An intelligent management system applied to monitoring aviation motor control

Abstract

The application discloses an intelligent management system applied to monitoring and controlling of an aeronautical motor, relates to the technical field of aeronautical motor monitoring, and comprises an intelligent management system including a motor control system hierarchical module, a working condition time length screening module, a power distinguishing module, a component reliability correction module, a whole machine failure probability analysis module, a risk working condition sequencing module and a warning critical time length determination module; the whole machine failure probability analysis module is used for optimizing traditional fixed cycle maintenance into a dynamic strategy; and the risk sequence is used for more directly displaying the possibility of whole machine failure risks existing under different working conditions; the maintenance mode is more dynamic and intelligent, and the situation of excessive maintenance and insufficient maintenance is avoided.

Description

Technical Field

[0001] This invention relates to the field of aircraft motor control technology, specifically an intelligent management system for monitoring aircraft motor control. Background Technology

[0002] In existing technologies, aircraft motor monitoring systems rely on offline simulation tools such as MATLAB and preset models for reliability assessment. This makes it difficult to respond in real time to changes in electrical, thermal, and mechanical stresses caused by different operating conditions, resulting in delayed component reliability assessments and a high misjudgment rate. Furthermore, maintenance strategies rely on fixed cycles, making it impossible to effectively monitor and adjust aircraft motors under different operating conditions based on the overall failure probability analyzed under different operating conditions, thus failing to achieve intelligent management with response and early warning. This presents a cost and risk contradiction between "excessive maintenance" and "insufficient maintenance." Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent management system for monitoring aircraft motor control, in order to solve the problems raised in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent management system for monitoring aircraft motor control, the intelligent management system including a motor control system classification module, an operating condition duration screening module, a power differentiation module, a component reliability correction module, a whole-machine failure probability analysis module, a risk operating condition ranking module, and a warning critical duration determination module;

[0005] The motor control system hierarchical module is used for a three-chip control system generated based on a heterogeneous three-chip architecture of ARM+DSP+FPGA, which divides the system into a four-level structure of components, subsystems, system units and complete machine.

[0006] The operating condition duration filtering module is used to obtain the running duration recorded under different operating conditions at four levels, and to filter the common duration data based on all types of operating conditions;

[0007] The power differentiation module is used to differentiate between different power levels recorded under the same operating condition and extract the monitoring data under the corresponding power level;

[0008] The component reliability correction module is used to obtain monitoring data from the power differentiation module at different power levels to analyze the fourth level of corrected reliability.

[0009] The overall failure probability analysis module is used to calculate the overall reliability based on the modified reliability, and then use the overall reliability analysis to output the overall failure probability; it iterates through the analysis of the overall failure probability corresponding to different power under the same operating condition to determine the target failure probability;

[0010] The risk condition ranking module is used to analyze the failure probability increase rate of various operating conditions under different operating conditions durations, and generate a risk sequence by ranking the risk conditions based on the failure probability increase rate.

[0011] The warning critical duration determination module is used to determine the warning critical duration based on the corresponding failure probability warning value obtained from the risk sequence, and to issue a warning response to the aircraft motor control center when the warning critical duration is reached.

[0012] Furthermore, the motor control system's hierarchical module uses an ARM processor as the main control chip to communicate with the host computer and other systems, and to issue the current working status and instructions; an FPGA is set as the main coordinating controller to drive multiple PWM channels; and a DSP is set to implement the control algorithm, perform sampling, and handle protection.

[0013] The motor control system hierarchical module sets the component level as the fourth level, which includes components with initial reliability values; sets the subsystem level as the third level, which consists of functional modules composed of components; sets the system level unit as the second level, which consists of subsystems connected in series or parallel; and sets the whole system as the first level, which includes a complete electric drive system with generator, controller, and cooling system.

[0014] Furthermore, the working condition duration filtering module includes a working condition type differentiation unit and a duration data analysis unit;

[0015] The operating condition type differentiation unit is used to differentiate the operating condition types of aircraft motors. The operating condition types include five types: peak power, rated power, high temperature derating, phase loss tolerance, and start-up mode switching.

[0016] The duration data analysis unit is used to extract historical operating data of aircraft motors, capturing the operating duration of aircraft motors under various operating conditions from the historical operating data. It constructs a duration set from all independent operating durations recorded by aircraft motors under the same operating condition. Independent operating duration refers to the continuous duration recorded during operation under different operating conditions. The minimum operating duration corresponding to the intersecting elements in the duration sets of all operating conditions is selected as the common duration for all operating conditions. The reason for selecting the minimum value is to prepare for subsequent analysis based on data changes after the duration increases, ensuring that the operating condition data corresponding to the historical records is still retained after the duration increases.

[0017] Furthermore, the component reliability correction module includes a monitoring data extraction unit, an attenuation factor calculation unit, and a component correction reliability calculation unit;

[0018] The monitoring data extraction unit is used to extract electrical stress parameters, thermal stress parameters and mechanical stress parameters of various power records under various operating conditions; electrical stress parameters include the effective current value I and rated current value I0 of the components under each power value of the corresponding operating condition, thermal stress parameters include the average temperature of the components under the corresponding power, and mechanical stress parameters include vibration acceleration.

[0019] The attenuation factor calculation unit is used to calculate the electrical stress reliability attenuation factor n based on the monitoring data output by the monitoring data extraction unit. 电 n 电 =(I / I0) -m ; m represents the empirical coefficient of the corresponding component; calculate the thermal stress reliability attenuation factor n 热 n 热 =L / L0; where L represents the component lifetime recorded at the average temperature under the corresponding power type, and L0 represents the component lifetime at the reference temperature; calculate the mechanical stress reliability decay factor n. 械 n 械 =1-F, where F represents the Weibull distribution failure probability formula;

[0020] The component correction reliability calculation unit is used to calculate the component correction reliability R based on various types of attenuation factors. 修正 R 修正 =R 初始 *n 电 *n 热 *n 械 ;where R 初始 This indicates the initial reliability of the component.

[0021] Furthermore, the overall failure probability analysis module includes an overall reliability calculation unit;

[0022] The overall system reliability calculation unit is used to obtain the corrected reliability of the fourth level output by the component reliability correction module under the corresponding power and operating condition, and to calculate the reliability of the third level. When the third level subsystem consists of n components connected in series, the reliability of the third level is R. S R S =(R 1修正 *R 2修正 *R 3修正 ...*R n修正 ); where R 1修正 *R 2修正 *R 3修正 ...*R n修 This represents the corrected reliability of the 1st, 2nd, 3rd...nth components in the fourth level under the same power condition; when the third-level subsystem consists of n identical components connected in parallel, the output R... S =1-[(1-R1修正 )*(1-R 2修正 )*...*(1-R n修正 Iterate through all components in the third level and output the reliability of each subsystem in the third level.

[0023] Construct a fault tree for the second-level functional logic, and use the failure of the third-level subsystem as the basic event to calculate the failure probability F of the second-level system unit. 二系统单元 F 二系统单元 =1-[(1-F 三1 )*(1-F 三2 )*...*(1-F 三m )];F 三1 F 三2 ..., F 三m This represents the 1st, 2nd, ..., mth third-level subsystems that caused the failure of the second-level system unit; where F 三m =1-R sm R sm Let R represent the reliability of the m-th subsystem at the third level; then the output reliability of each system unit at the second level is R. 二 R 二 =1-F 二系统单元 ;

[0024] Treating each system unit in the second level as a series component, calculate the overall system reliability R of the first level. 一 R 一 =R 二1 *R 二2 *...R 二k ;R 二1 R 二2 ...R 二k This represents the reliability of the 1st, 2nd, ..., kth system units in the second level.

[0025] Furthermore, the whole machine failure probability analysis module also includes a whole machine failure probability calculation unit and a target failure probability determination unit;

[0026] The overall failure probability calculation unit is used to calculate the overall failure probability F using the overall reliability. 一 F 一 =1-R 一 ;

[0027] The target failure probability determination unit is used to extract the overall failure probability of the aircraft under the same operating condition from records of different power levels, and selects the maximum failure probability as the target failure probability for the corresponding operating condition; and marks the corresponding power as the target power under the operating condition, and the operating time under the target power as the target operating time. The purpose of selecting the maximum value as the target failure probability is to improve the alertness of the aircraft motor control system under various operating conditions, increase the monitoring threshold, and make the early warning response more timely.

[0028] Furthermore, the risk condition ranking module includes a data group construction unit, an increase rate calculation unit, and a risk sequence analysis unit;

[0029] The data group construction unit is used to obtain the target working time and corresponding overall failure probability of each type of working condition; retrieve the historical monitoring data in the aviation motor control system, extract different target working times executed under the same target power to form a target working time sequence, and calculate the corresponding overall failure probability based on the monitoring data under the corresponding target working time. The target working time T and the corresponding overall failure probability F in the target working time sequence are combined to form a data group A, A=(T,F); the target working time sequence is sorted in ascending order of target working time.

[0030] The increase rate calculation unit is used to calculate the failure probability increase rate W under the corresponding working conditions based on the data set corresponding to each target working time in the target duration sequence, W=[1 / (u-1)]∑[(F h -F q ) / (T h -T q )]; u represents the total number of data groups in the target time series; F q F represents the overall failure probability corresponding to the previous data group based on the target duration sequence order. h Indicates the relationship between the target duration sequence order and F q The probability of system failure corresponding to the next adjacent data set; T q F represents q The target working time T corresponds to the data set. h F represents h The target working time in the corresponding data group;

[0031] The risk sequence analysis unit is used to extract the failure probability increase rate W calculated under various working conditions, and to generate a risk sequence by sorting all types of working conditions in ascending order based on the magnitude of the failure probability increase rate.

[0032] Furthermore, the early warning critical duration determination module includes a failure probability early warning value extraction unit and an early warning response control unit;

[0033] The failure probability warning value extraction unit is used to extract the overall failure probability warning value F of the risk sequence corresponding to each type of operating condition. y Based on the data set, a functional relationship f between the target working time and the overall machine failure probability under the corresponding working condition type is constructed. F f F =a*t T +b, where a represents the reference coefficient and b represents the error term, is substituted into the corresponding type of operating condition stored machine failure probability warning value F. y The critical warning duration T for the corresponding operating condition is obtained. y ;t T This represents the target working time substituted into the functional relationship;

[0034] The early warning response control unit is used to obtain the corresponding running time T under real-time operating conditions. z Calculate the warning duration limit T x T x =T y -T z Real-time monitoring of the corresponding type of operating condition within the warning duration limit T x If the system switches to another operating condition, monitor the duration of the new operating condition. If it does, continue monitoring the duration of the new operating condition. If the warning duration limit T is reached... x The system still failed to switch the transmission of the warning signal to the current working condition and the abnormal working time.

[0035] In this application, the risk sequence is analyzed based on the power state at which the probability of failure is most likely, thus improving the monitoring and early warning level to a certain extent. Secondly, when analyzing the running time of the real-time monitoring conditions, even if the calculated failure probability under the same conditions is different from the power at which the risk sequence is analyzed, the calculated early warning time limit is still the maximum possible advance response, thus avoiding the occurrence of risks.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] This application uses a component reliability correction module to collect monitoring data under different operating conditions in real time; and dynamically corrects the reliability of fourth-level components based on the Arrhenius equation and Weibull distribution to improve the accuracy of overall system reliability calculation.

[0038] This application optimizes traditional fixed-cycle maintenance into a dynamic strategy through a whole-machine failure probability analysis module; and through risk sequences, it more intuitively displays the possibility of whole-machine failure under different operating conditions; making the maintenance method more dynamic and intelligent, and avoiding over-maintenance and under-maintenance.

[0039] This application also analyzes the potential critical warning duration, accurately monitors the duration of potentially risky working conditions under different types of working conditions, and provides alerts to achieve intelligent and targeted dynamic management. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the structure of an intelligent management system for monitoring aircraft motor control according to the present invention. Detailed Implementation

[0041] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Example: Figure 1 As shown, the present invention provides an intelligent management system for monitoring aircraft motor control. The intelligent management system includes a motor control system classification module, an operating condition duration screening module, a power differentiation module, a component reliability correction module, a whole machine failure probability analysis module, a risk operating condition ranking module, and an early warning critical duration determination module.

[0043] The motor control system hierarchical module is used for a three-chip control system generated based on a heterogeneous three-chip architecture of ARM+DSP+FPGA, which divides the system into a four-level structure of components, subsystems, system units and complete machine.

[0044] The operating condition duration filtering module is used to obtain the running duration recorded under different operating conditions at four levels, and to filter the common duration data based on all types of operating conditions;

[0045] The power differentiation module is used to differentiate between different power levels recorded under the same operating condition and extract the monitoring data under the corresponding power level;

[0046] The component reliability correction module is used to obtain monitoring data from the power differentiation module at different power levels to analyze the fourth level of corrected reliability.

[0047] The overall failure probability analysis module is used to calculate the overall reliability based on the modified reliability, and then use the overall reliability analysis to output the overall failure probability; it iterates through the analysis of the overall failure probability corresponding to different power under the same operating condition to determine the target failure probability;

[0048] The risk condition ranking module is used to analyze the failure probability increase rate of various operating conditions under different operating conditions durations, and generate a risk sequence by ranking the risk conditions based on the failure probability increase rate.

[0049] The warning critical duration determination module is used to determine the warning critical duration based on the corresponding failure probability warning value obtained from the risk sequence, and to issue a warning response to the aircraft motor control center when the warning critical duration is reached.

[0050] In the hierarchical module of the motor control system, an ARM is set as the main control chip to realize communication with the host computer and other systems, and to issue the current working status and working instructions; an FPGA is set as the main coordinating controller to complete the multi-channel PWM drive; and a DSP is set to be responsible for the implementation of control algorithms, sampling and protection.

[0051] The motor control system hierarchical module sets the component level as the fourth level, which includes components with initial reliability values; sets the subsystem level as the third level, which consists of functional modules composed of components; sets the system level unit as the second level, which consists of subsystems connected in series or parallel; and sets the whole system as the first level, which includes a complete electric drive system with generator, controller, and cooling system.

[0052] The working condition duration filtering module includes a working condition type differentiation unit and a duration data analysis unit;

[0053] The operating condition type differentiation unit is used to differentiate the operating condition types of aircraft motors. The operating condition types include five types: peak power, rated power, high temperature derating, phase loss fault tolerance, and start-up mode switching. Different types of operating conditions are set with different switching conditions and corresponding triggering methods. For example, the switching conditions under peak power are speed > 27000 rpm and load > 250 kW, and the triggering method is automatic through sensors and control algorithms.

[0054] The duration data analysis unit is used to extract historical operating data of aircraft motors, capturing the operating duration of aircraft motors under various operating conditions from the historical operating data. It constructs a duration set by combining all independent operating durations recorded by aircraft motors under the same operating condition. Independent operating duration refers to the continuous duration recorded during operation under different operating conditions. Each element in the set represents the operating condition duration of one independent operating condition record. The minimum operating duration corresponding to the intersecting elements in the duration sets of all types of operating conditions is selected as the common duration for all types of operating conditions. The reason for selecting the minimum value is to prepare for subsequent analysis of data changes based on the increase in duration, ensuring that the operating condition data corresponding to the historical records is still retained after the duration increases.

[0055] The component reliability correction module includes a monitoring data extraction unit, an attenuation factor calculation unit, and a component correction reliability calculation unit;

[0056] The monitoring data extraction unit is used to extract electrical stress parameters, thermal stress parameters and mechanical stress parameters of various power records under various operating conditions; electrical stress parameters include the effective current value I and rated current value I0 of the components under each power value of the corresponding operating condition, thermal stress parameters include the average temperature of the components under the corresponding power, and mechanical stress parameters include vibration acceleration.

[0057] The attenuation factor calculation unit is used to calculate the electrical stress reliability attenuation factor n based on the monitoring data output by the monitoring data extraction unit. 电 n 电 =(I / I0) -m ; m represents the empirical coefficient for the corresponding component; as shown in the example: taking SiC MOSFET as an example, substituting I=480A, I0=350A, m=0.5; then n 电 =(480 / 350) -0.5 =0.85; Calculate the thermal stress reliability attenuation factor n 热 n 热 =L / L0; where L represents the component lifetime recorded at the average temperature under the corresponding power type, and L0 represents the component lifetime at the reference temperature; the reference temperature is generally 25 degrees Celsius; where L can be calculated based on the Arrhenius equation, L=L0*e (Ea / k1)*[(1 / T0)-(1 / T)] Where e represents the natural constant, Ea represents the activation energy, which is the energy barrier to material failure; k1 represents the Boltzmann constant, 8.617 × 10⁻⁶. -5 eV / K, used for energy-to-temperature conversion; T represents the current absolute temperature, T=128.1+273=401.1, T0 represents the absolute temperature under standard temperature, T0=25+273=296K; L0=10000h is the lifespan at 25℃; calculate the mechanical stress reliability decay factor n. 械 n 械 =1-F, where F represents the failure probability formula of the Weibull distribution. Where N is the fatigue life, t represents the running time, and k represents the Weibull shape parameter; C represents the material constant, b represents the fatigue strength index, and Δε represents the strain amplitude.

[0058] The component correction reliability calculation unit is used to calculate the component correction reliability R based on various types of attenuation factors. 修正 R 修正 =R 初始 *n 电 *n 热 *n 械 ;where R 初始 This indicates the initial reliability of the component. It can be extracted from existing databases; for example, ARM is 0.9999.

[0059] The overall failure probability analysis module includes an overall reliability calculation unit;

[0060] The overall system reliability calculation unit is used to obtain the corrected reliability of the fourth level output by the component reliability correction module under the corresponding power and operating condition, and to calculate the reliability of the third level. When the third level subsystem consists of n components connected in series, the reliability of the third level is R. S R S =(R 1修正 *R 2修正 *R 3修正 ...*R n修正 ); where R 1修正 *R 2修正 *R 3修正 ...*R n修 This represents the corrected reliability of the 1st, 2nd, 3rd...nth components in the fourth level under the same power condition; when the third-level subsystem consists of n identical components connected in parallel, the output R... S =1-[(1-R 1修正 )*(1-R 2修正 )*...*(1-R n修正 Iterate through all components in the third level and output the reliability of each subsystem in the third level.

[0061] Construct a fault tree for the second-level functional logic, and use the failure of the third-level subsystem as the basic event to calculate the failure probability F of the second-level system unit. 二系统单元 F 二系统单元 =1-[(1-F 三1 )*(1-F 三2 )*...*(1-F 三m )];F 三1 F 三2 ..., F 三m This represents the 1st, 2nd, ..., mth third-level subsystems that caused the failure of the second-level system unit; where F 三m =1-R sm R sm Let R represent the reliability of the m-th subsystem at the third level; then the output reliability of each system unit at the second level is R. 二 R 二 =1-F 二系统单元 ;

[0062] Treating each system unit in the second level as a series component, calculate the overall system reliability R of the first level. 一 R 一 =R 二1 *R 二2 *...R 二k ;R 二1 R 二2 ...R 二kThis represents the reliability of the 1st, 2nd, ..., kth system units in the second level.

[0063] The overall failure probability analysis module also includes an overall failure probability calculation unit and a target failure probability determination unit;

[0064] The overall failure probability calculation unit is used to calculate the overall failure probability F using the overall reliability. 一 F 一 =1-R 一 ;

[0065] The target failure probability determination unit is used to extract the overall failure probability of the aircraft under the same operating condition from records of different power levels, and selects the maximum failure probability as the target failure probability for the corresponding operating condition; and marks the corresponding power as the target power under the operating condition, and the operating time under the target power as the target operating time. The purpose of selecting the maximum value as the target failure probability is to improve the alertness of the aircraft motor control system under various operating conditions, increase the monitoring threshold, and make the early warning response more timely.

[0066] The risk condition ranking module includes a data group construction unit, an increase rate calculation unit, and a risk sequence analysis unit;

[0067] The data group construction unit is used to obtain the target working time and corresponding overall failure probability of each type of working condition; retrieve the historical monitoring data in the aviation motor control system, extract different target working times executed under the same target power to form a target working time sequence, and calculate the corresponding overall failure probability based on the monitoring data under the corresponding target working time. The target working time T and the corresponding overall failure probability F in the target working time sequence are combined to form a data group A, A=(T,F); the target working time sequence is sorted in ascending order of target working time.

[0068] The increase rate calculation unit is used to calculate the failure probability increase rate W under the corresponding working conditions based on the data set corresponding to each target working time in the target duration sequence, W=[1 / (u-1)]∑[(F h -F q ) / (T h -T q )]; u represents the total number of data groups in the target time series; F q F represents the overall failure probability corresponding to the previous data group based on the target duration sequence order. h Indicates the relationship between the target duration sequence order and F q The probability of system failure corresponding to the next adjacent data set; T q F represents q The target working time T corresponds to the data set. h F represents h The target working time in the corresponding data group;

[0069] As shown in the example: the target duration sequence is now recorded as follows: 2, 4, 7, in minutes;

[0070] The corresponding data sets for each target duration sequence are (2, 5%), (4, 5.5%), and (7, 8%).

[0071] Therefore, the corresponding increase in failure probability is:

[0072] W=[1 / (u-1)]∑[(F h -F q ) / (T h -T q )]=(1 / 2)[2 / 0.5%+3 / 2.5%]=2.6%;

[0073] The risk sequence analysis unit is used to extract the failure probability increase rate W calculated under various working conditions, and to generate a risk sequence by sorting all types of working conditions in ascending order based on the magnitude of the failure probability increase rate.

[0074] The early warning critical duration determination module includes a failure probability early warning value extraction unit and an early warning response control unit;

[0075] The failure probability warning value extraction unit is used to extract the overall failure probability warning value F of the risk sequence corresponding to each type of operating condition. y Based on the data set, a functional relationship f between the target working time and the overall machine failure probability under the corresponding working condition type is constructed. F f F =a*t T +b, where a represents the reference coefficient and b represents the error term, is substituted into the corresponding type of operating condition stored machine failure probability warning value F. y The critical warning duration T for the corresponding operating condition is obtained. y ;t T This represents the target working time substituted into the functional relationship;

[0076] The early warning response control unit is used to obtain the corresponding running time T under real-time operating conditions. z Calculate the warning duration limit T x T x =T y -T z Real-time monitoring of the corresponding type of operating condition within the warning duration limit T x If the system switches to another operating condition, monitor the duration of the new operating condition. If it does, continue monitoring the duration of the new operating condition. If the warning duration limit T is reached... x The system still failed to switch the transmission of the warning signal to the current working condition and the abnormal working time.

[0077] In this application, the risk sequence is analyzed based on the power state at which the probability of failure is most likely, thus improving the monitoring and early warning level to a certain extent. Secondly, when analyzing the running time of the real-time monitoring conditions, even if the calculated failure probability under the same conditions is different from the power at which the risk sequence is analyzed, the calculated early warning time limit is still the maximum possible advance response, thus avoiding the occurrence of risks.

[0078] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent management system for monitoring aircraft motor control, characterized in that: The intelligent management system includes a motor control system hierarchical module, an operating condition duration screening module, a power differentiation module, a component reliability correction module, a whole machine failure probability analysis module, a risk operating condition ranking module, and a warning critical duration determination module. The motor control system hierarchical module is used to generate a three-chip control system based on a heterogeneous three-chip architecture of ARM+DSP+FPGA, which divides the system into a four-level structure of components, subsystems, system units and complete machine. The operating condition duration filtering module is used to obtain the running duration recorded under different operating conditions at four levels, and to filter the common duration data based on all types of operating conditions. The power differentiation module is used to differentiate different power levels recorded under the same operating condition and extract monitoring data under the corresponding power level. The component reliability correction module is used to obtain monitoring data from the power differentiation module at different power levels to analyze the corrected reliability of the fourth level; the motor control system hierarchical module sets the component level as the fourth level. The overall failure probability analysis module is used to calculate the overall reliability based on the corrected reliability, and then use the overall reliability analysis to output the overall failure probability. The failure probability of the target machine is determined by traversing and analyzing the failure probability of the whole machine under different power levels under the same operating condition. The risk condition ranking module is used to analyze the failure probability increase rate of various operating conditions under different operating conditions durations, and generate a risk sequence by ranking the risk conditions based on the failure probability increase rate. The warning critical duration determination module is used to determine the warning critical duration based on the corresponding failure probability warning value obtained from the risk sequence, and to issue a warning response to the aircraft motor control center when the warning critical duration is reached.

2. The intelligent management system for monitoring aircraft motor control according to claim 1, characterized in that: The motor control system hierarchical module is configured with an ARM as the master control chip to enable communication with the host computer and other systems, and to issue the current working status and working instructions; an FPGA is configured as the master coordinating controller to complete multi-channel PWM driving; and a DSP is configured to be responsible for the implementation of control algorithms, sampling and protection. The fourth level includes components with initial reliability values; the subsystem level is set as the third level, which is a functional module composed of components; the system level unit is set as the second level, which is composed of subsystems connected in series or parallel; the whole system is set as the first level, which includes a complete electric drive system with generator, controller, and cooling system.

3. The intelligent management system for monitoring aircraft motor control according to claim 1, characterized in that: The working condition duration filtering module includes a working condition type differentiation unit and a duration data analysis unit; The operating condition type differentiation unit is used to differentiate the operating condition types of aircraft motors. The operating condition types include five types: peak power, rated power, high temperature derating, phase loss tolerance, and start-up mode switching. The duration data analysis unit is used to extract historical operating data of the aircraft motor and capture the operating duration of the aircraft motor under various operating conditions from the historical operating data. The duration of all independent operation recorded by the aircraft motor under the same operating condition is formed into a duration set. The duration of independent operation refers to the continuous duration recorded when each independent operating condition is running under the condition switching. The minimum value of the duration of operation corresponding to the intersecting elements in the duration set of all types of operating conditions is selected as the common duration of each type of operating condition.

4. The intelligent management system for monitoring aircraft motor control according to claim 2, characterized in that: The component reliability correction module includes a monitoring data extraction unit, an attenuation factor calculation unit, and a component correction reliability calculation unit; The monitoring data extraction unit is used to extract electrical stress parameters, thermal stress parameters and mechanical stress parameters of various power records under various operating conditions; the electrical stress parameters include the effective current value I and rated current value I0 of the components under each power value of the corresponding operating condition, the thermal stress parameters include the average temperature of the components under the corresponding power, and the mechanical stress parameters include vibration acceleration. The attenuation factor calculation unit is used to calculate the electrical stress reliability attenuation factor n based on the monitoring data output by the monitoring data extraction unit. 电 n 电 =(I / I0) -m ; m represents the empirical coefficient of the corresponding component; calculate the thermal stress reliability attenuation factor n 热 n 热 =L / L0; where L represents the component lifetime recorded at the average temperature under the corresponding power type, and L0 represents the component lifetime at the reference temperature. Calculate the mechanical stress reliability attenuation factor n 械 n 械 =1-F, where F represents the failure probability formula of the Weibull distribution. The component correction reliability calculation unit is used to calculate the component correction reliability R based on various types of attenuation factors. 修正 R 修正 =R 初始 *n 电 *n 热 *n 械 ;where R 初始 This indicates the initial reliability of the component.

5. The intelligent management system for monitoring aircraft motor control according to claim 4, characterized in that: The overall failure probability analysis module includes an overall reliability calculation unit; The overall system reliability calculation unit is used to obtain the corrected reliability of the fourth level output by the component reliability correction module under the corresponding power and operating condition, and to calculate the reliability of the third level. When the third level subsystem consists of n components connected in series, the reliability of the third level is R. S R S =(R 1修正 *R 2修正 *R 3修正 ...*R n修正 ); where R 1修正 *R 2修正 *R 3修正 ...*R n修 This represents the corrected reliability of the 1st, 2nd, 3rd...nth components in the fourth level under the same power condition; when the third-level subsystem consists of n identical components connected in parallel, the output R... S =1-[(1-R 1修正 )*(1-R 2修正 )*...*(1-R n修正 Iterate through all components in the third level and output the reliability of each subsystem in the third level. Construct a fault tree for the second-level functional logic, and use the failure of the third-level subsystem as the basic event to calculate the failure probability F of the second-level system unit. 二系统单元 F 二系统单元 =1-[(1-F 三1 )*(1-F 三2 )*...*(1-F 三m )];F 三1 F 三2 ..., F 三m This represents the 1st, 2nd, ..., mth third-level subsystems that caused the failure of the second-level system unit; where F 三m =1-R sm R sm Let R represent the reliability of the m-th subsystem at the third level; then the output reliability of each system unit at the second level is R. 二 R 二 =1-F 二系统单元 ; Treating each system unit in the second level as a series component, calculate the overall system reliability R of the first level. 一 R 一 =R 二1 *R 二2 *...R 二k ;R 二1 R 二2 ...R 二k This represents the reliability of the 1st, 2nd, ..., kth system units in the second level.

6. The intelligent management system for monitoring aircraft motor control according to claim 5, characterized in that: The whole machine failure probability analysis module also includes a whole machine failure probability calculation unit and a target failure probability determination unit; The overall failure probability calculation unit is used to calculate the overall failure probability F using the overall machine reliability. 一 F 一 =1-R 一 ; The target failure probability determination unit is used to extract the overall failure probability recorded at different power levels under the same operating condition, select the maximum failure probability as the target failure probability of the corresponding operating condition, and mark the corresponding power as the target power under the operating condition, and the working time under the target power as the target working time.

7. The intelligent management system for monitoring aircraft motor control according to claim 5, characterized in that: The risk condition ranking module includes a data group construction unit, an increase rate calculation unit, and a risk sequence analysis unit. The data group construction unit is used to obtain the target working time and corresponding overall failure probability of each type of working condition; retrieve the historical monitoring data in the aviation motor control system, extract different target working times executed under the same target power to form a target working time sequence, and calculate the corresponding overall failure probability based on the monitoring data under the corresponding target working time. The target working time T and the corresponding overall failure probability F in the target working time sequence are combined to form a data group A, A=(T,F); the target working time sequence is sorted in ascending order of target working time. The increase rate calculation unit is used to calculate the failure probability increase rate W under the corresponding type of working condition based on the data group corresponding to each target working time in the target time sequence, W=[1 / (u-1)]∑[(F h -F q ) / (T h -T q )]; u represents the total number of data groups in the target time series; F q F represents the overall failure probability corresponding to the previous data group based on the target duration sequence order. h Indicates the relationship between the target duration sequence order and F q The probability of system failure corresponding to the next adjacent data set; T q F represents q The target working time T corresponds to the data set. h F represents h The target working time in the corresponding data group; The risk sequence analysis unit is used to extract the failure probability increase rate W calculated under various working conditions, and to generate a risk sequence by sorting all types of working conditions in ascending order based on the magnitude of the failure probability increase rate.

8. The intelligent management system for monitoring aircraft motor control according to claim 6, characterized in that: The warning critical duration determination module includes a failure probability warning value extraction unit and a warning response control unit; The failure probability warning value extraction unit is used to extract the overall failure probability warning value F stored for each type of operating condition corresponding to the risk sequence. y Based on the data set, a functional relationship f between the target working time and the overall machine failure probability under the corresponding working condition type is constructed. F f F =a*t T +b, where a represents the reference coefficient and b represents the error term, is substituted into the corresponding type of operating condition stored machine failure probability warning value F. y The critical warning duration T for the corresponding working condition is obtained. y ;t T This represents the target working time substituted into the functional relationship; The early warning response control unit is used to obtain the running time T corresponding to the real-time type of working condition. z Calculate the warning duration limit T x T x =T y -T z Real-time monitoring of the corresponding type of operating condition within the warning duration limit T x If the operating conditions are switched to other types, continue to monitor the working time of the new type of operating condition. If the warning duration limit T is reached x The system still failed to switch the transmission of the warning signal to the current working condition and the abnormal working time.

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