A method for detecting batch quality stability of fiber raw materials based on color fingerprint spectrum

Abstract

The application discloses a kind of based on color fingerprint of fiber raw material batch quality stability detection method, belong to highway engineering material quality detection technical field, to solve the technical problem is: how to overcome the lag, poor representation, lack of unified identity determination standard defects existing in fiber raw material batch quality detection.It includes: selecting reference sample;The multi-dimensional color information collected when not heated is used as the first reference fingerprint, and the multi-dimensional color collected after heating is used as the second reference fingerprint;Using the same measurement conditions as obtaining the reference color fingerprint, the multi-dimensional color information of the sample to be tested when not heated is detected as the first test fingerprint, and using the same standard heating program as obtaining the reference color fingerprint, the multi-dimensional color information of the sample to be tested after heating is detected as the second test fingerprint;Calculate the fingerprint deviation of the reference sample before and after heating, and execute consistency determination logic based on multi-dimensional fingerprint deviation.

Description

Technical Field

[0001] This invention relates to the field of highway engineering material quality testing technology, specifically a method for batch quality stability testing of fiber raw materials based on color fingerprinting. Background Technology

[0002] In asphalt pavement engineering, the quality stability of flocculent wood fibers, used as stabilizers, directly affects the workability of the mixture and the durability of the pavement. However, due to the complex sources of fibers and the variability of raw materials, large quality fluctuations between different batches and inconsistencies between the actual supplied products and the submitted samples are the most prominent and practical pain points faced in the project.

[0003] Currently, on-site quality control of fiber materials mainly relies on the following methods:

[0004] 1. Verify the factory test report: You can only trust the data provided by the manufacturer, and you cannot independently verify it. There is a risk that the report may not match the actual product.

[0005] 2. Send samples to a third-party laboratory for testing: According to the "Fibers for Asphalt Pavement" (JT / T 533-2020), a comprehensive test is conducted on core indicators such as oil absorption rate, ash content, and heat resistance. However, this method is time-consuming (usually several days), and the test results can only represent the single sample submitted for testing, not the entire batch of materials. Furthermore, it is impossible to make a quick decision on whether to accept or reject the materials when they arrive at the site.

[0006] 3. Visual inspection: Relying solely on experience to observe color and shape is highly subjective and cannot be quantified. It is almost impossible to identify batch fluctuations with inconspicuous color differences or carefully mixed inferior fibers.

[0007] The main defects and shortcomings of existing technical solutions:

[0008] 1. Significant delay: Whether relying on reports or third-party testing, neither can provide a basis for decision-making as soon as the materials arrive on site, which means that unqualified materials may have already been used in production while waiting for test results;

[0009] 2. Poor representativeness: The above methods are all for precise testing of individual samples, which cannot achieve rapid and multi-point general inspection of large batches of incoming materials, and it is difficult to detect discrete quality problems within the batch.

[0010] 3. Lack of unified "identity" judgment criteria: There is a lack of objective, quantitative and on-site execution comparison methods and judgment criteria in the industry for determining whether new incoming materials are consistent with previously verified qualified samples, and they rely entirely on personal experience.

[0011] Overcoming the shortcomings of batch quality testing of fiber raw materials, such as lag, poor representativeness, and lack of unified identification standards, is a technical problem that needs to be solved. Summary of the Invention

[0012] The technical objective of this invention is to address the above-mentioned shortcomings by providing a method for detecting the batch quality stability of fiber raw materials based on color fingerprinting, thereby overcoming the technical problems of lag, poor representativeness, and lack of unified identification standards in the batch quality detection of fiber raw materials.

[0013] This invention provides a method for batch quality stability testing of fiber raw materials based on color fingerprinting, comprising the following operations:

[0014] Selecting benchmark samples: Select fiber samples that have passed a full set of performance tests and whose engineering acceptance results meet the requirements as benchmark samples;

[0015] Obtaining the reference color fingerprint: The multidimensional color information of the reference sample before heating is measured using a spectrophotometer. This unheated multidimensional color information is used as the first reference fingerprint spectrum. A standardized heating procedure is then applied to the reference sample, and the multidimensional color information of the heated sample is measured using the same spectrophotometer at predetermined time intervals. The heated multidimensional color information is used as the second reference fingerprint spectrum. The first reference fingerprint spectrum, the second reference fingerprint spectrum, and the sample information are stored in the fingerprint database as the color fingerprint file of the qualified fiber. The multidimensional color information includes lightness. Red-green axis and yellow-blue axis ;

[0016] Acquiring the color fingerprint of the test sample: For the test sample, the same measurement conditions as those for acquiring the reference color fingerprint are used to detect the multidimensional color information of the test sample when it is not heated as the first test fingerprint, and the same standard heating procedure as those for acquiring the reference color fingerprint is used to detect the multidimensional color information of the test sample after it is heated as the second test fingerprint.

[0017] Detection and screening: For the sample to be tested, the fingerprint deviation relative to the reference sample before and after heating is calculated to obtain the multidimensional fingerprint deviation. Based on the multidimensional fingerprint deviation, the consistency judgment logic is executed, and the multidimensional fingerprint deviation is compared with the preset qualified fluctuation threshold. Based on the comparison result, the quality stability evaluation conclusion is output.

[0018] Preferably, the multidimensional fingerprint deviation includes the original state deviation and the thermochromic deviation, and the calculation formula is as follows:

[0019] ,

[0020] ,

[0021] in, The original state deviation represents the fingerprint deviation between the test sample and the reference sample before heating. Indicates the brightness of the first fingerprint to be tested. This represents the red-green axis in the first fingerprint to be tested. This indicates the yellow-blue axis in the first fingerprint to be tested. Indicates the brightness in the first baseline fingerprint. This represents the red-green axis in the first baseline fingerprint. This indicates the yellow-blue axis in the first baseline fingerprint;

[0022] Thermochromic deviation represents the fingerprint difference between the test sample and the reference sample after heating. Indicates the brightness of the second fingerprint sample. This indicates the red-green axis in the second fingerprint to be tested. This indicates the yellow-blue axis in the second fingerprint sample. Indicates the brightness in the second baseline fingerprint. This indicates the red-green axis in the second baseline fingerprint. This indicates the yellow-blue axis in the second baseline fingerprint;

[0023] Correspondingly, when performing consistency judgment logic based on multidimensional fingerprint deviation, the original state deviation and thermal discoloration deviation are compared with the corresponding qualified fluctuation thresholds. Row comparison, if and If the sample being tested is highly consistent with the baseline in terms of raw material composition and thermally induced behavior, then the batch is deemed to be of stable quality and acceptable. This indicates that the sample to be tested has undergone significant changes in terms of raw material type and purity, posing a risk of material substitution or adulteration. Therefore, it is judged as having abnormal raw material composition, and rejection or retesting is recommended. but This indicates that the raw materials of the sample to be tested appear to be the same as those of the reference sample, but the chemical stability has deteriorated during the heating process, which is then judged as abnormal thermal stability and a risk of thermal damage.

[0024] Preferably, for a preset acceptable fluctuation threshold, the acceptable fluctuation threshold is dynamically updated using statistical methods based on the fingerprint deviations of multiple batches of reference samples. These statistical methods include setting... The method for controlling the upper limit dynamically updates the acceptable fluctuation threshold.

[0025] As a preferred method, during the detection and screening process, for the sample to be tested, a thermochromic tendency index is constructed based on the red-green axis and yellow-blue axis in the color information and through channel weighting. A thermochromic tendency index deviation is constructed based on the thermochromic tendency index of the benchmark sample and the thermochromic tendency index of the sample to be tested. The thermochromic tendency index deviation is used to replace the multidimensional fingerprint deviation for consistency judgment logic. The thermochromic tendency index deviation is compared with a preset threshold value. Based on the comparison result, a quality stability evaluation conclusion is output.

[0026] Among them, the red-yellow tendency index The calculation formula is as follows:

[0027] ,

[0028] in, Indicates channel weight, This indicates the color change tendency of the red-green axis after heating. This indicates the color change tendency of the yellow-blue axis after heating;

[0029] Correspondingly, the heat-induced discoloration tendency index deviation The calculation formula is as follows:

[0030] ,

[0031] ,

[0032] ,

[0033] in, This indicates the thermal discoloration tendency index of the sample under test. This indicates the heat-induced discoloration tendency index of the reference sample.

[0034] Preferably, when applying a standardized heating procedure to the reference sample or the sample to be tested, the heating procedure can be replaced by heating the reference sample or the sample to be tested using an oil bath at a constant temperature or a customized portable miniature heating container.

[0035] The method for batch quality stability testing of fiber raw materials based on color fingerprinting of the present invention has the following advantages:

[0036] 1. Rapid and objective, returning the initiative of quality control to the construction site: The laboratory evaluation that requires several days in the existing technology is simplified to on-site quantitative comparison within half an hour. The test results are driven by objective color difference values, completely eliminating subjective visual inspection, enabling the supervision and construction units to make immediate and scientific decisions on whether the materials are usable.

[0037] 2. No need to test specific performance, solve problems based solely on the "consistency" logic: Bypassing complex indicator tests, directly answer the fundamental question that the project cares about most: "Is this batch of material the same as the previously verified good material?" As long as the color deviation is consistent, its performance is likely to be reliable, greatly reducing the threshold for implementing rapid testing technology.

[0038] 3. Anti-counterfeiting and traceability, accurately cracking down on "substitution": By comparing the first benchmark fingerprint (original state), it can quickly detect any slight fluctuations in the hidden formula and raw material source of illegal suppliers, making the behavior of "reporting A, supplying B" nowhere to hide;

[0039] 4. Differentiate risk types and guide precise handling: By decoupling the deviations in the two dimensions of raw material composition and thermal stability, it is possible to clearly identify which link in the incoming material problem is located, whether the raw material has changed or the quality has deteriorated, providing clear guidance for subsequent corrective measures (return, downgrade or process adjustment). Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] The invention will be further described below with reference to the accompanying drawings.

[0042] Figure 1 This is a flowchart illustrating a method for batch quality stability testing of fiber raw materials based on color fingerprinting. Detailed Implementation

[0043] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments are not intended to limit the present invention. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0044] This invention provides a method for detecting the batch quality stability of fiber raw materials based on color fingerprinting, which addresses the technical problems of lagging, poor representativeness, and lack of unified identification standards in the batch quality detection of fiber raw materials.

[0045] Example:

[0046] This invention provides a method for batch quality stability testing of fiber raw materials based on color fingerprinting, comprising four steps: selecting a reference sample, obtaining a reference color fingerprint, obtaining the color fingerprint to be tested, and detection and screening.

[0047] Step S100: Select a reference sample: Select a fiber sample that has passed a full set of performance tests and whose engineering acceptance results meet the requirements as a reference sample.

[0048] As a specific implementation for selecting benchmark samples, fiber samples that have passed a full set of performance tests (such as passing heat resistance and oil absorption) and have shown good engineering verification results are selected as benchmark samples.

[0049] Step S200: Obtain the reference color fingerprint: Measure the multidimensional color information of the reference sample before heating using a spectrophotometer. Use this unheated multidimensional color information as the first reference fingerprint spectrum. Apply a standardized heating procedure to the reference sample, and measure the multidimensional color information of the heated reference sample using the same spectrophotometer at predetermined time intervals. Use the heated multidimensional color information as the second reference fingerprint spectrum. Store the first reference fingerprint spectrum, the second reference fingerprint spectrum, and the sample information as the color fingerprint file for qualified fibers in the fingerprint database. The multidimensional color information includes brightness. Red-green axis and yellow-blue axis .

[0050] In this embodiment, when heating the reference sample, the reference sample is subjected to a standardized heating procedure (e.g., placed in an oven at 205-215°C for 10-60 minutes, or rapidly heated using a portable heating table).

[0051] Step S300: Obtain the color fingerprint to be tested: For the sample to be tested, the same measurement conditions as those used to obtain the reference color fingerprint are adopted to detect the multidimensional color information of the sample when it is not heated as the first fingerprint to be tested, and the same standard heating procedure as those used to obtain the reference color fingerprint is adopted to detect the multidimensional color information of the sample after it is heated as the second fingerprint to be tested.

[0052] Step S400 Detection and Screening: For the sample to be tested, calculate the fingerprint deviation relative to the reference sample before and after heating to obtain the multidimensional fingerprint deviation amount, and execute the consistency judgment logic based on the multidimensional fingerprint deviation amount. Compare the multidimensional fingerprint deviation amount with the preset qualified fluctuation threshold, and output the quality stability evaluation conclusion based on the comparison result.

[0053] In a specific implementation, the multidimensional fingerprint deviation includes the original state deviation and the thermochromic deviation, and the calculation formula is as follows:

[0054] ,

[0055] ,

[0056] in, The original state deviation represents the fingerprint deviation between the test sample and the reference sample before heating. Indicates the brightness of the first fingerprint to be tested. This represents the red-green axis in the first fingerprint to be tested. This indicates the yellow-blue axis in the first fingerprint to be tested. Indicates the brightness in the first baseline fingerprint. This represents the red-green axis in the first baseline fingerprint. This indicates the yellow-blue axis in the first baseline fingerprint;

[0057] Thermochromic deviation represents the fingerprint difference between the test sample and the reference sample after heating. Indicates the brightness of the second fingerprint sample. This indicates the red-green axis in the second fingerprint to be tested. This indicates the yellow-blue axis in the second fingerprint sample. Indicates the brightness in the second baseline fingerprint. This indicates the red-green axis in the second baseline fingerprint. This indicates the yellow-blue axis in the second baseline fingerprint.

[0058] Correspondingly, when performing consistency judgment logic based on multidimensional fingerprint deviation, the original state deviation and thermal discoloration deviation are compared with the corresponding qualified fluctuation thresholds. Row comparison, if and If the sample being tested is highly consistent with the baseline in terms of raw material composition and thermally induced behavior, then the batch is deemed to be of stable quality and acceptable. This indicates that the sample to be tested has undergone significant changes in terms of raw material type and purity, posing a risk of material substitution or adulteration. Therefore, it is judged as having abnormal raw material composition, and rejection or retesting is recommended. but This indicates that the raw materials of the sample to be tested appear to be the same as those of the reference sample, but the chemical stability has deteriorated during the heating process. For example, recycled materials were used, the sample was stored for too long, or it has become damp and deteriorated. In this case, it is judged to have abnormal thermal stability and a risk of thermal damage.

[0059] As an improvement to this embodiment, for the preset acceptable fluctuation threshold, based on the fingerprint deviation of multiple batches of reference samples, the acceptable fluctuation threshold is dynamically updated using statistical methods. These statistical methods include setting... The method for controlling the upper limit dynamically updates the acceptable fluctuation threshold. In practice, the fingerprint deviation of each acceptable batch of samples is obtained as a statistic. Under the premise of stable production and qualified raw materials, the fingerprint deviation is assumed to follow a normal or approximately normal distribution. The mean and standard deviation of the fingerprint deviations from multiple batches are calculated. The upper limit of control is set as a dynamic threshold.

[0060] As an improvement to this embodiment, during the detection and screening process, for the sample to be tested, a thermochromic tendency index is constructed based on the red-green axis and yellow-blue axis in the color information using a channel weighting method. A thermochromic tendency index deviation is constructed based on the thermochromic tendency index of the benchmark sample and the thermochromic tendency index of the sample to be tested. The thermochromic tendency index deviation is used to replace the multidimensional fingerprint deviation for consistency judgment logic. The thermochromic tendency index deviation is compared with a preset threshold using a single numerical value. A simpler single numerical value is used for comparison, and a quality stability evaluation conclusion is output based on the comparison result.

[0061] Among them, the red-yellow tendency index The calculation formula is as follows:

[0062] ,

[0063] in, Indicates channel weight, This indicates the color change tendency of the red-green axis after heating. This indicates the color change tendency of the yellow-blue axis after heating.

[0064] Correspondingly, the heat-induced discoloration tendency index deviation The calculation formula is as follows:

[0065] ,

[0066] ,

[0067] ,

[0068] in, This indicates the thermal discoloration tendency index of the sample under test. This indicates the heat-induced discoloration tendency index of the reference sample.

[0069] As an improvement to this embodiment, when applying a standardized heating procedure to the reference sample or the sample to be tested, the heating procedure is replaced by heating the reference sample or the sample to be tested using a constant-temperature oil bath or a customized portable miniature heating container, thereby shortening the measurement time and adapting to extreme field environments. As a specific implementation of the portable miniature heating container, an existing fiber material heating container can be selected.

[0070] This embodiment's method determines the batch quality stability and thermal stability of fibers by comparing the color fingerprints of the original fiber state and the standard heated state with a reference fingerprint. It utilizes independent judgment logic based on the color difference of the original state and the color difference caused by heating, and a diagnostic method to distinguish between two different quality problems: abnormal raw material composition and abnormal thermal stability. This rapid detection method eliminates the need for actual calculations or knowledge of specific performance values ​​such as heat resistance and oil absorption rate; it allows for quantitative quality decisions based solely on color consistency. This method is particularly suitable for on-site engineering applications, requiring only a portable spectrophotometer and an established "reference fingerprint database."

[0071] The above provides a detailed description of a method for batch quality stability testing of fiber raw materials based on color fingerprint spectrum provided by the present invention. Specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for detecting batch quality stability of fiber raw materials based on color fingerprinting, characterized in that, This includes the following operations: Selecting benchmark samples: Select fiber samples that have passed a full set of performance tests and whose engineering acceptance results meet the requirements as benchmark samples; Obtaining the reference color fingerprint: The multidimensional color information of the reference sample before heating is measured using a spectrophotometer. This unheated multidimensional color information is used as the first reference fingerprint spectrum. A standardized heating procedure is then applied to the reference sample, and the multidimensional color information of the heated sample is measured using the same spectrophotometer at predetermined time intervals. The heated multidimensional color information is used as the second reference fingerprint spectrum. The first reference fingerprint spectrum, the second reference fingerprint spectrum, and the sample information are stored in the fingerprint database as the color fingerprint file of the qualified fiber. The multidimensional color information includes lightness. Red-green axis and yellow-blue axis ; Acquiring the color fingerprint of the test sample: For the test sample, the same measurement conditions as those for acquiring the reference color fingerprint are used to detect the multidimensional color information of the test sample when it is not heated as the first test fingerprint, and the same standard heating procedure as those for acquiring the reference color fingerprint is used to detect the multidimensional color information of the test sample after it is heated as the second test fingerprint. Detection and screening: For the sample to be tested, the fingerprint deviation relative to the reference sample before and after heating is calculated to obtain the multidimensional fingerprint deviation. Based on the multidimensional fingerprint deviation, the consistency judgment logic is executed, and the multidimensional fingerprint deviation is compared with the preset qualified fluctuation threshold. Based on the comparison result, the quality stability evaluation conclusion is output.

2. The method for batch quality stability testing of fiber raw materials based on color fingerprint spectrum according to claim 1, characterized in that, Multidimensional fingerprint deviation includes original state deviation and thermochromic deviation, and the calculation formula is as follows: ， ， in, The original state deviation represents the fingerprint deviation between the test sample and the reference sample before heating. Indicates the brightness of the first fingerprint to be tested. This represents the red-green axis in the first fingerprint to be tested. This indicates the yellow-blue axis in the first fingerprint to be tested. Indicates the brightness in the first baseline fingerprint. This represents the red-green axis in the first baseline fingerprint. This indicates the yellow-blue axis in the first baseline fingerprint; Thermochromic deviation represents the fingerprint difference between the test sample and the reference sample after heating. Indicates the brightness of the second fingerprint sample. This indicates the red-green axis in the second fingerprint to be tested. This indicates the yellow-blue axis in the second fingerprint sample. Indicates the brightness in the second baseline fingerprint. This indicates the red-green axis in the second baseline fingerprint. This indicates the yellow-blue axis in the second baseline fingerprint; Correspondingly, when performing consistency judgment logic based on multidimensional fingerprint deviation, the original state deviation and thermal discoloration deviation are compared with the corresponding qualified fluctuation thresholds. Row comparison, if and If the sample being tested is highly consistent with the baseline in terms of raw material composition and thermally induced behavior, then the batch is deemed to be of stable quality and acceptable. This indicates that the sample to be tested has undergone significant changes in terms of raw material type and purity, posing a risk of material substitution or adulteration. Therefore, it is judged as having abnormal raw material composition, and rejection or retesting is recommended. but This indicates that the raw materials of the sample to be tested appear to be the same as those of the reference sample, but the chemical stability has deteriorated during the heating process, which is then judged as abnormal thermal stability and a risk of thermal damage.

3. The method for batch quality stability testing of fiber raw materials based on color fingerprint spectrum according to claim 1, characterized in that, For a preset acceptable fluctuation threshold, based on the fingerprint deviation of multiple batches of reference samples, the acceptable fluctuation threshold is dynamically updated using statistical methods. These statistical methods include setting... The method for controlling the upper limit dynamically updates the acceptable fluctuation threshold.

4. The method for batch quality stability testing of fiber raw materials based on color fingerprint spectrum according to claim 2, characterized in that, During the detection and screening process, for the sample to be tested, a thermochromic tendency index is constructed based on the red-green axis and yellow-blue axis in the color information and through channel weighting. A thermochromic tendency index deviation is constructed based on the thermochromic tendency index of the benchmark sample and the thermochromic tendency index of the sample to be tested. The thermochromic tendency index deviation is used to replace the multidimensional fingerprint deviation for consistency judgment logic. The thermochromic tendency index deviation is compared with a preset threshold value. Based on the comparison result, a quality stability evaluation conclusion is output. Among them, the red-yellow tendency index The calculation formula is as follows: ， in, Indicates channel weight, This indicates the color change tendency of the red-green axis after heating. This indicates the color change tendency of the yellow-blue axis after heating; Correspondingly, the heat-induced discoloration tendency index deviation The calculation formula is as follows: ， ， ， in, This indicates the thermal discoloration tendency index of the sample under test. This indicates the heat-induced discoloration tendency index of the reference sample.

5. The method for batch quality stability testing of fiber raw materials based on color fingerprint spectrum according to claim 2, characterized in that, When applying a standardized heating procedure to a reference sample or a test sample, the heating procedure can be replaced by heating the reference sample or the test sample using a constant-temperature oil bath or a custom-designed portable miniature heating container.

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