Performance detection method and system for high-strength refractory material

Abstract

The invention discloses a performance detection method and system for a high-strength refractory material, and relates to the field of material detection. The method is applied to a detection system, and comprises the following steps: performing a first performance test on a refractory material to obtain first performance test data, the first performance test data being composed of performance data of a plurality of detection areas of the refractory material; performing signal precision evaluation on the performance data of the plurality of detection areas to obtain signal precision of the plurality of detection areas; determining detection paths of the plurality of detection areas according to the signal precision of the plurality of detection areas; based on the detection path, carrying out second performance test on the refractory material to obtain second performance test data; and matching the second performance test data with a preset refractory material performance evaluation index table, and outputting a performance detection result of the refractory material. By implementing the technical scheme provided by the invention, the problem that the real condition in the material is difficult to accurately judge according to the detection signal because the internal structure of the refractory material is complicated is solved.

Description

Technical Field

[0001] The present application relates to the technical field of material testing, and in particular to a performance testing method and system for high-strength refractory materials. Background Art

[0002] The working environment of the kiln is relatively harsh, often accompanied by ultra-high temperature, easy corrosion, strong thermal stress shock and other characteristics. Therefore, the construction materials of the kiln generally use high-strength refractory materials; however, the performance of this high-strength refractory material is unstable and requires regular performance testing to ensure that it can continue to be used normally.

[0003] At present, most of the performance tests of high-strength refractory materials are carried out by non-destructive testing technology, which transmits ultrasonic or infrared detection signals to the refractory materials to detect whether there are defects such as cracks and pores inside the materials. However, refractory materials are usually composed of a variety of mineral components and additives, and their internal structure and component distribution are often uneven, which will lead to complex and changeable propagation and reflection of detection signals during non-destructive testing, making it difficult to accurately judge the real situation inside the material and prone to misjudgment. Summary of the invention

[0004] In order to solve the problem that the internal structure of refractory materials is complex, making it difficult to accurately judge the actual condition inside the material based on the detection signal, the present application provides a performance detection method and system for high-strength refractory materials.

[0005] In a first aspect, the present application provides a method for detecting the performance of a high-strength refractory material, which is applied to a detection system, and the method comprises: Performing a first performance test on the refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material; Performing signal accuracy evaluation on the performance data of the plurality of detection areas to obtain the signal accuracy of the plurality of detection areas; Determining detection paths of the plurality of detection areas according to signal accuracy of the plurality of detection areas; Based on the detection path, performing a second performance test on the refractory material to obtain second performance test data; The second performance test data is matched with a preset refractory material performance evaluation index table, and the performance test result of the refractory material is output.

[0006] Optionally, the signal accuracy evaluation is performed on the performance data of the plurality of detection areas to obtain the signal accuracy of the plurality of detection areas, specifically: Performing spectrum analysis on the performance data of the plurality of detection areas to obtain signal-to-noise ratios of the plurality of detection areas; Based on the signal-to-noise ratios of the plurality of detection areas, clustering the plurality of detection areas to obtain a plurality of cluster clusters; Calculating the coefficient of variation of the plurality of clusters; The coefficients of variation of the plurality of clusters are normalized to obtain the signal accuracies of the plurality of clusters.

[0007] Optionally, determining the detection paths of the multiple detection areas according to the signal accuracy of the multiple detection areas specifically includes: Determining detection priorities of the plurality of clusters based on signal accuracy of the plurality of clusters; Comparing the signal accuracy of the plurality of clusters with a preset signal accuracy threshold, thereby dividing the plurality of clusters into a high-precision cluster set and a low-precision cluster set; If the first cluster belongs to the high-precision cluster set, calculating the center coordinates of the first cluster, the first cluster being any one of the plurality of clusters; Identifying a detection area corresponding to the center coordinates of the first cluster; A detection path for the second performance test is determined according to the detection priorities of the plurality of clusters and the detection area corresponding to the center coordinates of the first cluster.

[0008] Optionally, the calculating the coefficient of variation of the plurality of clusters further comprises: Calculating a regional volume of a second cluster, where the second cluster is any one of the plurality of clusters; Determining, according to the regional volume of the second cluster, the precision weight of the second cluster among the plurality of clusters; The precision weight of the second cluster is multiplied by its corresponding coefficient of variation to obtain a weighted coefficient of variation of the third cluster, and the weighted coefficient of variation is used as the coefficient of variation of the second cluster.

[0009] Optionally, based on the detection path, a second performance test is performed on the refractory material to obtain second performance test data, specifically: Acquiring application environment parameters of the refractory material, wherein the application environment parameters include ambient temperature, ambient thermal shock force, and ambient corrosion degree; The signal test strengths of the multiple detection areas are generated according to the application environment parameters and the signal accuracy of the multiple detection areas.

[0010] Optionally, the signal test strengths of the multiple detection areas are generated according to the application environment parameters and the signal accuracy of the multiple detection areas, and can be specifically generated by using the following formula: in, is the signal test intensity of the i-th detection area, is the initial signal test strength, is the environmental temperature characterization value, S is the environmental thermal shock characterization value, C is the environmental corrosion characterization value, is the signal accuracy of the i-th detection area, is the signal accuracy standard deviation, is the expected value of signal accuracy.

[0011] In a second aspect, the present application provides a performance detection system for high-strength refractory materials, the system being a detection system, the detection system comprising a testing module, a processing module and a sending module, wherein: The testing module is used to perform a first performance test on the refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material; The processing module is used to evaluate the signal accuracy of the performance data of the multiple detection areas to obtain the signal accuracy of the multiple detection areas; and determine the detection paths of the multiple detection areas according to the signal accuracy of the multiple detection areas; The testing module is further used to perform a second performance test on the refractory material based on the detection path to obtain second performance test data; The sending module is used to match the second performance test data with a preset refractory material performance evaluation index table and output the performance test result of the refractory material.

[0012] In a third aspect, the present application provides an electronic device comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method as described in any one of the first aspects.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method as described in any one of the first aspects is executed.

[0014] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The present application first performs a conventional first performance test on the refractory material to obtain first performance test data, so as to preliminarily understand the internal structure information of the refractory material. However, at this time, due to the uneven internal structure and component distribution of the refractory material itself, the first performance test data is not accurate. Therefore, by performing precision analysis on the first performance test data, the signal accuracy of each detection area is understood, and then a targeted detection path design is performed for the refractory material according to the detection accuracy, and multiple detection areas are divided into high-precision clustering groups and low-precision clustering groups. The detection areas in the low-precision clustering group are detected one by one, and the detection areas in the high-precision clustering group are merged for detection, so as to avoid excessive consumption of detection resources in areas with high signal accuracy and improve the detection efficiency; then, the signal detection strength of each detection area is set according to its signal accuracy, and a second performance test is performed to obtain second performance test data, so as to improve the performance test accuracy of the refractory material, and finally a comprehensive performance test result is made according to the second performance test data, which reduces the analysis workload of the staff and improves the detection efficiency.

[0015] 2. When evaluating the signal accuracy of multiple detection areas, the internal structure of refractory materials has changed after long-term use, and the signal accuracy of each detection area is highly discrete, making it difficult to make an overall evaluation of multiple detection areas using a fixed accuracy evaluation standard. This application obtains the signal-to-noise ratio by performing spectral analysis on the detection area performance data; then, based on the signal-to-noise ratio clustering, the detection areas of similar accuracy are reclassified to adapt to structural changes; the coefficient of variation of the clusters is then calculated to measure the degree of data discreteness within each cluster, so as to understand the stability of the signal accuracy of each cluster; finally, the coefficient of variation is normalized to obtain the relative signal accuracy of each cluster, thereby reducing the impact of changes in the internal structure of refractory materials on signal accuracy evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for testing the performance of a high-strength refractory material provided in an embodiment of the present application.

[0017] Figure 2 It is a structural schematic diagram of a performance detection system for high-strength refractory materials provided in an embodiment of the present application.

[0018] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0019] Explanation of the reference numerals: 1. Test module; 2. Processing module; 3. Sending module; 300. Electronic device; 301. Processor; 302. Communication bus; 303. User interface; 304. Network interface; 305. Memory. DETAILED DESCRIPTION

[0020] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0021] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0022] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0023] With the continuous development of materials science, many processing technologies that are difficult to achieve in industry have been effectively supported. In particular, through the continuous research and development and improvement of refractory materials, the development process of national economy fields such as steel, non-ferrous metals, glass, cement, ceramics, petrochemicals, machinery, boilers, light industry, electricity, and military industry has been greatly promoted.

[0024] At present, in the field of ceramic and glass processing, kilns are a very indispensable equipment. However, the working environment of kilns is relatively harsh, often accompanied by ultra-high temperature, easy corrosion, strong thermal stress shock and other characteristics. Therefore, the construction materials of kilns generally use high-strength refractory materials; but the performance of this high-strength refractory material is unstable, and regular performance testing is required to ensure that it can continue to be used normally.

[0025] Most of the performance tests of high-strength refractory materials are conducted by non-destructive testing technology, which emits ultrasonic or infrared detection signals to the refractory materials to detect whether there are defects such as cracks and pores inside the materials. However, refractory materials are usually composed of a variety of mineral components and additives, and their internal structure and component distribution are often uneven, which will lead to complex and changeable propagation and reflection of detection signals during non-destructive testing, making it difficult to accurately judge the true condition inside the material and prone to misjudgment.

[0026] In order to solve the above problems, the present application provides a performance detection method of high-strength refractory materials, which is applied to a detection system, such as Figure 1 As shown, the method includes steps S101 to S105, which are as follows: S101. Perform a first performance test on a refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material.

[0027] In the above steps, the first performance test is a conventional performance test, which transmits a preset ultrasonic signal or infrared detection signal to the refractory material to be tested, and then analyzes whether the internal organizational structure of the refractory material to be tested has defects such as pores and cracks that affect the performance based on the received feedback signal. In order to conduct a more refined analysis of the performance of the refractory material, the refractory material is divided into multiple detection areas, and the detection area of ​​each detection area is the same. Therefore, after the first performance test, the first performance test data obtained includes the performance data of multiple detection areas, and the performance data of each detection area reflects its corresponding internal organizational structure.

[0028] S102: Perform signal accuracy evaluation on the performance data of multiple detection areas to obtain signal accuracy of the multiple detection areas.

[0029] In the above steps, due to the influence of the high temperature working environment of the kiln during the long-term use of the refractory material, its internal structure and organizational composition have undergone unknown changes, and this change will cause the emitted preset detection signal to be absorbed or offset, resulting in more noise or incomplete signals in the received feedback signal, which in turn leads to low signal accuracy and inability to accurately judge the true internal structure. Therefore, the test results of the first performance test cannot be used directly to evaluate the performance of the refractory material, and the signal accuracy of the performance data of multiple detection areas needs to be further evaluated to ensure the accuracy of the test results. Specifically, first, a spectrum analysis is performed on the performance data of multiple detection areas, and the first performance test data is converted from a time domain signal to a frequency domain signal to amplify the difference between the signal and the noise. Then, the signal-to-noise ratio of the multiple detection areas is calculated to determine the degree to which the detection signal is interfered with by noise. At this time, although the signal-to-noise ratio of each detection area is affected by the internal structure, it is impossible to determine whether the influence is caused by a defect or by normal complex tissue components. In order to make a distinction, the present application clusters multiple detection areas according to the signal-to-noise ratio of each detection area, and divides the detection areas with similar signal-to-noise ratios into the same cluster. It can be understood that if multiple detection areas divided into the same cluster If the signal-to-noise ratio of the detected area is similar and continuous, it means that the signal-to-noise ratio in the detected area is caused by normal complex tissue components, and it can also further explain that the signal accuracy in the cluster cluster is relatively high. Therefore, the present application further calculates the coefficient of variation of multiple cluster clusters to judge the continuity of multiple detection areas in the cluster cluster. The coefficient of variation is the ratio of the standard deviation to the mean, which can effectively measure the degree of discreteness of the data in the cluster cluster; finally, the coefficient of variation of multiple cluster clusters is normalized to obtain the signal accuracy of the multiple cluster clusters, thereby providing an improved basis for subsequent further detection. Among them, if the coefficient of variation of the cluster cluster is smaller, the degree of discreteness of the data therein is lower, and the signal accuracy will be higher.

[0030] In one possible implementation, when calculating the coefficient of variation of clusters, since the shape of the refractory material may be irregular, the volumes of the various detection areas are not consistent. For the detection area with a low volume, the structural defects inside it do not have a significant impact on the performance compared to the detection area with a high volume, so the signal accuracy requirement is not high. Based on this feature, when calculating the coefficient of variation of clusters, the present application calculates the regional volume of each cluster to determine the accuracy weights of multiple clusters. Specifically, the accuracy weights of multiple clusters can be obtained by normalizing the ratio of the regional volumes of each cluster. The accuracy weights of each cluster are then multiplied by their corresponding coefficients of variation to obtain the weighted coefficients of variation of each cluster. Finally, the weighted coefficients of variation of each cluster are used as the coefficients of variation of each cluster, so as to more accurately identify which areas have a greater impact on the overall performance and which have a smaller impact, thereby providing a reliable basis for adjusting the detection signal during the subsequent second performance test.

[0031] S103: Determine detection paths for the multiple detection areas according to the signal accuracy of the multiple detection areas.

[0032] In the above steps, after clarifying the signal accuracy of each cluster, in order to avoid wasting too much detection resources in areas with high signal accuracy, thereby reducing detection efficiency; the present application sets the detection path of refractory materials according to the signal accuracy of multiple detection areas; first, based on the signal accuracy of multiple clusters, the detection priority of each cluster is determined, that is, if the signal accuracy is high, the detection priority is low; if the signal accuracy is low, the detection priority is high; then, the signal accuracy of the multiple clusters is compared with the preset signal accuracy threshold, so as to divide the multiple clusters into high-precision cluster sets and low-precision cluster sets, wherein the high-precision cluster set contains the signal accuracy There are multiple high-precision clusters with higher signal accuracy, and the low-precision cluster set contains multiple low-precision clusters with lower signal accuracy. For the clusters in the high-precision cluster set, since the signal accuracy is high enough, there is no need to invest too many detection resources. Therefore, by calculating the central coordinates of the high-precision cluster, and then identifying the high-precision detection area corresponding to the central coordinates of the high-precision cluster, the high-precision detection area is used as the characterization area of ​​the multiple detection areas in the high-precision cluster. When detecting the detection area in the high-precision cluster, only the high-precision detection area needs to be detected, so as to avoid excessive consumption of detection resources in areas with high signal accuracy, thereby improving detection efficiency. For multiple clusters in the low-precision cluster set, due to the low signal accuracy, each detection area in the low-precision cluster needs to be detected. When planning the detection path of multiple detection areas in the low-precision cluster, this application is based on the shortest path principle to further improve detection efficiency.

[0033] In summary, in order to make the detection path of the second performance test clearer, this application uses an example to illustrate: there are existing high-precision clusters A and B, and low-precision clusters C and D. The high-precision cluster A contains detection areas a1 and a2, the high-precision cluster B contains detection areas b1 and b2, the low-precision cluster C contains detection areas c1, c2, c3, and the low-precision cluster D contains detection areas d1, d2, and d3, where a1 is the representation area of ​​the high-precision cluster A, b2 is the representation area of ​​the high-precision cluster B, the shortest detection path of the low-precision cluster C is c2, c1, c3, and the shortest detection path of the low-precision cluster D is d1, d2, and d3. The detection priorities of the four clusters are C, D, B, and A. Then the detection path of the second performance test is c2, c1, c3, d1, d2, d3, b2, and a1.

[0034] S104. Based on the detection path, perform a second performance test on the refractory material to obtain second performance test data.

[0035] In the above steps, when the second performance test is performed, due to the different signal accuracy of each detection area, the signal strength of the detection signal needs to be readjusted to adapt to the internal structural changes of the refractory material; specifically: first, the application environment parameters of the refractory material are obtained. Since the refractory material in this application is used in the construction of a kiln, and the kiln working environment is accompanied by high temperature, strong thermal shock and strong slag corrosion, the application environment parameters include ambient temperature, ambient thermal shock and ambient corrosion; then, according to the application environment parameters and the signal accuracy of each detection area, the adjusted signal test strength of each detection area is generated; specifically, it can be calculated using the following formula: in, is the signal test intensity of the i-th detection area, is the initial signal test strength, is the environmental temperature characterization value, S is the environmental thermal shock characterization value, C is the environmental corrosion characterization value, is the signal accuracy of the i-th detection area, is the signal accuracy standard deviation, is the expected value of signal accuracy.

[0036] In the above formula, the initial signal test strength is the signal strength of the detection signal during the first performance test. The environmental thermal shock force characterization value, environmental corrosion degree characterization value and environmental temperature characterization value can be understood as the data obtained by normalizing the current application environment parameters of the kiln compared with the boundary conditions of the application environment parameters. The data converts the kiln environment evaluation indicators of different dimensions into a unified kiln environment evaluation indicator, that is, they are all mapped to the interval of 0 to 1. For example, if the environmental temperature characterization value is 1, it means that the current working environment temperature of the kiln has reached the highest tolerable temperature. If the environmental temperature characterization value is 0, it means that the current working environment temperature of the kiln has reached the lowest effective working temperature. It can be understood from the above formula that when the signal accuracy of the detection area is equal to the expected value of the signal accuracy, the adjusted signal test strength is equal to the initial signal test, indicating that the internal structure of the detection area has not changed much under the influence of the application environment parameters. In actual applications, this situation is too ideal. In most cases, the higher the ambient temperature, the greater the thermal shock force, and the higher the corrosion degree, the greater the impact on the performance of the refractory material. At this time, the corresponding signal test strength requirement is also higher to ensure that the final detection result is more accurate.

[0037] After obtaining the adjusted signal detection strength of each detection area according to the above formula, a second performance test is performed. The second performance test detects multiple detection areas in sequence according to the detection path to obtain second performance test data.

[0038] S105, matching the second performance test data with a preset refractory material performance evaluation index table, and outputting the performance test results of the refractory material.

[0039] In the above steps, the preset refractory material performance evaluation index table includes evaluation range indicators of defects that may exist in the refractory material, for example, it may include evaluation range indicators of pore defects "pore diameter less than 1mm is excellent", "pore diameter greater than 1mm and less than 3mm is good", "pore diameter greater than 3mm is poor"; by converting the second performance test data into structural data of each detection area, and then matching the structural data of each detection area with the preset refractory material performance evaluation index table, and performing defect analysis, defect information of multiple detection areas is obtained, and the defect information includes defect type, number of defects and defect evaluation (excellent, good or poor); then the proportion of detection areas containing major defects in all detection areas is counted, and the detection area containing major defects refers to the detection area whose defect information contains a defect evaluation of "poor"; if the proportion of detection areas containing major defects is greater than or equal to the preset threshold, it is determined that the performance test result of the refractory material is "unqualified" and needs to be replaced. If the proportion of detection areas containing major defects is less than the preset threshold, it is determined that the performance test result of the refractory material is "qualified", and the existing defects are counted and output to the display terminal together with the performance test results.

[0040] Reference Figure 2 The present application also provides a performance detection system for high-strength refractory materials. The system is a detection system, and the detection system includes a test module 1, a processing module 2 and a sending module 3, wherein: Testing module 1, used for performing a first performance test on the refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material; Processing module 2, used to evaluate the signal accuracy of the performance data of multiple detection areas to obtain the signal accuracy of the multiple detection areas; and determine the detection paths of the multiple detection areas according to the signal accuracy of the multiple detection areas; The test module 1 is further used to perform a second performance test on the refractory material based on the detection path to obtain second performance test data; The sending module 3 is used to match the second performance test data with a preset refractory material performance evaluation index table and output the performance test result of the refractory material.

[0041] In a possible implementation, the performance data of multiple detection areas are evaluated for signal accuracy to obtain the signal accuracy of the multiple detection areas, specifically: Performing spectrum analysis on the performance data of multiple detection areas to obtain the signal-to-noise ratios of the multiple detection areas; Based on the signal-to-noise ratios of the multiple detection areas, the multiple detection areas are clustered to obtain multiple clusters; Calculate the coefficient of variation of multiple clusters; The coefficients of variation of multiple clusters are normalized to obtain the signal accuracies of multiple clusters.

[0042] In a possible implementation, determining detection paths of the multiple detection areas according to the signal accuracy of the multiple detection areas specifically includes: Determining detection priorities of the multiple clusters based on signal accuracies of the multiple clusters; Comparing the signal accuracy of the multiple clusters with a preset signal accuracy threshold, thereby dividing the multiple clusters into a high-precision cluster set and a low-precision cluster set; If the first cluster belongs to the high-precision cluster set, the center coordinates of the first cluster are calculated, and the first cluster is any one of the multiple clusters; Identify the detection area corresponding to the center coordinates of the first cluster; A detection path for the second performance test is determined according to the detection priorities of the plurality of clusters and the detection area corresponding to the center coordinates of the first cluster.

[0043] In a possible implementation, calculating the coefficient of variation of multiple clusters further includes: Calculate the regional volume of the second cluster, where the second cluster is any one of the multiple clusters; Determine, according to the regional volume of the second cluster, the precision weight of the second cluster among the multiple clusters; The precision weight of the second cluster is multiplied by its corresponding coefficient of variation to obtain the weighted coefficient of variation of the third cluster, and the weighted coefficient of variation is used as the coefficient of variation of the second cluster.

[0044] In a possible implementation, based on the detection path, a second performance test is performed on the refractory material to obtain second performance test data, specifically: Obtain the application environment parameters of refractory materials, including ambient temperature, ambient thermal shock force and ambient corrosion degree; According to the application environment parameters and the signal accuracy of the multiple detection areas, the signal test strength of the multiple detection areas is generated.

[0045] In a possible implementation, the signal test strengths of the multiple detection areas are generated according to the application environment parameters and the signal accuracy of the multiple detection areas, and can be specifically generated using the following formula: in, is the signal test intensity of the i-th detection area, is the initial signal test strength, is the environmental temperature characterization value, S is the environmental thermal shock characterization value, C is the environmental corrosion characterization value, is the signal accuracy of the i-th detection area, is the signal accuracy standard deviation, is the expected value of signal accuracy.

[0046] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0047] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0048] The communication bus 302 is used to realize the connection and communication between these components.

[0049] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0050] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0051] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0052] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a performance detection method of a high-strength refractory material.

[0053] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program storing a performance detection method of a high-strength refractory material in the memory 305, and when executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0054] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0055] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0056] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0057] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0058] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0059] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0060] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for detecting the performance of a high-strength refractory material, characterized in that: Applied to a detection system, the method comprises: Performing a first performance test on the refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material; Performing signal accuracy evaluation on the performance data of the plurality of detection areas to obtain the signal accuracy of the plurality of detection areas; Determining detection paths of the plurality of detection areas according to signal accuracy of the plurality of detection areas; Based on the detection path, performing a second performance test on the refractory material to obtain second performance test data; The second performance test data is matched with a preset refractory material performance evaluation index table, and the performance test result of the refractory material is output.

2. The method according to claim 1, characterized in that The signal accuracy evaluation is performed on the performance data of the plurality of detection areas to obtain the signal accuracy of the plurality of detection areas, specifically: Performing spectrum analysis on the performance data of the plurality of detection areas to obtain signal-to-noise ratios of the plurality of detection areas; Based on the signal-to-noise ratios of the plurality of detection areas, clustering the plurality of detection areas to obtain a plurality of cluster clusters; Calculating the coefficient of variation of the plurality of clusters; The coefficients of variation of the plurality of clusters are normalized to obtain the signal accuracies of the plurality of clusters.

3. The method according to claim 2, characterized in that The step of determining the detection paths of the plurality of detection areas according to the signal accuracy of the plurality of detection areas specifically includes: Determining detection priorities of the plurality of clusters based on signal accuracy of the plurality of clusters; Comparing the signal accuracy of the plurality of clusters with a preset signal accuracy threshold, thereby dividing the plurality of clusters into a high-precision cluster set and a low-precision cluster set; If the first cluster belongs to the high-precision cluster set, calculating the center coordinates of the first cluster, the first cluster being any one of the plurality of clusters; Identifying a detection area corresponding to the center coordinates of the first cluster; A detection path for the second performance test is determined according to the detection priorities of the plurality of clusters and the detection area corresponding to the center coordinates of the first cluster.

4. The method according to claim 2, characterized in that: The calculating of the coefficient of variation of the plurality of clusters specifically further comprises: Calculating a regional volume of a second cluster, where the second cluster is any one of the plurality of clusters; Determining, according to the regional volume of the second cluster, the precision weight of the second cluster among the plurality of clusters; The precision weight of the second cluster is multiplied by its corresponding coefficient of variation to obtain a weighted coefficient of variation of the third cluster, and the weighted coefficient of variation is used as the coefficient of variation of the second cluster.

5. The method according to claim 1, characterized in that Based on the detection path, a second performance test is performed on the refractory material to obtain second performance test data, specifically: Acquiring application environment parameters of the refractory material, wherein the application environment parameters include ambient temperature, ambient thermal shock force, and ambient corrosion degree; The signal test strengths of the multiple detection areas are generated according to the application environment parameters and the signal accuracy of the multiple detection areas.

6. The method according to claim 5, characterized in that The signal test strengths of the multiple detection areas are generated according to the application environment parameters and the signal accuracy of the multiple detection areas, which can be specifically generated by the following formula: in, is the signal test intensity of the i-th detection area, is the initial signal test strength, is the environmental temperature characterization value, S is the environmental thermal shock characterization value, C is the environmental corrosion characterization value, is the signal accuracy of the i-th detection area, is the signal accuracy standard deviation, is the expected value of signal accuracy.

7. A performance detection system for high-strength refractory materials, characterized in that: The system is a detection system, which includes a testing module, a processing module and a sending module, wherein: The testing module is used to perform a first performance test on the refractory material to obtain first performance test data, wherein the first performance test data is composed of performance data of multiple detection areas of the refractory material; The processing module is used to evaluate the signal accuracy of the performance data of the multiple detection areas to obtain the signal accuracy of the multiple detection areas; and determine the detection paths of the multiple detection areas according to the signal accuracy of the multiple detection areas; The testing module is further used to perform a second performance test on the refractory material based on the detection path to obtain second performance test data; The sending module is used to match the second performance test data with a preset refractory material performance evaluation index table and output the performance test result of the refractory material.

8. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is performed.

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