Model construction method and device of ultrasonic sensor system, medium and product

Abstract

The invention relates to the technical field of model construction, and discloses a model construction method and device of an ultrasonic sensor system, a medium and a product, and the method comprises the steps: obtaining ultrasonic echo signals of multiple times of detection of a plurality of pipeline samples through an ultrasonic sensor; obtaining specification parameters of the pipeline sample; performing noise reduction processing on the ultrasonic echo signal, and determining the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample; the detection temperature of the pipeline sample is obtained, the pipeline sample density of the pipeline sample is corrected according to the detection temperature, and the corrected density is obtained; and determining acoustic impedance of the pipeline sample according to the corrected density and the wave velocity, determining acoustic characteristic parameters of the pipeline sample according to the acoustic impedance, and establishing an ultrasonic sensor system model based on the acoustic characteristic parameters. According to the method, through multi-step signal processing and data analysis, the detection precision of the ultrasonic sensor system model is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of model building, and in particular to a model building method, equipment, medium and product of an ultrasonic sensor system. Background Art

[0002] In modern industry and scientific research, ultrasonic sensors in ultrasonic sensor systems are widely used in various detection and measurement tasks, such as pipeline quality assessment, material property analysis, etc.

[0003] However, in practical applications, ultrasonic sensors in existing ultrasonic sensor systems are easily disturbed by interference factors such as environmental noise and environmental changes, resulting in inaccurate detection results.

[0004] Therefore, there is an urgent need for a model building method for ultrasonic sensor systems to improve detection accuracy, optimize system performance, and enhance model reliability and adaptability. Summary of the invention

[0005] The purpose of the present invention is to provide a model building method, equipment, medium and product of an ultrasonic sensor system to solve the problems of insufficient detection accuracy, large noise influence and poor system adaptability in the prior art.

[0006] In a first aspect, the present invention provides a model building method for an ultrasonic sensor system, comprising: obtaining ultrasonic echo signals of multiple detections of a plurality of pipeline samples through an ultrasonic sensor; the ultrasonic sensor is arranged at a predetermined position of the pipeline sample; obtaining specification parameters of the pipeline sample, the specification parameters including pipeline sample thickness and pipeline sample density; performing noise reduction processing on the ultrasonic echo signal, and determining the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample; obtaining the detection temperature of the pipeline sample, and correcting the pipeline sample density of the pipeline sample according to the detection temperature to obtain a corrected density; determining the acoustic impedance of the pipeline sample according to the corrected density and the wave velocity, and determining the acoustic characteristic parameters of the pipeline sample according to the acoustic impedance, and establishing an ultrasonic sensor system model based on the acoustic characteristic parameters; the ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline by detecting the acoustic characteristic parameters of the detected pipeline.

[0007] In some embodiments, the noise reduction processing of the ultrasonic echo signal includes: performing quality verification on the ultrasonic echo signal, amplifying the ultrasonic echo signal that passes the quality verification, and filtering the amplified ultrasonic echo signal; converting the filtered ultrasonic echo signal into a digital echo signal, wherein the digital echo signal includes an ultrasonic emission time and an ultrasonic reception time.

[0008] In some embodiments, the quality verification of the ultrasonic echo signal includes: creating at least one dimension of quality evaluation and its corresponding evaluation index; scoring the ultrasonic echo signal according to the evaluation index to obtain a quality score of the ultrasonic echo signal; comparing the quality score with a quality score threshold, if the quality score is greater than or equal to the quality score threshold, determining that the quality verification of the ultrasonic echo signal has passed; if the quality score is less than the quality score threshold, determining that the quality verification of the ultrasonic echo signal has failed, and re-testing the pipeline sample to obtain an ultrasonic echo signal.

[0009] In some embodiments, the dimension includes at least one of completeness, signal-to-noise ratio, noise level, and waveform characteristics.

[0010] In some embodiments, the step of determining the wave velocity of the ultrasonic wave in the pipeline sample corresponding to the ultrasonic echo signal according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample includes: determining the detection time of multiple detections according to the ultrasonic emission time and the ultrasonic reception time; determining the single wave velocity of the ultrasonic wave in the pipeline sample for each detection according to the thickness of the pipeline sample and the detection time, and determining that the average value of the single wave velocity is the wave velocity of the ultrasonic wave in the pipeline sample;

[0011] The wave speed is determined according to the following formula:

[0012]

[0013] Where V represents the wave velocity of ultrasonic wave in the pipe sample, H represents the thickness of the pipe sample, and T ai Indicates the ultrasonic receiving time of the i-th detection, T si It indicates the ultrasonic emission time of the i-th detection, and n indicates the number of detections.

[0014] In some embodiments, the pipeline sample density of the pipeline sample is corrected according to the detected temperature to obtain the corrected density, including: comparing the detected temperature with a standard temperature range, if the detected temperature is within the standard temperature range, determining the pipeline sample density as the corrected density; if the detected temperature is not within the standard temperature range, correcting the pipeline sample density, and if the detected temperature is lower than the standard temperature range, determining the temperature difference between the detected temperature and the lower limit of the standard temperature, and performing a positive correction on the pipeline sample density according to the temperature difference to obtain the corrected density; if the detected temperature is higher than the standard temperature range, determining the temperature difference between the detected temperature and the upper limit of the standard temperature, and performing a negative correction on the pipeline sample density according to the temperature difference to obtain the corrected density.

[0015] In some embodiments, the correction of the density of the pipeline sample includes: establishing a correspondence between multiple temperature difference intervals and multiple correction coefficients; the temperature difference interval is positively correlated with the correction coefficient; determining the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and correcting the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs.

[0016] In some embodiments, the multiple temperature difference intervals are divided by a pre-set first temperature difference, a second temperature difference and a third temperature difference; the first temperature difference, the second temperature difference and the third temperature difference increase in sequence; the determination of the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs includes: if the temperature difference is less than the first temperature difference, the correction coefficient is determined to be the first correction coefficient C1; if the temperature difference is greater than or equal to the first temperature difference, and the temperature difference is less than the second temperature difference, the correction coefficient is determined to be the second correction coefficient C2; if the temperature difference is greater than or equal to the second temperature difference, and the temperature difference is less than the third temperature difference, the correction coefficient is determined to be the third correction coefficient C3; if the temperature difference is greater than or equal to the third temperature difference, the correction coefficient is determined to be the fourth correction coefficient C4.

[0017] In some embodiments, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, including: if the detected temperature is lower than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1+Ci); if the detected temperature is higher than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1-Ci); wherein p0 represents the density of the pipeline sample, Ci represents the i-th correction coefficient, i=1, 2, 3, 4.

[0018] In some embodiments, determining the acoustic impedance of the pipeline sample according to the corrected density and the wave velocity includes: determining the product of the corrected density and the wave velocity as the acoustic impedance of the pipeline sample.

[0019] In some embodiments, the pipe sample is a single material sample.

[0020] In a second aspect, a model building device for an ultrasonic sensor system is provided, comprising: a communication unit and a processing unit; the communication unit is used to obtain ultrasonic echo signals of multiple detections of a plurality of pipeline samples through an ultrasonic sensor; the ultrasonic sensor is arranged at a predetermined position of the pipeline sample; the communication unit is also used to obtain specification parameters of the pipeline sample, the specification parameters including pipeline sample thickness and pipeline sample density; the processing unit is used to perform noise reduction processing on the ultrasonic echo signal, and determine the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the pipeline sample thickness; the communication unit is also used to obtain the detection temperature of the pipeline sample, and correct the pipeline sample density of the pipeline sample according to the detection temperature to obtain the corrected density; the processing unit is also used to determine the acoustic impedance of the pipeline sample according to the corrected density and wave velocity, and determine the acoustic characteristic parameters of the pipeline sample according to the acoustic impedance, and establish an ultrasonic sensor system model based on the acoustic characteristic parameters; the ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline by detecting the acoustic characteristic parameters of the detected pipeline.

[0021] In a third aspect, a model building device for an ultrasonic sensor system is provided, comprising a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory through a bus; when the model building device for an ultrasonic sensor system is running, the processor executes the computer execution instructions stored in the memory, so that the model building device for an ultrasonic sensor system executes the model building method for an ultrasonic sensor system described in the first aspect.

[0022] The model building device for the ultrasonic sensor system may be a network device, or a part of a device in a network device, such as a chip system in a network device. The chip system is used to support the network device to implement the functions involved in the first aspect and any possible implementation thereof, for example, to obtain, determine, and send the data and / or information involved in the above-mentioned model building method for the ultrasonic sensor system. The chip system includes a chip, and may also include other discrete devices or circuit structures.

[0023] In a fourth aspect, a computer-readable storage medium is provided, the computer-readable storage medium comprising computer execution instructions, and when the computer execution instructions are executed on a computer, the computer executes the model building method for an ultrasonic sensor system described in the first aspect.

[0024] In a fifth aspect, a computer program product is also provided, which includes computer instructions. When the computer instructions are run on a model building device for an ultrasonic sensor system, the model building device for an ultrasonic sensor system executes the model building method for an ultrasonic sensor system as described in the first aspect above.

[0025] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the model building device for the ultrasonic sensor system, or may be packaged separately from the processor of the model building device for the ultrasonic sensor system, which is not limited in the embodiments of the present application.

[0026] The description of the second, third, fourth and fifth aspects of the present application can refer to the detailed description of the first aspect.

[0027] In the embodiments of the present application, the name of the model building device for the ultrasonic sensor system does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. For example, the receiving unit may also be called a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of the present application, they belong to the scope of the claims of the present application and their equivalent technologies.

[0028] Compared with the prior art, the present invention obtains ultrasonic echo signals by setting ultrasonic sensors at predetermined positions and performing multiple tests. After noise reduction processing, these signals can more accurately reflect the characteristics of pipeline samples, that is, reduce the impact of environmental noise on ultrasonic echo signals, and improve the detection accuracy of the ultrasonic sensor system model.

[0029] Secondly, the density of the pipeline sample is corrected by using the specification parameters (such as pipeline sample thickness and pipeline sample density) and the detection temperature to obtain a more accurate acoustic impedance of the pipeline sample, and then obtain more accurate acoustic characteristic parameters of the pipeline sample. This method enables the ultrasonic sensor system model to maintain optimal performance under different conditions. Through the comprehensive analysis of multiple specification parameters, a more accurate ultrasonic sensor system model is established, so that the ultrasonic sensor system model can adapt to different application scenarios.

[0030] That is to say, the model building method of the ultrasonic sensor system of the present application, through multi-step signal processing and data analysis, significantly improves the detection accuracy, optimizes the sensor system performance, enhances the reliability and adaptability of the model, and provides strong support for various industrial applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0032] Figure 1 A schematic diagram of the structure of a model building system provided in an embodiment of the present application;

[0033] Figure 2 A schematic diagram of the hardware structure of a model building device provided in an embodiment of the present application;

[0034] Figure 3 A flow chart of a model building method provided in an embodiment of the present application;

[0035] Figure 4 A schematic diagram of a flow chart of another model building method provided in an embodiment of the present application;

[0036] Figure 5 A schematic diagram of a flow chart of another model building method provided in an embodiment of the present application;

[0037] Figure 6 A schematic diagram of a flow chart of another model building method provided in an embodiment of the present application;

[0038] Figure 7 A schematic diagram of a flow chart of another model building method provided in an embodiment of the present application;

[0039] Figure 8 A schematic diagram of a flow chart of another model building method provided in an embodiment of the present application;

[0040] Fig. 9 A schematic diagram of the structure of a model building device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" 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 "exemplary" or "for example" is intended to present related concepts in a specific way.

[0043] In order to facilitate a clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and order of execution.

[0044] As described in the background art, ultrasonic sensors in existing ultrasonic sensor systems are easily disturbed by interference factors such as environmental noise and environmental changes in actual applications, resulting in inaccurate detection results.

[0045] For example, the ultrasonic sensors in the conventional ultrasonic sensor system are easily interfered by the environmental noise, resulting in inaccurate detection results.

[0046] Another example is that the traditional ultrasonic sensor system only relies on a single detection parameter, ignoring the influence of other important parameters, making the detection results incomplete and inaccurate. In addition, the traditional ultrasonic sensor system fails to fully consider the impact of temperature changes on ultrasonic propagation speed and medium density, resulting in unstable detection results under different environments.

[0047] In response to the above problems, an embodiment of the present application provides a model building method for an ultrasonic sensor system, including: obtaining ultrasonic echo signals of multiple detections of several pipeline samples through an ultrasonic sensor (set at a predetermined position of the pipeline sample), and obtaining specification parameters of the pipeline samples (including pipeline sample thickness and pipeline sample density). Then, the ultrasonic echo signal can be subjected to noise reduction processing, and the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample can be determined according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample. Then, the detection temperature of the pipeline sample can be obtained, and the pipeline sample density of the pipeline sample can be corrected according to the detection temperature to obtain the corrected density. Subsequently, the acoustic impedance of the pipeline sample can be determined according to the corrected density and wave velocity, and the acoustic characteristic parameters of the pipeline sample can be determined according to the acoustic impedance, and an ultrasonic sensor system model can be established based on the acoustic characteristic parameters.

[0048] The ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline (such as the pipeline thickness after the detected pipeline is corroded, pipeline composition change information, etc.) by detecting the acoustic characteristic parameters of the detected pipeline.

[0049] As can be seen from the above, the present invention obtains ultrasonic echo signals by setting ultrasonic sensors at predetermined positions and performing multiple tests. After noise reduction processing, these signals can more accurately reflect the characteristics of pipeline samples, that is, reduce the impact of environmental noise on ultrasonic echo signals, and improve the detection accuracy of the ultrasonic sensor system model.

[0050] Secondly, the density of the pipeline sample is corrected by using the specification parameters (such as the thickness of the pipeline sample and the density of the pipeline sample) and the detection temperature, so as to obtain a more accurate acoustic impedance of the pipeline sample, and then obtain a more accurate acoustic characteristic parameter of the pipeline sample, and establish a more accurate ultrasonic sensor system model. This method enables the ultrasonic sensor system model to maintain optimal performance under different conditions. That is, through the comprehensive analysis of multiple specification parameters, a more accurate ultrasonic sensor system model is established, so that the ultrasonic sensor system model can adapt to different application scenarios.

[0051] That is to say, the model building method of the ultrasonic sensor system of the present application, through multi-step signal processing and data analysis, significantly improves the detection accuracy, optimizes the sensor system performance, enhances the reliability and adaptability of the model, and provides strong support for various industrial applications.

[0052] The above-mentioned model building method of the ultrasonic sensor system can be applied to the model building system. Figure 1 Figure 2 shows a schematic diagram of the structure of the model building system. Figure 1 As shown, the model building system includes: a plurality of pipeline samples 101 , ultrasonic sensors 102 arranged at predetermined positions of the pipeline samples 101 , a model building device 103 and a storage server 104 .

[0053] Optionally, the predetermined position may be the position of any one end of the pipeline sample 101, or the middle position of the pipeline sample 101, or other preset positions, which is not limited in the embodiment of the present application.

[0054] The pipeline sample 101 may be different types of pipeline samples, such as a natural gas pipeline sample, a crude oil pipeline sample, a refined oil pipeline sample, etc.

[0055] The ultrasonic sensor 102 is a sensor that converts ultrasonic signals into other energy signals (usually electrical signals), and is usually used to detect parameters such as the thickness of the object being detected.

[0056] Optionally, the ultrasonic sensor generally includes an ultrasonic transmitting module and an ultrasonic receiving module. The ultrasonic transmitting module can transmit an ultrasonic signal. After the ultrasonic signal is refracted and reflected in the pipeline sample, the ultrasonic receiving module can receive the refracted and reflected signal, that is, the ultrasonic echo signal.

[0057] In the embodiment of the present application, the ultrasonic sensor 102 may emit ultrasonic echo signals to a number of pipeline samples 101 , so that the model building device 103 builds an ultrasonic sensor system model according to the ultrasonic echo signals emitted by the ultrasonic sensor 102 .

[0058] Optionally, the ultrasonic sensor 102 may be any of the following types of ultrasonic sensors: a contact ultrasonic sensor, a non-contact ultrasonic sensor, an external clamp-on ultrasonic sensor, etc.

[0059] The storage server 104 stores data required for the model building device 103 to build an ultrasonic sensor system model, such as specification parameters of the pipeline sample 101 and the detection temperature of the pipeline sample 101 in the embodiment of the present application.

[0060] Optionally, the specification parameters of the pipeline sample 101 may be pre-stored in the storage server 104 when the pipeline sample 101 leaves the factory. The detected temperature of the pipeline sample 101 may be sent to the storage server 104 in real time by a temperature sensor on the pipeline sample 101, or may be input into the storage server 104 by an operator after obtaining the detected temperature of the pipeline sample 101.

[0061] The model building device 103 is used to obtain the ultrasonic echo signal emitted by the ultrasonic sensor 102 and the specification parameters of the pipeline sample 101, the detection temperature of the pipeline sample 101 and other parameters stored in the storage server 104, and establish an ultrasonic sensor system model according to the above parameters.

[0062] Optionally, the physical device of the model building device 103 may be a server, a terminal, or other types of electronic devices, which is not limited in the embodiments of the present application.

[0063] Optionally, the terminal may be at least one of a smart phone, a smart watch, a desktop computer, a laptop computer, a virtual reality terminal, an augmented reality terminal, a wireless terminal, a laptop computer and the like.

[0064] Optionally, the above-mentioned server can be a server in a server cluster (consisting of multiple servers), or a chip in the server, or a system on a chip in the server, or can be implemented by a virtual machine (VM) deployed on a physical machine, which is not limited in the embodiments of the present application.

[0065] The basic hardware structure of the model building device 103 includes Figure 2 The model building device shown in FIG. Figure 2 Taking the model building device shown in the figure as an example, the hardware structure of the model building device 103 is introduced.

[0066] like Figure 2, which is a schematic diagram of a hardware structure of a model building device provided in an embodiment of the present application. The model building device includes a processor 21, a memory 22, a communication interface 23, and a bus 24. The processor 21, the memory 22, and the communication interface 23 can be connected via a bus 24.

[0067] The processor 21 is the control center of the model building device, which can be a processor or a general term for multiple processing elements. For example, the processor 21 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0068] As an embodiment, the processor 21 may include one or more CPUs, such as Figure 2 CPU 0 and CPU 1 are shown in .

[0069] The memory 22 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0070] In a possible implementation, the memory 22 may exist independently of the processor 21, and the memory 22 may be connected to the processor 21 via a bus 24 to store instructions or program codes. When the processor 21 calls and executes the instructions or program codes stored in the memory 22, the model building method provided in the following embodiments of the present application can be implemented.

[0071] In the embodiment of the present application, for the model building device 103, the software programs stored in the memory 22 are different, so the functions implemented by the model building device 103 are different. The functions performed by each device will be described in conjunction with the following flowchart.

[0072] In another possible implementation, the memory 22 may also be integrated with the processor 21 .

[0073] The communication interface 23 is used to connect the model building device to other devices through a communication network, and the communication network may be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 23 may include a receiving unit for receiving data and a sending unit for sending data.

[0074] The bus 24 may be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0075] It should be pointed out that Figure 2 The structure shown in the figure does not constitute a limitation on the model building device, except Figure 2 In addition to the components shown, the model building device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0076] The model building method provided in the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0077] The model building method provided in the embodiment of the present application is applied to Figure 1 The model building device 103 in the model building system shown. Figure 3 As shown, the model building method includes:

[0078] S301. The model building device obtains ultrasonic echo signals of multiple detections of a plurality of pipeline samples through an ultrasonic sensor.

[0079] Wherein, the ultrasonic sensor is arranged at a predetermined position of the pipeline sample.

[0080] Optionally, the ultrasonic sensor may be provided with a timer. The timer is used to instruct the ultrasonic sensor to periodically perform multiple tests on a number of pipeline samples. During the detection process, the ultrasonic sensor may obtain an ultrasonic echo signal. Accordingly, the model building device may obtain the ultrasonic echo signal through the ultrasonic sensor, so as to subsequently establish an ultrasonic sensor system model based on the ultrasonic echo signal.

[0081] In some embodiments of the present application, the above pipeline samples are single material samples. That is, one pipeline sample contains one material. It is understandable that different pipeline samples can be different material samples.

[0082] Setting the pipeline sample as a sample of a single material can ensure the purity of the data obtained during the test. When the material of the pipeline sample is consistent, the impact on the test data is single. In addition, because the ultrasonic wave propagates in different media, the wave velocity and attenuation of the ultrasonic wave are affected differently. Therefore, when the sample is a single material, the propagation in the same pipeline sample is consistent, avoiding the problem of reduced accuracy of the established ultrasonic sensor system model due to different materials.

[0083] S302: The model building device obtains specification parameters of the pipeline sample.

[0084] Among them, the specification parameters include pipeline sample thickness and pipeline sample density.

[0085] Optional, as above Figure 1 As can be seen from the relevant description, the specification parameters of the pipeline sample can be pre-stored in the storage server. The model building device can obtain the specification parameters of the pipeline sample through the storage server.

[0086] Alternatively, the operator may also manually input the specification parameters of the pipeline sample into the model building device.

[0087] It should be understood that the specification parameters of the pipeline sample may also include other specification parameters such as pipeline sample weight, pipeline sample volume, etc. Thus, when the specification parameters of the pipeline sample obtained by the model building device do not include the pipeline sample density, the model building device may also determine the pipeline sample density based on the ratio of the pipeline sample weight to the pipeline sample volume.

[0088] S303, the model building device performs noise reduction processing on the ultrasonic echo signal, and determines the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after the noise reduction processing and the thickness of the pipeline sample.

[0089] Specifically, since the ultrasonic echo signal may be affected by environmental noise when it is transmitted in the pipeline sample, the ultrasonic echo signal may include a large number of unqualified signals. Therefore, the model building device can first perform noise reduction processing on the ultrasonic echo signal to eliminate the unqualified signals to ensure the reliability and effectiveness of the ultrasonic echo signal.

[0090] Since the ratio of the distance that ultrasound travels in a medium to its propagation time is the wave velocity of ultrasound in the medium, in the pipe sample, ultrasound travels from the transmitting end to the other side of the pipe sample and then reflects back to form an echo signal, so the distance that ultrasound travels is twice the thickness of the pipe sample.

[0091] Based on this principle, after the ultrasonic echo signal is subjected to noise reduction processing, the model building device can accurately determine the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample.

[0092] S304: The model building device obtains the detection temperature of the pipeline sample.

[0093] Specifically, since the density of the pipeline sample may be different at different detection temperatures, in order to establish an ultrasonic sensor system model with higher accuracy, the model building device needs to obtain the detection temperature of the pipeline sample.

[0094] Optional, as above Figure 1 As can be seen from the relevant description, the detected temperature of the pipeline sample can be obtained in real time through the temperature sensor and stored in the storage server. The model building device can obtain the detected temperature of the pipeline sample through the storage server.

[0095] Alternatively, the operator may also manually input the detected temperature of the pipeline sample into the model building device.

[0096] S305. The model building device corrects the pipeline sample density of the pipeline sample according to the detected temperature to obtain a corrected density.

[0097] Specifically, since the density of the pipeline sample may be different under different detection temperatures, in order to establish an ultrasonic sensor system model that is applicable to different temperature conditions and has high accuracy, the model building device can correct the pipeline sample density of the pipeline sample according to the detection temperature to obtain a corrected density. The specific correction process can be referred to the description below and will not be repeated here.

[0098] S306. The model building device determines the acoustic impedance of the pipeline sample according to the corrected density and wave velocity.

[0099] Specifically, acoustic impedance is a physical quantity that reflects the particle damping characteristics caused by acoustic disturbance at a certain position in the pipeline sample. Therefore, by determining the acoustic impedance of the pipeline sample, the impedance characteristics of each pipeline sample during the sound wave propagation process can be accurately evaluated, thereby providing an important reference for further research and application.

[0100] S307. The model building device determines the acoustic characteristic parameters of the pipeline sample according to the acoustic impedance.

[0101] Optionally, since the acoustic impedance can directly reflect the acoustic characteristics of the pipeline sample, the model building device can directly determine the acoustic impedance of the pipeline sample as the acoustic characteristic parameter of the pipeline sample.

[0102] Optionally, the model building device may also determine the acoustic characteristic parameters of the pipeline sample according to the acoustic impedance using a general acoustic characteristic parameter algorithm.

[0103] Optionally, the acoustic characteristic parameter may include at least one of a reflection coefficient, a transmission coefficient and an attenuation coefficient.

[0104] Specifically, when ultrasound propagates in a pipe sample, reflection and transmission phenomena occur. The reflection coefficient and transmission coefficient describe the proportion of ultrasound reflection and transmission in the pipe sample, respectively. The attenuation coefficient reflects the degree of energy attenuation when ultrasound propagates in the pipe sample.

[0105] S308. The model building device builds an ultrasonic sensor system model based on the acoustic characteristic parameters.

[0106] The ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline by detecting the acoustic characteristic parameters of the detected pipeline.

[0107] Optionally, the above-mentioned pipeline quality may be pipeline wall thickness (also referred to as pipeline thickness).

[0108] Specifically, the ultrasonic echo signal emitted by the ultrasonic sensor is transmitted from the ultrasonic sensor to the inner wall of the pipe, part of it is reflected back, and the other part continues to propagate to the outer wall of the pipe and then reflects again. By measuring the time difference between these two reflected waves and combining it with the acoustic characteristic parameters of the pipe sample, the wall thickness of the pipe can be accurately calculated.

[0109] Detecting the wall thickness of the inspected pipeline is very important for monitoring the corrosion of the inspected pipeline. For example, in oil and natural gas pipelines, the inner wall of the inspected pipeline may become thinner over time due to corrosion by the medium. Regularly using the ultrasonic sensor system model provided by this application to detect the wall thickness of the inspected pipeline can timely discover safety hazards of the pipeline and prevent accidents such as pipeline rupture.

[0110] Optionally, the above pipeline quality may also be internal defects of the pipeline.

[0111] Specifically, when the ultrasonic echo signal emitted by the ultrasonic sensor propagates inside the inspected pipeline, if it encounters defects such as cracks and holes, it will produce reflection, refraction and scattering phenomena. The ultrasonic sensor can receive these abnormal ultrasonic echo signals, and by analyzing these abnormal ultrasonic echo signals and combining them with the acoustic characteristic parameters of the pipeline sample, it can determine the location, size and shape of the defects inside the pipeline.

[0112] In some piping systems with high precision requirements, such as the coolant piping in nuclear power plants, it is crucial to detect internal defects in the pipelines being inspected, which can ensure the integrity of the pipelines being inspected and the safe operation of the system.

[0113] Optionally, the above pipeline quality may also be the state of the fluid in the pipeline.

[0114] Specifically, when the ultrasonic echo signal emitted by the ultrasonic sensor propagates inside the inspected pipe, the propagation speed of the ultrasonic echo signal in the fluid in the pipe changes. Combined with the acoustic characteristic parameters of the pipe sample, the density, viscosity and other physical properties of the fluid in the inspected pipe can be determined.

[0115] In the chemical production process, detecting the state of the fluid in the pipeline under inspection helps to monitor the progress of the chemical reaction or the state of the fluid mixing in the pipeline under inspection in real time.

[0116] In some embodiments of the present application, Figure 3 ,like Figure 4 As shown, in the above S303, the method for the model building device to perform noise reduction processing on the ultrasonic echo signal specifically includes:

[0117] S401. The model building device performs quality verification on the ultrasonic echo signal.

[0118] Specifically, the model building device verifies the quality of the ultrasonic echo signal to ensure the reliability and validity of the ultrasonic echo signal. In other words, the model building device verifies the quality of the ultrasonic echo signal to eliminate unqualified signals caused by noise or other interference factors by evaluating the quality of the ultrasonic echo signal.

[0119] Ultrasonic echo signals that pass the quality verification can be processed in the next step, while ultrasonic echo signals that fail the quality verification can be discarded.

[0120] S402: The model building device amplifies the ultrasonic echo signal that has passed the quality verification.

[0121] Specifically, the purpose of amplification is to enhance the signal strength of the ultrasonic echo signal, making it clearer and easier to analyze in the subsequent processing. Amplification usually involves adjusting the gain of the ultrasonic echo signal to ensure that the ultrasonic echo signal achieves the best amplification effect without distortion.

[0122] Optionally, the model building device may amplify the ultrasonic echo signal that has passed the quality verification through an amplification circuit.

[0123] The core component of the amplifier circuit is the amplifier, common ones include transistor amplifiers (such as triode amplifiers) and integrated circuit amplifiers (such as operational amplifiers).

[0124] S403: The model building device performs filtering processing on the amplified ultrasonic echo signal.

[0125] Specifically, the purpose of filtering is to remove noise and interference components that may exist in the ultrasonic echo signal and retain useful information.

[0126] The model building device usually uses different filters to filter the amplified ultrasonic echo signal.

[0127] Optionally, the filter may be a low-pass filter, a high-pass filter or a band-pass filter, etc. The model building device may select a suitable filtering method according to the specific conditions of the ultrasonic echo signal.

[0128] For example, when high-frequency noise is mixed in the ultrasonic echo signal and the signal frequency required to establish the ultrasonic sensor system model is relatively low, the model building device can use a low-pass filtering method to perform filtering processing.

[0129] For another example, when the ultrasonic echo signal is interfered by a specific frequency or a narrow frequency band, and other frequency components are useful signals, the model building device can use a band-stop filtering method to perform filtering processing.

[0130] S404: The model building device converts the ultrasonic echo signal after filtering into a digital echo signal.

[0131] The digital echo signal includes the ultrasonic emission time and the ultrasonic reception time.

[0132] Specifically, after obtaining the ultrasonic echo signal after filtering, in order to extract the ultrasonic emission time and the ultrasonic reception time for subsequent signal analysis and processing, the model building device can convert the ultrasonic echo signal after filtering into a digital echo signal.

[0133] Optionally, the model building device may convert the filtered ultrasonic echo signal into a digital echo signal through an analog-to-digital converter (used to convert an analog signal into a digital signal).

[0134] The converted digital echo signal contains two key time parameters: ultrasonic emission time and ultrasonic reception time. These two time parameters are crucial for subsequent signal analysis and processing, because they can be used to calculate the propagation speed and distance of ultrasonic waves in the medium, which can then be used in various applications such as non-destructive testing, medical imaging, etc.

[0135] In the embodiment of the present application, the wave velocity of the ultrasonic wave in the pipeline sample corresponding to the ultrasonic echo signal can be accurately calculated through the ultrasonic emission time and the ultrasonic reception time, thereby providing data support for the subsequent establishment of an ultrasonic sensor system model. It can be seen that, first, this scheme can improve the quality and reliability of the ultrasonic echo signal by verifying the quality of the ultrasonic echo signal, thereby ensuring the accuracy of subsequent analysis. Secondly, the effective ultrasonic echo signal is enhanced by amplification processing, which is convenient for subsequent signal analysis and feature extraction. Secondly, the filtering process eliminates the noise in the ultrasonic echo signal, which can improve the clarity of the signal and help to more accurately identify and analyze the signal. Secondly, the ultrasonic echo signal is converted into a digital signal for easy storage, transmission and processing, thereby improving the efficiency of signal processing. Here, by recording the ultrasonic emission and reception time, a data basis can be provided for subsequent signal time analysis.

[0136] In some embodiments of the present application, Figure 4 ,like Figure 5 As shown, in the above S401, the method for the model building device to perform quality verification on the ultrasonic echo signal specifically includes:

[0137] S501. A model building device creates at least one dimension of quality evaluation and its corresponding evaluation index.

[0138] Specifically, in the process of quality verification of ultrasonic echo signals, it is first necessary to construct multiple quality evaluation dimensions and set corresponding evaluation indicators for each dimension. These dimensions and indicators together constitute a comprehensive quality evaluation system.

[0139] In some embodiments, the above-mentioned dimension includes at least one of integrity, signal-to-noise ratio, noise level and waveform characteristics.

[0140] The completeness dimension can be used to evaluate whether the ultrasonic echo signal is complete and whether there are any missing parts. The signal-to-noise ratio dimension can be used to measure the ratio of effective information to noise in the ultrasonic echo signal. The higher the signal-to-noise ratio, the better the signal quality is. The noise level dimension is used to determine the intensity of the noise in the ultrasonic echo signal. A lower noise level usually means a higher signal quality. The waveform feature dimension can be used to evaluate whether the characteristics of the ultrasonic echo signal waveform meet expectations, such as whether the shape, amplitude, and frequency of the waveform are within the normal range.

[0141] Each of the above dimensions has its corresponding evaluation index. For example, the evaluation index of the completeness dimension may be a completeness rate index, the evaluation index of the signal-to-noise ratio dimension may be a signal-to-noise ratio index, the evaluation index of the noise level dimension may be a noise level index, and the evaluation index of the waveform feature dimension may be a waveform feature index.

[0142] S502. The model building device scores the ultrasonic echo signal according to the evaluation index to obtain a quality score of the ultrasonic echo signal.

[0143] Specifically, the model building device can score the ultrasonic echo signal in detail according to the evaluation indicators corresponding to the above dimensions, thereby obtaining a comprehensive quality score. This score reflects the performance of the ultrasonic echo signal in various dimensions. Through the comprehensive evaluation of these dimensions and evaluation indicators, the quality of the ultrasonic echo signal can be judged more accurately, thereby ensuring the reliability and accuracy of the test results.

[0144] In one achievable manner, the model building device may determine the sum of the evaluation indicators corresponding to each dimension as the quality score of the ultrasonic echo signal.

[0145] In another possible implementation, the model building device may also set different weights for different evaluation indicators according to different business needs, and perform weighted summation on the evaluation indicators corresponding to each dimension to obtain a quality score for the ultrasonic echo signal.

[0146] S503, the model building device compares the quality score with the quality score threshold. If the quality score is greater than or equal to the quality score threshold, it is determined that the quality verification of the ultrasonic echo signal has passed; if the quality score is less than the quality score threshold, it is determined that the quality verification of the ultrasonic echo signal has failed, and the pipeline sample is re-tested to obtain the ultrasonic echo signal.

[0147] Specifically, after obtaining the quality score, the model building device needs to compare it with a pre-set quality score threshold.

[0148] If the quality score is greater than or equal to the quality score threshold, it can be determined that the quality verification of the ultrasonic echo signal has passed. This means that the performance of the ultrasonic echo signal in each dimension has reached the expected standard, and its quality can be considered reliable.

[0149] However, if the quality score is less than the quality score threshold, it indicates that the performance of the ultrasonic echo signal in some dimensions fails to meet the expected standards, and therefore it is necessary to determine that the quality verification of the ultrasonic echo signal has failed.

[0150] In this case, the model building equipment needs to re-test the pipeline sample to obtain a new ultrasonic echo signal. Through re-testing, it is possible to try to obtain an ultrasonic echo signal with higher quality to meet the quality verification requirements.

[0151] In some embodiments of the present application, Figure 5 ,like Figure 6 As shown, in the above S303, the method in which the model building device determines the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample specifically includes:

[0152] S601. The model building device determines the detection time of multiple detections according to the ultrasonic emission time and the ultrasonic reception time.

[0153] In order to accurately calculate the propagation speed of ultrasound in different pipeline samples, the model building equipment needs to first determine the detection time of multiple tests.

[0154] Specifically, the model building device needs to record the time point when the ultrasonic wave is emitted and the time point when the ultrasonic wave is received (ie, the ultrasonic wave emission time and the ultrasonic wave reception time). Through these two time points, the total time of each detection (ie, the detection time of multiple detections) can be calculated.

[0155] S602. The model building device determines the single wave velocity of the ultrasonic wave in the pipeline sample for each detection according to the thickness of the pipeline sample and the detection time, and determines the average value of the single wave velocity as the wave velocity of the ultrasonic wave in each pipeline sample.

[0156] The above wave speed is determined according to the following formula:

[0157]

[0158] Where V represents the wave velocity of ultrasonic wave in the pipe sample, H represents the thickness of the pipe sample, and T ai Indicates the ultrasonic receiving time of the i-th detection, T si It indicates the ultrasonic emission time of the i-th detection, and n indicates the number of detections.

[0159] Specifically, the model building device can use the thickness information of the pipeline sample and the above-calculated detection time to further determine the single propagation speed of the ultrasonic wave in each pipeline sample in each detection. Subsequently, the model building device can obtain the average wave speed of the ultrasonic wave in each pipeline sample by averaging the single wave speeds obtained from multiple detections.

[0160] That is to say, in this embodiment, by performing noise reduction processing on the ultrasonic echo signal and combining it with the actual thickness of the pipeline sample, the propagation speed of the ultrasonic wave in different pipeline samples (i.e., the average wave speed) can be accurately calculated. This average wave speed reflects the overall propagation characteristics of the ultrasonic wave in a specific pipeline sample, and provides important basic data for subsequent analysis and application.

[0161] In some embodiments of the present application, Figure 6 ,like Figure 7 As shown, in the above S305, the model building device corrects the pipeline sample density of the pipeline sample according to the detected temperature to obtain the corrected density, which specifically includes:

[0162] S701. The model building device compares the detection temperature with the standard temperature range. If the detection temperature is within the standard temperature range, the pipeline sample density is determined as the corrected density.

[0163] That is, no correction is made for the density of the pipeline samples.

[0164] Specifically, in order to ensure that density values ​​measured under different temperature conditions are comparable, the model building device may compare the detection temperature during actual detection with a pre-set standard temperature range.

[0165] Optionally, the standard temperature range is a reference interval, usually determined by relevant industry standards or experimental requirements.

[0166] If the test temperature during the test happens to fall within this standard temperature range, it can be assumed that no correction is required for the density of the pipeline sample.

[0167] S702. If the detection temperature is not within the standard temperature range, the model building device corrects the density of the pipeline sample, and if the detection temperature is lower than the standard temperature range, the temperature difference between the detection temperature and the lower limit of the standard temperature is determined, and the density of the pipeline sample is positively corrected according to the temperature difference.

[0168] S703. If the detected temperature is higher than the standard temperature range, the model building device determines the temperature difference between the detected temperature and the upper limit of the standard temperature, and performs a negative correction on the density of the pipeline sample according to the temperature difference.

[0169] That is to say, if the detected temperature exceeds the standard temperature range, the density value needs to be corrected accordingly.

[0170] Specifically, if the test temperature is lower than the lower limit of the standard temperature range, the difference between the test temperature and the lower limit of the standard temperature needs to be calculated. Based on this temperature difference, the density of the pipeline sample is positively corrected, that is, a certain value is added to compensate for the impact of the low temperature.

[0171] On the contrary, if the test temperature is higher than the upper limit of the standard temperature range, it is also necessary to calculate the difference between the test temperature and the upper limit of the standard temperature. In this case, the density of the pipeline sample is negatively corrected, that is, a certain value is subtracted to compensate for the impact of the high temperature. In this way, it can ensure that the density values ​​obtained under different temperature conditions have high accuracy and consistency.

[0172] It can be seen that this scheme can enhance the accuracy of pipeline sample density measurement and reduce the impact of temperature fluctuation on density measurement.

[0173] In some embodiments of the present application, the method for correcting the density of a pipeline sample by a model building device specifically includes:

[0174] The model building device can establish a correspondence between multiple temperature difference intervals and multiple correction coefficients. Subsequently, the model building device can determine the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and correct the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs.

[0175] Among them, the temperature difference range is positively correlated with the correction coefficient.

[0176] By presetting the temperature difference and the corresponding correction coefficient, the operator can quickly determine the required correction coefficient when performing density correction, simplifying the operation process and improving work efficiency. In addition, by clarifying the corresponding relationship between the temperature range and the correction coefficient, the operator's subjective judgment in judging and selecting the correction coefficient is reduced, thereby reducing the error caused by human factors.

[0177] In some embodiments, the plurality of temperature difference intervals may be divided by presetting a first temperature difference, a second temperature difference, and a third temperature difference, wherein the first temperature difference, the second temperature difference, and the third temperature difference increase in sequence.

[0178] The method for the model building device to determine the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs specifically includes:

[0179] If the temperature difference is less than the first temperature difference, the model building device determines the correction coefficient to be the first correction coefficient C1.

[0180] If the temperature difference is greater than or equal to the first temperature difference, and the temperature difference is less than the second temperature difference, the model building device determines that the correction coefficient is the second correction coefficient C2.

[0181] If the temperature difference is greater than or equal to the second temperature difference, and the temperature difference is less than the third temperature difference, the model building device determines that the correction coefficient is the third correction coefficient C3.

[0182] If the temperature difference is greater than or equal to the third temperature difference, the model building device determines the correction coefficient to be a fourth correction coefficient C4.

[0183] In this embodiment, by setting different temperature difference intervals and corresponding different correction coefficients, the measured value of the pipeline sample density can be adjusted more accurately, thereby improving the accuracy of the overall measurement.

[0184] It should be noted that this application can flexibly select different correction coefficients according to the actual temperature difference, adapt to a wider range of temperature changes, and ensure that more accurate density measurement results can be obtained under different conditions. In addition, more accurate corrected density data can be obtained through the above correction coefficients, which is helpful for subsequent data analysis and decision-making, and improves the management level and product quality of the entire production process.

[0185] In some embodiments of the present application, a method for a model building device to correct the density of a pipeline sample according to a correction coefficient corresponding to a temperature difference interval to which the temperature difference belongs specifically includes:

[0186] If the detected temperature is lower than the standard temperature range, the model building device corrects the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1+Ci).

[0187] If the detected temperature is higher than the standard temperature range, the model building device corrects the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1-Ci).

[0188] Wherein, p0 represents the density of the pipeline sample, Ci represents the i-th correction coefficient, i=1, 2, 3, 4.

[0189] In this embodiment, in the process of correcting the density of the pipeline sample, the difference between the detection temperature and the standard temperature range needs to be considered. Specifically, if the detection temperature is lower than the standard temperature range, the corrected density will be p=p0×(1+Ci). On the contrary, if the detection temperature is higher than the standard temperature range, the corrected density will be p=p0×(1-Ci). Here, Ci represents the i-th correction coefficient, where i can take the values ​​of 1, 2, 3 or 4. In this way, it can be ensured that the density values ​​obtained under different temperature conditions are more accurate, thereby improving the reliability of the measurement results.

[0190] In some embodiments of the present application, Figure 7 ,like Figure 8 As shown, in the above S306, the method for the model building device to determine the acoustic impedance of the pipeline sample according to the corrected density and wave velocity specifically includes:

[0191] S801. The model building device determines the product of the corrected density and the wave velocity as the acoustic impedance of the pipeline sample.

[0192] That is, the acoustic impedance is determined by the following formula:

[0193] Z = pV;

[0194] Where Z represents acoustic impedance, p represents modified density, and V represents wave velocity.

[0195] In this embodiment, acoustic impedance is a physical quantity that reflects the particle damping characteristics caused by acoustic disturbance at a certain position in the medium. According to the specific values ​​of the modified density and wave velocity mentioned above, the acoustic impedance value of each pipeline sample can be further determined. The specific operation steps are as follows: First, calculate the product between the modified density and the wave velocity. This product represents the resistance encountered by the sound wave when propagating in the medium. Then, we set this product as the acoustic impedance value of each pipeline sample. In this way, the impedance characteristics of each pipeline sample during the sound wave propagation process can be accurately evaluated, thereby providing an important reference for further research and application.

[0196] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0197] The embodiment of the present application can divide the functional modules of the model building device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0198] like Fig. 9 , which is a schematic diagram of the structure of a model building device provided in an embodiment of the present application. Fig. 9 The model building device shown includes: a communication unit 901 and a processing unit 902;

[0199] The communication unit 901 is used to obtain ultrasonic echo signals of multiple detections of a plurality of pipeline samples through an ultrasonic sensor; the ultrasonic sensor is arranged at a predetermined position of the pipeline sample;

[0200] The communication unit 901 is also used to obtain specification parameters of the pipeline sample, the specification parameters including the thickness and density of the pipeline sample;

[0201] The processing unit 902 is used to perform noise reduction processing on the ultrasonic echo signal, and determine the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample;

[0202] The communication unit 901 is also used to obtain the detected temperature of the pipeline sample, and correct the pipeline sample density of the pipeline sample according to the detected temperature to obtain a corrected density;

[0203] The processing unit 902 is also used to determine the acoustic impedance of the pipeline sample based on the corrected density and wave velocity, and determine the acoustic characteristic parameters of the pipeline sample based on the acoustic impedance, and establish an ultrasonic sensor system model based on the acoustic characteristic parameters; the ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline by detecting the acoustic characteristic parameters of the detected pipeline.

[0204] Optionally, the processing unit 902 is specifically configured to:

[0205] Performing quality verification on the ultrasonic echo signal, amplifying the ultrasonic echo signal that has passed the quality verification, and filtering the amplified ultrasonic echo signal;

[0206] The ultrasonic echo signal after filtering is converted into a digital echo signal, and the digital echo signal includes the ultrasonic emission time and the ultrasonic reception time.

[0207] Optionally, the processing unit 902 is specifically configured to:

[0208] Create at least one dimension of quality evaluation and its corresponding evaluation indicators;

[0209] Scoring the ultrasonic echo signal according to the evaluation index to obtain the quality score of the ultrasonic echo signal;

[0210] The quality score is compared with the quality score threshold, and if the quality score is greater than or equal to the quality score threshold, it is determined that the quality verification of the ultrasonic echo signal has passed;

[0211] If the quality score is less than the quality score threshold, it is determined that the quality verification of the ultrasonic echo signal has failed, and the pipeline sample is retested to obtain the ultrasonic echo signal.

[0212] Optionally, the dimension includes at least one of integrity, signal-to-noise ratio, noise level, and waveform characteristics.

[0213] Optionally, the processing unit 902 is specifically configured to:

[0214] Determine the detection time of multiple detections according to the ultrasonic emission time and the ultrasonic reception time;

[0215] Determine the single wave velocity of the ultrasonic wave in the pipeline sample for each test according to the thickness of the pipeline sample and the test time, and determine the average value of the single wave velocity as the wave velocity of the ultrasonic wave in the pipeline sample;

[0216] The wave speed is determined according to the following formula:

[0217]

[0218] Where V represents the wave velocity of ultrasonic wave in the pipe sample, H represents the thickness of the pipe sample, and T ai Indicates the ultrasonic receiving time of the i-th detection, T si It indicates the ultrasonic emission time of the i-th detection, and n indicates the number of detections.

[0219] Optionally, the processing unit 902 is specifically configured to:

[0220] The test temperature is compared with the standard temperature range. If the test temperature is within the standard temperature range, the density of the pipeline sample is determined as the corrected density;

[0221] If the detection temperature is not within the standard temperature range, the density of the pipeline sample is corrected, and if the detection temperature is lower than the standard temperature range, the temperature difference between the detection temperature and the lower limit of the standard temperature is determined, and the density of the pipeline sample is positively corrected according to the temperature difference to obtain the corrected density;

[0222] If the detected temperature is higher than the standard temperature range, the temperature difference between the detected temperature and the upper limit of the standard temperature is determined, and the density of the pipeline sample is negatively corrected according to the temperature difference to obtain the corrected density.

[0223] Optionally, the processing unit 902 is specifically configured to:

[0224] Establishing the corresponding relationship between multiple temperature difference intervals and multiple correction coefficients; the temperature difference interval is positively correlated with the correction coefficient;

[0225] Determine the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and correct the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs.

[0226] Optionally, the plurality of temperature difference intervals are divided by a preset first temperature difference, a second temperature difference and a third temperature difference; the first temperature difference, the second temperature difference and the third temperature difference increase in sequence;

[0227] The processing unit 902 is specifically configured to:

[0228] If the temperature difference is less than the first temperature difference, the correction coefficient is determined to be the first correction coefficient C1;

[0229] If the temperature difference is greater than or equal to the first temperature difference, and the temperature difference is less than the second temperature difference, then the correction coefficient is determined to be the second correction coefficient C2;

[0230] If the temperature difference is greater than or equal to the second temperature difference, and the temperature difference is less than the third temperature difference, the correction coefficient is determined to be the third correction coefficient C3;

[0231] If the temperature difference is greater than or equal to the third temperature difference, the correction coefficient is determined to be the fourth correction coefficient C4.

[0232] Optionally, the processing unit 902 is specifically configured to:

[0233] If the detected temperature is lower than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density is p=p0×(1+Ci);

[0234] If the detected temperature is higher than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density is p=p0×(1-Ci); wherein p0 represents the density of the pipeline sample, Ci represents the i-th correction coefficient, i=1, 2, 3, 4.

[0235] Optionally, the processing unit 902 is specifically configured to:

[0236] The product of the corrected density and the wave velocity is determined as the acoustic impedance of the pipe sample.

[0237] Optionally, the pipe sample is a single material sample.

[0238] An embodiment of the present application also provides a computer-readable storage medium, which includes computer execution instructions. When the computer execution instructions are executed on a computer, the computer executes the model building method provided in the above embodiment.

[0239] The embodiment of the present application also provides a computer program product, which can be directly loaded into a memory and contains software code. After the computer is loaded and executed, the computer program product can implement the model building method provided in the above embodiment. Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention is described in detail with reference to the preferred embodiments, ordinary technicians in this field should understand that they can still modify or replace the technical solution of the present invention, and these modifications or equivalent replacements cannot make the modified technical solution deviate from the spirit and scope of the technical solution of the present invention.

[0240] The system provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0241] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

Claims

1. A model building method for an ultrasonic sensor system, characterized in that: include: Acquiring ultrasonic echo signals of multiple detections of a plurality of pipeline samples by means of an ultrasonic sensor; the ultrasonic sensor is arranged at a predetermined position of the pipeline sample; Obtaining specification parameters of the pipeline sample, wherein the specification parameters include pipeline sample thickness and pipeline sample density; Performing noise reduction processing on the ultrasonic echo signal, and determining the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after the noise reduction processing and the thickness of the pipeline sample; Acquiring a detected temperature of the pipeline sample, and correcting a pipeline sample density of the pipeline sample according to the detected temperature to obtain a corrected density; The acoustic impedance of the pipeline sample is determined according to the corrected density and the wave velocity, and the acoustic characteristic parameters of the pipeline sample are determined according to the acoustic impedance, and an ultrasonic sensor system model is established based on the acoustic characteristic parameters; the ultrasonic sensor system model is used to detect the pipeline quality of the detected pipeline by detecting the acoustic characteristic parameters of the detected pipeline.

2. The model building method for an ultrasonic sensor system according to claim 1, characterized in that: The step of performing noise reduction processing on the ultrasonic echo signal comprises: Performing quality verification on the ultrasonic echo signal, amplifying the ultrasonic echo signal that has passed the quality verification, and filtering the amplified ultrasonic echo signal; The ultrasonic echo signal after filtering is converted into a digital echo signal, wherein the digital echo signal includes an ultrasonic emission time and an ultrasonic reception time.

3. The model building method for an ultrasonic sensor system according to claim 2, characterized in that: The quality verification of the ultrasonic echo signal includes: Create at least one dimension of quality evaluation and its corresponding evaluation indicators; Scoring the ultrasonic echo signal according to the evaluation index to obtain a quality score of the ultrasonic echo signal; Comparing the quality score with a quality score threshold, and if the quality score is greater than or equal to the quality score threshold, determining that the quality verification of the ultrasonic echo signal passes; If the quality score is less than the quality score threshold, it is determined that the quality verification of the ultrasonic echo signal has failed, and the pipeline sample is retested to obtain an ultrasonic echo signal.

4. The model building method for an ultrasonic sensor system according to claim 3, characterized in that: The dimension includes at least one of integrity, signal-to-noise ratio, noise level, and waveform characteristics.

5. The model building method for an ultrasonic sensor system according to claim 2, characterized in that: The step of determining the wave velocity of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipeline sample according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample comprises: Determining the detection time of multiple detections according to the ultrasonic emission time and the ultrasonic reception time; Determine the single wave velocity of the ultrasonic wave in the pipeline sample at each test according to the thickness of the pipeline sample and the test time, and determine the average value of the single wave velocity as the wave velocity of the ultrasonic wave in the pipeline sample; The wave speed is determined according to the following formula: Where V represents the wave velocity of ultrasonic wave in the pipe sample, H represents the thickness of the pipe sample, and T ai Indicates the ultrasonic receiving time of the i-th detection, T si It indicates the ultrasonic emission time of the i-th detection, and n indicates the number of detections.

6. The model building method for an ultrasonic sensor system according to claim 1, characterized in that: The step of correcting the pipeline sample density of the pipeline sample according to the detected temperature to obtain a corrected density includes: Comparing the detected temperature with a standard temperature range, and if the detected temperature is within the standard temperature range, determining the pipeline sample density as the corrected density; If the detected temperature is not within the standard temperature range, the density of the pipeline sample is corrected, and if the detected temperature is lower than the standard temperature range, the temperature difference between the detected temperature and the lower limit of the standard temperature is determined, and the density of the pipeline sample is positively corrected according to the temperature difference to obtain the corrected density; If the detected temperature is higher than the standard temperature range, the temperature difference between the detected temperature and the upper limit of the standard temperature is determined, and the density of the pipeline sample is negatively corrected according to the temperature difference to obtain the corrected density.

7. The model building method for an ultrasonic sensor system according to claim 6, characterized in that: The correcting of the density of the pipeline sample comprises: Establishing a correspondence between a plurality of temperature difference intervals and a plurality of correction coefficients; the temperature difference intervals are positively correlated with the correction coefficients; A correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs is determined, and the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs.

8. The model building method for an ultrasonic sensor system according to claim 7, characterized in that: The multiple temperature difference intervals are divided by a preset first temperature difference, a second temperature difference and a third temperature difference; the first temperature difference, the second temperature difference and the third temperature difference increase in sequence; The determining of the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs includes: If the temperature difference is less than the first temperature difference, determining the correction coefficient to be the first correction coefficient C1; If the temperature difference is greater than or equal to the first temperature difference, and the temperature difference is less than the second temperature difference, determining the correction coefficient to be the second correction coefficient C2; If the temperature difference is greater than or equal to the second temperature difference, and the temperature difference is less than the third temperature difference, then the correction coefficient is determined to be the third correction coefficient C3; If the temperature difference is greater than or equal to the third temperature difference, the correction coefficient is determined to be a fourth correction coefficient C4.

9. The model building method for an ultrasonic sensor system according to claim 8, characterized in that: The correcting the density of the pipeline sample according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs includes: If the detected temperature is lower than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1+Ci); If the detected temperature is higher than the standard temperature range, the density of the pipeline sample is corrected according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs, and the corrected density obtained is p=p0×(1-Ci); wherein p0 represents the density of the pipeline sample, Ci represents the i-th correction coefficient, i=1, 2, 3, 4.

10. The model building method for an ultrasonic sensor system according to claim 1, characterized in that: The step of determining the acoustic impedance of the pipeline sample according to the corrected density and the wave velocity comprises: The product of the modified density and the wave velocity is determined as the acoustic impedance of the pipe sample.

11. The model building method for an ultrasonic sensor system according to any one of claims 1 to 10, characterized in that: The pipeline sample is a single material sample.

12. A model building device for an ultrasonic sensor system, characterized in that: include: A processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the device is running, the processor executes the computer-executable instructions stored in the memory to enable the device to perform the method described in any one of claims 1 to 11.

13. A computer-readable storage medium, characterized in that: When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is capable of performing the method as claimed in any one of claims 1 to 11.

14. A computer program product, characterized in that The computer program product comprises: a computer program or instructions, and when the computer program or instructions are run on a computer, the computer is caused to perform the method according to any one of claims 1 to 11.

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