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

Abstract

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

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of model construction, in particular to a model construction method, device, medium and product of an ultrasonic sensor system. BACKGROUND

[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 evaluation, material property analysis, etc.

[0003] However, the ultrasonic sensors in existing ultrasonic sensor systems are easily disturbed by environmental noise, environmental changes and other interference factors in actual application, resulting in inaccurate detection results.

[0004] Therefore, there is an urgent need for a model construction method for an ultrasonic sensor system to improve detection accuracy, optimize system performance, enhance model reliability and adaptability. SUMMARY

[0005] The purpose of the present application is to provide a model construction method, device, medium and product of an ultrasonic sensor system, which solves the problems of insufficient detection accuracy, large noise influence and poor system adaptability in the prior art.

[0006] In a first aspect, the present application provides a model construction method for an ultrasonic sensor system, comprising: acquiring ultrasonic echo signals for multiple detections of a plurality of pipeline samples by an ultrasonic sensor; the ultrasonic sensor is arranged at a predetermined position of the pipeline sample; acquiring 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 signals, determining the wave speed of the ultrasonic echo signals corresponding to the ultrasonic wave in the pipeline sample according to the ultrasonic echo signals after noise reduction processing and the pipeline sample thickness; acquiring 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 speed, 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 on the ultrasonic echo signals comprises: quality verification of the ultrasonic echo signals, amplification processing of the ultrasonic echo signals passing the quality verification, and filtering processing of the ultrasonic echo signals after amplification processing; converting the ultrasonic echo signals after filtering processing into digital echo signals, the digital echo signals including ultrasonic wave transmission time and ultrasonic wave reception time.

[0008] In some embodiments, the quality verification of the ultrasonic echo signal comprises: 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 is passed; if the quality score is less than the quality score threshold, determining that the quality verification of the ultrasonic echo signal is failed, and re-detecting the pipeline sample to obtain an ultrasonic echo signal.

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

[0010] In some embodiments, the wave speed of the ultrasonic echo signal corresponding to the ultrasonic wave in the pipeline sample is determined according to the ultrasonic echo signal after noise reduction processing and the thickness of the pipeline sample, comprising: determining the detection time of multiple detections according to the ultrasonic wave emission time and the ultrasonic wave receiving time; determining the single wave speed of the ultrasonic wave in the pipeline sample of each detection according to the thickness of the pipeline sample and the detection time, and determining the average value of the single wave speed as the wave speed of the ultrasonic wave in the pipeline sample.

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

[0012]

[0013] Wherein, V represents the wave speed of the ultrasonic wave in the pipeline sample, H represents the thickness of the pipeline sample, T ai represents the ultrasonic wave receiving time of the i-th detection, T si represents the ultrasonic wave emission time of the i-th detection, and n represents the detection number.

[0014] In some embodiments, the pipeline sample density of the pipeline sample is corrected according to the detection temperature to obtain a corrected density, comprising: comparing the detection temperature with a standard temperature range, if the detection temperature is within the standard temperature range, determining the pipeline sample density as the corrected density; if the detection temperature is not within the standard temperature range, correcting the pipeline sample density, and if the detection temperature is lower than the standard temperature range, determining the temperature difference between the detection temperature and the lower limit of the standard temperature, positively correcting the pipeline sample density according to the temperature difference to obtain the corrected density; if the detection temperature is higher than the standard temperature range, determining the temperature difference between the detection temperature and the upper limit of the standard temperature, negatively correcting the pipeline sample density according to the temperature difference to obtain the corrected density.

[0015] In some embodiments, the correcting the pipeline sample density 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; determining a correction coefficient corresponding to a temperature difference interval to which the temperature difference belongs, and correcting the pipeline sample density according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs.

[0016] In some embodiments, the plurality of temperature difference intervals are divided by a first temperature difference, a second temperature difference and a third temperature difference preset in sequence; the first temperature difference, the second temperature difference and the third temperature difference increase in sequence; the determining the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs comprises: if the temperature difference is less than the first temperature difference, determining a first correction coefficient C1 as the correction coefficient; if the temperature difference is greater than or equal to the first temperature difference and less than the second temperature difference, determining a second correction coefficient C2 as the correction coefficient; if the temperature difference is greater than or equal to the second temperature difference and less than the third temperature difference, determining a third correction coefficient C3 as the correction coefficient; if the temperature difference is greater than or equal to the third temperature difference, determining a fourth correction coefficient C4 as the correction coefficient.

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

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

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

[0020] In a second aspect, a model construction device for an ultrasonic sensor system is provided, comprising a communication unit and a processing unit; the communication unit is configured to acquire, by an ultrasonic sensor, ultrasonic echo signals obtained by detecting a plurality of pipe samples for a plurality of times; the ultrasonic sensor is arranged at a predetermined position of the pipe sample; the communication unit is further configured to acquire specification parameters of the pipe sample, the specification parameters comprising a pipe sample thickness and a pipe sample density; the processing unit is configured to perform noise reduction processing on the ultrasonic echo signals, and determine a wave speed of the ultrasonic echo signals in the pipe sample according to the ultrasonic echo signals after the noise reduction processing and the pipe sample thickness; the communication unit is further configured to acquire a detection temperature of the pipe sample, and correct the pipe sample density of the pipe sample according to the detection temperature to obtain a corrected density; the processing unit is further configured to determine an acoustic impedance of the pipe sample according to the corrected density and the wave speed, and determine an acoustic characteristic parameter of the pipe sample according to the acoustic impedance, and establish an ultrasonic sensor system model based on the acoustic characteristic parameter; the ultrasonic sensor system model is configured to detect a pipe quality of a detected pipe by detecting the acoustic characteristic parameter of the detected pipe.

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

[0022] The model construction device for the ultrasonic sensor system can be a network device, or a part of the device in the network device, for example, a chip system in the network device. The chip system is configured to support the network device to implement the functions involved in the first aspect and any possible implementation manner thereof, for example, acquiring, determining, and sending the data and / or information involved in the model construction method for the ultrasonic sensor system. The chip system comprises a chip, and can further comprise other discrete devices or circuit structures.

[0023] In a fourth aspect, a computer readable storage medium is provided, comprising computer execution instructions; when the computer execution instructions are running on a computer, the computer is caused to execute the model construction method for the ultrasonic sensor system in the first aspect.

[0024] In a fifth aspect, a computer program product is further provided, comprising computer instructions; when the computer instructions are running on the model construction device for the ultrasonic sensor system, the model construction device for the ultrasonic sensor system is caused to execute the model construction method for the ultrasonic sensor system in the first aspect.

[0025] It should be noted that the above computer instructions can be stored in whole or in part on a computer readable storage medium. The computer readable storage medium can be packaged together with the processor of the model construction device for the ultrasonic sensor system, or packaged separately from the processor of the model construction device for the ultrasonic sensor system, and the embodiments of the present application do not limit this.

[0026] The description of the second aspect, the third aspect, the fourth aspect and the fifth aspect in 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 above-mentioned model construction device for the ultrasonic sensor system does not constitute a limitation on the device or functional module itself, and in actual implementation, these devices or functional modules can appear with other names. For example, the receiving unit can also be referred to as 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 equivalent technologies.

[0028] Compared with the prior art, the present application acquires ultrasonic echo signals by setting ultrasonic sensors at predetermined positions and performing multiple detections. After noise reduction processing, these signals can more accurately reflect the characteristics of the pipe sample, i.e., the influence of environmental noise on the ultrasonic echo signal is reduced, and the detection accuracy of the ultrasonic sensor system model is improved.

[0029] Secondly, the pipe sample density is corrected using specification parameters (such as pipe sample thickness and pipe sample density) and detection temperature, so as to obtain more accurate acoustic impedance of the pipe sample, and further obtain acoustic characteristic parameters of the pipe sample with higher accuracy. This method enables the ultrasonic sensor system model to maintain optimal performance under different conditions. Through comprehensive analysis of various 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, the model construction method of the ultrasonic sensor system of the present application significantly improves the detection accuracy, optimizes the performance of the sensor system, enhances the reliability and adaptability of the model, and provides strong support for various industrial applications through multi-step signal processing and data analysis. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only embodiments of the present application, and those skilled in the art can obtain other drawings according to the provided drawings without creative labor.

[0032] Figure 1 A structural schematic diagram of a model construction system provided for an embodiment of the present application is shown in FIG. 1.

[0033] Figure 2 A hardware structural schematic diagram of a model construction apparatus provided for an embodiment of the present application is shown in FIG. 2.

[0034] Figure 3 A flowchart of a model construction method provided for an embodiment of the present application is shown in FIG. 3.

[0035] Figure 4 A flowchart of another model construction method provided for an embodiment of the present application is shown in FIG. 4.

[0036] Figure 5 A flowchart of another model construction method provided for an embodiment of the present application is shown in FIG. 5.

[0037] Figure 6 A flowchart of another model construction method provided for an embodiment of the present application is shown in FIG. 6.

[0038] Figure 7 A flowchart of another model construction method provided for an embodiment of the present application is shown in FIG. 7.

[0039] Figure 8 A flowchart of another model construction method provided for an embodiment of the present application is shown in FIG. 8.

[0040] Figure 9 A structural schematic diagram of a model construction apparatus provided for an embodiment of the present application is shown in FIG. 9. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0042] It should be noted that in the embodiments of the present application, the words such as “exemplary” or “for example” are used to mean serving as an example, an instance, or an illustration. Any embodiment or design scheme described as “exemplary” or “for example” in the embodiments of the present application should not be interpreted as being more preferred or having more advantages than other embodiments or design schemes. Rather, the words “exemplary” or “for example” are used in the sense of presenting a related concept in a specific manner.

[0043] In order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", etc. are used to distinguish the same or similar items with basically the same function and role, and those skilled in the art can understand that the terms "first", "second", etc. are not used to limit the quantity and execution order.

[0044] As described in the background, the ultrasonic sensors in the existing ultrasonic sensor system are easily disturbed by environmental noise, environmental changes and other interference factors in actual application, resulting in inaccurate detection results.

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

[0046] Further, the conventional ultrasonic sensor system only relies on a single detection parameter, ignores the influence of other important parameters, and makes the detection results not comprehensive and accurate. Moreover, the conventional ultrasonic sensor system fails to fully consider the influence of temperature change on the ultrasonic propagation speed and medium density, resulting in unstable detection results in different environments.

[0047] To solve the above problems, the embodiments of the present application provide a model construction method for an ultrasonic sensor system, which comprises: acquiring ultrasonic echo signals obtained by detecting a plurality of pipeline samples through an ultrasonic sensor (arranged at a predetermined position of the pipeline samples) multiple times, and acquiring specification parameters (including pipeline sample thickness and pipeline sample density) of the pipeline samples. Then, the ultrasonic echo signals can be denoised, and the wave speed of the ultrasonic echo signals corresponding to the ultrasonic waves in the pipeline samples is determined according to the denoised ultrasonic echo signals and the pipeline sample thickness. Then, the detection temperature of the pipeline samples can be acquired, and the pipeline sample density of the pipeline samples is corrected according to the detection temperature to obtain a corrected density. Subsequently, the acoustic impedance of the pipeline samples can be determined according to the corrected density and the wave speed, and the acoustic characteristic parameters of the pipeline samples are determined according to the acoustic impedance, and an ultrasonic sensor system model is established based on the acoustic characteristic parameters.

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

[0049] As can be seen from the above, the present application acquires ultrasonic echo signals by arranging an ultrasonic sensor at a predetermined position and performing multiple detections. After these signals are denoised, the characteristics of the pipeline samples can be more accurately reflected, that is, the influence of environmental noise on the ultrasonic echo signals is reduced, and the detection accuracy of the ultrasonic sensor system model is improved.

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

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

[0052] The model construction method of the ultrasonic sensor system described above can be applied to a model construction system. Figure 1 The structural schematic diagram of the model construction system is shown. As shown in the figure, Figure 1 The model construction system includes a plurality of pipe samples 101, an ultrasonic sensor 102 arranged at a predetermined position of the pipe sample 101, a model construction device 103, and a storage server 104.

[0053] Optionally, the predetermined position can be a position of any one end of the pipe sample 101, a middle position of the pipe sample 101, or other preset positions, which are not limited in the present application.

[0054] The pipe sample 101 can be different types of pipe samples, such as natural gas pipe samples, crude oil pipe samples, and refined oil pipe samples.

[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 the thickness and other parameters of the detected object.

[0056] Optionally, the ultrasonic sensor generally includes an ultrasonic wave transmitting module and an ultrasonic wave receiving module. The ultrasonic wave transmitting module can emit ultrasonic signals. After the ultrasonic signals are refracted and reflected in the pipe sample, the ultrasonic wave receiving module can receive the refracted and reflected signals, i.e., ultrasonic echo signals.

[0057] In the present application, the ultrasonic sensor 102 can emit ultrasonic echo signals to the plurality of pipe samples 101, so that the model construction device 103 establishes an ultrasonic sensor system model according to the ultrasonic echo signals emitted by the ultrasonic sensor 102.

[0058] Optionally, the ultrasonic sensor 102 can be any one of the following ultrasonic sensors: a contact ultrasonic sensor, a non-contact ultrasonic sensor, an outer clamp ultrasonic sensor, etc.

[0059] The storage server 104 stores data required by the model construction device 103 to construct the ultrasonic sensor system model, such as the specification parameters of the pipe sample 101, the detection temperature of the pipe sample 101, etc.

[0060] Optionally, the specification parameters of the pipe sample 101 can be pre-stored in the storage server 104 when the pipe sample 101 is manufactured. The detection temperature of the pipe sample 101 can be sent by the temperature sensor on the pipe sample 101 to the storage server 104 in real time, or can be input into the storage server 104 by the operator after obtaining the detection temperature of the pipe sample 101.

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

[0062] Optionally, the entity device of the model construction device 103 can be a server, a terminal, or other types of electronic devices, which are not limited in the embodiments of the present application.

[0063] Optionally, the terminal can 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, and a laptop computer, etc.

[0064] Optionally, the server can be one server in a server cluster (composed of multiple servers), a chip in the server, a system on chip in the server, or implemented through a virtual machine (VM) deployed on a physical machine, which are not limited in the embodiments of the present application.

[0065] The basic hardware structure of the model construction device 103 includes Figure 2 The elements included in the model construction device shown in FIG. 1. The hardware structure of the model construction device 103 is introduced below taking the model construction device shown in FIG. 1 as an example. Figure 2

[0066] As shown in FIG. 1, the model construction device 103 includes a processor 101, a memory 102, a communication interface 103, and a power supply 104. Figure 2 ​As shown in FIG. 1, a hardware structure schematic diagram of a model construction device provided by an embodiment of the present application is shown. The model construction 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 through the bus 24.

[0067] The processor 21 is the control center of the model construction device, and can be one processor or a general term of multiple processing elements. For example, the processor 21 can be a general central processing unit (CPU), or other general processors, etc. The general processor can be a microprocessor or any conventional processor, etc.

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

[0069] The memory 22 can 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 magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes 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 can exist independently of the processor 21. The memory 22 can be connected to the processor 21 through the bus 24, and is used to store instructions or program codes. When the processor 21 invokes and executes the instructions or program codes stored in the memory 22, the model construction method provided by the embodiments of the present application can be implemented.

[0071] In the embodiments of the present application, the software programs stored in the memory 22 are different for the model construction device 103, and therefore the functions implemented by the model construction device 103 are different. The functions performed by the devices will be described in combination with the flowcharts below.

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

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

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

[0075] It should be pointed out that, Figure 2 The structures shown do not constitute a limitation on the model building apparatus, except Figure 2 In addition to the components shown, the model building apparatus may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0076] The model construction method provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

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

[0078] S301 The model building equipment acquires ultrasonic echo signals from multiple tests on several pipe samples using an ultrasonic sensor.

[0079] The ultrasonic sensor is installed at a predetermined position on the pipe sample.

[0080] Optionally, the ultrasonic sensor can be equipped with a timer. This timer instructs the ultrasonic sensor to periodically perform multiple tests on several pipe samples. During the testing process, the ultrasonic sensor acquires ultrasonic echo signals. Correspondingly, the model building device can acquire these ultrasonic echo signals through the ultrasonic sensor to facilitate the subsequent creation of an ultrasonic sensor system model based on the ultrasonic echo signals.

[0081] In some embodiments of the present application, the pipeline sample is a single material sample. That is, one material is contained in one pipeline sample. It can be understood that different pipeline samples can be different material samples.

[0082] Setting the pipeline sample as a single material sample can ensure the purity of the data obtained during detection. When the materials of the pipeline samples are consistent, the influence on the detection data is single. Moreover, because the wave speed and attenuation of the ultrasonic wave are different when the ultrasonic wave propagates in different media, when the sample is a single material, the propagation in the same pipeline sample is consistent, thereby avoiding the problem of reducing the accuracy of the ultrasonic sensor system model established due to different materials.

[0083] S302, the model construction device obtains the specification parameters of the pipeline sample.

[0084] The specification parameters include the thickness of the pipeline sample and the density of the pipeline sample.

[0085] Optionally, as described above Figure 1 It can be understood that the specification parameters of the pipeline sample can be pre-stored in the storage server. The model construction device can obtain the specification parameters of the pipeline sample through the storage server.

[0086] Alternatively, the operator can also input the specification parameters of the pipeline sample into the model construction device in an artificial input manner.

[0087] It should be understood that the specification parameters of the pipeline sample can also include the weight of the pipeline sample, the volume of the pipeline sample, and other specification parameters. In this way, when the model construction device does not include the density of the pipeline sample in the specification parameters of the pipeline sample, the model construction device can also determine the density of the pipeline sample according to the ratio of the weight of the pipeline sample to the volume of the pipeline sample.

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

[0089] Specifically, because the ultrasonic echo signal can be affected by environmental noise during transmission in the pipeline sample, the ultrasonic echo signal includes a large number of unqualified signals. Therefore, the model construction device can first perform noise reduction processing on the ultrasonic echo signal to eliminate unqualified signals, so as to ensure the reliability and effectiveness of the ultrasonic echo signal.

[0090] Since the ratio of the distance of ultrasonic wave propagation in the medium and the propagation time is the wave velocity of the ultrasonic wave in the medium, in the pipeline sample, the ultrasonic wave propagates from the transmitting end to the other side of the pipeline sample, and then reflects back to form an echo signal, so the distance of ultrasonic wave propagation is twice the thickness of the pipeline sample.

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

[0092] S304, the model construction 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 a more accurate ultrasonic sensor system model, the model construction device needs to obtain the detection temperature of the pipeline sample.

[0094] Optionally, as described above Figure 1 As described above, the detection temperature of the pipeline sample can be obtained in real time by the temperature sensor and stored in the storage server. The model construction device can obtain the detection temperature of the pipeline sample through the storage server.

[0095] Alternatively, the operator can also input the detection temperature of the pipeline sample into the model construction device by manual input.

[0096] S305, the model construction device corrects the pipeline sample density of the pipeline sample according to the detection temperature to obtain a corrected density.

[0097] Specifically, since the density of the pipeline sample may be different at different detection temperatures, in order to establish an ultrasonic sensor system model that is applicable and accurate at different temperature conditions, therefore, the model construction 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, which is not repeated here.

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

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

[0100] S307, the model construction 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 construction device can directly determine the acoustic impedance of the pipeline sample as the acoustic characteristic parameter of the pipeline sample.

[0102] Optionally, the model construction device can also determine the acoustic characteristic parameter of the pipeline sample according to the acoustic impedance through a general acoustic characteristic parameter algorithm.

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

[0104] Specifically, when the ultrasonic wave propagates in the pipeline sample, reflection and transmission phenomena occur. The reflection coefficient and the transmission coefficient respectively describe the proportion of the ultrasonic wave reflected and transmitted in the pipeline sample. The attenuation coefficient reflects the degree of energy attenuation of the ultrasonic wave propagating in the pipeline sample.

[0105] S308, the model construction device establishes an ultrasonic sensor system model based on the acoustic characteristic parameter.

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

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

[0108] Specifically, the ultrasonic echo signal emitted by the ultrasonic sensor is emitted from the ultrasonic sensor to the inner wall of the pipeline, part of which is reflected back, and the other part continues to propagate to the outer wall of the pipeline and is reflected again. By measuring the time difference of the two reflected waves, combined with the acoustic characteristic parameter of the pipeline sample, the wall thickness of the pipeline can be accurately calculated.

[0109] Detecting the pipeline wall thickness of the detected pipeline is very important for monitoring the corrosion of the detected pipeline. For example, in the oil and gas pipeline, the inner wall of the detected pipeline may be thinned due to the corrosion of the medium over time. Regularly detecting the pipeline wall thickness of the detected pipeline using the ultrasonic sensor system model provided in the present application can timely find the safety hazards of the pipeline and prevent pipeline rupture accidents.

[0110] Optionally, the above-mentioned pipeline quality can also be a pipeline internal defect.

[0111] Specifically, when the ultrasonic echo signal emitted by the ultrasonic sensor propagates inside the detected pipeline, if it encounters defects such as cracks, holes, etc., 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, in combination with the acoustic characteristic parameters of the pipeline sample, the position, size and shape of the internal defects of the pipeline can be determined.

[0112] In some high-precision pipeline systems, such as the coolant pipelines of nuclear power plants, detecting the internal defects of the detected pipeline is crucial to ensure the integrity of the detected pipeline and the safe operation of the system.

[0113] Optionally, the pipeline quality described above can 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 detected pipeline, the propagation speed of the ultrasonic echo signal in the fluid in the pipeline changes, and in combination with the acoustic characteristic parameters of the pipeline sample, the density, viscosity and other physical properties of the fluid in the detected pipeline can be determined.

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

[0116] In some embodiments of the present application, in combination with Figure 3 As shown in Figure 4 The method for noise reduction processing of the ultrasonic echo signal by the model construction device in S303 specifically includes:

[0117] S401, the model construction device verifies the quality of the ultrasonic echo signal.

[0118] Specifically, the model construction device verifies the quality of the ultrasonic echo signal to ensure the reliability and effectiveness of the ultrasonic echo signal. That is, the model construction 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] The ultrasonic echo signal that passes the quality verification can be processed further. The ultrasonic echo signal that does not pass the quality verification can be discarded.

[0120] S402, the model construction device amplifies the ultrasonic echo signal that passes the quality verification.

[0121] Specifically, the purpose of the amplification processing is to enhance the signal strength of the ultrasonic echo signal, making it clearer and easier to analyze in subsequent processing. The amplification processing 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 construction device can amplify the ultrasonic echo signal that passes the quality verification through an amplification circuit.

[0123] The core component of the amplification circuit is an amplifier, commonly including transistor amplifiers (such as triode amplifiers) and integrated circuit amplifiers (such as operational amplifiers).

[0124] S403, the model construction device performs filtering processing on the ultrasonic echo signal after amplification processing.

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

[0126] The model construction device usually uses different filters to perform filtering processing on the ultrasonic echo signal after amplification processing.

[0127] Optionally, the above-mentioned filter can be a low-pass filter, a high-pass filter, or a band-pass filter, etc. The model construction device can select a suitable filtering method according to the specific situation of the ultrasonic echo signal.

[0128] For example, when high-frequency noise is mixed in the ultrasonic echo signal, and the signal frequency required for establishing the ultrasonic wave sensor system model is relatively low, the model construction device can use low-pass filtering method for filtering processing.

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

[0130] S404, the model construction device converts the ultrasonic echo signal after filtering processing into a digital echo signal.

[0131] Among them, the digital echo signal includes the ultrasonic wave transmission time and the ultrasonic wave receiving time.

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

[0133] Optionally, the model construction device can convert the filtered ultrasonic echo signal into a digital echo signal through an analog-to-digital converter (for converting an analog signal into a digital signal).

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

[0135] In the embodiments of the present application, the ultrasonic wave transmission time and the ultrasonic wave reception time can be used to accurately calculate the wave speed of the ultrasonic echo signal corresponding to the ultrasonic wave in the pipeline sample, thereby providing data support for subsequent establishment of the ultrasonic sensor system model. As can be seen, first, the present scheme can improve the quality and reliability of the ultrasonic echo signal by verifying the quality of the ultrasonic echo signal, ensuring the accuracy of subsequent analysis. Secondly, by amplifying the effective ultrasonic echo signal, it is convenient for subsequent signal analysis and feature extraction. Thirdly, the filter processing 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. Fourthly, converting the ultrasonic echo signal into a digital signal facilitates storage, transmission and processing, improving the efficiency of signal processing. Here, by recording the ultrasonic wave transmission and reception time, data basis can be provided for subsequent signal time analysis.

[0136] In some embodiments of the present application, in combination with Figure 4 As shown in Figure 5 In the above S401, the method for the model construction device to verify the quality of the ultrasonic echo signal specifically includes:

[0137] S501, the model construction device creates at least one dimension of quality evaluation and its corresponding evaluation index.

[0138] Specifically, in the process of verifying the quality of the ultrasonic echo signal, first, multiple dimensions of quality evaluation need to be constructed, and corresponding evaluation indexes need to be set for each dimension. These dimensions and indexes together constitute a comprehensive quality evaluation system.

[0139] In some embodiments, the above dimensions include at least one of completeness, signal-to-noise ratio, noise level, and waveform characteristics.

[0140] The completeness dimension can be used to evaluate whether the ultrasound echo signal is complete or whether there is a missing part. The signal-to-noise ratio dimension can be used to measure the proportion of effective information and noise in the ultrasound echo signal. The higher the signal-to-noise ratio, the better the quality of the signal. The noise level dimension is used to determine the intensity of the noise in the ultrasound echo signal. A lower noise level generally means higher signal quality. The waveform feature dimension can be used to evaluate whether the waveform features of the ultrasound echo signal meet the 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 can be the completeness rate index, the evaluation index of the signal-to-noise ratio dimension can be the signal-to-noise ratio index, the evaluation index of the noise level dimension can be the noise level index, and the evaluation index of the waveform feature dimension can be the waveform feature index.

[0142] S502, the model construction device scores the ultrasound echo signal according to the evaluation index to obtain a quality score of the ultrasound echo signal.

[0143] Specifically, the model construction device can score the ultrasound echo signal in detail according to the evaluation index corresponding to each of the above dimensions, thereby obtaining a comprehensive quality score. This score reflects the performance of the ultrasound echo signal in each dimension. Through the comprehensive evaluation of these dimensions and evaluation indexes, the quality of the ultrasound echo signal can be more accurately judged, thereby ensuring the reliability and accuracy of the detection result.

[0144] In one implementable manner, the model construction device can determine the sum of the evaluation indexes corresponding to each dimension as the quality score of the ultrasound echo signal.

[0145] In another implementable manner, the model construction device can also set different weights for different evaluation indexes according to different business needs, and perform weighted summation on the evaluation indexes corresponding to each dimension to obtain the quality score of the ultrasound echo signal.

[0146] S503, the model construction device compares the quality score with a 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 ultrasound echo signal passes. If the quality score is less than the quality score threshold, it is determined that the quality verification of the ultrasound echo signal fails, and the pipeline sample is re-detected to obtain the ultrasound echo signal.

[0147] Specifically, after obtaining the quality score, the model construction device needs to compare it with the 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 is passed. This means that the ultrasonic echo signal performs well in various dimensions and can be considered to have reliable quality.

[0149] However, if the quality score is less than the quality score threshold, it indicates that the ultrasonic echo signal does not perform well in some dimensions, and thus it needs to be determined that the quality verification of the ultrasonic echo signal is failed.

[0150] In this case, the model construction device needs to re-detect the pipe sample to obtain new ultrasonic echo signals. By re-detecting, it can be attempted to obtain ultrasonic echo signals with higher quality to meet the requirements of quality verification.

[0151] In some embodiments of the present application, in combination Figure 5 As shown in Figure 6 In the above S303, the method for determining the wave speed of the ultrasonic wave corresponding to the ultrasonic echo signal in the pipe sample by the model construction device according to the denoised ultrasonic echo signal and the pipe sample thickness, specifically includes:

[0152] S601, the model construction device determines the detection time of multiple detections according to the ultrasonic wave transmission time and the ultrasonic wave receiving time.

[0153] In order to accurately calculate the propagation speed of the ultrasonic wave in different pipe samples, the model construction device needs to determine the detection time of multiple detections first.

[0154] Specifically, the model construction device needs to record the time point of ultrasonic wave transmission and the time point of ultrasonic wave receiving (i.e. ultrasonic wave transmission time and ultrasonic wave receiving time), and through these two time points, the total time of each detection (i.e. the detection time of multiple detections) can be calculated.

[0155] S602, the model construction device determines the single wave speed of the ultrasonic wave in the pipe sample for each detection according to the pipe sample thickness and the detection time, and determines the average value of the single wave speed as the wave speed of the ultrasonic wave in each pipe sample.

[0156] Wherein, the wave speed is determined according to the following formula:

[0157]

[0158] Wherein, V represents the wave speed of the ultrasonic wave in the pipe sample, H represents the pipe sample thickness, T ai represents the i-th detection ultrasonic wave receiving time, T si represents the i-th detection ultrasonic wave transmission time, and n represents the detection number.

[0159] Specifically, the model-building device can utilize the thickness information of the pipe samples and the calculated detection time to further determine the single propagation velocity of ultrasonic waves in each pipe sample during each detection. Subsequently, the model-building device can obtain the average wave velocity of ultrasonic waves in each pipe sample by averaging the single wave velocities obtained from multiple detections.

[0160] In other words, in this embodiment, by performing noise reduction processing on the ultrasonic echo signal and combining it with the actual thickness of the pipe sample, the propagation speed (i.e., average wave velocity) of ultrasonic waves in different pipe samples can be accurately calculated. This average wave velocity reflects the overall propagation characteristics of ultrasonic waves in a specific pipe sample, providing important basic data for subsequent analysis and applications.

[0161] In some embodiments of this application, combined with Figure 6 ,like Figure 7 As shown, in S305 above, the method by which the model building device corrects the pipe sample density based on the detection temperature to obtain the corrected density specifically includes:

[0162] S701 The model building equipment compares the detected temperature with the standard temperature range. If the detected temperature is within the standard temperature range, the density of the pipe sample is determined as the corrected density.

[0163] That is, the density of the pipe sample is not corrected.

[0164] Specifically, in order to ensure the comparability of density values ​​measured under different temperature conditions, the model building equipment can compare the actual detection temperature 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 falls within this standard temperature range, then the density of the pipe sample can be considered to require no correction.

[0167] S702. If the detection temperature is not within the standard temperature range, the model building equipment will correct the density of the pipe sample. 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 will be determined, and the density of the pipe sample will be positively corrected based on the temperature difference.

[0168] S703. If the detected temperature is higher than the standard temperature range, the model building equipment 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 pipe sample based on the temperature difference.

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

[0170] Specifically, if the detected temperature is lower than the lower limit value of the standard temperature range, the difference between the detected temperature and the lower limit value of the standard temperature needs to be calculated. According to 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 low temperature.

[0171] On the contrary, if the detected temperature is higher than the upper limit value of the standard temperature range, the difference between the detected temperature and the upper limit value of the standard temperature also needs to be calculated. 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 high temperature. In this way, the density values obtained under different temperature conditions can have higher accuracy and consistency.

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

[0173] In some embodiments of the present application, the model construction device corrects the density of the pipeline sample by the following method:

[0174] The model construction device can establish a corresponding relationship between multiple temperature difference intervals and multiple correction coefficients. Subsequently, the model construction 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 interval is positively correlated with the correction coefficient.

[0176] The pre-set temperature difference and the corresponding correction coefficient can enable the operator to quickly determine the required correction coefficient when correcting the density, simplify the operation process, and improve the work efficiency. Moreover, through the clear corresponding relationship between the temperature interval and the correction coefficient, the subjective judgment of the operator when judging and selecting the correction coefficient is reduced, thereby reducing the error caused by human factors.

[0177] In some embodiments, the multiple temperature difference intervals can be divided by pre-setting a first temperature difference, a second temperature difference, and a third temperature difference. Among them, the first temperature difference, the second temperature difference, and the third temperature difference increase in turn.

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

[0179] If the temperature difference is less than the first temperature difference, the model construction device determines that the correction coefficient is the first correction coefficient C1.

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

[0181] If the temperature difference is greater than or equal to the second temperature difference and less than the third temperature difference, the model building device determines the correction coefficient as 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 as the fourth correction coefficient C4.

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

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

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

[0186] If the detection temperature is lower than the standard temperature range, the model building device corrects the pipeline sample density according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs to obtain a corrected density p=p0x(1+Ci).

[0187] If the detection temperature is higher than the standard temperature range, the model building device corrects the pipeline sample density according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs to obtain a corrected density p=p0x(1-Ci).

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

[0189] In this embodiment, during 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 obtained will be p=p0x(1+Ci). Conversely, if the detection temperature is higher than the standard temperature range, the corrected density will be p=p0x(1-Ci). Here, Ci represents the i-th correction coefficient, where i can take the values 1, 2, 3, or 4. In this way, the density values obtained under different temperature conditions can be ensured to be more accurate, thereby improving the reliability of the measurement results.

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

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

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

[0193] Z=pV;

[0194] Where Z represents the acoustic impedance, p represents the corrected density, and V represents the wave speed.

[0195] In this embodiment, the acoustic impedance is a physical quantity that reflects the damping characteristics of a certain position in the medium caused by acoustic disturbance. According to the specific values of the corrected density and the wave speed mentioned above, the acoustic impedance values of each pipeline sample can be further determined. The specific operation steps are as follows: first, calculate the product of the corrected density and the wave speed. 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 in 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 scheme provided by the embodiments of the present application from the perspective of method. In order to realize the above functions, it contains the hardware structure and / or software module 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 the examples described in the embodiments disclosed herein, the present application can be realized in the form of hardware or the combination of hardware and computer software. Whether a certain function is executed in hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0197] The model construction device can be divided into functional modules according to the above method examples. 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 integrated module can be realized in the form of hardware or in the form of a software functional module. Optionally, the division of the modules in the embodiments of the present application is illustrative, and is only a logical functional division. In actual implementation, another division mode can be used.

[0198] As shown in Figure 9 FIG. 1 is a structural schematic diagram of a model construction device provided by an embodiment of the present application. Figure 9 The model construction device shown in the figure includes a communication unit 901 and a processing unit 902.

[0199] The communication unit 901 is configured to acquire, by an ultrasonic sensor, ultrasonic echo signals obtained by detecting a plurality of pipe samples for multiple times. The ultrasonic sensor is arranged at a predetermined position of the pipe sample.

[0200] The communication unit 901 is further configured to acquire a specification parameter of the pipe sample, the specification parameter including a pipe sample thickness and a pipe sample density.

[0201] The processing unit 902 is configured to perform noise reduction processing on the ultrasonic echo signals, and determine a wave speed of the ultrasonic wave corresponding to the ultrasonic echo signals in the pipe sample according to the ultrasonic echo signals after the noise reduction processing and the pipe sample thickness.

[0202] The communication unit 901 is further configured to acquire a detection temperature of the pipe sample, and correct the pipe sample density of the pipe sample according to the detection temperature to obtain a corrected density.

[0203] The processing unit 902 is further configured to determine an acoustic impedance of the pipe sample according to the corrected density and the wave speed, determine an acoustic characteristic parameter of the pipe sample according to the acoustic impedance, and establish an ultrasonic sensor system model based on the acoustic characteristic parameter. The ultrasonic sensor system model is configured to detect a pipe quality of a detected pipe by detecting the acoustic characteristic parameter of the detected pipe.

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

[0205] perform quality verification on the ultrasonic echo signals, amplify the ultrasonic echo signals passing the quality verification, and perform filtering processing on the ultrasonic echo signals after the amplification processing.

[0206] convert the ultrasonic echo signals after the filtering processing into digital echo signals, the digital echo signals including an ultrasonic wave emission time and an ultrasonic wave receiving time.

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

[0208] create at least one dimension of the quality evaluation and a corresponding evaluation index thereof;

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

[0210] compare the quality score with a quality score threshold value, and if the quality score is greater than or equal to the quality score threshold value, determine that the quality verification of the ultrasonic echo signal is passed;

[0211] if the quality score is less than the quality score threshold value, determine that the quality verification of the ultrasonic echo signal is not passed, and re-detect the pipe sample to obtain the ultrasonic echo signal.

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

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

[0214] determine a detection time of the multiple detections according to the ultrasonic wave transmission time and the ultrasonic wave receiving time;

[0215] determine a single wave speed of the ultrasonic wave in the pipe sample for each detection according to the pipe sample thickness and the detection time, and determine an average value of the single wave speed as a wave speed of the ultrasonic wave in the pipe sample;

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

[0217]

[0218] wherein V represents the wave speed of the ultrasonic wave in the pipe sample, H represents the pipe sample thickness, T ai represents the ultrasonic wave receiving time of the i-th detection, T si represents the ultrasonic wave transmission time of the i-th detection, and n represents the number of detections.

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

[0220] compare the detection temperature with a standard temperature range, and if the detection temperature is within the standard temperature range, determine the pipe sample density as a corrected density;

[0221] if the detection temperature is not within the standard temperature range, correct the pipe sample density, and if the detection temperature is lower than the lower limit of the standard temperature range, determine a temperature difference between the detection temperature and the lower limit of the standard temperature, and correct the pipe sample density in a positive direction according to the temperature difference to obtain the corrected density;

[0222] If the detection temperature is higher than the standard temperature range, a temperature difference between the detection temperature and an upper limit value of the standard temperature is determined, and the pipe sample density is negatively corrected according to the temperature difference, to obtain a corrected density.

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

[0224] A corresponding relationship between a plurality of temperature difference intervals and a plurality of correction coefficients is established; the temperature difference intervals are positively correlated with the correction coefficients;

[0225] The correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs is determined, and the pipe sample density is corrected 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 first temperature difference value, a second temperature difference value and a third temperature difference value; the first temperature difference value, the second temperature difference value and the third temperature difference value increase in turn;

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

[0228] If the temperature difference is less than the first temperature difference value, the correction coefficient is determined as a first correction coefficient C1;

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

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

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

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

[0233] If the detection temperature is lower than the standard temperature range, the corrected density obtained by correcting the pipe sample density according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs is p=p0×(1+Ci);

[0234] If the detection temperature is higher than the standard temperature range, the corrected density obtained by correcting the pipe sample density according to the correction coefficient corresponding to the temperature difference interval to which the temperature difference belongs is p=p0×(1-Ci); wherein p0 represents the pipe sample density, 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 determined correction density and the wave velocity is determined to be the acoustic impedance of the pipe sample.

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

[0238] The embodiment of the present application further provides a computer readable storage medium, which comprises computer execution instructions, and when the computer execution instructions run on a computer, the computer execution instructions make the computer execute the model construction method provided in the above embodiment.

[0239] The embodiment of the present application further provides a computer program product, which can be directly loaded into a memory and contains software codes, and the computer program product can realize the model construction method provided in the above embodiment after being loaded and executed by a computer. Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application but not to limit the same, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can still be modified or replaced equivalently, and these modifications or equivalent replacements should not make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

[0240] The system provided in the above embodiment is only used as an example for the division of the above functional modules, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the modules or steps in the embodiments of the present application are further decomposed or combined, for example, the modules in the above embodiments can be combined into one module, or can be further split 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 application are only for distinguishing the modules and steps, and should not be considered as improper limitation of the present application.

[0241] Those skilled in the art should be able to realize that the modules, method steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware, computer software or combination of the two. The programs corresponding to the software modules and method steps can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM or any other form of storage medium known in the art. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been described in the above description in general terms. Whether the functions are executed by electronic hardware or software depends on the specific application and design constraints of the technical solutions. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

Claims

1. A model construction method for an ultrasonic sensor system, characterized by, The method comprises the following steps: acquiring ultrasonic echo signals of multiple detections on a plurality of pipeline samples by an ultrasonic sensor arranged at a predetermined position of the pipeline sample; acquiring specification parameters of the pipeline sample, including pipeline sample thickness and pipeline sample density; performing noise reduction processing on the ultrasonic echo signals, and determining the wave speed of the ultrasonic echo signals corresponding to the ultrasonic wave in the pipeline sample according to the ultrasonic echo signals after noise reduction processing and the pipeline sample thickness; acquiring 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 speed, 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.

2. The model construction method for an ultrasonic sensor system according to claim 1, characterized by, The noise reduction processing on the ultrasonic echo signals comprises: performing quality verification on the ultrasonic echo signals, amplifying the ultrasonic echo signals passing the quality verification, and filtering the amplified ultrasonic echo signals; converting the filtered ultrasonic echo signals into digital echo signals, the digital echo signals including ultrasonic wave emission time and ultrasonic wave receiving time.

3. The model construction method for an ultrasonic sensor system according to claim 2, characterized by, The quality verification on the ultrasonic echo signals comprises: creating at least one dimension of quality evaluation and its corresponding evaluation index; scoring the ultrasonic echo signals according to the evaluation index to obtain a quality score of the ultrasonic echo signals; comparing the quality score with a quality score threshold value, if the quality score is greater than or equal to the quality score threshold value, it is determined that the quality verification of the ultrasonic echo signals is passed; if the quality score is less than the quality score threshold value, it is determined that the quality verification of the ultrasonic echo signals is failed, and the pipeline sample is detected again to acquire ultrasonic echo signals.

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

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

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

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

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

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

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

11. The method of model building 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 It comprises: A processor and a memory; wherein the memory is used to store one or more programs, the one or more programs comprising computer execution instructions, when the device is running, the processor executes the computer execution instructions stored in the memory, so that the device executes the method in any one of claims 1 to 11.

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

14. A computer program product, characterised in that, The computer program product includes a computer program or instructions that, when run on a computer, cause the computer to perform the method of any one of claims 1 to 11.

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