Rocket engine nine-engine parallel redundancy control method and device and storage medium

Abstract

The invention relates to the technical field of rocket launching, in particular to a nine-engine parallel redundancy control method and device for rocket engines and a storage medium. The method comprises the following steps: acquiring real-time operation data of each engine, and judging whether abnormity occurs or not according to the real-time operation data of each engine; if no abnormity occurs, flight state data and real-time operation data of the engines are obtained, and thrust data of all the engines are adjusted in a self-adaptive mode through a mosquito algorithm; if abnormity occurs, a fault engine is positioned in combination with a mosquito algorithm, after the fault engine is positioned, an isolation mechanism is started, the fault engine is removed from thrust output calculation, then thrust distribution is automatically adjusted in the remaining engines through the mosquito algorithm, and thrust is reconfigured to the engines working normally. The flight balance and reliability of the rocket can be improved.

Description

Technical Field

[0001] The present invention relates to the field of rocket launching technology, and in particular to a method, device and storage medium for parallel redundant control of nine rocket engines. Background Art

[0002] During rocket launch and flight, engine failure will directly affect the thrust and flight trajectory of the rocket, which may lead to mission termination or deviation from the established orbit. In traditional rocket multi-engine parallel control, the failure of a single engine may lead to reduced system redundancy and even affect the overall propulsion efficiency. Therefore, an effective redundant control method is needed to ensure that the target thrust can still be achieved in the event of a failure. Therefore, the nine-engine parallel rocket engine layout has high system complexity and diverse failure modes. By connecting nine engines to work in parallel and utilizing the thrust adjustment and operating status feedback mechanism of each engine, the redundant control method can detect and judge the working status of each engine in real time, and adopt effective failure isolation and redundant allocation strategies to ensure that when one or more engines fail, the remaining engines can automatically adjust the thrust output according to the fault type, thereby balancing the thrust loss and maintaining flight stability. However, the existing redundant control methods have the following shortcomings:

[0003] 1. Insufficient fault tolerance: When a single engine fails, the traditional parallel control system is often unable to effectively adjust the thrust of the remaining engines, resulting in insufficient system thrust or flight trajectory deviation. The lack of an effective redundant control mechanism makes the overall fault tolerance of the multi-engine parallel system low, increasing the risk of mission failure;

[0004] 2. Fault detection delay: Existing technologies have response delays in fault detection, especially in a complex environment with multiple engines, where it is difficult to monitor and determine the source of the fault in real time. This delay may cause the system to be unable to isolate and handle the fault in a timely manner after the fault occurs, thus affecting the overall performance;

[0005] 3. Low efficiency of redundant configuration: Most parallel engine systems rely only on fixed preset redundancy strategies, which make it difficult to dynamically adjust the thrust output of each engine to adapt to failure conditions. As a result, the system is inefficient in dealing with different failure modes and fails to fully utilize the performance of the remaining rocket engines to compensate for the thrust loss caused by the failure;

[0006] 4. System complexity and high resource consumption: In traditional redundant control, additional hardware and control logic are usually required to support coordination and redundant operation between engines. This increases the complexity and resource consumption of the system, such as data transmission bandwidth, processor load and power consumption, further affecting the overall stability and efficiency of the rocket propulsion system. Summary of the invention

[0007] In order to solve the above technical problems, the present invention proposes a rocket engine nine-engine parallel redundant control method to improve the reliability and fault tolerance of the system and improve the overall stability and efficiency of the rocket propulsion system.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: a rocket engine nine-engine parallel redundant control method, comprising the following steps:

[0009] Step 1: Obtain the real-time operating data of each engine, and determine whether an abnormality occurs according to the real-time operating data of each engine; if no abnormality occurs, proceed to step 2; if an abnormality occurs, proceed to step 3;

[0010] Step 2: Obtain flight status data and real-time engine operation data, and use the mosquito algorithm to adaptively adjust the thrust data of each engine;

[0011] Step 3: Locate the faulty engine using the Mosquito Algorithm. After locating the faulty engine, start the isolation mechanism to remove the faulty engine from the thrust output calculation. Then use the Mosquito Algorithm to automatically adjust the thrust distribution among the remaining engines and reallocate the thrust to the normally working engines to maintain the overall thrust balance and redundancy compensation.

[0012] Step 4: Return to step 1 and repeat steps 1 to 3.

[0013] In step 1, whether an abnormality occurs is determined based on the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

[0014] In step 1, the real-time operation data of each engine is obtained through the control center, and the fault detection module is used to determine whether an abnormality occurs.

[0015] In step 3, the control center runs the mosquito algorithm to automatically adjust the thrust distribution in the remaining engines.

[0016] In step 2, the flight status data and the real-time operation data of the engine are obtained through the control center, and the thrust data of each engine is adaptively adjusted using the mosquito algorithm.

[0017] The method for parallel redundant control of nine rocket engines further comprises the following steps:

[0018] Step 0: Establish a condition monitoring system for nine engines.

[0019] In step 0, the state monitoring system includes a thrust chamber pressure sensor, a temperature sensor, a vibration sensor, and a rotation speed sensor, which are respectively used to detect the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

[0020] In addition, the present invention also provides a rocket engine nine-engine parallel redundant control device, comprising: a processor and a memory communicatively connected to the processor;

[0021] The memory stores computer-executable instructions;

[0022] The processor executes the computer execution instructions stored in the memory to implement the method for parallel redundant control of nine rocket engines.

[0023] The nine-engine parallel redundant control device for rocket engines also includes a status monitoring system, which is used to detect the real-time thrust chamber air pressure, temperature, vibration, and speed data of each engine.

[0024] In addition, the present invention also provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by a processor, they are used to implement the nine-engine parallel redundant control method of a rocket engine.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. Higher fault tolerance and mission reliability: The present invention utilizes the adaptability and fault detection capabilities of the Mosquito Algorithm to enable the rocket system to quickly isolate faults and redistribute thrust in the event of single or multiple engine failures, significantly improving the fault tolerance of the rocket system and the reliability of the overall mission.

[0027] 2. Real-time dynamic thrust adjustment: Traditional redundant control mostly relies on preset fixed redundant paths or simple thrust allocation strategies. The present invention simulates the adaptive optimization behavior of mosquito groups through the mosquito algorithm, dynamically allocates thrust according to real-time conditions, achieves more efficient thrust compensation and balance, and effectively improves the thrust utilization efficiency in the event of engine failure.

[0028] 3. Rapid response and precise control: After detecting a fault, the present invention can quickly identify and take corresponding isolation measures by utilizing the rapid response characteristics of the mosquito algorithm. Subsequent dynamic thrust distribution optimization enables the rocket system to accurately control the output thrust of each engine, ensuring balance and control accuracy during flight. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A schematic flow chart of a method for parallel redundant control of nine rocket engines provided in the first embodiment of the present invention;

[0030] Figure 2 A schematic diagram of the structure of a rocket engine nine-engine parallel redundant control device provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0032] Embodiment 1

[0033] The first embodiment of the present invention provides a method for parallel redundant control of nine rocket engines, which uses the Mosquito Algorithm to achieve intelligent redundant control. By simulating the behavior strategy of mosquitoes when searching for targets, with the characteristics of strong adaptability and dynamic adjustment, it helps the rocket power system to achieve rapid response and precise control in complex engine failure modes. It has the following characteristics:

[0034] Distributed perception: Mosquito relies on a distributed perception network to find its target and quickly locates it through signal feedback from the surrounding environment. Based on this feature, the mosquito algorithm control system of the present invention will continuously monitor the status of each engine, share fault information in the control network, and achieve rapid judgment and isolation of the fault location. In this way, even if multiple engines fail, the system can identify and isolate them in time to prevent the spread of the fault.

[0035] Path optimization and group collaboration: The mosquito swarm will optimize the path when searching for the target and use group collaboration to improve the success rate of target tracking. Based on this feature, in the control process of nine engines in parallel, the mosquito algorithm of this embodiment coordinates the thrust output of each engine by simulating group collaboration, avoiding the limitations of a fixed path. The algorithm can flexibly adjust the thrust distribution of each engine according to the fault situation to achieve the balance and optimization of the overall thrust of the system.

[0036] Fault tolerance and adaptive optimization: The Mosquito Algorithm has strong fault tolerance. Even when encountering multiple interference sources or complex environments, it can adjust the tracking strategy through adaptive optimization. Similarly, in rocket engine redundant control, the fault tolerance of the Mosquito Algorithm can help the system automatically adjust the thrust distribution when dealing with multiple engine failures, maximize the thrust output of the remaining engines, and ensure that the entire system still has sufficient thrust redundancy and stability.

[0037] Specifically, Figure 1 As shown, the first embodiment of the present invention provides a method for parallel redundant control of nine rocket engines, comprising the following steps:

[0038] Step 0: Establish a condition monitoring system for nine engines.

[0039] In step 0, the state monitoring system includes a thrust chamber pressure sensor, a temperature sensor, a vibration sensor, and a rotation speed sensor, which are respectively used to detect the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

[0040] In this embodiment, a status monitoring system for nine engines is established to transmit the operating data of each engine (thrust chamber air pressure, temperature, vibration, and speed) to the control center. This distributed sensing network simulates the mosquito's perception mechanism of the odor source, collects and updates the engine status in real time, and provides basic data for subsequent thrust adjustment.

[0041] Step 1: Obtain the real-time operating data of each engine, and determine whether an abnormality occurs based on the real-time operating data of each engine. If an abnormality occurs, proceed to step 3; if no abnormality occurs, proceed directly to step 2.

[0042] In this embodiment, the sensing network formed by the state monitoring system continuously monitors the engine operating status. Once an abnormal signal (such as thrust drop or temperature abnormality) is detected, the control center will immediately start the fault detection module and quickly locate the faulty engine in combination with the sensitive response mechanism of the mosquito algorithm. This process is similar to a mosquito accurately tracking the source of an odor, ensuring that the fault location is quickly determined and prepared for subsequent isolation and compensation.

[0043] Specifically, in step 1, it is determined whether an abnormality occurs based on the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

[0044] Furthermore, in step 1, the real-time operating data of each engine is obtained through the control center, and the fault detection module is used to determine whether an abnormality occurs.

[0045] Step 2: Obtain flight status data, real-time engine operation data, and mission requirements, and use the Mosquito Algorithm to adaptively adjust the thrust data of each engine.

[0046] Specifically, in step 2, the flight status data and the real-time operation data of the engine are obtained through the control center, and the thrust data of each engine is adaptively adjusted using the mosquito algorithm.

[0047] Step 3: Use the Mosquito Algorithm to locate the faulty engine. After locating the faulty engine, start the isolation mechanism and remove the faulty engine from the thrust output calculation. Then use the Mosquito Algorithm to automatically adjust the thrust distribution among the remaining engines and reallocate the thrust to the normally working engines to maintain the overall thrust balance and redundancy compensation.

[0048] Specifically, in step 3, the control center runs the mosquito algorithm to automatically adjust the thrust distribution in the remaining engines.

[0049] In this embodiment, after confirming the fault location, the system control center activates the isolation mechanism to remove the faulty engine from the thrust output calculation to prevent the fault from affecting other parts of the system. Then, the mosquito algorithm simulates the behavior of mosquito group collaboration, automatically adjusts the thrust distribution among the remaining engines, and reconfigures the thrust to the normally working engines to maintain the overall thrust balance and redundancy compensation.

[0050] In this embodiment, the mosquito algorithm can adaptively reallocate the thrust of each engine based on the fault status. Specifically, the ant algorithm dynamically adjusts the thrust of each normal engine according to the current flight status, mission requirements and real-time engine operation data to compensate for the thrust gap caused by the fault, so as to ensure the optimal path selection for tracking the target, achieve efficient redistribution of thrust and optimize reconstruction of the thrust path.

[0051] Step 4: Return to step 1 and repeat steps 1 to 3.

[0052] The control method in this embodiment has real-time feedback and adaptive adjustment functions. By continuously monitoring the flight status and engine operation, and according to changes in the environment and fault status, the adaptive characteristics of the mosquito algorithm are used to adjust the thrust distribution in real time. If a new fault occurs or the environmental demand changes, the algorithm will respond quickly and re-optimize the thrust configuration to ensure the continuous and stable operation of the system.

[0053] The feasibility of the present invention has been proved through a series of simulation verifications. The following is part of the implementation source code:

[0054]

[0055]

[0056]

[0057] isolate_and_reassign(engines,failures)

[0058] #Dynamic thrust optimization

[0059] optimize_thrust(engines)

[0060] #Real-time feedback status

[0061] active_thrust=sum(engine.thrust for engine in engines ifengine.status=="active")

[0062] print(f"Current thrust total:{active_thrust}")

[0063] for engine in engines:

[0064] print(f"Engine {engine.id} status: {engine.status}, thrust: {engine.thrust}")

[0065] #Simulate random failures

[0066] def simulate_random_failures(engines,fail_rate=0.2):

[0067] for engine in engines:

[0068] if np.random.rand() <fail_rate:

[0069] engine.fail()

[0070] #Test control system

[0071] simulate_random_failures(engines)#Simulate random failures

[0072] control_loop(engines)#Execute control loop

[0073] Code Description

[0074] Engine class: Represents the status of a single engine, including thrust value and fault status.

[0075] detect_failure function: Checks the thrust status of each engine, and marks the engine below the set threshold as "failure".

[0076] isolate_and_reassign function: Isolate the faulty engine and redistribute the thrust of the remaining engines to maintain the balance of system thrust.

[0077] optimize_thrust function: uses the dynamic characteristics of the mosquito algorithm to optimize the thrust of the normal engine.

[0078] control_loop function: simulates the main control loop and combines fault detection, isolation and thrust optimization to achieve redundant control of the engine.

[0079] simulate_random_failures function: Randomly simulate engine failures to test the fault tolerance of the control algorithm.

[0080] In summary, this embodiment provides a method for parallel redundant control of nine rocket engines, which implements parallel redundant control of nine rocket engines through the mosquito algorithm to improve the reliability and fault tolerance of the system. Its features include the following aspects:

[0081] 1. Intelligent redundant allocation and dynamic thrust adjustment: After a fault is detected, the present invention can realize intelligent redundant allocation of thrust through the mosquito algorithm, automatically adjust the thrust output of the remaining engines, and ensure the overall thrust balance.

[0082] 2. Distributed perception and collaboration mechanism: The distributed perception mechanism of the Mosquito Algorithm can achieve collaborative control by sharing the operating data of each engine. In the present invention, the nine engines back up each other and coordinate to complete thrust adjustment, effectively avoiding thrust instability caused by single point failure.

[0083] 3. Thrust output path optimization and adaptive redundant control: The Mosquito Algorithm can simulate the path optimization characteristics of mosquitoes in complex environments, optimize the thrust output path, and ensure that the engine can still maintain the system's thrust stability and flight balance under complex fault modes.

[0084] 4. Efficient redundancy control and resource utilization: Compared with traditional redundant control methods, the present invention achieves efficient thrust redundancy and resource utilization through the adaptive allocation and dynamic optimization mechanism of the mosquito algorithm without increasing the system complexity and hardware resources.

[0085] Embodiment 2

[0086] like Figure 2 As shown, the second embodiment of the present invention provides a rocket engine nine-engine parallel redundant control device, including: a processor and a memory connected to the processor in communication;

[0087] The memory stores computer-executable instructions;

[0088] The processor executes the computer execution instructions stored in the memory to implement a rocket engine nine-engine parallel redundant control method as described in Example 1.

[0089] Furthermore, a rocket engine nine-engine parallel redundant control device of this embodiment also includes a state monitoring system, which includes a thrust chamber air pressure sensor, a temperature sensor, a vibration sensor, and a speed sensor. The state monitoring system is used to detect real-time thrust chamber air pressure, temperature, vibration, and speed data of each engine.

[0090] Embodiment 3

[0091] Embodiment 3 of the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement a rocket engine nine-engine parallel redundant control method as described in Embodiment 1.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for parallel redundant control of nine rocket engines, characterized in that: The following steps are involved: Step 1: Obtain the real-time operating data of each engine, and determine whether an abnormality occurs based on the real-time operating data of each engine; If no abnormality occurs, proceed to step 2; If an exception occurs, go to step 3; Step 2: Obtain flight status data and real-time engine operation data, and use the mosquito algorithm to adaptively adjust the thrust data of each engine; Step 3: Locate the faulty engine using the Mosquito Algorithm. After locating the faulty engine, start the isolation mechanism to remove the faulty engine from the thrust output calculation. Then use the Mosquito Algorithm to automatically adjust the thrust distribution among the remaining engines and reallocate the thrust to the normally working engines to maintain the overall thrust balance and redundancy compensation. Step 4: Return to step 1 and repeat steps 1 to 3.

2. A rocket engine nine-engine parallel redundant control method according to claim 1, characterized in that: In step 1, whether an abnormality occurs is determined based on the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

3. The method for parallel redundant control of nine rocket engines according to claim 1, characterized in that: In step 1, the real-time operation data of each engine is obtained through the control center, and the fault detection module is used to determine whether an abnormality occurs.

4. The method for parallel redundant control of nine rocket engines according to claim 1, characterized in that: In step 3, the control center runs the mosquito algorithm to automatically adjust the thrust distribution in the remaining engines.

5. The method for parallel redundant control of nine rocket engines according to claim 1, characterized in that: In step 2, the flight status data and the real-time operation data of the engine are obtained through the control center, and the thrust data of each engine is adaptively adjusted using the mosquito algorithm.

6. A rocket engine nine-engine parallel redundant control method according to claim 1, characterized in that: The following steps are also included: Step 0: Establish a condition monitoring system for nine engines.

7. A rocket engine nine-engine parallel redundant control method according to claim 6, characterized in that: In step 0, the state monitoring system includes a thrust chamber pressure sensor, a temperature sensor, a vibration sensor, and a rotation speed sensor, which are respectively used to detect the thrust chamber pressure, temperature, vibration, and rotation speed of each engine.

8. A rocket engine nine-engine parallel redundant control device, characterized in that: include: A processor and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement a rocket engine nine-engine parallel redundant control method as described in any one of claims 1 to 7.

9. The rocket engine nine-engine parallel redundant control device according to claim 8, characterized in that: It also includes a status monitoring system, which is used to detect the real-time thrust chamber air pressure, temperature, vibration, and rotation speed data of each engine.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement a rocket engine nine-engine parallel redundant control method as described in any one of claims 1 to 7.

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