Precious metal data processing method, system and storage medium

Abstract

The present application relates to the technical field of financial service technology, and in particular to a method for processing precious metal data, including: collecting precious metal samples and reflection waveform data and associating and entering them into a database; in the detection process, recording the target unmelted reflection waveform data; obtaining the gold content, gram weight, and thickness of the target unmelted precious metal and determining them as a first set of data, and obtaining the unmelted detection result; if the unmelted detection result is normal, performing gold melting processing, obtaining the melted detection result, and the gold content, gram weight, and thickness of the melted gold block are the second set of data; if the melted detection result is a normal gold block, the gold content, gram weight, and thickness of the normal gold block are the third set of data, and the first set of data, the second set of data, the third set of data, and the reflection waveform data of the third set of data are associated and entered into a database, and the gold content, gram weight, and thickness are obtained by X-ray irradiation, weighing, and visual recognition. The present application can improve the accuracy of non-destructive detection of the purity of precious metals.

Description

Technical Field

[0001] The present application relates to the technical field of financial services technology, and in particular to a method, system and storage medium for processing precious metal data. Background Art

[0002] As the precious metals trading market continues to expand, the demand for testing the purity and authenticity of precious metals is also increasing. Traditional precious metal testing methods, such as water density method and X-ray testing, can only provide surface or partial information and cannot fully evaluate the internal structure and composition. Therefore, the industry urgently needs a method that can accurately and non-destructively test the purity of precious metals.

[0003] From the above, we can see that how to accurately detect the purity of precious metals non-destructively remains to be solved. Summary of the invention

[0004] In order to improve the accuracy of non-destructive detection of precious metal purity, the present application provides a precious metal data processing method, system and storage medium.

[0005] In the first aspect, the present application provides a method for processing precious metal data, which adopts the following technical solution:

[0006] A method for processing precious metal data comprises: collecting precious metal samples with different gold contents, weights and thicknesses, measuring each precious metal sample with an ultrasonic device, recording corresponding reflection waveform data, and recording the reflection waveform data in association with the precious metal sample into a database, wherein the reflection waveform data comprises speed, intensity and reflection mode, and the precious metal sample is an unmelted gold bar and a melted gold block; in an actual detection process, determining the corresponding target unmelted precious metal, measuring the target unmelted precious metal with an ultrasonic device, and recording the corresponding target unmelted reflection waveform data; performing X-ray irradiation, weighing and visual recognition on the target precious metal to obtain the gold content, weight and thickness corresponding to the target unmelted precious metal, determining the corresponding first reference precious metal sample in the database based on the gold content, weight and thickness corresponding to the target unmelted precious metal, detecting the target unmelted reflection waveform data with the reflection waveform data of the first reference precious metal sample, and obtaining the corresponding unmelted detection result, wherein the gold content, weight and thickness corresponding to the target unmelted precious metal are the first group of data; if the unmelted detection result is abnormal, marking the target unmelted precious metal as an abnormal gold bar; if If the unmelted gold detection result is normal, the target unmelted precious metal is melted to obtain the corresponding melted gold block, the melted gold block is subjected to X-ray irradiation, weighing, and visual identification to obtain the corresponding gold content, gram weight, and thickness of the melted gold block, the melted gold block is measured using an ultrasonic device, and the corresponding reflected waveform data of the melted gold block is recorded. Based on the corresponding gold content, gram weight, and thickness of the melted gold block, the corresponding second reference precious metal sample in the database is determined, the reflected waveform data of the melted gold block is tested with the reflected waveform data corresponding to the second reference precious metal sample in the database to obtain the corresponding The melt test result, wherein the gold content, gram weight, and thickness corresponding to the melted gold block are the second set of data; if the melt test result is abnormal, the melted gold block is marked as an abnormal gold block; if the melt test result is a normal gold block, the normal gold block is sent to the laboratory for gold content, gram weight, and thickness testing, and the gold content, gram weight, thickness, and reflection waveform data corresponding to the normal gold block are obtained. The gold content, gram weight, and thickness corresponding to the normal gold block are the third set of data, and the first set of data, the second set of data, the third set of data, and the reflection waveform data corresponding to the third set of data are associated and entered into the database. If the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal is determined as a new precious metal sample; the new precious metal sample is sent to the laboratory for testing, and the corresponding new sample data is obtained, and the new sample data is associated with the reflection waveform data and entered into the database, wherein the new sample data includes the thickness, weight, and gold content of the target precious metal.

[0007] Optionally, the method also includes: obtaining target weight data of precious metals that are missing in the database; retrieving adjacent reflection waveform data corresponding to the derived precious metal samples based on the weight adjacent to the weight corresponding to the target weight data in the database, wherein there are multiple adjacent reflection waveform data; predicting the corresponding reflection waveform change trend based on the multiple adjacent reflection waveform data, determining the derived reflection waveform data corresponding to the target weight data in the reflection waveform change trend, associating the derived reflection waveform data with the target weight data and entering them into the database.

[0008] Optionally, in the process of using ultrasonic equipment to measure each sample and record the corresponding reflection waveform data, the method also includes: performing ultrasonic reflection waveform measurement at the geometric center of the precious metal sample to obtain central reflection waveform data corresponding to the central area; performing ultrasonic reflection waveform measurement at multiple positions equidistantly distributed at the edge of the precious metal sample to obtain a corresponding set of circumferential reflection waveform data; comparing and integrating all circumferential reflection waveform data of the circumferential reflection waveform data set with the central reflection waveform data to generate corresponding reflection waveform data.

[0009] Optionally, the method also includes: extracting corresponding key parameters based on the central reflection waveform data and the peripheral reflection waveform data set, wherein the key parameters include peak position, amplitude, spectrum distribution, and data points that deviate from the normal range; judging whether there is a corresponding specific change in the reflection waveform corresponding to a specific point based on all the key parameters; if so, sending the corresponding precious metal sample to the laboratory for measurement, obtaining a quality assessment report corresponding to the precious metal sample based on the experimental results, and associating the specific changes with the quality assessment report and entering them into a database, wherein the quality assessment report includes purity, uniformity, and thickness.

[0010] Optionally, the method also includes: extracting target key parameters of the target unmelted reflection waveform data corresponding to the new precious metal sample, and performing a detailed comparison between the target key parameters and the target key parameters of the corresponding reflection waveform data in the database; obtaining the corresponding detailed comparison results, retrieving a pre-set threshold interval, wherein the threshold interval includes a threshold value for each key parameter, and comparing the detailed comparison results with the threshold interval; if the key parameter error of the detailed comparison result is not within the threshold interval, the new precious metal sample is marked as risky or unknown; if the key parameter error of the detailed comparison result is within the threshold interval, based on retrieving the known influence of different metal components on ultrasonic propagation characteristics, the specific impurity type and content present in the new precious metal sample are predicted.

[0011] Optionally, in the process of entering into the database, the method also includes: obtaining actual volume information and density information of the precious metal sample, obtaining physical parameters corresponding to the precious metal sample, the physical parameters including hardness, melting point, and conductivity; in the actual detection process, while performing a detailed comparison between the target unmelted reflection waveform data corresponding to the target precious metal and the reflection waveform data in the database, the actual volume information and density information of the target precious metal are also compared with the corresponding data in the database in multiple dimensions.

[0012] Optionally, the method also includes: conducting market research regularly, and obtaining new precious metal samples processed with new materials and new processes according to market demand; performing ultrasonic reflection waveform measurement on the new precious metal samples, and associating corresponding physical parameters to obtain corresponding reflection waveform data, wherein the parameter data corresponding to the new precious metal samples are all verified in the laboratory; comparing the reflection waveform data of the new precious metal samples with the data in the database in detail to identify differential data; associating the reflection waveform data, physical parameters and differential data corresponding to the new precious metal samples and entering them into the database.

[0013] In a second aspect, the present application provides a precious metal data processing system, which adopts the following technical solution:

[0014] A precious metal data processing system, comprising:

[0015] A reflection waveform data recording module collects precious metal samples of different gold contents, weights, and thicknesses, uses ultrasonic equipment to measure each precious metal sample, and is used to record corresponding reflection waveform data, and associates the reflection waveform data with the precious metal sample and enters it into the database, wherein the reflection waveform data includes speed, intensity, and reflection mode, and the precious metal samples are unmelted gold bars and melted gold blocks;

[0016] The unmelted detection result acquisition module determines the corresponding target unmelted precious metal during the actual detection process, uses ultrasonic equipment to measure the target unmelted precious metal, and records the corresponding target unmelted reflection waveform data; performs X-ray irradiation, weighing, and visual identification on the target precious metal to obtain the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; determines the corresponding first reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; and detects the target unmelted reflection waveform data with the reflection waveform data of the first reference precious metal sample to obtain the corresponding unmelted detection result, wherein the gold content, gram weight, and thickness corresponding to the target unmelted precious metal are the first group of data;

[0017] A melted detection result acquisition module, if the unmelted detection result is abnormal, marks the target unmelted precious metal as an abnormal gold bar; if the unmelted detection result is normal, performs gold melting on the target unmelted precious metal to obtain the corresponding melted gold block, performs X-ray irradiation, weighing, and visual identification on the melted gold block to obtain the gold content, gram weight, and thickness corresponding to the melted gold block, uses ultrasonic equipment to measure the melted gold block, records the corresponding reflected waveform data of the melted gold block, determines the corresponding second reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the melted gold block, and detects the reflected waveform data of the melted gold block with the reflected waveform data corresponding to the second reference precious metal sample in the database to obtain the corresponding melted detection result, wherein the gold content, gram weight, and thickness corresponding to the melted gold block are the second set of data;

[0018] A multi-group data association module, if the melted detection result is abnormal, the melted gold block will be marked as an abnormal gold block; if the melted detection result is a normal gold block, the normal gold block will be sent to the laboratory for testing of gold content, weight, and thickness, and the gold content, weight, thickness and reflection waveform data corresponding to the normal gold block will be obtained. The gold content, weight, and thickness corresponding to the normal gold block are the third group of data, which are used to associate the first group of data, the second group of data, the third group of data and the reflection waveform data corresponding to the third group of data and enter them into the database.

[0019] A detection module, if the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal is determined as a new precious metal sample; it is used to send the new precious metal sample to the laboratory for detection, obtain corresponding new sample data, associate the new sample data with the reflection waveform data and enter them into the database, wherein the new sample data includes the thickness, weight and gold content of the target precious metal.

[0020] In a third aspect, the present application provides a method for processing precious metal data, which adopts the following technical solution:

[0021] A method for processing precious metal data comprises a processor, wherein a program of the method for processing precious metal data described above is run in the processor.

[0022] In a fourth aspect, the present application provides a storage medium, which adopts the following technical solution:

[0023] A storage medium stores a program of the method for processing precious metal data as described above.

[0024] In summary, the present application includes at least one of the following beneficial technical effects:

[0025] 1. The present invention ensures that the overall structural characteristics of the sample are fully captured by performing ultrasonic reflection waveform measurements at multiple locations equidistantly distributed at the geometric center and edge of the precious metal sample. This method not only provides a more detailed data basis, but also generates more accurate reflection waveform data by comparing and integrating the center reflection waveform data with the peripheral reflection waveform data set. In addition, the key parameters extracted based on these reflection waveform data (such as peak position, amplitude, and spectrum distribution) can effectively identify abnormal changes at specific points, thereby improving the sensitivity and accuracy of detection. For samples with specific changes, the system will automatically send them to the laboratory for further measurement to ensure that the final quality assessment report is accurate and reliable.

[0026] 2. In order to further improve the accuracy of detection, the present invention adopts a multi-dimensional data analysis method. In the actual detection process, in addition to comparing the reflection waveform data, the actual volume information and density information of the target precious metal are also compared in detail with the corresponding data in the database. This not only increases the coverage of the detection, but also forms a comprehensive quality assessment framework by combining other physical parameters (such as hardness, melting point, and conductivity). At the same time, the system sets a reasonable threshold range for each key parameter. When the key parameter error of a new sample exceeds this threshold, it is marked as "risky" or "unknown" and triggers further inspection procedures. This multi-dimensional analysis and strict threshold judgment mechanism greatly reduce the possibility of misjudgment and ensure the high reliability of the test results.

[0027] 3. The present invention emphasizes the regular updating of the standard waveform library in the database to reflect the new materials and new processes appearing on the market, ensuring the continuous optimization and adaptability of the system. By obtaining precious metal samples treated with representative new materials and new processes and conducting strict laboratory verification on them, the system can timely enter the reflection waveform data and related physical parameters of the new precious metal samples into the database. This process not only ensures the cutting-edge nature and accuracy of the database content, but also enables the system to continuously learn and adapt to the changing laws brought about by new materials, thereby maintaining high-precision detection capabilities when faced with samples of unknown specifications or complex structures. The regular update and self-optimization mechanism enables the present invention to always maintain optimal performance in an ever-changing market environment, significantly improving the accuracy of non-destructive detection of precious metal purity. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The figure is a flow chart of a method for processing precious metal data according to an exemplary embodiment.

[0029] Figure 2 The figure is a structural block diagram of a system for processing precious metal data according to an exemplary embodiment. DETAILED DESCRIPTION

[0030] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings.

[0031] In the description of this specification, the description with reference to the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0032] The present application embodiment discloses a method for processing precious metal data, referring to Figure 1 ,include:

[0033] S100, collecting precious metal samples with different gold contents, measuring each precious metal sample using an ultrasonic device, recording corresponding reflection waveform data, and associating the reflection waveform data with the precious metal sample and entering them into a database.

[0034] Among them, according to the common types and specifications of precious metals in the market, a series of samples with different gold contents are selected. These samples should cover pure gold, K gold (such as 18K, 24K, etc.), and other alloys containing different metal components; it is pointed out here that it is necessary to ensure that the source of each sample is reliable and undergo preliminary verification to ensure its representativeness and accuracy. For each type of sample, as many examples of different shapes, thicknesses and weights as possible are selected, and the basic information of each sample is recorded in detail, including but not limited to shape, thickness, weight and gold content. This information will be entered into the database together with the data collected later. Through the extensive and representative sample selection, a solid foundation is laid for the construction of a comprehensive standard waveform library to ensure the accuracy and reliability of subsequent test results.

[0035] The measurement process for each precious metal sample is performed using ultrasonic equipment:

[0036] First, the ultrasonic equipment needs to be calibrated to ensure that it works in the best condition, and the appropriate frequency, power and other parameters are set to adapt to precious metal samples of different types and specifications. Ultrasonic reflection waveform measurements are performed at multiple locations equidistantly distributed at the geometric center (i.e., the middle point) and the edge of each sample. The reflection waveform data such as speed, intensity and reflection mode obtained in each measurement are recorded. Ensure the integrity and accuracy of the data for subsequent analysis. Through precise multi-point measurement, the overall structural characteristics of the sample are fully captured, providing detailed data support and improving the credibility of the test results.

[0037] Subsequently, the reflection waveform data obtained from each sample is collated into a standardized format, and the basic information of each sample (such as shape, thickness, weight and gold content) is associated. The collated reflection waveform data and its associated information are entered into a specially designed database, and a version control system is implemented to record the specific content and time of each update for easy traceability and management.

[0038] By establishing a standard waveform library containing rich reflection waveform data as the basis for subsequent detection and comparison, the continuous optimization and self-learning ability of the system are ensured.

[0039] Here, for the use of ultrasonic equipment to measure each precious metal sample, the following steps are required:

[0040] S101, performing ultrasonic reflection waveform measurement at the geometric center of the precious metal sample to obtain central reflection waveform data corresponding to the central area.

[0041] First, use precision measuring tools (such as calipers, laser rangefinders) to accurately find the geometric center of the sample. For irregularly shaped samples, three-dimensional scanning technology can be used to assist in positioning; fix the sample on a stable platform to ensure that its surface is flat and perpendicular to the ultrasonic probe. This helps to obtain clearer and more consistent reflection waveforms.

[0042] Accurately align the ultrasonic probe with the geometric center of the sample to measure the reflected waveform. Record the reflected waveform data such as the speed, intensity and reflection mode at that location; in order to improve the reliability of the data and reduce accidental errors, multiple measurements can be made at the same center point, and the average value is taken as the final center reflected waveform data. By accurately measuring the geometric center of the sample, it is ensured that the information of the core area of ​​the sample can be captured, providing a benchmark reference for subsequent multi-point comparisons and improving the overall accuracy of the test results.

[0043] S102, measuring ultrasonic reflection waveforms at a plurality of positions equidistantly distributed at the edge of the precious metal sample to obtain a corresponding peripheral reflection waveform data set.

[0044] Among them, select four equally spaced key positions on the edge of the sample (for example, north, south, east, and west). These positions should be evenly distributed around the periphery of the sample to ensure full coverage of the main boundary area of ​​the sample. In addition, the position of each measurement point can be lightly marked on the surface of the sample with a non-destructive marking method (such as an erasable marker) to facilitate quick positioning during subsequent operations.

[0045] It should be pointed out here that before each measurement, the ultrasonic probe must be cleaned and calibrated to avoid data deviation caused by probe contamination or wear; the ultrasonic probe is aimed at each marked measurement point in turn to measure the reflected waveform, and the reflected waveform data such as speed, intensity and reflection pattern at each position are also recorded.

[0046] During the entire measurement process, constant temperature and humidity conditions are maintained to reduce the impact of external environmental factors on the measurement results. Finally, the reflection waveform data obtained from various peripheral positions are sorted out to form a complete peripheral reflection waveform data set. By measuring multiple key positions on the edge of the sample, it is ensured that the overall structural characteristics of the sample can be captured, possible local defects or unevenness can be identified, and the comprehensiveness and reliability of the test results can be enhanced.

[0047] S103, comparing and integrating all the circumferential reflection waveform data of the circumferential reflection waveform data set with the central reflection waveform data to generate corresponding reflection waveform data.

[0048] Among them, all the reflection waveform data obtained from the center point and the circumferential position are imported into the data analysis system, and key parameters are extracted from each reflection waveform data, such as peak position, amplitude, spectrum distribution, etc. Mathematical algorithms (such as correlation coefficient, Euclidean distance) are used to compare the similarity between each circumferential reflection waveform data and the center reflection waveform data, so as to identify any data points that significantly deviate from the normal range.

[0049] Based on the comparison results, areas where internal interlayers, cracks or other non-uniformly distributed inclusions may exist are identified. It should be noted that these anomalies usually show unique waveform changes at certain specific points.

[0050] All the circumferential reflection waveform data are integrated with the central reflection waveform data to generate a comprehensive reflection waveform image, which not only contains the specific information of each point, but also reflects the overall structural characteristics of the entire sample. By performing pattern recognition on the integrated reflection waveform image, different types of internal structures and component distributions can be effectively distinguished. For example, the difference in the comprehensive reflection waveform between pure gold samples and samples containing impurities will be more obvious.

[0051] Through the detailed execution process of the above three steps, the present invention can not only perform comprehensive and accurate ultrasonic reflection waveform measurement at key positions of precious metal samples, but also generate a comprehensive reflection waveform image through comparison and integration, thereby ensuring the high accuracy and reliability of the detection results.

[0052] S110, during the actual detection process, determine the corresponding target unmelted precious metal, use ultrasonic equipment to measure the target unmelted precious metal, and record the corresponding target unmelted reflection waveform data; perform X-ray irradiation, weighing, and visual identification on the target precious metal to obtain the gold content, gram weight, and thickness corresponding to the target unmelted precious metal, determine the corresponding first reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the target unmelted precious metal, detect the target unmelted reflection waveform data with the reflection waveform data of the first reference precious metal sample, and obtain the corresponding unmelted detection result, wherein the gold content, gram weight, and thickness corresponding to the target unmelted precious metal are the first group of data;

[0053] When a new sample needs to be tested, its basic information (such as shape, thickness, and weight) is first confirmed. This information helps to preliminarily determine the specifications that the sample may correspond to, and the target precious metal is measured using a calibrated ultrasonic device. Reflection waveform data is also collected at multiple key locations, and the target unmelted reflection waveform data obtained from each measurement is recorded to ensure the integrity and accuracy of the data, providing a basis for subsequent comparative analysis.

[0054] Then, the process of X-ray irradiation, weighing and visual identification of the target unmelted precious metal is as follows:

[0055] X-ray irradiation: Use a high-precision X-ray fluorescence spectrometer to irradiate the target unmelted precious metal and collect the corresponding spectrum to obtain the type and content information of the elements inside it, especially the gold content.

[0056] Weighing: Use an electronic balance to accurately weigh the target unmelted precious metal and record the weight.

[0057] Visual Identification: Use the visual identification system to measure the size and shape of the target unmelted precious metal to ensure the accuracy of thickness and other geometric parameters. This information helps to more fully understand the physical characteristics of the sample.

[0058] It should be pointed out here that in the embodiment of the present application scheme, the execution steps involving multiple X-ray irradiation, weighing, and visual identification have been explained for each execution step and will not be repeated later.

[0059] In addition, historical sample data with the same or similar specifications as the target unmelted precious metal is retrieved from the database as the first reference precious metal sample to ensure that the selected sample covers the main characteristics of the target unmelted precious metal to improve the accuracy of the comparison. Among them, it is necessary to compare the similarities and differences between the key parameters, for example, to compare the consistency of parameters such as gold content, gram weight, thickness, etc., so the closest target unmelted precious metal sample is selected as the first reference sample. Through a strict multi-dimensional comparison mechanism, the closest target unmelted precious metal sample can be quickly screened out, reducing unnecessary laboratory testing workload and improving testing efficiency.

[0060] Finally, mathematical algorithms (such as correlation coefficient, Euclidean distance, etc.) are used to compare the reflection waveform data of the target unmelted precious metal with the reflection waveform data of the first reference precious metal sample in detail to identify any data points that significantly deviate from the normal range. Based on the comparison results, a detailed unmelted detection report is generated, listing all points marked as "needing further inspection" and their specific parameter changes.

[0061] S120, if the unmelted detection result is abnormal, mark the target unmelted precious metal as an abnormal gold bar; if the unmelted detection result is normal, perform gold melting on the target unmelted precious metal to obtain the corresponding melted gold block, perform X-ray irradiation, weighing, and visual identification on the melted gold block to obtain the corresponding gold content, gram weight, and thickness of the melted gold block, use ultrasonic equipment to measure the melted gold block, record the corresponding reflected waveform data of the melted gold block, determine the corresponding second reference precious metal sample in the database based on the corresponding gold content, gram weight, and thickness of the melted gold block, detect the reflected waveform data of the melted gold block with the reflected waveform data corresponding to the second reference precious metal sample in the database, and obtain the corresponding melted detection result, wherein the corresponding gold content, gram weight, and thickness of the melted gold block are the second group of data.

[0062] Among them, if the unmelted detection result is abnormal, the target unmelted precious metal will be marked as "abnormal gold bar" and a corresponding alarm notification will be generated to remind relevant personnel to pay attention to the sample or prompt the equipment not to recycle it. It is recommended to send it back to the laboratory for testing and recycling. According to the specific situation, further testing or verification suggestions can also be made, such as sending it to the laboratory for more detailed analysis.

[0063] If the unmelted test result is normal, the target unmelted precious metal will be sent to the gold melting equipment for melting treatment to ensure that the temperature and time during the melting process are properly controlled to avoid the volatilization of impurities or other chemical changes affecting the subsequent test results; after melting, a molten gold block is formed to ensure its physical state is stable, which is convenient for subsequent X-ray irradiation detection.

[0064] The melted gold block is subjected to X-ray irradiation, weighing and visual identification. The corresponding gold content, gram weight and thickness of the melted gold block are also required to be determined as the second set of data acquisition. The execution process of X-ray irradiation, weighing and visual identification of the target unmelted precious metal is the same as mentioned above, so it will not be repeated here.

[0065] Similarly, by comparing the consistency of parameters such as gold content, gram weight, thickness, etc., historical sample data with the same or similar specifications as the melted gold block is retrieved from the database as the second reference precious metal sample. Here it is necessary to ensure that the selected sample covers the main characteristics of the melted gold block to improve the accuracy of the comparison.

[0066] At the same time, the reflection waveform data of the melted gold block is compared in detail with the reflection waveform data of the second reference precious metal sample to identify any data points that significantly deviate from the normal range; based on the comparison results, a detailed melted test report is generated, listing all points marked as "needing further inspection" and their specific parameter changes. Through detailed comparison analysis, it is ensured that the differences between the melted gold block and the second reference sample can be accurately identified, providing reliable test results.

[0067] S130, if the melted gold nugget is abnormal, mark the melted gold nugget as an abnormal gold nugget; if the melted gold nugget is normal, send the normal gold nugget to the laboratory for testing of gold content, weight and thickness, and obtain the gold content, weight, thickness and reflection waveform data corresponding to the normal gold nugget. The gold content, weight and thickness corresponding to the normal gold nugget are the third group of data. The first group of data, the second group of data, the third group of data and the reflection waveform data corresponding to the third group of data are associated and entered into the database.

[0068] Among them, if the melted gold detection result is abnormal, the melted gold block will be marked as an "abnormal gold block" and the abnormal gold block will be treated in the same way as the abnormal gold bar.

[0069] For the normal results of the melted gold nuggets, the normal gold nuggets are sent to the laboratory for detailed testing to obtain their true gold content, weight, thickness and other physical parameters. It is necessary to ensure that the laboratory has sufficient resources and technical capabilities to handle these special samples. Then, the results of each laboratory test are recorded in detail to ensure the integrity and accuracy of the data, especially those points that show consistency in ultrasonic testing, to ensure that the test covers every suspicious point, and to record the type and content of each element, as well as the environmental conditions during the test.

[0070] The first set of data (target unmelted precious metal), the second set of data (melted gold nuggets), the third set of data (normal gold nuggets) and their corresponding reflection waveform data are associated and entered into the database, ensuring that each data item is clearly marked with its source and measurement conditions for easy subsequent retrieval and management. By associating and entering multiple sets of data into the database, not only is the content of the database enriched, but the system's self-learning ability is also enhanced, making future detection more accurate and better able to cope with the challenges brought by new materials and technologies.

[0071] S140, if the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal is determined as a new precious metal sample; the new precious metal sample is sent to the laboratory for testing to obtain corresponding new sample data, and the new sample data is associated with the reflection waveform data and entered into the database, wherein the new sample data includes the thickness, weight and gold content of the target precious metal.

[0072] Among them, if the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal will be marked as a "new precious metal sample", and the new precious metal sample will be sent to the laboratory for detailed testing to obtain its actual gold content, gram weight, thickness and other physical parameters. The final confirmed results of the laboratory will be fed back to the database, and the reflection waveform data of the new sample and its related information (such as shape, thickness, weight and gold content) will be associated and entered into the database.

[0073] By associating and entering the relevant data of new precious metal samples into the database, not only the content of the database is enriched, but also the system's self-learning ability is enhanced, making future detection more accurate and better able to respond to the challenges brought by new materials and technologies.

[0074] In order to specifically demonstrate the application of the above precious metal data processing method, we take a common 24K pure gold bar as an example. Assume that we already have a database containing a variety of precious metal samples, and we are going to include a common 24K pure gold bar in the database. The following is a specific application description of the detection and data processing of the 24K pure gold bar according to the above technical solution, ensuring that the logic is smooth and in line with the solution itself.

[0075] Initial testing and multimodal data collection: When a new sample needs to be tested, the basic information of the 24K pure gold bar (such as shape, thickness, and weight) is first confirmed. This information helps to preliminarily determine its possible specifications. Use calibrated ultrasonic equipment to collect reflection waveform data of the 24K pure gold bar at multiple key locations, and record the target unmelted reflection waveform data obtained in each measurement to ensure the integrity and accuracy of the data, providing a basis for subsequent comparative analysis.

[0076] Subsequently, the 24K pure gold bars were subjected to X-ray irradiation, weighing and visual identification: X-ray irradiation: high-precision X-ray fluorescence spectrometer is used to obtain the types and content information of internal elements, especially the gold content; weighing: accurate weighing is performed using an electronic balance and the gram weight is recorded; visual identification: the visual identification system is used to measure the size and shape to ensure the accuracy of thickness and other geometric parameters. These comprehensive physical parameters (gold content, gram weight, thickness) are used as the first set of data for subsequent comparison and analysis.

[0077] Database matching and comparison analysis: retrieve historical sample data with the same or similar specifications as the target unmelted 24K pure gold bar from the database as the first reference precious metal sample. By comparing the consistency of key parameters (gold content, gram weight, thickness, etc.), select the closest target unmelted 24K pure gold bar sample as the first reference sample. Then compare the reflection waveform data in detail, identify any data points that significantly deviate from the normal range, and generate a detailed unmelted detection report.

[0078] Abnormal and normal path processing: If the unmelted test results show abnormalities, the 24K pure gold bar will be marked as an "abnormal gold bar" and an alarm notification will be generated to remind relevant personnel to pay attention or suggest sending it back to the laboratory for further analysis. If the unmelted test results are normal, the 24K pure gold bar will be sent to the gold melting equipment for melting to ensure that the temperature and time during the melting process are properly controlled to avoid the volatilization of impurities or other chemical changes affecting the subsequent test results. After melting, a molten gold block is formed to ensure its physical state is stable, which is convenient for subsequent X-ray irradiation detection. Repeat the above X-ray irradiation, weighing, and visual recognition process for the melted gold block to obtain the second set of data (gold content, gram weight, thickness). Again, retrieve historical sample data with the same or similar specifications as the melted gold block from the database as the second reference sample, compare the reflection waveform data, and generate a melted test report.

[0079] Final inspection and data entry: If the melted test results show abnormalities, the melted gold nugget will be marked as an "abnormal gold nugget" and treated the same way as the abnormal gold bar. If the melted test results are normal, the normal gold nugget will be sent to the laboratory for detailed inspection to obtain its true gold content, gram weight, thickness and other physical parameters to ensure the integrity and accuracy of the data. Finally, the first set of data (target unmelted 24K pure gold bar), the second set of data (melted gold nugget), the third set of data (normal gold nugget) and their corresponding reflection waveform data are associated and entered into the database to ensure that each data item is clearly marked with its source and measurement conditions for subsequent retrieval and management.

[0080] New sample processing: If the corresponding first reference precious metal sample in the database cannot be determined based on the 24K pure gold bar, it will be marked as a "new precious metal sample". The new precious metal sample will be sent to the laboratory for detailed testing to obtain its true gold content, gram weight, thickness and other physical parameters. The final confirmed results of the laboratory will be fed back to the database, and the reflection waveform data of the new sample and its related information (such as shape, thickness, weight and gold content) will be associated and entered into the database to enhance the system's self-learning ability and make future testing more accurate.

[0081] In the embodiment of the present application, the database has self-learning capability, so the method further includes:

[0082] S1201, obtaining the missing target weight data of precious metals in the database.

[0083] Among them, the database is regularly reviewed to identify the weight specifications of precious metals that have not yet been covered. This can be done by analyzing market trends, user feedback or laboratory test records to determine which weight specifications are missing; for each missing weight specification identified, its specific value range is clarified. For example, if there is data of 9.0 grams and 9.5 grams in the database, but data of 9.2 grams is missing, 9.2 grams is set as the target weight; other relevant information about the target weight specification is recorded, such as possible shape, thickness and expected gold content.

[0084] S1202, based on the derived precious metal samples of the weight adjacent to the weight corresponding to the target weight data in the database, retrieve the adjacent reflection waveform data corresponding to the derived precious metal samples.

[0085] Among them, according to the target weight (such as 9.2 grams), the closest known weight specifications (such as 9.0 grams and 9.5 grams) are selected as reference samples to ensure that the selected samples cover the upper and lower limits of the target weight. All precious metal samples of selected adjacent specifications and their corresponding reflection waveform data are retrieved from the database to ensure that each sample contains complete measurement information, including the reflection waveform data set at the center point and the peripheral position.

[0086] The retrieved reflection waveform data is sorted and standardized to facilitate subsequent analysis. At the same time, the basic information of each sample (such as shape, thickness, weight and gold content) is recorded. By selecting and retrieving precious metal samples of adjacent specifications, reliable basic data is provided for subsequent derivation to ensure the accuracy and representativeness of the derivation results.

[0087] In addition, for each precious metal sample of adjacent specifications, the reflection waveform data of multiple key positions at the geometric center and edge are extracted; all the extracted reflection waveform data are integrated into a data set, which should contain reflection waveform characteristics at multiple different positions, such as speed, intensity, and reflection mode. Each reflection waveform data is parameterized to extract key parameters (such as peak position, amplitude, and spectrum distribution); by comprehensively extracting and arranging the multi-point reflection waveform data of adjacent specification samples, a rich and detailed data set is constructed to provide a solid foundation for predicting the trend of reflection waveform changes.

[0088] S1203, predicting the corresponding reflection waveform change trend based on a plurality of adjacent reflection waveform data, determining the derived reflection waveform data corresponding to the target weight data in the reflection waveform change trend, associating the derived reflection waveform data with the target weight data and entering them into a database.

[0089] Among them, using mathematical algorithms (such as linear interpolation, spline interpolation or regression analysis) to model the reflection waveform data of multiple adjacent specification samples can help predict the change trend of the reflection waveform under the target weight (such as 9.2 grams). Based on the established mathematical model, predict the change trend of the reflection waveform under the target weight, which includes but is not limited to the change law of the speed, intensity and reflection pattern of the waveform. Check whether there are any abnormal fluctuations or illogical places in the prediction results. If necessary, adjust the model parameters to improve the accuracy of the prediction.

[0090] According to the predicted reflection waveform change trend, the reflection waveform data corresponding to the target weight (such as 9.2 grams) is synthesized, and the final derived reflection waveform data is associated with the target weight data and entered into the database. By synthesizing and verifying the derived reflection waveform data, the newly generated data is ensured to be accurate and updated to the database in a timely manner, improving the system's self-learning ability and data integrity.

[0091] In order to demonstrate the application of the self-learning ability of the above database, we take the data of 9.2g pure gold bar as an example. Assume that the current database already has the reflection waveform data of 9.0g and 9.5g pure gold bars, but lacks the data of 9.2g.

[0092] During the periodic review of the database, through analysis of market trends, user feedback and laboratory test records, it was found that the market demand for 9.2 grams of pure gold bars was gradually increasing, and the database was missing data for this weight specification. Therefore, 9.2 grams was set as the target weight, and other relevant information about this weight specification was recorded, such as possible shapes (such as rectangular), thickness, and expected gold content (100% pure gold).

[0093] According to the target weight of 9.2 grams, the closest known weight specifications - 9.0 grams and 9.5 grams - were selected as reference samples. All precious metal samples of these two adjacent specifications and their corresponding reflection waveform data were retrieved from the database to ensure that each sample contained complete measurement information, including a collection of reflection waveform data at multiple key locations of the geometric center and edge. These data were organized into a standardized format for subsequent analysis, and the basic information of each sample (such as shape, thickness, weight, and gold content) was recorded in detail.

[0094] For each adjacent specification of 9.0g and 9.5g pure gold bar samples, the reflection waveform data of multiple key positions at the geometric center and edge are extracted. All extracted reflection waveform data are integrated into a data set, which not only contains characteristics such as speed, intensity and reflection mode, but also has been parameterized to extract key parameters such as peak position, amplitude size, and spectrum distribution. By comprehensively extracting and collating the multi-point reflection waveform data of adjacent specification samples, a rich and detailed data set is constructed, which provides a solid foundation for predicting the trend of reflection waveform changes.

[0095] Model the reflection waveform data of 9.0g and 9.5g pure gold bars using mathematical algorithms (such as linear interpolation, spline interpolation, or regression analysis) to predict the changing trend of the reflection waveform under 9.2g pure gold bars. Based on the established mathematical model, predict the changing patterns of the velocity, intensity, and reflection pattern of 9.2g pure gold bars at different locations. Check whether there are any abnormal fluctuations or illogicalities in the prediction results. If necessary, adjust the model parameters to improve the accuracy of the prediction.

[0096] According to the predicted reflection waveform change trend, the reflection waveform data corresponding to the 9.2g pure gold bar is synthesized. It is ensured that the synthesized waveform not only reflects the overall structural characteristics, but also captures the local details. The final derived reflection waveform data is associated with the target weight of 9.2g and is entered into the database in a timely manner. By synthesizing and verifying the derived reflection waveform data, the newly generated data is ensured to be accurate and the system's self-learning ability and data integrity are improved.

[0097] Through the above self-learning process, the database can not only automatically identify and fill in the missing precious metal weight specification data, but also scientifically derive the reflection waveform change trend under the target weight, thereby synthesizing the corresponding reflection waveform data. This method not only enhances the self-learning ability of the database, ensures the comprehensiveness and accuracy of the data, but also significantly improves the accuracy of non-destructive detection of precious metal purity.

[0098] It should be noted here that the method also includes:

[0099] S1411, extracting corresponding key parameters based on the center reflection waveform data and the peripheral reflection waveform data set.

[0100] Among them, professional data analysis software or custom scripts are used to process each reflection waveform data. These tools can automatically identify and extract a series of key parameters. The key parameters are accurately extracted through automated tools to ensure that the basic data for subsequent analysis is accurate and improve the reliability and accuracy of the test results.

[0101] It should be pointed out here that the key parameters include but are not limited to:

[0102] Peak position: Determines the position where the maximum amplitude occurs in the reflected waveform, which can reflect changes in the internal structure of the sample.

[0103] Amplitude: Measures the maximum amplitude of the reflected waveform. Changes in amplitude may indicate differences in density or composition within the sample.

[0104] Spectral distribution: Analyze the energy distribution of the reflected waveform at different frequencies. Spectral distribution helps to identify tiny structural differences within the sample.

[0105] Data points that deviate from the normal range: Detect whether there are any data points that deviate significantly from the normal range. These abnormal points may be signs of internal defects in the sample (such as cracks, interlayers).

[0106] S1412, based on all key parameters, determine whether the reflection waveform corresponding to the specific point has a corresponding specific change.

[0107] Among them, mathematical algorithms (such as correlation coefficient, Euclidean distance, etc.) are used to compare the similarities and differences between key parameters; for example, compare whether the peak positions of the center point and the peripheral points are consistent, whether there are significant differences in the amplitude, whether there are obvious changes in the spectrum distribution, etc. A reasonable threshold range is set for each key parameter. When any parameter of a new sample exceeds this threshold, it is considered that there may be quality problems. For example, if the amplitude at a certain position is significantly higher than that at other positions, it may indicate the existence of local defects, which will be explained in detail later.

[0108] Through comprehensive analysis of multiple key parameters, any data points that significantly deviate from the normal range are identified and marked as "needing further inspection"; pattern recognition can help distinguish different types of internal structures and component distributions. By generating a detailed anomaly detection report, all points marked as "needing further inspection" and their specific parameter changes are listed. Through strict multi-dimensional comparison and threshold judgment mechanisms, specific points that may have abnormal internal structures or components can be quickly screened out to reduce unnecessary laboratory testing workload.

[0109] S1413, if yes, the corresponding precious metal sample is sent to the laboratory for measurement, and a quality assessment report corresponding to the precious metal sample is obtained based on the experimental results, and the specific changes are associated with the quality assessment report and entered into the database.

[0110] Among them, for precious metal samples marked as "needing further inspection", physical marking (such as labeling) should be carried out immediately to ensure that the samples will not be confused during the entire transmission process. It is necessary to contact laboratory technicians, prepare the corresponding testing equipment and environmental conditions, and conduct comprehensive and accurate measurements of the marked samples in the laboratory, including but not limited to purity, uniformity, thickness and other aspects of testing, and use high-precision instruments (such as X-ray fluorescence spectrometers, electron microscopes, etc.) to obtain detailed physical parameters; record the results of each measurement in detail to ensure the integrity and accuracy of the data, especially those points that show abnormalities in ultrasonic testing, to ensure that laboratory verification can cover every suspicious point.

[0111] Then, based on the laboratory's measurement results, a detailed quality assessment report is generated. The quality assessment report should include the following:

[0112] Purity: The actual gold content of the sample, whether it meets the expected standards.

[0113] Uniformity: Whether the internal structure of the sample is uniform, whether there are interlayers or other uneven distribution phenomena.

[0114] Thickness: Whether the physical dimensions of the sample are consistent and whether there is any local thinning or thickening.

[0115] The physical parameters of the sample and their changing trends can be intuitively displayed by combining charts and text. For example, a three-dimensional model of the sample's internal structure can be drawn, marking the specific locations of all abnormal points.

[0116] Finally, all the information in the quality assessment report is collated into a standardized format. Special attention should be paid to the one-to-one correspondence between specific changes verified by the laboratory (such as internal interlayers, cracks, etc.) and abnormal points in the original reflection waveform data; the collated information is entered into a specially designed database. Ensure that the detailed information of each abnormal point is associated with the corresponding reflection waveform data for subsequent retrieval and management.

[0117] Through the detailed execution process of S1411 to S1413 above, not only can comprehensive and accurate ultrasonic reflection waveform measurements be performed at key locations of precious metal samples, but also it is possible to scientifically determine whether there are internal structural or compositional abnormalities at specific points based on the extracted key parameters. For samples with problems, precise laboratory measurements and quality assessments are performed to ensure the final accuracy of the test results, and this information is linked and entered into the database to enhance the system's self-learning ability and the accuracy of future tests. This not only improves the reliability of non-destructive testing, but also provides users with detailed quality assessment reports to help them make more informed decisions.

[0118] In an embodiment of the present application, the method further includes:

[0119] S1421, extracting target key parameters of the target unmelted reflection waveform data corresponding to the new precious metal sample, and performing a detailed comparison between the target key parameters and the target key parameters of the corresponding reflection waveform data in the database.

[0120] Among them, the target key parameters are the same as the key parameters mentioned above and will not be elaborated here; similarly, a suitable mathematical algorithm is selected for comparison to compare the similarities and differences between the key parameters, for example, to compare whether the peak positions of the center point and the peripheral points are consistent, whether there are significant differences in the amplitudes, whether there are obvious changes in the spectrum distribution, etc.

[0121] S1422, obtain the corresponding detailed comparison results, call the pre-set threshold range, where the threshold range includes the threshold of each key parameter, compare the detailed comparison results with the threshold range, if the key parameter error of the detailed comparison results is not within the threshold range, the new precious metal sample is marked as risky or unknown.

[0122] Among them, a reasonable threshold range is set for each key parameter. For example, for the amplitude size, a range of allowable fluctuations is set; for the peak position, an allowable deviation value is set. These thresholds should be determined based on historical data and laboratory verification results. The detailed comparison results are recorded, including the specific value of each key parameter and its deviation from the threshold range; each key parameter error in the detailed comparison results is compared with the pre-set threshold range. If the error of a parameter exceeds the threshold range, the parameter is considered to be abnormal. Through a strict threshold judgment mechanism, key parameters that exceed the normal range can be quickly identified.

[0123] In addition, when the error of a key parameter exceeds the threshold range, the new precious metal sample is immediately subject to risk assessment, including possible internal defects (such as interlayers, cracks) or other non-uniform distribution phenomena. The new precious metal sample is marked as "risky" or "unknown" and this status is marked in the database. At the same time, a corresponding alarm notification is generated to remind relevant personnel to pay attention to the sample.

[0124] S1423: If the key parameter error of the detailed comparison result is within the threshold range, the specific impurity type and content in the new precious metal sample are predicted based on the known influence of different metal components on ultrasonic propagation characteristics.

[0125] Among them, the known laws of influence of different metal components on ultrasonic propagation characteristics are retrieved. These laws usually come from laboratory research and literature, and describe how specific metal components affect the speed, intensity and pattern of the reflected waveform; these influence laws are used to establish a prediction model, and the key parameter errors of the new precious metal samples are input as variables to predict the types of impurities that may exist and their content. For example, if the amplitude at a certain place is slightly lower than expected, it may be due to the presence of a small amount of silver or copper impurities.

[0126] The prediction results are compared with existing data to ensure the accuracy of the prediction; if necessary, the model parameters are adjusted to improve the prediction accuracy; a detailed prediction report is generated, listing the possible impurity types and their estimated contents. These reports provide users with clear quality information to help them make informed decisions.

[0127] Through the detailed execution process of S1421 to S1423, not only can comprehensive and accurate reflection waveform measurements be performed at key locations of new precious metal samples, but also detailed comparative analysis can be performed based on the extracted key parameters. For key parameters that exceed the threshold range, they are promptly marked as "risky" or "unknown" to ensure that potential problems are dealt with in a timely manner; for parameters within the threshold range, the known metal composition influence rules are used to predict the type and content of impurities in new samples, providing a more comprehensive quality assessment; not only the accuracy of non-destructive testing is improved, but also the system's self-learning ability and the reliability of future testing are enhanced, providing users with more reliable and accurate testing services.

[0128] During the process of entering into the database, the method further comprises:

[0129] S1431, obtaining the actual volume information and density information of the precious metal sample, and obtaining the physical parameters corresponding to the precious metal sample.

[0130] Among them, prepare precise measuring tools, such as electronic balance for measuring weight, measuring tools or 3D scanner for measuring size, and place the precious metal sample on a stable and flat platform to ensure that its position is fixed to avoid movement or deformation during the measurement process.

[0131] Use measuring tools or 3D scanners to accurately measure the geometric dimensions of the sample (such as length, width, and height). For irregularly shaped samples, the displacement method can be used to measure their volume. Record the volume information of each sample and ensure the integrity and accuracy of the data. Use an electronic balance to measure the weight of the sample, and then combine the known volume information to calculate the density of the sample through the density formula, record the calculation results, and ensure the accuracy and consistency of the data.

[0132] The execution process of obtaining the physical parameters corresponding to the precious metal samples:

[0133] Hardness test: Use a hardness tester (such as Rockwell hardness tester, Vickers hardness tester) to test the hardness of the sample. Select appropriate test points to ensure that the test results are representative. Record the hardness value of each sample and mark the test method and conditions.

[0134] Melting point determination: Determine the melting point of the sample using a differential scanning calorimeter (DSC) or other melting point determination instrument according to standard procedures. Record the melting point data and ensure the consistency of experimental conditions.

[0135] Conductivity measurement: Use a resistivity tester or a four-probe tester to measure the conductivity of the sample. Ensure that the test environment (such as temperature and humidity) is stable to reduce the influence of external factors. Record the conductivity data and indicate the test conditions.

[0136] S1432, during the actual detection process, the target unmelted reflection waveform data corresponding to the target precious metal is compared in detail with the reflection waveform data in the database, and the actual volume information and density information of the target precious metal are compared with the corresponding data in the database in multiple dimensions.

[0137] Among them, the similarities and differences between key parameters are compared, for example, whether the peak positions of the center point and the peripheral points are consistent, whether there are significant differences in the amplitude, whether there are obvious changes in the spectrum distribution, etc.; any data points that deviate significantly from the normal range are identified and marked as "need further inspection". This helps to find potential problem areas.

[0138] Retrieve historical sample data with the same or similar specifications as the target precious metal from the database to ensure that the data contains complete volume, density and other physical parameter information; compare the actual volume and density information of the new sample with the historical sample data in detail, for example, to compare whether the volume is consistent and whether the density fluctuates within a reasonable range.

[0139] And set a reasonable threshold range for each physical parameter. For example, for density, set a range of allowable fluctuations; for volume, set an allowable deviation value. These thresholds should be determined based on historical data and laboratory verification results; record the detailed comparison results, including the specific value of each physical parameter and its deviation from the threshold range; combine the comparison results of the reflection waveform data and the comparison results of the physical parameters to conduct a comprehensive evaluation; if any parameter of the new sample exceeds the threshold range, it is considered that the sample has potential problems and requires further inspection.

[0140] Through the detailed execution process of the above two steps, the present invention can not only perform comprehensive and accurate reflection waveform measurement at key positions of precious metal samples, but also obtain its actual volume and density information and related physical parameters (such as hardness, melting point, conductivity). In the actual detection process, while the target unmelted reflection waveform data of the new sample is compared in detail with the reflection waveform data in the database, the actual volume information and density information of the new sample are also compared with the corresponding data in the database in multiple dimensions. This method not only improves the comprehensiveness and accuracy of the detection, but also can discover potential problems earlier, reduce the possibility of misjudgment, and significantly improve the accuracy and reliability of non-destructive detection of precious metal purity.

[0141] For the constructed database, the method also includes:

[0142] S1441, conduct market research regularly and obtain new precious metal samples processed by new materials and new processes according to market demand.

[0143] Among them, formulate a detailed market research plan, including the frequency of research (such as quarterly or semi-annual), the scope of research (such as different regions, different application fields) and the content of research (such as new material types, new process characteristics). Ensure that the research plan can fully cover market demand; collect market information through various channels, including but not limited to industry reports, academic papers, exhibition exchanges, customer feedback, etc. Pay special attention to the latest industry trends and technological development trends.

[0144] Conduct in-depth analysis of the collected information to identify the market demand for new materials and precious metals processed by new processes. For example, some fields may focus more on lightweight materials, while other fields may focus more on high strength or high conductivity. Based on the results of the market demand analysis, contact suppliers or manufacturers to obtain representative samples of new materials and precious metals processed by new processes. Ensure that the samples are from reliable sources and have been initially verified to ensure their representativeness and accuracy.

[0145] S1442, performing ultrasonic reflection waveform measurement on the new precious metal sample, and associating corresponding physical parameters to obtain corresponding reflection waveform data.

[0146] Ultrasonic reflection waveform measurements are performed at multiple locations equidistantly distributed at the geometric center (i.e., the middle point) and the edge of each new precious metal sample, and the reflection waveform data such as speed, intensity, and reflection mode obtained in each measurement are recorded. At the same time, professional testing instruments (such as hardness testers, melting point testers, and conductivity testers) are used to measure the physical parameters of new precious metal samples. Ensure that each sample contains complete physical parameter information, such as hardness, melting point, conductivity, etc.

[0147] All measured data are sent to the laboratory for precise verification to ensure the accuracy and reliability of the reflection waveform data and physical parameters. The laboratory should have sufficient resources and technical capabilities to handle these special samples; the reflection waveform data and its corresponding physical parameters obtained from each new precious metal sample are sorted into a standardized format to ensure the integrity and consistency of the data for subsequent analysis and entry.

[0148] S1443, compare the reflection waveform data of the new precious metal sample with the data in the database in detail to identify differential data.

[0149] The comparison process here is the same as that described above and will not be described in detail. A suitable mathematical algorithm (such as correlation coefficient, Euclidean distance, etc.) is selected for comparison. The similarities and differences between key parameters are compared; any data points that deviate significantly from the normal range need to be identified and marked as "need further inspection". Based on the comparison results, the difference data between the new precious metal samples and the known samples in the existing database are identified. In particular, attention should be paid to those places where there are significant differences in reflection waveform characteristics or physical parameters.

[0150] Through a rigorous multi-dimensional comparison mechanism, the differences between new precious metal samples and existing data can be quickly screened out, ensuring that the unique properties brought by new materials and new processes can be accurately identified.

[0151] S1444, the reflection waveform data, physical parameters and difference data corresponding to the new precious metal sample are associated and entered into the database.

[0152] Among them, the reflection waveform data, physical parameters and identified difference data of the new precious metal samples are sorted into a standardized format; ensure that each data item is clearly marked with its source and measurement conditions. The sorted data is entered into a specially designed database. Ensure that the reflection waveform data, physical parameters and difference data of each new precious metal sample can be related to each other for subsequent retrieval and management.

[0153] Through the detailed execution of the above four steps, not only can we conduct regular market research and obtain new precious metal samples after new materials and new processes according to market demand, but we can also perform accurate ultrasonic reflection waveform measurements and physical parameter measurements, and verify the authenticity and reliability of the data through laboratory verification. Subsequently, the data of the new precious metal samples are compared in detail with the existing data in the database to identify differential data, and finally the data are associated and entered into the database. The above scheme not only ensures the cutting-edge and accuracy of the database content, but also enhances the self-learning ability of the system, significantly improving the accuracy and reliability of non-destructive detection of precious metal purity, enabling the system to cope with the challenges brought by new materials and technologies.

[0154] For the above scheme, solid precious metals are more taken into consideration. Let's take a hypothetical hollow gold tube as an example: through market research, it is found that there is a demand for lightweight and high-strength hollow precious metals (such as hollow gold tubes). Based on market demand, representative hollow gold tube samples are obtained and their basic information, including shape, thickness, inner and outer diameters, and gold content, are recorded.

[0155] Use calibrated ultrasonic equipment to perform multi-point measurements on the hollow gold tube, paying special attention to key locations on the inner and outer walls to ensure that the overall structural characteristics of the sample are fully captured; at the same time, measure physical parameters such as volume, density, hardness, melting point and conductivity of the hollow gold tube. All data are verified in the laboratory to ensure accuracy.

[0156] The reflection waveform data of the hollow gold tube and its corresponding physical parameters are compared in detail with the existing data in the database to identify any data points that significantly deviate from the normal range, especially focusing on the unique reflection waveform changes that may be caused by the hollow structure. The newly acquired hollow gold tube reflection waveform data, physical parameters and identified difference data are associated and entered into the database to ensure that these data are interrelated for subsequent retrieval and management.

[0157] By adding new data to the database, the system's self-learning ability is enhanced, making future detection more accurate and better able to cope with the challenges brought by new materials and technologies. In the actual detection process, not only the reflection waveform data of the target hollow precious metal is compared with the reflection waveform data in the database, but also the actual volume information and density information of the target precious metal is compared with the corresponding data in the database in multiple dimensions to ensure the comprehensiveness and accuracy of the detection results.

[0158] The present application embodiment discloses a precious metal data processing system, referring to Figure 2 ,include:

[0159] The reflection waveform data recording module 200 collects precious metal samples of different gold contents, weights, and thicknesses, uses ultrasonic equipment to measure each precious metal sample, and is used to record corresponding reflection waveform data, and associates the reflection waveform data with the precious metal sample and enters it into the database, wherein the reflection waveform data includes speed, intensity, and reflection mode, and the precious metal samples are unmelted gold bars and melted gold blocks;

[0160] The unmelted detection result acquisition module 210 determines the corresponding target unmelted precious metal during the actual detection process, uses ultrasonic equipment to measure the target unmelted precious metal, and records the corresponding target unmelted reflection waveform data; performs X-ray irradiation, weighing, and visual identification on the target precious metal to obtain the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; determines the corresponding first reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; and detects the target unmelted reflection waveform data with the reflection waveform data of the first reference precious metal sample to obtain the corresponding unmelted detection result, wherein the gold content, gram weight, and thickness corresponding to the target unmelted precious metal are the first set of data;

[0161] The melted detection result acquisition module 220, if the unmelted detection result is abnormal, marks the target unmelted precious metal as an abnormal gold bar; if the unmelted detection result is normal, performs gold melting on the target unmelted precious metal to obtain the corresponding melted gold block, performs X-ray irradiation, weighing, and visual identification on the melted gold block to obtain the gold content, gram weight, and thickness corresponding to the melted gold block, uses ultrasonic equipment to measure the melted gold block, records the corresponding reflected waveform data of the melted gold block, determines the corresponding second reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the melted gold block, and detects the reflected waveform data of the melted gold block with the reflected waveform data corresponding to the second reference precious metal sample in the database to obtain the corresponding melted detection result, wherein the gold content, gram weight, and thickness corresponding to the melted gold block are the second group of data;

[0162] The multi-group data association module 230, if the melted gold nugget is abnormal, marks the melted gold nugget as an abnormal gold nugget; if the melted gold nugget is normal, sends the normal gold nugget to the laboratory for testing of gold content, weight and thickness, and obtains the gold content, weight, thickness and reflection waveform data corresponding to the normal gold nugget. The gold content, weight and thickness corresponding to the normal gold nugget are the third group of data, which is used to associate the first group of data, the second group of data, the third group of data and the reflection waveform data corresponding to the third group of data and enter them into the database.

[0163] The detection module 240 determines the target precious metal as a new precious metal sample if the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal; and is used to send the new precious metal sample to the laboratory for detection, obtain corresponding new sample data, associate the new sample data with the reflection waveform data and enter them into the database, wherein the new sample data includes the thickness, weight and gold content of the target precious metal.

[0164] The embodiment of the present application further discloses a method for processing precious metal data, including a processor, in which a program of the method for processing precious metal data described above is run.

[0165] The embodiment of the present application further discloses a storage medium storing a program of the above-mentioned method for processing precious metal data.

[0166] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for processing precious metal data, characterized in that: include: Collect precious metal samples of different gold content, gram weight and thickness, use ultrasonic equipment to measure each precious metal sample, record corresponding reflection waveform data, and associate the reflection waveform data with the precious metal sample and enter it into the database, wherein the reflection waveform data includes speed, intensity and reflection mode, and the precious metal samples are unmelted gold bars and melted gold blocks; In the actual detection process, the corresponding target unmelted precious metal is determined, and the target unmelted precious metal is measured using ultrasonic equipment, and the corresponding target unmelted reflection waveform data is recorded; the target precious metal is subjected to X-ray irradiation, weighing, and visual identification to obtain the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; based on the gold content, gram weight, and thickness corresponding to the target unmelted precious metal, the corresponding first reference precious metal sample in the database is determined, and the target unmelted reflection waveform data is tested with the reflection waveform data of the first reference precious metal sample to obtain the corresponding unmelted detection result, wherein the gold content, gram weight, and thickness corresponding to the target unmelted precious metal are the first group of data; If the unmelted test result is abnormal, the target unmelted precious metal is marked as an abnormal gold bar; if the unmelted test result is normal, the target unmelted precious metal is melted to obtain the corresponding melted gold block, the melted gold block is subjected to X-ray irradiation, weighing, and visual identification to obtain the corresponding gold content, gram weight, and thickness of the melted gold block, the melted gold block is measured using an ultrasonic device, and the corresponding reflected waveform data of the melted gold block is recorded, and the corresponding second reference precious metal sample in the database is determined based on the corresponding gold content, gram weight, and thickness of the melted gold block, and the reflected waveform data of the melted gold block is tested with the reflected waveform data corresponding to the second reference precious metal sample in the database to obtain the corresponding melted test result, wherein the corresponding gold content, gram weight, and thickness of the melted gold block are the second set of data; If the melted gold nugget is abnormal, the melted gold nugget is marked as an abnormal gold nugget; if the melted gold nugget is normal, the normal gold nugget is sent to the laboratory for testing of gold content, weight, and thickness, and the gold content, weight, thickness, and reflection waveform data corresponding to the normal gold nugget are obtained. The gold content, weight, and thickness corresponding to the normal gold nugget are the third group of data. The first group of data, the second group of data, the third group of data, and the reflection waveform data corresponding to the third group of data are associated and entered into the database; If the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal is determined as a new precious metal sample; the new precious metal sample is sent to the laboratory for testing to obtain corresponding new sample data, and the new sample data is associated with the reflection waveform data and entered into the database, wherein the new sample data includes the thickness, weight and gold content of the target precious metal.

2. The method for processing precious metal data according to claim 1, characterized in that: The method also includes: Obtain missing target weight data for precious metals in the database; Based on the derived precious metal samples of the weight adjacent to the weight corresponding to the target weight data in the database, retrieve the adjacent reflection waveform data corresponding to the derived precious metal samples, wherein there are multiple adjacent reflection waveform data; Predict the corresponding reflection waveform change trend based on a plurality of adjacent reflection waveform data, determine the derived reflection waveform data corresponding to the target weight data based on the reflection waveform change trend, associate the derived reflection waveform data with the target weight data and enter them into a database.

3. The method for processing precious metal data according to claim 1, characterized in that: The method also includes: Perform ultrasonic reflection waveform measurement at the geometric center of the precious metal sample to obtain central reflection waveform data corresponding to the central area; Perform ultrasonic reflection waveform measurement at multiple locations equidistantly distributed on the edge of the precious metal sample to obtain a corresponding peripheral reflection waveform data set; All the circumferential reflection waveform data of the circumferential reflection waveform data set are compared and integrated with the central reflection waveform data to generate corresponding reflection waveform data.

4. The method for processing precious metal data according to claim 3, characterized in that: The method also includes: Extracting corresponding key parameters based on the central reflection waveform data and the peripheral reflection waveform data set, wherein the key parameters include peak position, amplitude, spectrum distribution, and data points that deviate from a normal range; Based on all the key parameters, determine whether the reflection waveform corresponding to the specific point has a corresponding specific change; If so, the corresponding precious metal sample is sent to the laboratory for measurement, and a quality assessment report corresponding to the precious metal sample is obtained based on the experimental results. The specific change is associated with the quality assessment report and entered into the database, wherein the quality assessment report includes purity, uniformity, and thickness.

5. The method for processing precious metal data according to claim 4, characterized in that: The method also includes: Extract target key parameters of target unmelted reflection waveform data corresponding to the new precious metal sample, and compare the target key parameters with target key parameters of corresponding reflection waveform data in the database in detail; Obtain the corresponding detailed comparison result, call the preset threshold interval, wherein the threshold interval includes the threshold of each key parameter, compare the detailed comparison result with the threshold interval, and if the key parameter error of the detailed comparison result is not within the threshold interval, mark the new precious metal sample as risky or unknown; If the key parameter errors of the detailed comparison results are within the threshold range, the specific impurity types and contents in the new precious metal samples can be predicted based on the known influence of different metal components on ultrasonic propagation characteristics.

6. The method for processing precious metal data according to claim 1, characterized in that: During the process of entering the data into the database, the method further comprises: Obtaining actual volume information and density information of the precious metal sample, and obtaining physical parameters corresponding to the precious metal sample, the physical parameters including hardness, melting point, and conductivity; During the actual detection process, the target unmelted reflection waveform data corresponding to the target precious metal is compared in detail with the reflection waveform data in the database, and the actual volume information and density information of the target precious metal are also compared with the corresponding data in the database in multiple dimensions.

7. The method for processing precious metal data according to claim 1, characterized in that: The method also includes: Conduct market research regularly and obtain new precious metal samples processed by new materials and new processes according to market demand; Conduct ultrasonic reflection waveform measurement on new precious metal samples, and associate corresponding physical parameters to obtain corresponding reflection waveform data, wherein the parameter data corresponding to the new precious metal samples are all verified in the laboratory; Compare the reflection waveform data of the new precious metal sample with the data in the database in detail to identify the difference data; The reflection waveform data, physical parameters and difference data corresponding to the new precious metal samples are associated and entered into the database.

8. A precious metal data processing system, characterized in that: include: A reflection waveform data recording module collects precious metal samples of different gold contents, weights, and thicknesses, uses ultrasonic equipment to measure each precious metal sample, and is used to record corresponding reflection waveform data, and associates the reflection waveform data with the precious metal sample and enters it into the database, wherein the reflection waveform data includes speed, intensity, and reflection mode, and the precious metal samples are unmelted gold bars and melted gold blocks; The unmelted detection result acquisition module determines the corresponding target unmelted precious metal during the actual detection process, uses ultrasonic equipment to measure the target unmelted precious metal, and records the corresponding target unmelted reflection waveform data; performs X-ray irradiation, weighing, and visual identification on the target precious metal to obtain the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; determines the corresponding first reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the target unmelted precious metal; and detects the target unmelted reflection waveform data with the reflection waveform data of the first reference precious metal sample to obtain the corresponding unmelted detection result, wherein the gold content, gram weight, and thickness corresponding to the target unmelted precious metal are the first group of data; A melted detection result acquisition module, if the unmelted detection result is abnormal, marks the target unmelted precious metal as an abnormal gold bar; if the unmelted detection result is normal, performs gold melting on the target unmelted precious metal to obtain the corresponding melted gold block, performs X-ray irradiation, weighing, and visual identification on the melted gold block to obtain the gold content, gram weight, and thickness corresponding to the melted gold block, uses ultrasonic equipment to measure the melted gold block, records the corresponding reflected waveform data of the melted gold block, determines the corresponding second reference precious metal sample in the database based on the gold content, gram weight, and thickness corresponding to the melted gold block, and detects the reflected waveform data of the melted gold block with the reflected waveform data corresponding to the second reference precious metal sample in the database to obtain the corresponding melted detection result, wherein the gold content, gram weight, and thickness corresponding to the melted gold block are the second set of data; A multi-group data association module, if the melted gold nugget is abnormal, marks the melted gold nugget as an abnormal gold nugget; if the melted gold nugget is normal, sends the normal gold nugget to the laboratory for testing of gold content, weight, thickness, and obtains the gold content, weight, thickness, and reflection waveform data corresponding to the normal gold nugget. The gold content, weight, and thickness corresponding to the normal gold nugget are the third group of data, which is used to associate the first group of data, the second group of data, the third group of data, and the reflection waveform data corresponding to the third group of data and enter them into the database; A detection module, if the corresponding first reference precious metal sample in the database cannot be determined based on the target precious metal, the target precious metal is determined as a new precious metal sample; it is used to send the new precious metal sample to the laboratory for detection, obtain corresponding new sample data, associate the new sample data with the reflection waveform data and enter them into the database, wherein the new sample data includes the thickness, weight and gold content of the target precious metal.

9. A storage medium, characterized in that: A program storing the method for processing precious metal data according to any one of claims 1 to 7.

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