A method for pressure detection health diagnosis of an electric propulsion system

Abstract

This invention provides a method for health diagnosis of pressure detection in electric propulsion systems, relating to the field of spacecraft electric propulsion system technology. This invention addresses the problem of the inability to quickly identify faults in multiple pressure sensors within an electric propulsion system. The invention employs a tiered health diagnosis approach for multiple pressure sensors, including: setting health indicators for multiple pressure sensors in the electric valve pressure reduction system of the electric propulsion system; using clustering / outlier diagnosis when the number of pressure sensors to be assessed is not less than three; and using exhaust cycle diagnosis when the number of pressure sensors to be assessed is two. This tiered health diagnosis method can quickly identify performance degradation or faults in pressure sensors, and unhealthy pressure sensors are no longer introduced into the pressure control system, effectively improving the reliability of the pressure acquisition source.

Description

Technical Field

[0001] This invention relates to the field of spacecraft electric propulsion system technology, and more specifically to a method for pressure detection and health diagnosis of electric propulsion systems. Background Technology

[0002] my country's first small body exploration mission will achieve near-Earth small body sample return and main-belt comet exploration, obtaining scientific results in stages and through multiple means. During the asteroid return transfer phase, a combination of chemical and electric propulsion will provide thrust for orbital maneuvers and attitude control; during the transfer phase to the main-belt comet, the electric propulsion system will provide thrust for orbital maneuvers.

[0003] As the probe cruises through deep space, its distance from the sun varies significantly, resulting in a substantial decrease in the power it can provide for electric propulsion. To utilize the probe's power resources more efficiently and adapt to these wide-ranging input power variations, a multi-operating-point electric propulsion system is designed, configuring multiple operating points. This means the electric propulsion system has the capability to ignite up to 20 power points within a range of 0.5 kW to 3 kW. Simultaneously, to provide the probe with greater velocity increments, the electric propulsion system uses high-pressure supercritical storage for xenon gas, typically at 15 MPa. Since electric thrusters generally require a micro-flow xenon supply, an electric valve pressure reduction system is incorporated to reduce the 15 MPa high-pressure gas source to 0.2–0.3 MPa before supplying it to the flow module for fine-tuned micro-flow control. This electric valve pressure reduction system generally uses an electronic valve and a pressure sensor for pressure control. The basic logic of this pressure control is as follows: when the pressure sensor reading is below the lower limit of the target pressure, the electronic valve opens to pressurize the pressure reduction system pipeline; when the pressure exceeds the upper limit of the target pressure, the electronic valve closes. This demonstrates the crucial role of pressure sensors in the control process; malfunction of a pressure sensor can lead to a decline in the performance or failure of the pressure reduction system. Electric propulsion systems utilize multiple pressure sensors for pressure determination to enhance the reliability of the pressure acquisition source. However, given the presence of multiple pressure sensors, the ability to quickly identify and resolve the issue of one or more sensors failing or degrading becomes critical for effective pressure determination.

[0004] Therefore, it is necessary to develop pressure detection and health diagnosis methods for electric propulsion systems to support the reliable and autonomous operation of electric propulsion systems. Summary of the Invention

[0005] This invention addresses the problem of the inability to quickly identify faults in multiple pressure sensors in electric propulsion systems, and proposes a method for pressure detection and health diagnosis of electric propulsion systems.

[0006] The technical solution adopted by the present invention to solve the above problems is as follows: This invention provides a method for health diagnosis of pressure detection in an electric propulsion system, which employs tiered health diagnosis for multiple pressure sensors, including: Health indicators are set for multiple pressure sensors in the electric valve pressure reduction system of the electric propulsion system; When the number of pressure sensors that need to be evaluated is not less than 3, cluster outlier diagnosis is used. When there are two pressure sensors that need to be evaluated, exhaust cycle diagnosis is used.

[0007] Furthermore, a health indicator of 0 indicates that the pressure sensor is healthy, and its pressure data is used for pressure regulation and health diagnosis; a health indicator of 1 indicates that the pressure sensor is unhealthy, and its pressure data is not used for pressure regulation and health diagnosis.

[0008] Furthermore, the cluster outlier diagnosis includes: Sort the pressure sensor values ​​according to health status; Calculate the average value Pavr for the data located in the middle region after sorting. Calculate the percentage deviation ηx between each health pressure sensor value and Pavr; If the deviation percentage value ηx exceeds the preset deviation diagnosis threshold m, the health status of the pressure sensor is set to unhealthy.

[0009] Furthermore, the deviation diagnosis threshold m ranges from 8% to 15%.

[0010] Furthermore, the exhaust cycle diagnostic method includes: a. Set one of the two health pressure sensors to healthy and the other to unhealthy in sequence; b. Switch the electric propulsion system to exhaust mode and obtain pressure change data through periodic pressurization and exhaust; c. During the pressurization and venting process, record the pressure high points Phi and Pli of each cycle, as well as the corresponding time points Thi and Tli. Calculate the venting time Tpi = (Phi - Pli) / (Tli - Thi) for each cycle. Take no less than 3 pressurization and venting cycles to obtain the average venting time Tpavr. d. Compare the average exhaust time Tpavr with the average exhaust time Tpavr1 of the assembly, and calculate the deviation percentage в. If the deviation percentage в exceeds the exhaust cycle deviation diagnosis threshold s, then the sensor currently set as healthy is judged to be unhealthy; otherwise, it is healthy. e. Set the electric propulsion system to standby mode; f. Switch the health indicators of the two sensors; g. Repeat steps b to e to determine if the other pressure sensor is healthy.

[0011] h. Based on the results of the exhaust cycle diagnosis, set the health status of the two pressure sensors.

[0012] Furthermore, the range of the exhaust cycle deviation diagnosis threshold s is 5% to 10%.

[0013] Furthermore, the electric propulsion system has n pressure sensors, where n is an odd number not less than 3.

[0014] The beneficial effects of this invention are: This invention designs a graded health diagnosis method for multiple pressure sensors in an electric propulsion system. This method can quickly identify performance degradation or malfunctions of pressure sensors and prevent unhealthy pressure sensors from being introduced into the pressure control system, thereby effectively improving the reliability of the pressure acquisition source.

[0015] This invention does not introduce additional hardware, has low implementation cost, and its diagnostic method is simple, reliable, and easy to implement; it can be carried out conveniently and quickly and has broad application prospects. Attached Figure Description

[0016] Figure 1 This is a flowchart of a method for pressure detection and health diagnosis of an electric propulsion system according to the present invention. Detailed Implementation like Figure 1 As shown, this embodiment provides a pressure detection and health diagnosis method for an electric propulsion system. It is mainly used for the health diagnosis of multiple pressure sensors in an electric valve pressure reduction system. A tiered health diagnosis method is employed, which improves the pressure health diagnosis capability without increasing the hardware requirements of the electric propulsion system. The electric valve pressure reduction system of the electric propulsion system is equipped with multiple pressure sensors. Each pressure sensor is assigned a health flag. When the performance of a pressure sensor deteriorates or malfunctions, its health flag is set to unhealthy. Each time the electric propulsion system adjusts the pressure, it only accepts data from healthy pressure sensors; and it only performs health diagnosis on pressure sensors with a healthy health flag.

[0017] Let the pressure sensors of the electric valve pressure reduction system in the electric propulsion system be PT1, PT2, ..., PTn, where n ≥ 3 and is an odd number. Let the health indicators of the pressure sensors be HS1, HS2, ..., HSn; when HSx is 0, it means that the pressure sensor Ptx is healthy, and its pressure data is used for pressure regulation and health diagnosis; when HSx is 1, it means that the pressure sensor Ptx is unhealthy, and its pressure data is no longer used for pressure regulation and health diagnosis.

[0018] The pressure detection health diagnosis method for electric propulsion systems adopts a graded health diagnosis. When the number of pressure sensors to be judged is ≥3, clustering and outlier diagnosis is adopted; when the number of pressure sensors to be judged is 2, exhaust cycle diagnosis is adopted.

[0019] The specific steps are as follows: 1) When the number of healthy pressure sensors PTx (x is 1~n) is ≥3, sort the healthy pressure sensor values, obtain the average value Pavr of the pressure sensor data in the middle area (accounting for 1 / 3 of the total healthy number), calculate the percentage deviation ηx between each healthy pressure sensor value and the average value Pavr, and set the health status of pressure sensors that exceed the deviation diagnosis threshold m (e.g., 10%) to unhealthy.

[0020] 2) When the number of healthy pressure sensors PTx (x is 1~n) is 2, calculate the deviation percentage а between the two pressure sensors. If it exceeds the deviation diagnosis threshold n (e.g., 10%), then one of the two pressure sensors is considered to have degraded performance or is faulty. Further diagnosis needs to be carried out in conjunction with the exhaust cycle. The following is an example using pressure sensors PT1 and PT2: a) Set the health indicator of pressure sensor PT1 to healthy and the health indicator of pressure sensor PT2 to unhealthy; (b) Set the electric propulsion system to exhaust mode. In this mode, the downstream valve of the electric propulsion system will open, allowing internal gas to be expelled and the system pressure to decrease. When the pressure falls below the lower limit of the target pressure, the electronic valve will open to pressurize the depressurization system pipeline, causing the pressure to rise. When the pressure exceeds the upper limit of the target pressure, the electronic valve will close. This initiates a pressurization and exhaust cycle. The pressure drop process involves the electric propulsion system expelling the working fluid at a fixed flow rate. Therefore, the exhaust cycle can be used to determine the health of the pressure sensor.

[0021] c) During the pressurization and venting process, record the pressure peaks Phi and Pli for each cycle, as well as the corresponding time points Thi and Tli. Calculate the venting time Tpi = (Phi - Pli) / (Tli - Thi). Generally, after obtaining more than 3 pressurization and venting cycles, the average venting time Tpavr = (Tp1 + Tp2 + ... + Tpn) / n can be obtained. d) Calculate the percentage deviation в between the average exhaust time Tpavr and the average exhaust time Tpavr1. If the deviation exceeds the exhaust cycle deviation diagnosis threshold s (e.g., 8%), set the health flag of the pressure sensor to unhealthy; otherwise, set the health flag of the pressure sensor to healthy.

[0022] e) Set the electric propulsion system to standby mode; f) Set the health indicator of pressure sensor PT1 to unhealthy and the health indicator of pressure sensor PT2 to healthy; g) Similarly, calculate the exhaust cycle according to steps b)~e) to determine whether the pressure sensor PT2 is healthy.

[0023] h) Set the health status of pressure sensor 1 and pressure sensor 2 according to the results of the exhaust cycle diagnosis.

[0024] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent substitutions, and improvements made to the above embodiments without departing from the scope of the present invention, based on the technical essence of the present invention and within the spirit and principles of the present invention, shall still fall within the protection scope of the present invention.

Claims

1. A method for pressure detection and health diagnosis of an electric propulsion system, characterized in that, A tiered health diagnostic process is employed for multiple pressure sensors, including: Health indicators are set for multiple pressure sensors in the electric valve pressure reduction system of the electric propulsion system; When the number of pressure sensors that need to be evaluated is not less than 3, cluster outlier diagnosis is used. When there are two pressure sensors that need to be evaluated, exhaust cycle diagnosis is used.

2. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 1, characterized in that, The health indicator being 0 indicates that the pressure sensor is healthy, and its pressure data is used for pressure regulation and health diagnosis. The health indicator being 1 indicates that the pressure sensor is unhealthy, and its pressure data is not used for pressure regulation or health diagnosis.

3. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 1, characterized in that, The cluster outlier diagnosis includes: Sort the pressure sensor values ​​according to health status; Calculate the average value Pavr for the data located in the middle region after sorting. Calculate the percentage deviation ηx between each health pressure sensor value and Pavr; If the deviation percentage value ηx exceeds the preset deviation diagnosis threshold m, the health status of the pressure sensor is set to unhealthy.

4. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 3, characterized in that, The deviation diagnosis threshold m ranges from 8% to 15%.

5. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 1, characterized in that, The exhaust cycle diagnostic method includes: a. Set one of the two health pressure sensors to healthy and the other to unhealthy in sequence; b. Switch the electric propulsion system to exhaust mode and obtain pressure change data through periodic pressurization and exhaust; c. During the pressurization and venting process, record the pressure high points Phi and Pli of each cycle, as well as the corresponding time points Thi and Tli. Calculate the venting time Tpi = (Phi - Pli) / (Tli - Thi) for each cycle. Take no less than 3 pressurization and venting cycles to obtain the average venting time Tpavr. d. Compare the average exhaust time Tpavr with the average exhaust time Tpavr1 of the assembly, and calculate the deviation percentage в. If the deviation percentage в exceeds the exhaust cycle deviation diagnosis threshold s, then the sensor currently set as healthy is judged to be unhealthy; otherwise, it is healthy. e. Set the electric propulsion system to standby mode; f. Switch the health indicators of the two sensors; g. Repeat steps b to e to determine if the other pressure sensor is healthy. h. Based on the results of the exhaust cycle diagnosis, set the health status of the two pressure sensors.

6. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 5, characterized in that, The range of the exhaust cycle deviation diagnosis threshold s is 5% to 10%.

7. The method for pressure detection and health diagnosis of an electric propulsion system according to claim 1, characterized in that, The electric propulsion system has n pressure sensors, where n is an odd number not less than 3.

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