the correction degree is greater than the preset correction degree, it indicates that the deviation is within the acceptable inherent error range, and the data can be used through correction, triggering the correction process.

[0036] The formula for calculating the correction degree is as follows: ; in, This represents the value corresponding to the i-th third detection result. This represents the average value of the test results. This represents the value corresponding to the i-th second detection result. This represents the baseline average.

[0037] Once the correction process is triggered, a specific correction function is invoked to correct the third detection result, obtaining the current correction value. The deviation between the current correction value and the baseline average is calculated. If this deviation is less than or equal to a first preset deviation threshold (e.g., target accuracy requirement), it indicates that the result of the unqualified evaluation instrument has been successfully calibrated to an acceptable range after this correction, and the iteration process terminates. Conversely, if the deviation is still greater than the threshold, it indicates that the correction is not yet complete. In this case, the original data is not used directly. Instead, the current correction value is used as the new detection average (for the next round of correction calculation), and the process of "calculate correction degree - judge - correct - calculate deviation" is repeated to enter the next iteration. This loop continues until the deviation meets the requirements or reaches the safe iteration limit, thus ensuring that the correction process converges to a stable and accurate result.

[0038] Specifically, the correction function can be: ; in, Indicates the correction value. Indicates the intercept. Indicates the slope. This indicates the value corresponding to the third test result.

[0039] In a specific implementation process, the slope of the above correction function can be obtained by inputting the detection values ​​corresponding to each second detection result, the detection values ​​corresponding to each third detection result, the benchmark average value, and the detection average value into a preset slope formula.

[0040] Specifically, firstly, the second test results of the benchmark instrument for all corrected comparison oil samples, and the third test results of the non-compliant instrument for the same oil samples are collected. Simultaneously, the calculated benchmark average and test average are obtained. These data are input into a preset slope formula to obtain a first calculated value, which can be directly used as the slope.

[0041] The preset slope formula can be: ; in, This represents the first calculated value, which can be directly used as the slope.

[0042] In a specific implementation, the intercept of the above correction function can be obtained as follows: Input the slope, the baseline average value, and the detected average value into a preset intercept formula to obtain the intercept. Specifically, the preset intercept formula can be: ; in, This represents the second calculated value, which can be directly used as the intercept.

[0043] In one specific implementation, the present invention further provides a process for dynamically obtaining a preset correction degree, which may include: Obtain the historical Z-scores for each participating instrument, calculated multiple times for the same type of component in historical comparisons. Calculate the standard deviation of all historical Z-ratio scores as an indicator of historical volatility; The historical fluctuation index is compared with a preset benchmark fluctuation threshold. If the historical fluctuation index is greater than the benchmark fluctuation threshold, the basic correction degree is reduced according to the first adjustment coefficient to obtain the preset correction degree. If the historical fluctuation index is less than or equal to the benchmark fluctuation threshold, the basic correction degree is amplified according to the second adjustment coefficient to obtain the preset correction degree. The preset correction degree is calculated using the following formula: When the historical volatility index is greater than the benchmark volatility threshold, the preset correction degree = the basic correction degree × (1-α); When the historical volatility index is less than or equal to the benchmark volatility threshold, the preset correction degree is equal to the base correction degree × (1+β). Wherein, α is the first reduction coefficient determined based on the degree to which the historical volatility index exceeds the benchmark volatility threshold, and β is the second amplification coefficient determined based on the degree to which the historical volatility index is below the benchmark volatility threshold, and 0 < α < 1, 0 < β < 1.

[0044] Among them, historical Z-scores refer to the Z-score sequence calculated by the same instrument for the same component in multiple similar comparisons in the past.

[0045] The historical fluctuation index is a measure describing the stability of the instrument's historical test results, and is expressed here as the standard deviation of the historical Z-ratio score series.

[0046] The baseline fluctuation threshold refers to the reference standard value used to determine whether the historical performance of an instrument is stable.

[0047] The base correction refers to the initial correction calculated based on the current comparison data.

[0048] The preset correction level refers to the threshold used to determine whether to initiate correction after historical stability adjustments.

[0049] The first reduction factor α is a factor used to lower the correction threshold when historical fluctuations are large.

[0050] The second amplification factor β refers to the coefficient used to increase the correction threshold when historical fluctuations are small.

[0051] In detail, this embodiment establishes a file for each participating instrument, recording its historical Z-scores for each component in each comparison. When a new round of comparison begins and a correction judgment is needed for a certain instrument, the system first retrieves all historical Z-scores for that instrument for that component and calculates the standard deviation of these scores as a historical fluctuation index. This index reflects the long-term stability of the instrument in detecting that component: a large index value indicates large fluctuations in historical results and unstable performance; a small index value indicates stable and reliable historical results.

[0052] The calculated historical volatility index is compared with a preset benchmark volatility threshold. The comparison result is used to dynamically adjust the preset correction level. 1. If the historical fluctuation index is greater than the baseline fluctuation threshold, it indicates that the instrument has historically been unstable. For such instruments, the system adopts a conservative strategy, using a first reduction factor α to reduce the base correction degree, resulting in a smaller preset correction degree. This means that as long as the current detection result shows a small deviation (small correction degree), the correction procedure will be triggered because its history indicates that it is prone to problems.

[0053] 2. If the historical fluctuation index is less than or equal to the baseline fluctuation threshold, it indicates that the instrument has historically performed stably. For such instruments, the system adopts a lenient strategy, using a second amplification factor β to amplify the baseline correction, resulting in a larger preset correction. This means that only when the current detection result shows a large deviation is it considered that there may actually be a problem and a correction is triggered, avoiding excessive intervention in stable instruments.

[0054] The values ​​of coefficients α and β can be dynamically set based on the degree to which historical fluctuation indicators deviate from the benchmark threshold (for example, the greater the deviation, the larger the coefficient). In this way, the preset correction degree is no longer a fixed value, but is dynamically adjusted according to the "credit history" of each instrument, realizing differentiated intelligent correction management.

[0055] In some embodiments, the present invention further provides a process for selecting a benchmark instrument from qualified evaluation instruments, which may include: Obtain the laboratory weight coefficient of the participating unit corresponding to each qualified participating instrument, the historical performance weight coefficient of the instrument itself, and the current performance weight coefficient of this test and comparison; Based on the laboratory weight coefficient, the historical performance weight coefficient, and the current performance weight coefficient, as well as the preset weights of each coefficient, the comprehensive score of each qualified participating instrument is calculated. The qualified instrument with the highest comprehensive score is selected as the benchmark instrument.

[0056] The process of obtaining the performance weighting coefficients includes: Calculate the robust average of the first detection results for the same class of components from all qualified participating instruments; For each qualified instrument, calculate the absolute deviation between its first test result and the robust average value of the corresponding component; Based on the set of absolute deviations of all qualified participating instruments, calculate the average and standard deviation of the absolute deviations; For each qualified participating instrument, its performance weighting coefficient is calculated based on the relationship between its absolute deviation and the average and standard deviation of the absolute deviation; the smaller the absolute deviation, the higher the performance weighting coefficient.

[0057] In a specific implementation process, the laboratory weighting coefficient is obtained by comprehensively evaluating the qualification level of the laboratory to which the participating unit belongs, the satisfaction rate of historical comparison results, and the quality system certification status; the historical performance weighting coefficient is obtained by evaluating the stability of the Z-score in the past preset number of comparisons of the participating instrument and the consistency of daily quality control data.

[0058] In a specific implementation process, the laboratory weighting coefficient is a quantitative indicator reflecting the comprehensive strength and long-term quality reputation of the participating unit's laboratory. The historical performance weighting coefficient is a quantitative indicator reflecting the long-term operational stability and reliability of a single participating instrument. The current performance weighting coefficient is an immediate evaluation indicator reflecting the accuracy of the instrument's test results in the current round of comparison. The absolute deviation is the absolute value of the difference between the test result of a single instrument and the robust average. The accreditation level is the level of capability of the laboratory as recognized by national or industry accreditation, such as CNAS accreditation level. The historical comparison result satisfaction rate is the proportion of test results that the laboratory has been satisfied with in previous comparison activities. Z-score stability is the degree of fluctuation of the instrument's Z-score in historical comparisons; the smaller the fluctuation, the more stable the instrument. It can be expressed as the standard deviation of all historical Z-scores.

[0059] In detail, firstly, weighting coefficients for three dimensions are calculated for each qualified participating instrument that passes the initial evaluation and robustness screening: Laboratory weighting coefficient: This coefficient is derived from the background of the institution to which the instrument belongs. The system comprehensively evaluates the institution's laboratory based on factors such as its qualification level (e.g., national or provincial level), the satisfaction rate of historical results in similar comparisons (e.g., the percentage of satisfactory results in the past 5 comparisons), and whether it has passed quality system certification, using preset scoring rules to generate a coefficient representing the reliability of its parent laboratory.

[0060] Historical performance weighting coefficient: This coefficient focuses on the instrument's historical performance. The system retrieves records from the instrument's past preset number of comparisons (e.g., the last 3 times), analyzes its Z-score stability (e.g., calculates the standard deviation of each Z-score; the smaller the standard deviation, the higher the stability), and combines this with its daily internal quality control data (e.g., controlling the consistency of sample testing) to assess its long-term operational reliability and stability, generating this coefficient.

[0061] Current Performance Weighting Coefficient: This coefficient evaluates the instrument's performance in the current round. For each gas component, the system uses the robust average of the test results from all qualified instruments as the reference true value. For each qualified instrument, the absolute deviation of its test result from the corresponding component's robust average is calculated. Then, the set of absolute deviations of all qualified instruments for that component is statistically analyzed, and the average and standard deviation of this set are calculated. The current performance weighting coefficient for each instrument is dynamically calculated based on the degree of deviation of its absolute deviation from the overall distribution: the smaller the absolute deviation, the closer its current result is to the "consensus," and the higher its coefficient value; the larger the absolute deviation, the lower the coefficient value. This ensures that instruments that perform better in this comparison receive a higher immediate evaluation.

[0062] After obtaining the three coefficients for each instrument, a comprehensive score for each instrument can be calculated using a weighted summation formula, based on preset weight allocations (e.g., 30% for laboratory performance, 40% for historical performance, and 30% for current performance). Finally, the system selects the instrument with the highest comprehensive score from all qualified instruments and officially designates it as the benchmark instrument used in this revision process. Benchmark instruments selected in this way are not only technically reliable (with good current and historical performance), but also have a more robust laboratory quality management system, thus maximizing the authority and credibility of the benchmark values.

[0063] This embodiment comprehensively considers three factors: "laboratory background and reputation," "long-term instrument stability," and "real-time accuracy," making the selection process for benchmark instruments more scientific, objective, and comprehensive. This method effectively reduces the risk of potential biases in the benchmark values ​​themselves due to random selection, significantly improving the representativeness and credibility of the benchmark values, thus laying the most crucial and reliable foundation for the accuracy and effectiveness of the entire subsequent correction process. At the same time, this mechanism also indirectly incentivizes laboratories and instrument operators to focus on long-term quality development and routine maintenance.

[0064] In some embodiments, the present invention also provides the following technical solutions: Based on the results of the initial evaluation, the first total number of non-conforming components of the non-conforming instruments of each participating unit is counted. Based on the screening results, the second total number of non-compliant components of the non-compliant instruments of each participating unit was counted. Summing the first total number with the second total number yields the third total number of nonconforming components; Calculate the product of the total number of instruments evaluated for each participating unit and the number of components; The detection error rate of each participating unit is obtained by dividing the product of the third total number and the product of the two numbers. The samples were sorted in descending order of error rate and then sent to the terminal of each participating unit.

[0065] In detail, after completing the evaluation of all instruments, the results can be summarized by unit. First, count the number of all non-compliant components resulting from the initial evaluation failure of instruments under each unit, and record this as the first total number. Secondly, the number of all components deemed unqualified in robustness analysis by instruments belonging to the same unit is counted and recorded as the second total number. Then, the detection error rate of each participating unit is calculated using the following formula:

[0066] in, This indicates the testing error rate of the participating unit. This represents the total number of instruments submitted by the participating unit, and j represents the number of components. In this embodiment, j can be 8.

[0067] Subsequently, the error rates of all participating units can be calculated and sorted from largest to smallest, generating an evaluation report which is automatically sent to each participating unit's terminal via the network. This achieves transparent and real-time feedback of the evaluation results, helping each unit understand its position among its peers, identify weaknesses, and thus drive it to proactively improve its internal quality.

[0068] Based on the same general inventive concept, this invention also protects a chromatographic detection correction system. The chromatographic detection correction system provided by this invention will be described below. The chromatographic detection correction system described below can be referred to in correspondence with the chromatographic detection correction method described above.

[0069] Figure 2 This is a schematic diagram of the chromatographic detection correction system provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the chromatographic detection correction system of this embodiment includes an acquisition module 21, a rejection module 22, a screening module 23, a selection module 24, and a correction module 25.

[0070] Among them, the acquisition module 21 is used to acquire the first detection results of various components of the prepared detection ratio oil sample by the participating instruments of each participating unit through chromatographic detection; The elimination module is used to perform an initial evaluation of the first test results of each participating instrument and eliminate the first test results that do not meet the preset requirements. The screening module 23 is used to analyze the remaining first test results and screen out the qualified and unqualified test instruments. Select module 24 is used to select a benchmark instrument from qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two reconstituted comparison oil samples with corrected concentrations. The correction module 25 is used to obtain the third test results of each correction comparison oil sample from the unqualified evaluation instrument, and to iteratively correct the third test results based on the second test results until the deviation between the correction results and the second test results is less than the first preset deviation threshold.

[0071] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. The processor 310, communication interface 320, and memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions stored in the memory 330 to execute a chromatographic detection correction method.

[0072] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] It should be noted that all relevant information that may be involved in the various embodiments of the present invention is processed in strict accordance with the requirements of laws and regulations, following the principles of legality, legitimacy, and necessity, based on the reasonable purpose of the business scenario, and is information that users actively provide or generate during the use of the product / service, as well as information obtained with user authorization.

[0074] The information processed by this invention may vary depending on the specific product / service scenario and should be based on the specific scenario in which the user uses the product / service. This may involve user account information, device information, or other related information. This invention will treat the relevant information and its processing with the utmost diligence.

[0075] This invention places great emphasis on the security of relevant information and has adopted reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent unauthorized access, public disclosure, use, modification, damage or loss of relevant information.

[0076] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0077] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A chromatographic detection correction method, characterized in that, include: Obtain the first detection results of various components of the oil sample by the chromatographic analysis of the prepared test ratio using the instruments of each participating unit; An initial evaluation is performed on the first test results of each participating instrument, and the first test results that do not meet the preset requirements are eliminated. The remaining first test results are analyzed to screen out the qualified and unqualified instruments for evaluation. Select a benchmark instrument from the qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two corrected comparison oil samples of the reconstituted concentration. Obtain the third test results of each corrected comparison oil sample from the unqualified participating instruments, and iteratively correct the third test results based on the second test results until the deviation between the corrected results and the second test results is less than the first preset deviation threshold.

2. The chromatographic detection correction method according to claim 1, characterized in that, The third detection result is iteratively corrected based on the second detection result, including: Determine the baseline average value corresponding to the second test result, and the test average value corresponding to the third test result; Based on the benchmark average value and the detection average value, the correction degree of the unqualified participating instruments is determined; If the correction degree is greater than the preset correction degree, the third detection result is corrected to obtain the current correction value; Calculate the deviation between the current correction value and the baseline average value. If the deviation value is less than or equal to a first preset deviation threshold, stop the iteration. If the deviation value is greater than the first preset deviation threshold, update the detection average value using the current correction value and proceed to the next iteration.

3. The chromatographic detection correction method according to claim 2, characterized in that, The third detection result is corrected to obtain the current correction value, including: Based on the constructed correction function, the third detection result is corrected to obtain the corrected value for this detection; where the correction function is: ; in, Indicates the correction value. Indicates the intercept. Indicates the slope. This indicates the value corresponding to the third test result.

4. The chromatographic detection correction method according to claim 3, characterized in that, The process of obtaining the slope includes: The slope is obtained by inputting the detection values ​​corresponding to each second detection result, the detection values ​​corresponding to each third detection result, the benchmark average value, and the detection average value into a preset slope formula.

5. The chromatographic detection correction method according to claim 4, characterized in that, The process of obtaining the intercept includes: The slope, the baseline average value, and the detection average value are input into a preset intercept formula to obtain the intercept.

6. The chromatographic detection correction method according to claim 1, characterized in that, An initial evaluation is performed on the first test results of each participating instrument, and the first test results that do not meet the preset requirements are eliminated, including: For each participating instrument, obtain two initial test results; Calculate the average of the two first detection results; If the average value of the first detection result is greater than a preset concentration threshold, determine whether the difference between the two detection results is less than a second preset deviation threshold; the second preset deviation threshold is a first proportion of the average value of the first detection result. If the difference between the two first detection results is less than the second preset deviation threshold, it is determined that the preset requirements are met; If the difference between the two first detection results is greater than or equal to the second preset deviation threshold, it is determined that the preset requirements are not met.

7. The chromatographic detection correction method according to claim 6, characterized in that, Also includes: If the average value of the first detection result is less than or equal to the preset concentration threshold, determine whether the difference between the two first detection results is less than the third preset deviation threshold. The third preset deviation threshold is the sum of a second ratio of the average value of the first detection result and a preset multiple of the minimum detection concentration of the component corresponding to the first detection result; If the difference between the two first detection results is less than the third preset deviation threshold, it is determined that the preset requirements are met; If the difference between the two first detection results is greater than or equal to the third preset deviation threshold, it is determined that the preset requirements are not met.

8. The chromatographic detection correction method according to claim 1, characterized in that, The remaining first test results are analyzed to screen out the participating instruments that pass the first test and those that fail, including: Calculate the robust mean and robust standard deviation for each class of components; For each value corresponding to the first detection result, calculate the difference between the value corresponding to the first detection result and the robust average, and use the absolute value of the quotient of the robust standard deviation as the Z-ratio score of each component. Instruments with a Z-score greater than the preset pass threshold are considered unqualified, while those with a Z-score less than or equal to the preset pass threshold are considered qualified.

9. The chromatographic detection correction method according to claim 1, characterized in that, Also includes: Based on the results of the initial evaluation, the first total number of non-conforming components of the non-conforming instruments of each participating unit is counted. Based on the screening results, the second total number of non-compliant components of the non-compliant instruments of each participating unit was counted. Summing the first total number with the second total number yields the third total number of nonconforming components; Calculate the product of the total number of instruments evaluated for each participating unit and twice the number of components; The detection error rate of each participating unit is obtained by dividing the product of the third total number and the product of the two numbers. The samples were sorted in descending order of error rate and then sent to the terminal of each participating unit.

10. A chromatographic detection correction system, characterized in that, include: The acquisition module is used to acquire the first detection results of various components of the prepared test ratio oil sample by the participating instruments of each participating unit through chromatographic detection; The elimination module is used to perform an initial evaluation of the first test results of each participating instrument and eliminate the first test results that do not meet the preset requirements. The screening module is used to analyze the remaining first test results and screen out the participating instruments that have passed the first test and those that have failed. The selection module is used to select a benchmark instrument from qualified evaluation instruments and obtain the second test results of the benchmark instrument for at least two reconstituted comparison oil samples with corrected concentrations. The correction module is used to obtain the third test results of each correction comparison oil sample from the unqualified evaluation instrument, and to iteratively correct the third test results based on the second test results until the deviation between the correction results and the second test results is less than the first preset deviation threshold.

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