Rocket engine test stand measurement system online calibration system and method thereof

Abstract

The present application relates to the technical field of liquid rocket engine testing, and discloses a rocket engine test stand measurement system online calibration system and method thereof, the rocket engine test stand measurement system online calibration system comprises a requirement configuration module, an environment construction module, a calibration processing module and a data processing module; the requirement configuration module is used for identifying and counting sensor equipment parameters and test conditions according to test requirements, and generating corresponding first and second configuration files; the environment construction module is used for constructing a test environment benchmark according to the second configuration file; the calibration processing module is used for setting sampling parameters according to the first configuration file, online comparing the calibration sensor with the field sensor based on the sampling parameters, and generating calibration comparison data; and the data processing module is used for establishing an error correction model according to the calibration comparison data and global environment parameters. The present application can improve the calibration accuracy and efficiency of the test stand measurement system.

Description

Technical Field

[0001] This invention relates to the field of liquid rocket engine testing technology, and in particular to an online calibration system and method for a rocket engine test bench measurement system. Background Technology

[0002] The liquid rocket engine test stand is a core infrastructure for engine development, performance verification, and reliability testing. The accuracy of its measurement system directly determines the validity of the test data, which in turn affects engine design optimization, performance evaluation, and safety assurance. During liquid rocket engine testing, the measurement system needs to collect multiple parameters in real time, including pressure, temperature, flow rate, thrust, and rotational speed. This involves a wide variety of sensors with diverse measurement ranges, and the test environment is harsh, including complex conditions such as high and low temperatures, strong vibrations, and strong electromagnetic interference.

[0003] Currently, the calibration of measurement sensors on liquid rocket engine test stands mainly adopts an offline disassembly and calibration mode. This involves removing the sensors from the test stand after shutdown, sending them to a metrology laboratory for calibration, and then reinstalling them. This offline disassembly and calibration mode has the following problems: offline calibration is a calibration of the individual sensor, not a full-link calibration from the sensor, safety barrier, acquisition equipment to signal processing and physical quantity reconstruction, leading to inconsistencies between calibration results and measurement accuracy under actual operating conditions; additional errors such as installation stress and alignment deviations are introduced during disassembly and reinstallation; offline calibration requires interruption of the normal test stand testing process, resulting in low efficiency and failing to meet the demands of fast-paced, multi-batch engine testing; different rocket engine models have significant differences in test stand measurement point layout, parameter range, and operating condition requirements, and existing calibration systems have poor universality and cannot adapt to differentiated calibration needs, requiring separate calibration for different test stands, increasing development costs and time.

[0004] In addition, existing calibration systems are mostly single-parameter calibrations, which cannot achieve multi-parameter integrated calibration. Furthermore, the calibration strategies are fixed and cannot be customized according to test conditions and sensor types, making it difficult to meet the online calibration requirements of the entire liquid rocket engine test process.

[0005] Therefore, there is an urgent need to propose an online calibration system and method for rocket engine test stand measurement systems to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to propose an online calibration system and method for a rocket engine test stand measurement system, which can improve the calibration accuracy and efficiency of the test stand measurement system.

[0007] To address the aforementioned technical problems, this invention provides an online calibration system for a rocket engine test stand measurement system, comprising a requirement configuration module, an environment construction module, a calibration processing module, and a data processing module. The requirement configuration module is used to identify and statistically analyze the sensor equipment parameters and test conditions according to the test requirements, and generate corresponding first configuration file and second configuration file respectively. The environment building module is used to build a test environment benchmark based on the second configuration file; The calibration processing module is used to set sampling parameters according to the first configuration file, and, without interrupting the normal measurement link of the test bench, to compare the calibration sensor and the field sensor online based on the sampling parameters under the test environment benchmark, and generate calibration comparison data. The data processing module is used to establish an error correction model based on the calibration comparison data and global environmental parameters, correct the error of the measurement data of the field sensors based on the error correction model, and adaptively reconstruct the physical quantities based on the corrected measurement data and the test conditions.

[0008] Furthermore, the sensor device parameters include at least one of the following: the sensor device used, the measurement range, the accuracy, the response time, the frequency characteristics, and the restoration method.

[0009] Furthermore, the environment construction module includes a multi-condition simulation unit, a synchronous control unit, and an online calibration dedicated process unit; The multi-condition simulation unit is used to simulate the entire test run process conditions according to the second configuration file and generate control commands. The synchronization control unit is used to construct the test environment benchmark according to the control command; The online calibration process unit is used to connect the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner, so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark.

[0010] Furthermore, the calibration processing module includes a sensor calibration comparison unit and a synchronous acquisition unit; The synchronous acquisition unit is used to set sampling parameters according to the first configuration file, and synchronously acquire measurement data of the field sensor and the calibration sensor in real time based on the sampling parameters; The sensor calibration comparison unit is used to compare the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark without interrupting the normal measurement link of the test bench, and generate the calibration comparison data.

[0011] Furthermore, the data processing module includes an error correction unit and an algorithm unit; The error correction unit is used to establish the error correction model based on the calibration comparison data and global environmental parameters, and to correct the error in the measurement data of the field sensor based on the error correction model. The algorithm unit is used to adaptively reconstruct physical quantities based on the corrected measurement data and the test conditions.

[0012] Furthermore, the global environmental parameters include at least one of thermal radiation, structural stress, vibration coupling, humidity and heat, and low air pressure.

[0013] Furthermore, this invention also proposes an online calibration method for a rocket engine test stand measurement system, using the online calibration system for a rocket engine test stand measurement system as described above, specifically including the following: Based on the test requirements, the sensor equipment parameters and test conditions are identified and statistically analyzed, and corresponding first and second configuration files are generated respectively. Build a test environment baseline based on the second configuration file; The sampling parameters are set according to the first configuration file, and without interrupting the normal measurement link of the test bench, the calibration sensor and the field sensor are compared online based on the sampling parameters under the test environment benchmark to generate calibration comparison data. An error correction model is established based on the calibration comparison data and global environmental parameters. The measurement data of the field sensors are then corrected based on the error correction model. The physical quantities are then adaptively reconstructed based on the corrected measurement data and the test conditions.

[0014] Furthermore, the steps for constructing the test environment benchmark specifically include: simulating the entire test run process according to the second configuration file and generating control commands; constructing the test environment benchmark according to the control commands; and connecting the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner, so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark.

[0015] Furthermore, the step of generating the calibration comparison data specifically includes: setting sampling parameters according to the first configuration file, and synchronously collecting measurement data of the field sensor and the calibration sensor in real time based on the sampling parameters; and, without interrupting the normal measurement link of the test bench, comparing the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark to generate the calibration comparison data.

[0016] Furthermore, an error correction model is established based on the calibration comparison data and global environmental parameters. Based on this model, the measurement data from the field sensors are corrected for errors. The physical quantities are then adaptively reconstructed based on the corrected measurement data and the test conditions, specifically including: The error correction model is established based on the calibration comparison data and global environmental parameters. Based on the error correction model, the zero drift, gain offset, nonlinearity, hysteresis and bidirectional stroke deviation in the field sensor measurement data are dynamically corrected in real time. The physical quantities are adaptively reconstructed based on the corrected measurement data and the test conditions.

[0017] Through the above technical solution, the present invention has the following beneficial effects: The requirement configuration module generates a first configuration file and a second configuration file according to the test requirements. The environment construction module builds a test environment benchmark based on the second configuration file. The calibration processing module performs online comparison to generate calibration comparison data without interrupting the normal measurement link of the test bench. The data processing module establishes an error correction model to correct errors and adaptively reconstructs physical quantities. This enables online calibration without interrupting the normal measurement link of the test bench, avoiding the installation stress and alignment deviation introduced by offline disassembly and calibration, improving calibration efficiency and measurement accuracy, and adapting to the differentiated calibration requirements of different engine models.

[0018] Furthermore, the system employs a multi-condition simulation unit to simulate the entire test process, a synchronous control unit to construct a locally consistent test environment benchmark, and an online calibration process unit to connect to the calibration sensors via a non-intrusive bypass parallel connection, enabling the replication of the real test environment and achieving multi-parameter integrated calibration. A synchronous acquisition unit sets sampling parameters according to the first configuration file and synchronously acquires measurement data in real time, improving the synchronization and accuracy of data acquisition. An error correction unit establishes an error correction model based on global environmental parameters, enabling real-time dynamic correction of zero-point drift, gain offset, nonlinearity, hysteresis, and bidirectional stroke deviation, thus improving calibration accuracy under complex conditions. Finally, an algorithm unit adaptively reconstructs physical quantities, generating high-precision analytical solutions for the restored physical quantities across all measurement points, enhancing the reliability of physical quantity restoration. Attached Figure Description

[0019] Figure 1 This is a block diagram of an online calibration system for a rocket engine test stand measurement system according to an embodiment of the present invention; Figure 2 This is a schematic block diagram of the online calibration system of the rocket engine test stand measurement system in one embodiment of the present invention; Figure 3 This is a flowchart of an online calibration method for a rocket engine test stand measurement system according to an embodiment of the present invention. Detailed Implementation

[0020] Based on the teachings of this specification, those skilled in the art can form new technical solutions through cross-combination of different implementation methods without creating technical contradictions. Such variations should all be considered to fall within the protection scope of this invention.

[0021] The online calibration system and method for a rocket engine test stand measurement system according to the present invention will now be described in more detail with reference to the accompanying drawings, which illustrate preferred embodiments of the invention. It should be understood that those skilled in the art can modify the invention described herein while still achieving its advantageous effects. Therefore, the following description should be understood as being of general knowledge to those skilled in the art and is not intended to limit the invention.

[0022] The invention is described more specifically by way of example in the following paragraphs with reference to the accompanying drawings. The advantages and features of the invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the invention.

[0023] like Figures 1-2 As shown in the figure, this embodiment of the invention proposes an online calibration system for a rocket engine test stand measurement system, including a requirement configuration module, an environment construction module, a calibration processing module, and a data processing module.

[0024] Specifically, the requirement configuration module is used to identify and statistically analyze sensor equipment parameters and test conditions according to test requirements, and generate corresponding first and second configuration files respectively; the environment construction module is used to construct a test environment benchmark based on the second configuration file; the calibration processing module is used to set sampling parameters according to the first configuration file, and, without interrupting the normal measurement link of the test bench, to perform online comparison between the calibrated sensor and the field sensor based on the sampling parameters under the test environment benchmark, and generate calibration comparison data; the data processing module is used to establish an error correction model based on the calibration comparison data and global environmental parameters, to correct the error of the measurement data of the field sensor based on the error correction model, and to adaptively reconstruct physical quantities based on the corrected measurement data and the test conditions.

[0025] This embodiment transforms customer-customized requirements into executable configuration files and drives the entire calibration process, enabling flexible adaptation to test benches of different models and operating conditions. It completes in-situ online calibration without interrupting the normal measurement link of the test bench, avoiding additional errors such as installation stress and alignment deviation introduced by offline disassembly and calibration, and improving calibration accuracy and efficiency.

[0026] Preferably, the sensor device parameters include at least one of the following: the sensor device used, the measurement range, the accuracy, the response time, the frequency characteristics, and the restoration method. Those skilled in the art will understand that the sensor device parameters also include other embodiments besides those mentioned in this embodiment, and can be set according to actual needs. The requirement configuration module converts the above-identified and statistically analyzed sensor device parameters into a first configuration file, which is used for setting the sampling parameters of the subsequent synchronous acquisition unit and for customized calibration of the full-domain sensor.

[0027] In this embodiment, the environment construction module includes a multi-condition simulation unit, a synchronous control unit, and an online calibration dedicated process unit. Specifically, the multi-condition simulation unit is used to simulate the entire test run process according to the second configuration file and generate control commands; the synchronous control unit is used to construct the test environment benchmark according to the control commands; the online calibration process unit is used to connect the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner, so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark. This embodiment changes the traditional simple bidirectional stroke sensor calibration method through the multi-condition simulation unit, supporting comprehensive force and thermal environment calibration under steady-state, transient, extreme, and fault conditions; by dividing and constructing a locally consistent test environment benchmark through the synchronous control unit, the calibration sensor (e.g., a high-precision calibration sensor) can perform in-situ comparison with multiple similar field sensors under the same environmental conditions, eliminating system errors introduced by environmental inconsistencies; through the non-intrusive bypass parallel access method, multi-parameter synchronous online calibration is completed without interrupting the test run process, meeting the needs of multiple batches of fast-paced test runs.

[0028] Preferably, the full-process test run includes at least one of the following: cold adjustment, ignition, steady state, variable operating conditions, shutdown, water hammer impact, high and low temperature environment, and pulsating pressure. Those skilled in the art will understand that the full-process test run also includes other embodiments besides those mentioned in this embodiment, and can be set according to actual needs.

[0029] In this embodiment, the non-invasive bypass parallel access method adopted by the online calibration dedicated process unit includes: parallel connection of pressure tapping ports (three-way valves), with the pressure sensor and calibration pressure sensor in the domain measuring the same pressure source; simultaneous insertion of measuring probe and calibration probe at the temperature measurement point in the domain, measuring the same temperature source; bypass installation of a calibration flow meter; high-precision traceable reference source module synchronously outputting standard thrust value electrical signal according to a preset loading scheme, with the thrust sensor placed alongside the calibration force sensor; and the reference source module synchronously outputting standard rotational speed electrical signal according to a preset loading scheme, with the main rotational speed probe and calibration rotational speed sensor simultaneously measuring at least one of the same rotating shafts non-contactly. By using a bypass parallel access method customized for different parameters such as pressure, temperature, flow rate, thrust, and rotational speed, full-coverage online in-situ calibration of multi-parameter sensors can be achieved, ensuring that the calibration results truly reflect the sensor's performance under actual operating conditions. As those skilled in the art will know, the bypass parallel access method may also include other access methods besides those mentioned in this embodiment, which can be selected and set according to the actual measurement point type and process requirements.

[0030] In this embodiment, the calibration processing module includes a sensor calibration comparison unit and a synchronous acquisition unit. Specifically, the synchronous acquisition unit is used to set sampling parameters according to the first configuration file, and synchronously acquire measurement data of the field sensor and the calibration sensor in real time based on the sampling parameters; the sensor calibration comparison unit is used to compare the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark without interrupting the normal measurement link of the test bench, and generate the calibration comparison data.

[0031] Preferably, the synchronous acquisition unit employs a 24-bit AD synchronous acquisition card, and the sampling rate, filtering bandwidth, and triggering mode can be configured through the first configuration file. The synchronous acquisition unit uses BeiDou second pulse time synchronization to achieve time alignment of calibration data from multiple measurement points and across workstations, improving comparison accuracy. The combination of the 24-bit AD synchronous acquisition card and BeiDou second pulse time synchronization ensures that the calibration comparison data from multiple measurement points and multiple parameters maintain consistency in acquisition accuracy and time reference, providing a high-quality data foundation for the subsequent establishment of error correction models.

[0032] Preferably, the calibration sensor uses an ultra-high precision, high-sensitivity sensing core and a low-delay outer mold, maintaining ultra-high linearity, extremely low hysteresis, and minimal temperature drift under complex operating conditions. It is equipped with a highly stable signal conditioning and isolation unit, supporting weak signal conditioning, multi-stage highly stable filtering, and electrical isolation. It also features temperature and humidity compensation and EMC suppression modules to reduce the impact of temperature, humidity, and electromagnetic interference on calibration accuracy. By ensuring the ultra-high precision calibration sensor stably maintains high accuracy under complex operating conditions, the online comparison results possess authoritativeness and metrological traceability, providing a reliable benchmark reference for error correction of field sensors.

[0033] In this embodiment, the data processing module includes an error correction unit and an algorithm unit. Specifically, the error correction unit is used to establish the error correction model based on the calibration comparison data and global environmental parameters, and to correct the error in the measurement data of the field sensors based on the error correction model; the algorithm unit is used to adaptively reconstruct physical quantities based on the corrected measurement data and the test conditions.

[0034] Preferably, the error correction model employs multivariate coupling modeling for test bench thermal radiation, structural stress, vibration coupling, humid heat, and low-pressure conditions, and performs real-time dynamic correction of zero-point drift, gain offset, nonlinearity, hysteresis, and bidirectional stroke deviation in the field sensor measurement data. By establishing a multivariate coupled error model and dynamically correcting various error components in real time, the accuracy of measurement data under complex test environments can be effectively improved, minimizing the impact of the comprehensive mechanical and thermal environment on measurement accuracy.

[0035] Preferably, the global environmental parameters include at least one of thermal radiation, structural stress, vibration coupling, humid heat, and low air pressure.

[0036] In this embodiment, the physical quantity reconstruction method employed by the algorithm unit includes at least one of the following: the KB value method, the list method, the univariate polynomial equation method, and a multivariate decoupling correction algorithm based on the above methods. Through the flexible combination and adaptive selection of various analytical solution fitting methods, real-time generation of high-precision analytical solutions for physical quantities across all measurement points is achieved, ensuring the accuracy of the physical quantity reconstruction algorithm while meeting the differentiated reconstruction requirements of different parameter types. As those skilled in the art will know, the physical quantity reconstruction method may also include other fitting methods besides those mentioned in this embodiment, which can be selected and set according to the actual parameter characteristics and accuracy requirements.

[0037] In addition, such as Figure 3 As shown, this embodiment also proposes an online calibration method for a rocket engine test stand measurement system, using the online calibration system for the rocket engine test stand measurement system described above, specifically including the following steps: S1. Identify and statistically analyze the sensor equipment parameters and test conditions according to the test requirements, and generate the corresponding first configuration file and second configuration file respectively. S2. Build a test environment baseline based on the second configuration file; S3. Set the sampling parameters according to the first configuration file, and without interrupting the normal measurement link of the test bench, compare the calibration sensor and the field sensor online based on the sampling parameters under the test environment benchmark to generate calibration comparison data; S4. Establish an error correction model based on the calibration comparison data and global environmental parameters, and correct the error of the measurement data of the field sensors based on the error correction model; adaptively reconstruct the physical quantities based on the corrected measurement data and the test conditions.

[0038] In step S2, the construction step of the test environment benchmark specifically includes: simulating the entire test process conditions according to the second configuration file and generating control commands; constructing the test environment benchmark according to the control commands; and connecting the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark.

[0039] In step S3, the step of generating the calibration comparison data specifically includes: setting sampling parameters according to the first configuration file, and synchronously and in real time collecting measurement data of the field sensor and the calibration sensor based on the sampling parameters; and, without interrupting the normal measurement link of the test bench, comparing the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark to generate the calibration comparison data.

[0040] Step S4 specifically includes: establishing the error correction model based on the calibration comparison data and global environmental parameters; performing real-time dynamic correction on zero drift, gain offset, nonlinearity, hysteresis, and bidirectional stroke deviation in the field sensor measurement data based on the error correction model; and adaptively reconstructing physical quantities based on the corrected measurement data and the test conditions.

[0041] In this embodiment, the entire online calibration system operates in a closed loop through three stages: pre-calibration configuration, calibration environment construction and data acquisition, and post-calibration data processing. Each module works together to achieve end-to-end online calibration, as detailed below.

[0042] Phase 1: Pre-calibration Configuration. Upon receiving the user's test run request, the requirement configuration module identifies and statistically analyzes the range, accuracy, response time, frequency characteristics, and restoration methods of the sensor equipment used, generating a first configuration file for customized calibration of all sensors. Simultaneously, it identifies and statistically analyzes the test run conditions, generating a second configuration file, which is then passed to the environment construction module for inputting the force and thermal environment under specific operating conditions. This completes the standardized conversion of all configuration parameters required for calibration, laying the foundation for the orderly and coordinated operation of subsequent modules.

[0043] Phase Two: Environment Construction and Data Acquisition during Calibration. After receiving the second configuration file, the environment construction module serializes it into control commands for specific operating conditions and outputs them to the synchronous control unit. The creation of the test environment relies on the debugging operations in the pre-test process, i.e., the engine load has been installed and the gas, electrical, and hydraulic interfaces have been connected. After the fuel cooling, pressurization, and purging systems are started in sequence, the synchronous control unit completes the multi-condition environment simulation according to the control commands, divides and constructs multiple locally consistent test environment benchmarks, and controls the online calibration dedicated process unit to embed the calibration sensors into the locally consistent test environment benchmarks in a non-intrusive bypass parallel manner. The pressure measurement points employ parallel three-way connections at the pressure tapping ports, with the pressure sensor and calibration pressure sensor within the same domain measuring the same pressure source. Temperature measurement points simultaneously insert both a measuring probe and a calibration probe within the domain. Flow measurement points are bypassed by a calibration flow meter. Thrust measurement points utilize a reference source module that synchronously outputs a standard thrust value electrical signal according to a preset loading scheme, with the calibration force sensor positioned alongside the thrust sensor. Rotational speed measurement points utilize a reference source module that synchronously outputs a standard rotational speed electrical signal according to a preset loading scheme, with the main rotational speed probe and calibration rotational speed sensor simultaneously measuring the same rotating shaft non-contactly. The synchronous acquisition unit sets the sampling rate, range, filter bandwidth, and triggering mode according to the first configuration file, using BeiDou second pulse timing to achieve time alignment of calibration data from multiple measurement points and across workstations, accurately and synchronously acquiring measurement data from both the field sensors and the calibration sensor in real time. The sensor calibration comparison unit performs online comparison of the two measurement data under a test environment benchmark, generating calibration comparison data and completing the full-parameter online synchronous comparison acquisition of Phase Two.

[0044] Phase Three: Post-calibration Data Processing. After receiving calibration comparison data and global environmental parameters, the data processing module establishes a multivariate coupled error model to dynamically correct zero-point drift, gain offset, nonlinearity, hysteresis, and bidirectional stroke deviation in real time, improving effective calibration accuracy. The algorithm unit integrates the error correction results with real-time high-precision measurement results, employing KB value methods, listing methods, univariate polynomial equation methods, or multivariate decoupling correction algorithms to adaptively reconstruct all physical quantities in the field, providing high-precision analytical solutions for the restored physical quantities at all measurement points. After the restored analytical solutions are bound and solidified online, the online calibration-dedicated process unit is shut down and decoupled from the test bench via the synchronous control unit, completing the full-link calibration closed loop and laying the foundation for solidifying the physical quantity restoration method for subsequent test runs.

[0045] In summary, the online calibration system and method for a rocket engine test stand measurement system proposed in this invention have the following advantages: 1. Customized testing: The calibration module and calibration strategy can be customized according to the measurement point parameters, range and operating conditions of different rocket engine test. This solves the problems of poor universality and insufficient adaptability of traditional calibration systems, and reduces the development cost and cycle of calibration equipment for multiple test models.

[0046] 2. Online Calibration: Non-invasive online calibration avoids offline disassembly and calibration errors: Through a bypass parallel connection method, the sensor under test can be calibrated in situ without disassembling it or interrupting the normal measurement link of the test bench, thereby improving calibration efficiency and meeting the needs of multiple batches of test runs.

[0047] 3. End-to-end calibration: It realizes end-to-end calibration from sensors, safety barriers, acquisition equipment to signal processing and restoration methods, which improves the accuracy of physical quantity restoration algorithms.

[0048] 4. Multi-parameter integrated calibration: Simultaneous calibration of multiple parameters, fully automated process calibration, and real-time generation of analytical solutions for restored physical quantities, improving the efficiency of calibration and commissioning.

[0049] 5. Environmental simulation and influence factor correction: The integrated multi-condition simulation system can replicate the real test environment, achieve accurate calibration under complex conditions, and meet the stringent requirements of aerospace tests for measurement data; Real-time dynamic correction: Through the dynamic error real-time correction system, it provides analytical solutions for the physical quantities of the full measurement points with high precision.

[0050] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An online calibration system for a rocket engine test stand measurement system, characterized in that, It includes a requirements configuration module, an environment construction module, a calibration processing module, and a data processing module; The requirement configuration module is used to identify and statistically analyze the sensor equipment parameters and test conditions according to the test requirements, and generate corresponding first configuration file and second configuration file respectively. The environment building module is used to build a test environment benchmark based on the second configuration file; The calibration processing module is used to set sampling parameters according to the first configuration file, and, without interrupting the normal measurement link of the test bench, to compare the calibration sensor and the field sensor online based on the sampling parameters under the test environment benchmark, and generate calibration comparison data. The data processing module is used to establish an error correction model based on the calibration comparison data and global environmental parameters, correct the measurement data of the field sensors based on the error correction model, and adaptively reconstruct the physical quantities based on the corrected measurement data and the test conditions.

2. The online calibration system for the rocket engine test stand measurement system as described in claim 1, characterized in that, The sensor device parameters include at least one of the following: the sensor device used, the measurement range, the accuracy, the response time, the frequency characteristics, and the restoration method.

3. The online calibration system for the rocket engine test stand measurement system as described in claim 1, characterized in that, The environment construction module includes a multi-condition simulation unit, a synchronous control unit, and an online calibration dedicated process unit; The multi-condition simulation unit is used to simulate the entire test run process conditions according to the second configuration file and generate control commands. The synchronization control unit is used to construct the test environment benchmark according to the control command; The online calibration process unit is used to connect the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner, so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark.

4. The online calibration system for the rocket engine test stand measurement system as described in claim 3, characterized in that, The calibration processing module includes a sensor calibration comparison unit and a synchronous acquisition unit; The synchronous acquisition unit is used to set sampling parameters according to the first configuration file, and synchronously acquire measurement data of the field sensor and the calibration sensor in real time based on the sampling parameters; The sensor calibration comparison unit is used to compare the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark without interrupting the normal measurement link of the test bench, and generate the calibration comparison data.

5. The online calibration system for the rocket engine test stand measurement system as described in claim 1, characterized in that, The data processing module includes an error correction unit and an algorithm unit; The error correction unit is used to establish the error correction model based on the calibration comparison data and global environmental parameters, and to correct the error in the measurement data of the field sensor based on the error correction model. The algorithm unit is used to adaptively reconstruct physical quantities based on the corrected measurement data and the test conditions.

6. The online calibration system for the rocket engine test stand measurement system as described in claim 5, characterized in that, The global environmental parameters include at least one of thermal radiation, structural stress, vibration coupling, humidity and heat, and low air pressure.

7. An online calibration method for a rocket engine test stand measurement system, using the online calibration system for a rocket engine test stand measurement system as described in any one of claims 1-6, characterized in that, Specifically, it includes the following: Based on the test requirements, the sensor equipment parameters and test conditions are identified and statistically analyzed, and corresponding first and second configuration files are generated respectively. Build a test environment baseline based on the second configuration file; The sampling parameters are set according to the first configuration file, and without interrupting the normal measurement link of the test bench, the calibration sensor and the field sensor are compared online based on the sampling parameters under the test environment benchmark to generate calibration comparison data. An error correction model is established based on the calibration comparison data and global environmental parameters, and the measurement data of the field sensors are corrected based on the error correction model. The physical quantities are adaptively reconstructed based on the corrected measurement data and the test conditions.

8. The online calibration method for the rocket engine test stand measurement system as described in claim 7, characterized in that, The steps for constructing the test environment benchmark specifically include: simulating the entire test run process according to the second configuration file and generating control commands; constructing the test environment benchmark according to the control commands; and connecting the calibration sensor to the test bench measurement link in a non-intrusive bypass parallel manner, so that the calibration sensor and the field sensor are in a locally consistent test environment benchmark.

9. The online calibration method for the rocket engine test stand measurement system as described in claim 7, characterized in that, The steps for generating the calibration comparison data specifically include: setting sampling parameters according to the first configuration file, and synchronously collecting measurement data of the field sensor and the calibration sensor in real time based on the sampling parameters; and, without interrupting the normal measurement link of the test bench, comparing the measurement data of the field sensor and the measurement data of the calibration sensor online under the test environment benchmark to generate the calibration comparison data.

10. The online calibration method for the rocket engine test stand measurement system as described in claim 7, characterized in that, An error correction model is established based on the calibration comparison data and global environmental parameters, and the measurement data of the field sensors are corrected based on the error correction model. Based on the corrected measurement data and the aforementioned test conditions, the physical quantities are adaptively reconstructed, specifically including: The error correction model is established based on the calibration comparison data and global environmental parameters. Based on the error correction model, the zero drift, gain offset, nonlinearity, hysteresis and bidirectional stroke deviation in the field sensor measurement data are dynamically corrected in real time. The physical quantities are adaptively reconstructed based on the corrected measurement data and the test conditions.

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