Spray pipe modal consistency detection system and method

Abstract

The invention relates to the technical field of composite material product tests, and discloses a spray pipe modal consistency detection system and method, and the system comprises a test system which is used for simulating the free state of a spray pipe; the excitation device is used for applying external excitation to the spray pipe so as to obtain dynamic response; the response data generation system comprises a response sensor and a data acquisition system; and the consistency analysis system is used for analyzing the consistency of the spray pipe by responding to the sensor data. According to the spray pipe modal consistency detection system and method, hardware equipment is simple, operation is convenient, dependence on professionals is reduced, the equipment cost and the maintenance cost are reduced, and the practicability of the system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of composite material product testing, for example, to a nozzle modal consistency detection system and method. Background Art

[0002] C / SiC composites are widely used in spacecraft engine nozzle components due to their lightweight and ultra-high temperature resistance. In the design and manufacturing of spacecraft engines, precise understanding of C / SiC nozzle modal parameters, such as natural frequencies and vibration shapes, plays a key role in evaluating their structural dynamic characteristics, optimizing their design, and ensuring engine reliability and performance. C / SiC nozzles can be used to determine the nozzle's structural transfer characteristics, ensuring quality consistency, and providing a basis for dynamic coupling analysis between the nozzle and the engine system.

[0003] However, existing modal testing systems have numerous drawbacks. They are complex, costly, and require specialized technicians for operation and maintenance. These drawbacks make them difficult to meet the demands of efficient and cost-effective testing in practical applications, particularly for quality consistency checks on mass-produced C / SiC nozzles. Summary of the Invention

[0004] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not intended to be an extensive review, nor to identify key / critical elements or to delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0005] The embodiments of the present disclosure provide a nozzle modal consistency detection system and method to solve the problem that the existing modal testing of nozzles is complex and tedious.

[0006] In some embodiments, a nozzle modal consistency detection system is provided, comprising: a test system for simulating the free state of the nozzle, the test system comprising a ceiling, a suspension system and a nozzle, the suspension system comprising multiple ropes and an intelligent adjustment suspension device, the intelligent adjustment suspension device integrating a micro motor, a displacement sensor and a controller, the displacement sensor being used to monitor the posture change of the nozzle, the controller controlling the micro motor to adjust the length and tension of the suspension rope according to the monitoring result of the displacement sensor; an excitation device being used to apply external excitation to the nozzle to obtain a dynamic response; a response data generation system comprising a response sensor and a data acquisition system, the response sensor being used to measure the stress distribution of a specific part of the nozzle, the data acquisition system being used to collect data from the response sensor and transmit it to a consistency analysis system; a consistency analysis system being used to analyze the consistency of the nozzle through the response sensor data.

[0007] Preferably, the response sensor is arranged at a stress concentration area or a structural joint.

[0008] Preferably, the excitation device comprises any one or more of an excitation hammer assembly, an electromagnetic exciter, an electric vibration table and a hydraulic exciter.

[0009] Preferably, the excitation hammer assembly comprises an excitation hammer and a dynamometer.

[0010] Preferably, the rope comprises a suspension rope and a balance rope.

[0011] Preferably, the test system further comprises a protective cotton cloth laid on the ground.

[0012] Preferably, the total mass of the additional connectors mounted on the nozzle cannot exceed 2% of the mass of the nozzle.

[0013] In some embodiments, a nozzle modal consistency detection method is disclosed, characterized in that it is applied to a nozzle modal consistency detection system, and the method comprises the following steps: S10, a rope suspends a test piece below a ceiling through an intelligent adjustment suspension device, and the intelligent adjustment suspension device is adjusted to make the test piece in a free state; S20, the test piece is excited multiple times, and a response data generation system collects response data of the test piece under different excitations in real time; and S30, the modal consistency of the test piece is analyzed through the response data.

[0014] Preferably, the modal consistency of the test piece is analyzed through the response data, which comprises the following steps: S31, sample modal data is obtained; S32, sample response data corresponding to the sample modal data is tested; S33, the sample response data and the sample modal data are used to train a modal data neural network model, wherein the modal data neural network model is used to train the sample modal data according to input sample response data; S34, test nozzle response data is obtained; and S35, the test nozzle response data is input into the modal data neural network model to generate test nozzle modal data.

[0015] The nozzle modal consistency detection system and method provided by the embodiments of the present disclosure have simple hardware devices, are convenient to operate, reduce the dependence on professional technicians, reduce equipment cost and maintenance cost, and improve the practicability of the system.

[0016] The foregoing general description and the following description are only exemplary and explanatory, and are not used to limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0017] One or more embodiments are exemplarily illustrated by corresponding drawings, which do not constitute a limitation on the embodiments, and elements with the same reference numerals in the drawings are shown as similar elements, the drawings do not constitute a proportional limitation, and wherein: Figure 1 is a schematic diagram of a nozzle modal consistency detection system provided by an embodiment of the present disclosure; Figure 2 is an application schematic diagram of a test system provided by an embodiment of the present disclosure; Figure 3 is a schematic diagram of the positions of an excitation point and a measurement point provided by an embodiment of the present disclosure; Figure 4 Schematic diagram of a nozzle modal consistency detection method provided by an embodiment of the present disclosure; Reference numerals: 1: Ceiling; 2: Suspension rope; 3: Balance rope; 4: Nozzle; 5: Excitation point; 6: Measurement point. DETAILED DESCRIPTION

[0018] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, multiple sections are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments can still be implemented without these sections. In other cases, to simplify the drawings, the well-known structures can be simplified for display.

[0019] The following description and drawings are illustrative of specific embodiments of the application and are not intended to be limiting thereof. Other embodiments can include structural, logical, electrical, process, and many other changes. Examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the order of operations can be varied. Parts and features of some embodiments can be included or replaced in or by parts and features of other embodiments. The scope of embodiments of the application encompasses the entire scope of the claims, and all available equivalents of the claims. In the present disclosure embodiments, each embodiment can be referred to, individually or collectively, by the term "application" merely for convenience and without intending to voluntarily limit the ambit of this application to any single application or inventive concept if more than one is, in fact, disclosed. In the present disclosure embodiments, the term "relationship" such as first and second is used merely to distinguish one entity or operation from another without requiring or implying any actual relationship or order between such entities or operations. Also, the terms "comprises", "comprising", or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element. The disclosure embodiments are described in a progressive manner, each embodiment focusing on the differences from other embodiments, and the same or similar parts between embodiments are cross-referenced. For the methods, products, and the like disclosed in the embodiments, since they correspond to the method part of the embodiments, the description is relatively simple, and the relevant part is referred to the method part.

[0020] The existing modal test system has many disadvantages. The system structure is complex, the equipment cost is high, the operation process is cumbersome, and professional technical personnel are needed for operation and maintenance, which is difficult to meet the efficient and low-cost detection needs in actual application, especially for the quality consistency inspection of batch-produced nozzle products.

[0021] In order to solve the problems in the related art, the present disclosure embodiments provide a nozzle modal consistency detection system and method to solve the problems of complex and cumbersome modal test of nozzles in the prior art.

[0022] In combination with Figure 1 As shown in the figure, the nozzle modal consistency detection system comprises: A test system for simulating the free state of a nozzle, comprising a ceiling, a suspension system and a nozzle, the suspension system comprising a plurality of ropes and an intelligent adjustment suspension device, the intelligent adjustment suspension device integrating a micro motor, a displacement sensor and a controller, the displacement sensor being used to monitor the attitude change of the nozzle, and the controller being used to control the micro motor to adjust the length and tension of the suspension rope according to the monitoring result of the displacement sensor.

[0023] An excitation device for applying an external excitation to the nozzle to obtain a dynamic response.

[0024] A response data generation system, comprising a response sensor used to measure the stress distribution of a specific part of the nozzle and a data acquisition system used to acquire the data of the response sensor and transmit the data to a consistency analysis system.

[0025] A consistency analysis system used to analyze the consistency of the nozzle through the response sensor data.

[0026] Specifically, referring to Figure 2 is a schematic diagram of the application of a test system. The test system is used to simulate the free state of a nozzle. The ceiling 1 adopts a high-strength steel beam structure and is fixed stably above the test site to provide reliable support for the suspension system. The suspension system is composed of a plurality of ropes and an intelligent adjustment suspension device. Among them, the ropes include suspension ropes 2 and balance ropes 3. The intelligent adjustment suspension device integrates a micro motor, a displacement sensor and a controller.

[0027] In the intelligent adjustment suspension device, the displacement sensor serves as a feedback element and continuously monitors the attitude change data of the nozzle. When the nozzle tilts or the center of gravity deviates, the attitude change data becomes a deviation signal. The proportional link adjusts the output according to the size of the current deviation, so that the length and tension of the suspension rope change quickly; the integral link accumulates the deviation over a period of time to eliminate the steady-state error of the system and ensure that the nozzle can accurately return to the ideal position; the derivative link predicts the trend of future deviation according to the rate of change of the deviation and adjusts the control quantity in advance to make the adjustment process faster and smoother. Through the cooperative work of the three links, the PID control algorithm can accurately calculate the parameters of the micro motor to adjust the length and tension of the suspension rope 2 according to the feedback of the displacement sensor, so that the nozzle can maintain a stable simulated free state.

[0028] At the same time, in order to reduce the influence of additional mass on the test results, it is stipulated that the total mass of the additional connecting parts installed on the nozzle shall not exceed 2% of the mass of the nozzle. The additional connecting parts can be rubber ropes and the like. In addition, protective cotton cloth is laid on the ground of the test site to prevent the test piece from being damaged during operation.

[0029] Lay protective cotton sheeting on the ground and suspend the product with thin rope approximately 20 mm above the protective sheeting. Select three or four bolt holes as suspension points, spaced evenly apart, depending on the number of bolt holes. Use soft carbon wire with a diameter of 0.3 mm to 0.5 mm and a length of at least 1.5 m for the rope. Preliminary experiments have shown that too few or too many suspension points can lead to significant errors in the response mode.

[0030] The excitation device utilizes a variety of excitation methods, including one or more of an excitation hammer assembly, electromagnetic vibrator, electrodynamic shaker, and hydraulic vibrator. For example, the excitation hammer assembly comprises an excitation hammer and a dynamometer. The choice of the excitation hammer is determined by the characteristics of the response data generation system and the test requirements, and is precisely calibrated. The excitation device applies external excitation to the nozzle, generating a dynamic response and providing data for subsequent measurements. Conduct a preliminary experiment using the excitation hammer to determine the appropriate excitation point. Create a test, begin acquisition, and simultaneously apply excitation using the excitation hammer.

[0031] The response data generation system consists of response sensors and a data acquisition system. Response sensors are placed in stress concentration areas or structural connections within the nozzle to measure stress distribution at specific locations. The data acquisition system collects data from the response sensors and transmits it to the consistency analysis system for subsequent analysis.

[0032] Specifically, see Figure 3 Figure 2 shows the locations of the excitation and measurement points. Use beeswax to bond the measuring end of the response sensor to the product's response output measurement point 6, located 10 to 20 mm from the bottom edge of the product. Preliminary experiments have shown that the distance from the bottom edge of the product can lead to significant errors in modal test results. The excitation point is the impact point of the excitation hammer.

[0033] The consistency analysis system analyzes the nozzle consistency by receiving response sensor data transmitted by the response data generation system. The system performs in-depth processing and analysis on the collected data to determine whether there are any quality issues with the nozzle.

[0034] For corresponding reference, see Figure 4 , applied to the above-mentioned nozzle modal consistency detection system, the nozzle modal consistency detection method includes: S10, the rope suspends the test piece below the ceiling through the intelligent adjustment suspension device, and the intelligent adjustment suspension device is adjusted to put the test piece in a free state.

[0035] It should be understood that the test piece is suspended below the ceiling using a rope through an intelligent adjustable suspension device, and the intelligent adjustable suspension device is carefully adjusted to place the test piece in a free state, simulating its stress environment in actual work.

[0036] S20, the test piece is stimulated multiple times, and the response data generation system collects response data of the test piece under different stimulations in real time.

[0037] It should be understood that S20 is used to comprehensively obtain dynamic performance information of the test piece under various excitation conditions.

[0038] S30, analyze the modal consistency of the test piece through the response data.

[0039] Furthermore, in a preferred embodiment, analyzing the modal consistency of the test piece using the response data in S30 includes: S31, obtaining sample modal data.

[0040] It should be understood that the modal parameters of different nozzle models are obtained from the test. A specific example is obtaining the natural frequencies of the nozzle models XXX-A-1, XXX-B-1, and XXX-C-1. It should be noted that each model has 30 products, and the test results for each product show the average natural frequency.

[0041] See the XXX-A-1 model nozzle natural frequency test data, the XXX-B-1 model nozzle natural frequency test data, and the XXX-C-1 model nozzle natural frequency test data, which are shown in Table 1, Table 2, and Table 3, respectively.

[0042] Table 1

[0043] Table 2

[0044] Table 3

[0045] S32, sample response data corresponding to the test sample modal data.

[0046] It should be understood that in order to fully understand the modal characteristics of the nozzle, representative sample response data is collected. Multiple samples are selected from nozzles manufactured from different batches and different production processes for testing. During the test, the response sensor in the response data generation system is used. The response sensor includes one or more of an acceleration sensor, an optical fiber sensor, and a strain gauge sensor. Sample response data is collected under multiple excitation conditions, including any one or more information of acceleration, displacement, stress distribution, and small strain changes. It should be noted that as many sample response data as possible are collected. In this way, the acquired data covers the response data of the nozzle in different states, which can more comprehensively reflect the diversity of the nozzle modal characteristics.

[0047] Specifically, acceleration is used as sample response data. During the test, the response sensor is an accelerometer, which collects and calculates the average time-domain amplitude value of acceleration for each product. The response data is collected by the accelerometer and transmitted to the consistency analysis system via the data acquisition system. See Tables 4, 5, and 6 for the typical acceleration response values ​​of the XXX-A-1 nozzle natural frequency test, the typical acceleration response values ​​of the XXX-B-1 nozzle natural frequency test, and the typical acceleration response values ​​of the XXX-C-1 nozzle natural frequency test, respectively.

[0048] Table 4

[0049] Table 5

[0050] Table 6

[0051] S33, using the sample response data and the sample modal data to train a modal data neural network model, wherein the modal data neural network model is used to train the sample modal data according to the input sample response data.

[0052] It should be understood that a modal data neural network model, such as a convolutional neural network (CNN) or a recurrent neural network (RNN), is constructed. The previously acquired sample response data is used as input, and the corresponding sample modal data is used as the training target to train the model. During the training process, the model will automatically learn the mapping relationship between the sample response data and the sample modal data. As the training progresses, the model continuously adjusts its own parameters to improve the ability to extract and predict modal features. After training with a large amount of data, the model can gradually and accurately output the corresponding sample modal data based on the input sample response data, providing reliable model support for the subsequent modal analysis of the test nozzle.

[0053] S34, obtaining test nozzle response data.

[0054] It should be understood that when testing the nozzle under test, the same response data generation system and excitation method used to obtain the sample response data should be used to collect the test nozzle response data under the same or similar test conditions. Ensure that the collection process for the test nozzle response data is consistent with the collection process for the sample response data to ensure the accuracy and comparability of subsequent analysis results.

[0055] S35, inputting the test nozzle response data into the modal data neural network model to generate test nozzle modal data.

[0056] It should be understood that the acquired test nozzle response data is input into a trained modal data neural network model. Based on the previously learned mapping relationships, the model processes and analyzes the test nozzle response data and outputs the corresponding test nozzle modal data, including parameters such as natural frequency and mode shape. This test nozzle modal data is compared with the modal data of a standard sample. If the deviation is within the allowable range, the test nozzle is deemed to be of qualified quality and has good modal consistency. If the deviation exceeds the allowable range, it indicates that the test nozzle may have structural defects or quality issues, requiring further analysis and treatment.

[0057] The above description and the accompanying drawings sufficiently illustrate the embodiments of the present disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless expressly required, individual components and functions are optional, and the order of operations may vary. Portions and features of some embodiments may be included in or replace portions and features of other embodiments. Moreover, the terms used in the present invention are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, the singular forms "a", "an" and "the" are intended to also include the plural forms unless the context clearly indicates otherwise. Similarly, the term "and / or" as used in the present invention means any and all possible combinations of one or more associated listings. In addition, when used in the present invention, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, an element defined by the sentence "comprising a..." does not exclude the presence of other identical elements in the process, method or module that includes the element. In the embodiments of the present disclosure, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the embodiments can be referenced to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be referenced to the description of the method part.

[0058] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present disclosure can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The skilled person may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure.

[0059] Each box in a flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for realizing a specified logical function. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flow charts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. Each box in the block diagram and / or flow chart, and the combination of boxes in the block diagram and / or flow chart, can be implemented with a combination of dedicated hardware and computer instructions.

Claims

1. A nozzle modal consistency detection system, characterized in that: include: A test system for simulating the free state of the nozzle, comprising a ceiling, a suspension system, and a nozzle. The suspension system comprises a plurality of ropes and an intelligently adjustable suspension device. The intelligently adjustable suspension device integrates a micromotor, a displacement sensor, and a controller. The displacement sensor is used to monitor changes in the nozzle's posture. The controller controls the micromotor to adjust the length and tension of the suspension rope based on the monitoring results of the displacement sensor. an excitation device, used for applying external excitation to the nozzle to obtain a dynamic response; A response data generation system includes a response sensor and a data acquisition system. The response sensor is used to measure the stress distribution of a specific part of the nozzle. The data acquisition system is used to collect data from the response sensor and transmit it to the consistency analysis system. A consistency analysis system is used to analyze the consistency of the nozzle by responding to sensor data.

2. The nozzle modal consistency detection system according to claim 1, characterized in that: The response sensor is set at the stress concentration area or the structural connection position.

3. The nozzle modal consistency detection system according to claim 1, characterized in that: The excitation device includes any one or more of an excitation hammer assembly, an electromagnetic vibrator, an electric vibration table and a hydraulic vibrator.

4. The nozzle modal consistency detection system according to claim 3, characterized in that: The excitation hammer assembly includes an excitation hammer and a dynamometer.

5. The nozzle modal consistency detection system according to claim 1, characterized in that: The ropes include a suspension rope and a balance rope.

6. The nozzle modal consistency detection system according to claim 1, characterized in that: The test system also includes: a protective cotton cloth laid on the ground.

7. The nozzle modal consistency detection system according to claim 1, characterized in that: The total mass of additional connectors installed on the nozzle cannot exceed 2% of the nozzle mass.

8. A nozzle modal consistency detection method, characterized in that: The method applied to the nozzle modal consistency detection system as claimed in claims 1 to 7 comprises: S10, the rope suspends the test piece below the ceiling through the intelligent adjustable suspension device, and the intelligent adjustable suspension device is adjusted to put the test piece in a free state; S20, the test piece is stimulated multiple times, and the response data generation system collects response data of the test piece under different stimulations in real time; S30, analyze the modal consistency of the test piece through the response data.

9. The nozzle modal consistency detection method according to claim 8, characterized in that: Analyze the modal consistency of the test specimen using response data, including: S31, obtaining sample modal data; S32, sample response data corresponding to the test sample modal data; S33, using the sample response data and the sample modal data to train a modal data neural network model, wherein the modal data neural network model is used to train the sample modal data based on the input sample response data; S34, obtaining test nozzle response data; S35, inputting the test nozzle response data into the modal data neural network model to generate test nozzle modal data.

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