Verification method of sample detection result
By comparing the sample detection results of the target terahertz detection system with the standard sample results, and combining multiple repeated detections with the results of different operators and traditional detection methods, the uncertainty and standardization of the sample detection method are solved, and the detection results are achieved. Accuracy and reliability have promoted the standardization and sustainable development of terahertz detection technology.
Patent Information
- Application Number
- CN202411294696.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-14
- Publication Date
- 2025-01-17
AI Technical Summary
There are uncertainties and differences in results of existing sample detection methods, and it is difficult to standardize and promote. As new technologies emerge, verification methods need to be updated to ensure the accuracy and reliability of the detection results.
By obtaining the sample detection result data set of target terahertz detection system and comparing the standard sample detection results, calibrating the detection system parameters, performing multiple repeated tests, and comparing the results of different operators and traditional detection methods to ensure the accuracy of the verification results and reliability.
Effectively verify the accuracy of the detection system, promote the standardization and standardization of terahertz detection technology, improve the comparability and reliability of detection results, guide technical iteration and optimization, and improve scientificity and practicality.
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Figure CN119322032A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of analytical method verification, and in particular to a method for verifying sample detection results. Background Art
[0002] In many fields such as analytical chemistry, pharmacy, environmental science, and biomedicine, it is crucial to conduct accurate and reliable testing of samples. The accuracy of sample test results is directly related to the reliability of scientific research data, the correctness of disease diagnosis, and the effectiveness of environmental monitoring. Therefore, ensuring the accuracy and reliability of test results is a core requirement of analytical work; traditional sample testing methods usually rely on a single analytical technique, such as chromatography, mass spectrometry, or spectroscopy. However, these methods are often affected by multiple factors such as instrument performance, operator skills, and sample characteristics, which may lead to certain uncertainties in the test results. In addition, there may be differences in results between different detection methods, which makes it challenging to select and compare different methods.
[0003] In order to solve these problems, analytical method validation technology came into being. This technology systematically validates the detection method to ensure that it meets specific performance index requirements. These performance indicators include accuracy, precision, specificity, detection limit, quantification limit, linearity and range, which together constitute a standard system for evaluating the reliability of the detection method.
[0004] In practical applications, analytical method validation techniques usually involve a series of experiments using standard samples or reference substances with known contents to evaluate key parameters such as repeatability, accuracy, and recovery of the method. The design and execution of these experiments require strictly controlled conditions to ensure the accuracy and comparability of the data.
[0005] Although analytical method validation technology plays an important role in improving the accuracy of test results, there are still some limitations and challenges. For example, the selection and preparation of standard samples may affect the accuracy of validation results; there may be differences in method validation results between different laboratories, which affects the standardization and promotion of methods; in addition, with the continuous emergence of new technologies, existing validation methods may need to be updated to adapt to new analytical needs.
[0006] Therefore, developing more standardized, universal and transferable analytical method verification technology will be an important research direction in the field of analytical chemistry in the future. By continuously optimizing and improving the verification method, the accuracy and reliability of sample test results can be better guaranteed, providing strong technical support for scientific research, medical treatment and environmental monitoring. Summary of the invention
[0007] In view of this, the present invention aims at the deficiencies of the prior art and proposes a method for verifying sample detection results, aiming to solve at least one of the problems raised by the above background technology.
[0008] The present invention provides a method for verifying sample detection results, comprising: obtaining a target terahertz detection system sample detection result data group;
[0009] The verification result of the target sample detection result is obtained by comparing the target terahertz detection system sample detection result data group value with the standard sample detection result data value.
[0010] In some embodiments, the parameters of the terahertz detection system are calibrated before obtaining the target terahertz detection system sample detection result data set.
[0011] In some embodiments, the parameters of the terahertz detection system are frequency, power, and waveform.
[0012] In some embodiments, the target terahertz detection system performs repeated detection on the sample multiple times to obtain a first data set of the target terahertz detection system sample detection results.
[0013] In some embodiments, a plurality of different operators perform repeated detections on the target terahertz detection system sample to obtain a second data set of detection results of the target terahertz detection system sample.
[0014] In some embodiments, the first data group of the target terahertz detection system sample detection results is compared with the second data group of the target terahertz detection system sample detection results, and when the first data group of the target terahertz detection system sample detection results and the second data group of the target terahertz detection system sample detection results are the same, a target terahertz detection system sample detection result data group is obtained;
[0015] When the results of the first data group of sample detection results of the target terahertz detection system are different from the results of the second data group of sample detection results of the target terahertz detection system, the parameters of the terahertz detection system are recalibrated, and the first data group of sample detection results of the target terahertz detection system and the second data group of sample detection results of the target terahertz detection system are obtained again, until the data values of the first data group of sample detection results of the target terahertz detection system and the second data group of sample detection results of the target terahertz detection system are the same, then the target terahertz detection system sample detection result data group is output.
[0016] In some embodiments, the target terahertz detection system sample detection result data set is compared with the detection result measured by the traditional detection method and then compared with the standard sample detection result data value to obtain the verification result.
[0017] In some embodiments, the conventional detection methods are X-ray and infrared imaging.
[0018] In some embodiments, experts in the field to which the target samples belong compare the target terahertz detection system sample detection result data set with the detection results measured by traditional detection methods, and then compare it with the standard sample detection result data value to obtain the verification result for review and analysis.
[0019] In some embodiments, experts in the field to which the target sample belongs compare the target terahertz detection system sample detection result data set with the detection results measured by traditional detection methods, and then store the verification results obtained by comparing with the standard sample detection result data values.
[0020] Compared with the prior art, the present invention has the following beneficial effects:
[0021] By comparing the test results with those of standard samples, the accuracy of the target terahertz detection system can be effectively verified to ensure the reliability of the test results. Comparative analysis can reveal possible problems or deviations in the detection system, and make timely corrections and optimizations, thereby enhancing users' trust in the detection system. Using unified standard samples for verification will help promote the standardization and normalization of terahertz detection technology and improve the comparability between different systems. Feedback on verification results can guide the technical iteration and functional improvement of the terahertz detection system and promote the continuous development and optimization of technology. This application can not only improve the scientificity and practicality of terahertz detection technology, but also contribute to social development and technological progress at multiple levels.
[0022] The foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.
[0023] Other features and aspects of the present disclosure will become more apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0025] Figure 1 A flow chart of a method for verifying sample test results provided in an embodiment of the present invention. DETAILED DESCRIPTION
[0026] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0027] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.
[0028] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.
[0029] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.
[0030] As mentioned in the background technology, in practical applications, analytical method validation technology usually involves a series of experiments using standard samples or reference substances with known contents to evaluate key parameters such as repeatability, accuracy and recovery of the method. The design and execution of these experiments require strict control conditions to ensure the accuracy and comparability of the data.
[0031] Although analytical method validation technology plays an important role in improving the accuracy of test results, there are still some limitations and challenges. For example, the selection and preparation of standard samples may affect the accuracy of validation results; there may be differences in method validation results between different laboratories, which affects the standardization and promotion of methods; in addition, with the continuous emergence of new technologies, existing validation methods may need to be updated to adapt to new analytical needs.
[0032] To improve the above-mentioned problems, the present application proposes a method for verifying sample test results, which can effectively verify the accuracy of the target terahertz detection system by comparing the test results with those of standard samples, and ensure the reliability of the test results. Comparative analysis can discover possible problems or deviations in the detection system, and make corrections and optimizations in a timely manner, thereby enhancing users' trust in the detection system; using a unified standard sample for verification will help promote the standardization and normalization of terahertz detection technology and improve the comparability between different systems; through feedback from verification results, the technical iteration and functional improvement of the terahertz detection system can be guided, and the continuous development and optimization of the technology can be promoted. The present application can not only improve the scientificity and practicality of terahertz detection technology, but also contribute to social development and technological progress at multiple levels.
[0033] See also Figure 1 As shown, a method for verifying a sample detection result according to an embodiment of the present application includes:
[0034] Obtaining a target terahertz detection system sample detection result data set;
[0035] The verification result of the target sample detection result is obtained by comparing the target terahertz detection system sample detection result data group value with the standard sample detection result data value.
[0036] In some specific embodiments, the parameters of the terahertz detection system are calibrated before obtaining the target terahertz detection system sample detection result data set.
[0037] Specifically, parameter calibration can ensure that the working state of the terahertz detection system is consistent with the preset performance standards, thereby improving the accuracy of the detection results and reducing errors; through calibration, the stability and reliability of the detection system in long-term use can be ensured, making the acquired data sets more credible and facilitating subsequent data analysis and decision-making; the calibrated terahertz detection system can provide standardized data output, which makes the detection results at different times and on different devices more consistent and comparable; an uncalibrated detection system may have systematic deviations, which will cause the detection results to deviate from the true value. Calibration can identify and correct these deviations and improve the accuracy of the results; regular calibration helps to detect potential equipment problems, so that timely maintenance or replacement can be carried out, optimizing the use of resources and reducing resource waste caused by equipment failure; the calibration process complies with international standards and industry specifications, which can increase user confidence in the test results, especially in key application areas such as safety inspections and medical testing; through regular calibration, small problems can be preventively identified and solved to prevent them from developing into expensive repair problems, thereby reducing long-term maintenance costs; performance evaluation during the calibration process can quickly locate the source of the fault, simplify the fault diagnosis process, and shorten the repair time; calibration records provide a detailed history of the performance of the detection system, increase the transparency of data processing, and facilitate scientific research and audit tracking; in summary, calibrating the parameters of the terahertz detection system before obtaining the target terahertz detection system sample test result data set can improve the quality and performance of the detection system in many aspects and ensure the accuracy and reliability of the test results.
[0038] In some specific embodiments, the parameters of the terahertz detection system are frequency, power, and waveform.
[0039] In some specific embodiments, the target terahertz detection system performs repeated detection on the sample for multiple times to obtain a first data set of the target terahertz detection system sample detection results.
[0040] Specifically, through repeated detection, the impact of single measurement errors can be reduced and the reliability of the overall detection results can be improved. Repeated detection can evaluate the stability and repeatability of the terahertz detection system under the same conditions and ensure the consistency of system performance. The data sets generated by multiple detections can be used for statistical analysis to draw more scientific and reasonable conclusions. Through the analysis of the first data set, possible system deviations or outliers can be identified, and measures can be taken to correct them. Repeated detection helps to determine the best detection parameters (such as frequency, power and waveform) to achieve the most accurate detection results. The first data set can be used as a benchmark for subsequent detections to compare the results of different samples or at different time points. Repeated detection ensures the consistency of the results and makes the results between different studies more comparable. Multiple detections can provide a more comprehensive understanding of the characteristics of the sample in the terahertz band and provide data support for further research and application. Through repeated detection, signal averaging and other methods can be used to improve the signal-to-noise ratio and reduce the impact of noise on the detection results. The impact of repeated tests on the results; if the test results are used to establish a predictive model, repeated tests can improve the accuracy and generalization ability of the model; the first data set can reveal potential problems in the experimental design and provide a basis for the optimization of subsequent experiments; in scientific research and commercial applications, the data set obtained by repeated tests is more convincing, which is conducive to the publication of research results and the marketing of products; if the test results are abnormal, repeated tests can help to quickly locate the problem and improve the efficiency of fault diagnosis and problem solving; for occasions where important decisions need to be made based on the test results, repeated tests provide more accurate data support and help make more reasonable decisions; in some industries, such as medicine and food safety, regulations may require multiple tests to ensure the accuracy and compliance of the results. The target terahertz detection system performs multiple repeated tests on the samples, and the first data set obtained provides a solid foundation for the accuracy, reliability and consistency of the test results, bringing many benefits to scientific research, industrial applications and regulatory compliance.
[0041] In some specific embodiments, a plurality of different operators perform repeated detections on the target terahertz detection system sample to obtain a second data set of detection results of the target terahertz detection system sample.
[0042] In some specific embodiments, a first data group of target terahertz detection system sample detection results is compared with a second data group of target terahertz detection system sample detection results, and a target terahertz detection system sample detection result data group is obtained when the first data group of target terahertz detection system sample detection results and the second data group of target terahertz detection system sample detection results are the same;
[0043] When the results of the first data group of target terahertz detection system sample detection results are different from the second data group of target terahertz detection system sample detection results, the parameters of the terahertz detection system are recalibrated, and the first data group of target terahertz detection system sample detection results and the second data group of target terahertz detection system sample detection results are obtained again, until the data values of the first data group of target terahertz detection system sample detection results and the second data group of target terahertz detection system sample detection results are the same, then the target terahertz detection system sample detection result data group is output.
[0044] Specifically, the participation of different operators can reduce the bias that may be caused by a single operator and improve the objectivity of the test results. Multi-operator testing can evaluate and reduce the impact of different operator skills and operating methods on the test results. By ensuring that different operators obtain consistent test results, the robustness of the test method and the reliability of the results can be verified. This process can be used as a tool for operator training and verification to ensure that all operators can perform tests according to the same standards. Multi-operator testing helps to identify and reduce human operating errors and improve overall test accuracy. By comparing multiple sets of data, it ensures that the test results can be reproduced under different conditions, thereby enhancing the universality of the results.
[0045] When the results of the first data set are inconsistent with the second data set, recalibrating the terahertz detection system helps to discover and correct deficiencies in the process and optimize the detection process. This process can be used as part of the performance verification of the detection system to ensure that the system can maintain stable performance under the use of different operators. The data sets obtained by multiple operators can provide a more comprehensive perspective and provide richer information for data analysis and decision-making. Repeated verification by multiple operators can help promote the standardization and normalization of terahertz detection technology. Multi-operator detection provides more data points, increases the transparency of system operation, and facilitates future audits and traceability. The test results verified by multiple operators can gain more trust from customers, especially in areas that require high accuracy. The field of accuracy and reliability; through multi-operator detection, the detection process can reduce the dependence on the skills of a single operator, making the detection results more stable; in scientific research and quality control, cross-validation is an important means to ensure the accuracy of the results, and multi-operator detection meets this requirement; in international cooperation projects, multi-operator detection ensures that operators from different cultural backgrounds can obtain consistent results, which is conducive to international cooperation and communication. By repeatedly testing the target terahertz detection system samples by multiple different operators and comparing them with the first data set until the results are consistent, this process improves the accuracy, reliability and objectivity of the detection results, and provides a solid foundation for the application and development of terahertz detection technology.
[0046] In some specific embodiments, the target terahertz detection system sample detection result data set is compared with the detection result measured by the traditional detection method, and then compared with the standard sample detection result data value to obtain the verification result.
[0047] In some embodiments, conventional detection methods are X-ray and infrared imaging.
[0048] Specifically, terahertz waves have the characteristics of strong penetration and sensitivity to non-metallic materials, which can make up for the limitations of traditional detection methods in specific fields; the comparison between terahertz detection and traditional methods can reveal the response characteristics of samples in different bands, providing an additional information dimension for research; the combination of terahertz detection technology with X-ray and infrared imaging may open up new application scenarios, especially in the fields of safety inspection and quality control. The fast and non-contact detection characteristics of terahertz detection systems can be combined with traditional methods to improve the overall efficiency of the detection process; the comparison and combination of different detection technologies can promote the integration and innovation of interdisciplinary technologies; terahertz detection technology In some cases, terahertz technology may provide higher resolution and sensitivity than traditional methods, thereby improving the quality of test results; the combination of different detection technologies can optimize the detection cost while ensuring the accuracy of the results, thus achieving a balance between cost and benefit; the results of multiple detection methods verify each other, which helps to improve the credibility of the test results; the comparative analysis of different technologies helps to promote the standardization and regularization of detection technologies; comparing and verifying the results of the target terahertz detection system with those of traditional detection methods can not only improve the accuracy and reliability of the test results, but also promote the integration and innovation of technologies, expand the application areas, and improve the overall detection efficiency and safety.
[0049] In some specific embodiments, experts in the field to which the target samples belong compare the target terahertz detection system sample detection result data set with the detection results measured by traditional detection methods, and then compare it with the standard sample detection result data value to obtain the verification result for review and analysis.
[0050] In some specific embodiments, experts in the field to which the target samples belong compare the target terahertz detection system sample detection result data set with the detection results measured by traditional detection methods, and then store the verification results obtained by comparing with the standard sample detection result data values.
[0051] Specifically, storing verification results can ensure data integrity, prevent data loss or tampering, and ensure the reliability of test results; stored verification results can be used to compare with historical data to analyze changes in the accuracy and stability of the test method over time; in long-term research projects, stored verification results can be used as part of the research data to support scientific research and data analysis; stored verification results are convenient for future audits and reviews to ensure the transparency and traceability of the test process and results; stored verification results can be accessed by other researchers or institutions to promote knowledge sharing and the dissemination of scientific research results; stored verification results can provide strong data support in situations where decisions need to be made based on test results; comparing the target terahertz detection system sample test result data group with the test results measured by traditional detection methods, and comparing them with the standard sample test result data values to obtain the verification results, reviewing, analyzing and storing them, can bring benefits in data management, scientific research, cooperation, education, legal compliance and other aspects, and provide strong support for scientific research, industrial applications and social development.
[0052] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.
Claims
1. A method for verifying sample detection results, characterized in that: include: Obtaining a target terahertz detection system sample detection result data set; The verification result of the target sample detection result is obtained by comparing the target terahertz detection system sample detection result data group value with the standard sample detection result data value.
2. A method for verifying sample detection results according to claim 1, characterized in that: The parameters of the terahertz detection system are calibrated before obtaining the target terahertz detection system sample detection result data set.
3. A method for verifying sample detection results according to claim 2, characterized in that: The parameters of the terahertz detection system are frequency, power and waveform.
4. The method for verifying a sample detection result according to claim 1, characterized in that: The target terahertz detection system performs repeated detection on the sample for multiple times to obtain a first data set of the target terahertz detection system sample detection results.
5. A method for verifying sample detection results according to claim 4, characterized in that: The target terahertz detection system sample is repeatedly detected by multiple different operators to obtain a second data set of the target terahertz detection system sample detection results.
6. A method for verifying sample detection results according to claim 5, characterized in that: Comparing the first data group of the target terahertz detection system sample detection results with the second data group of the target terahertz detection system sample detection results, and obtaining the target terahertz detection system sample detection result data group when the first data group of the target terahertz detection system sample detection results and the second data group of the target terahertz detection system sample detection results are the same; When the results of the first data group of sample detection results of the target terahertz detection system are different from the results of the second data group of sample detection results of the target terahertz detection system, the parameters of the terahertz detection system are recalibrated, and the first data group of sample detection results of the target terahertz detection system and the second data group of sample detection results of the target terahertz detection system are obtained again, until the data values of the first data group of sample detection results of the target terahertz detection system and the second data group of sample detection results of the target terahertz detection system are the same, then the target terahertz detection system sample detection result data group is output.
7. A method for verifying sample detection results according to claim 6, characterized in that: The target terahertz detection system sample test result data set is compared with the test results measured by the traditional detection method, and then compared with the standard sample test result data value to obtain the verification result.
8. A method for verifying sample detection results according to claim 7, characterized in that: The traditional detection methods are X-ray and infrared imaging.
9. A method for verifying sample detection results according to claim 8, characterized in that: Experts in the field to which the target samples belong compare the target terahertz detection system sample test result data set with the test results measured by traditional detection methods, and then compare it with the standard sample test result data value to obtain the verification results for review and analysis.
10. A method for verifying sample detection results according to claim 9, characterized in that: Experts in the field of the target sample compare the target terahertz detection system sample test result data set with the test results measured by traditional detection methods, and then compare it with the standard sample test result data value to obtain the verification result and store it.