CN117078059A - Method and device for determining performance indexes of airplane prediction and health management - Google Patents
Method and device for determining performance indexes of airplane prediction and health management Download PDFInfo
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Abstract
The invention discloses a method and a device for determining performance indexes of airplane prediction and health management, wherein the method comprises the following steps: acquiring data information of an aircraft guarantee process and a workflow of the aircraft guarantee process; constructing an airplane operation guarantee simulation model according to airplane guarantee process data information; simulating the work flow of the aircraft guarantee process by using a system simulation method to obtain simulation process data information; processing the simulation process data information by using a mathematical statistics method to obtain airplane guarantee efficiency indexes; the influence degree of the change of the performance index of the prediction and health management system on the aircraft guarantee performance index is analyzed, so that scientific and reasonable demonstration of the prediction and health management system index is realized. The method is not only suitable for the aircraft, but also can be popularized as a simulation modeling framework of the prediction and health management system, and is applied to the prediction and health management systems of other key industrial equipment.
Description
Technical Field
The invention relates to the technical field of index requirement demonstration, in particular to a method and a device for determining performance indexes of airplane prediction and health management.
Background
The main functions of prediction and health management (Prognostics and Health Management, PHM) are to sense the health condition of equipment by utilizing the original data information of various aspects such as performance, control, operation, maintenance and the like provided by a sensing monitoring system, identify and diagnose the performance degradation or fault type of the equipment, predict the residual service life of the equipment and make equipment operation guarantee decision according to the performance degradation or fault type, optimize equipment maintenance guarantee work, and play an important role in improving the success rate and the use availability of an aircraft mission, reducing the comprehensive use cost and improving the comprehensive guarantee benefit of the whole life cycle.
The requirement demonstration is a primary link in the whole life cycle of the aircraft prediction and health management system, and the task is to put forward the overall architecture and specific performance index requirements of the prediction and health management system according to the requirements of the aircraft in terms of use scene environment, guarantee performance and the like so as to guide the subsequent system research, development and deployment work. One of the core problems to be solved in the process is to establish a mapping relation between prediction and health management performance indexes, namely mapping the use guarantee requirement indexes (use availability, running-out rate, task success rate and the like) of the aircraft to specific capability indexes (fault detection rate, fault isolation rate, life prediction advance, life prediction precision, preventive maintenance interval and the like) of the prediction and health management, which has important significance for reasonably determining the overall technical requirements of the prediction and health management, controlling the implementation cost of the prediction and health management, guiding the development design of the prediction and health management, and even guiding the overall design, performance allocation and use mode of the aircraft. The mapping relation between the performance index of prediction and health management and the use guarantee requirement index of the airplane not only needs to consider the level of prediction and health management system design and guarantee design of the airplane, but also needs to consider the influence of factors such as guarantee resources, guarantee organization and the like, and the multi-factor nonlinear coupling relation leads to the failure of directly establishing a mathematical model between the two. Therefore, how to extract the related requirements of prediction and health management from the actual use scene of the aircraft by adopting a scientific and reasonable method, and establish the influence relationship between the performance indexes of prediction and health management and the use guarantee requirement indexes of the aircraft are the difficulties in the current prediction and health management performance index demonstration.
Disclosure of Invention
The invention aims to provide a method and a device for determining an aircraft prediction and health management performance index, which are used for simulating an aircraft use guarantee process assembled with a prediction and health management system by using a discrete event driven simulation method by establishing an aircraft operation guarantee process model and a guarantee efficiency evaluation index, analyzing the influence degree of the change of the prediction and health management performance index on the aircraft guarantee efficiency index, further establishing the mapping from the use guarantee requirement of an aircraft to the prediction and health management capacity index, and realizing scientific and reasonable demonstration of the prediction and health management index.
In order to solve the above technical problems, a first aspect of the embodiments of the present invention discloses a method for determining performance indexes of prediction and health management of an aircraft, where the method includes:
s1, acquiring data information of an aircraft guarantee process and an aircraft guarantee process workflow;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
the performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
The aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
s2, constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
s3, simulating the work flow of the aircraft guarantee process by using a preset system simulation method to obtain simulation process data information;
the simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
S4, processing the simulation process data information by using a mathematical statistics method to obtain aircraft guarantee efficiency indexes;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
s5, adjusting the performance index information of the prediction and health management in the airplane operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and health management on the guarantee efficiency;
s6, combining the predicted and health-managed performance index information according to the influence degree information to obtain a predicted and health-managed performance index information combination;
s7, evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the task model is used to describe task profile information executed by the aircraft, and drive the operation assurance activity of the aircraft;
The aircraft configuration model is used for describing basic composition information of an aircraft and failure rates, average maintenance time, failure detection rate, failure isolation rate, life prediction advance, life prediction precision and preventive maintenance interval parameters of various subsystems;
the maintenance model is used for describing how the aircraft performs repair maintenance, preventive maintenance and predictive maintenance under the support of prediction and health management;
the guarantee resource model is used for describing a storage and supply mode and a scheduling rule of various aviation material spare parts required by guaranteeing normal flight of an aircraft;
the guarantee organization model is used for describing various guarantee entities and interaction relations among the various guarantee entities involved in the operation process of the aircraft.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the simulating the workflow of the aircraft security process by using a preset system simulation method to obtain simulation process data information includes:
s31, simulating the work flow of the aircraft guarantee process by using a discrete event driving method to obtain a task list;
s32, generating the initial state of the aircraft and the fault occurrence time through random sampling according to the task list, and obtaining simulation process data information.
In a first aspect of the embodiment of the present invention, the processing the simulation process data information by using a mathematical statistics method to obtain an aircraft guarantee efficiency index includes:
s41, processing the aircraft security process data information by using an availability calculation model to obtain availability;
the usage availability calculation model is as follows:
wherein A is O For availability, OT is working time, ST is standby time, TCM is repair maintenance time, TPM is preventive maintenance time, ALDT is management and guarantee delay time;
s42, processing the aircraft guarantee process data information by using a lifting rate calculation model to obtain lifting rate;
the overhead rate calculation model is as follows:
wherein SGR is the overhead rate, D i For the total number of days of play, n is the total number of days of play, m i For the number of aircraft to be launched per day, T FL For the number of hours an aircraft can fly per day, T DU Average number of hours per flight for aircraft, T GM For average ground taxi time of aircraft, T TA Preparation time for aircraft to restart, T CM For average repairable repair time per take-out of aircraft, T PM For average preventive maintenance time per outgoing train of aircraft, T AB For the average fight damage repair time per moving frame time, T SM Average replenishment time per overhead;
s43, processing the aircraft security process data information by using a task success rate calculation model to obtain a task success rate;
the task success rate calculation model is as follows:
where MCSP is the task success rate.
In a first aspect of the embodiment of the present invention, the adjusting the performance index information of the prediction and the health management to obtain the information about the influence degree of the performance index information of each prediction and the health management on the guarantee efficiency includes:
s51, setting a change range and a change step length of the fault detection rate, the fault isolation rate, the life prediction advance, the life prediction precision and the preventive maintenance interval information;
s52, changing the performance index information of prediction and health management according to the change step length each time, fixing the performance index information of other prediction and health management, and obtaining the guarantee performance index of the airplane by using a sensitivity analysis method;
and S53, calculating the average change rate of the performance indexes of the aircraft on different predictions and health management, and sorting from large to small according to the average change rate to obtain the influence degree information of the performance index information of each prediction and health management on the performance.
The second aspect of the embodiment of the invention discloses an aircraft prediction and health management performance index determining device, which comprises:
the data acquisition module is used for acquiring data information of the aircraft guarantee process and the workflow of the aircraft guarantee process;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
the performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
the aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
the simulation model construction module is used for constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
the workflow simulation module is used for simulating the workflow of the aircraft guarantee process by using a preset system simulation method to obtain simulation process data information;
The simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
the data processing module is used for processing the simulation process data information by utilizing a mathematical statistics method to obtain aircraft guarantee efficiency indexes;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
the index evaluation module is used for adjusting the performance index information of the prediction and the health management in the airplane operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and the health management on the guarantee efficiency;
The index combination module is used for combining the performance index information of the prediction and the health management according to the influence degree information to obtain a performance index information combination of the prediction and the health management;
the index evaluation module is used for evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
In a second aspect of the embodiment of the present invention, the task model is used to describe task profile information executed by the aircraft, and drive the aircraft to perform a guarantee activity;
the aircraft configuration model is used for describing basic composition information of an aircraft and failure rates, average maintenance time, failure detection rate, failure isolation rate, life prediction advance, life prediction precision and preventive maintenance interval parameters of various subsystems;
the maintenance model is used for describing how the aircraft performs repair maintenance, preventive maintenance and predictive maintenance under the support of prediction and health management;
The guarantee resource model is used for describing a storage and supply mode and a scheduling rule of various aviation material spare parts required by guaranteeing normal flight of an aircraft;
the guarantee organization model is used for describing various guarantee entities and interaction relations among the various guarantee entities involved in the operation process of the aircraft.
In a second aspect of the present invention, the simulating the workflow of the aircraft security process by using a preset system simulation method to obtain simulation process data information includes:
s31, simulating the work flow of the aircraft guarantee process by using a discrete event driving method to obtain a task list;
s32, generating the initial state of the aircraft and the fault occurrence time through random sampling according to the task list, and obtaining simulation process data information.
In a second aspect of the embodiment of the present invention, the processing the simulation process data information by using a mathematical statistics method to obtain an aircraft guarantee efficiency index includes:
s41, processing the aircraft security process data information by using an availability calculation model to obtain availability;
The usage availability calculation model is as follows:
wherein A is O For availability, OT is working time, ST is standby time, TCM is repair maintenance time, TPM is preventive maintenance time, ALDT is management and guarantee delay time;
s42, processing the aircraft guarantee process data information by using a lifting rate calculation model to obtain lifting rate;
the overhead rate calculation model is as follows:
wherein SGR is the overhead rate, D i For the total number of days of play, n is the total number of days of play, m i For the number of aircraft to be launched per day, T FL For the number of hours an aircraft can fly per day, T DU Average number of hours per flight for aircraft, T GM For average ground taxi time of aircraft, T TA Preparation time for aircraft to restart, T CM For average repairable repair time per take-out of aircraft, T PM For average preventive maintenance time per outgoing train of aircraft, T AB For the average fight damage repair time per moving frame time, T SM Average replenishment time per overhead;
s43, processing the aircraft security process data information by using a task success rate calculation model to obtain a task success rate;
the task success rate calculation model is as follows:
Where MCSP is the task success rate.
In a second aspect of the embodiment of the present invention, the adjusting the performance index information of the prediction and the health management to obtain the information about the degree of influence of the performance index information of each prediction and the health management on the guarantee efficiency includes:
s51, setting a change range and a change step length of the fault detection rate, the fault isolation rate, the life prediction advance, the life prediction precision and the preventive maintenance interval information;
s52, changing the performance index information of prediction and health management according to the change step length each time, fixing the performance index information of other prediction and health management, and obtaining the guarantee performance index of the airplane by using a sensitivity analysis method;
and S53, calculating the average change rate of the performance indexes of the aircraft on different predictions and health management, and sorting from large to small according to the average change rate to obtain the influence degree information of the performance index information of each prediction and health management on the performance.
In a third aspect, the present invention discloses another aircraft prediction and health management performance index determining apparatus, the apparatus comprising:
A memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform some or all of the steps in the aircraft prediction and health management performance index determination method disclosed in the first aspect of the embodiment of the present invention.
In a fourth aspect, the present invention discloses a computer storage medium, where computer instructions are stored, where the computer instructions are used to execute part or all of the steps in the method for determining an aircraft prediction and health management performance index disclosed in the first aspect of the embodiment of the present invention when the computer instructions are called.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
(1) According to the invention, the aircraft operation guarantee process model and the indexes for evaluating the guarantee efficiency are established, the aircraft use guarantee process assembled with the prediction and health management system is simulated by using the system simulation method, and the influence degree of the change of the prediction and health management performance indexes on the aircraft guarantee efficiency indexes is analyzed, so that the scientific and reasonable demonstration of the prediction and health management indexes is realized.
(2) The method establishes a comprehensive and detailed guarantee simulation model, simulates real guarantee logic and flow, and ensures the scientificity and rationality of the forecasting and health management performance index requirement demonstration method.
(3) The method utilizes the discrete event driving method to simulate the guarantee process of the aircraft, and reduces the simulation time and the statistics times of the guaranteed efficacy indexes.
(4) The prediction and health management performance index demonstration method provided by the method is not only suitable for the aircraft, but also can be applied to prediction and health management systems of other military equipment or industrial products, and has strong popularization.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for determining performance indexes of prediction and health management of an aircraft according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for determining aircraft prediction and health management performance indicators according to an embodiment of the present invention;
FIG. 3 is a flow chart of a repair service disclosed in an embodiment of the present invention;
FIG. 4 is a flow chart of preventative maintenance as disclosed in an embodiment of the present invention;
FIG. 5 is a predictive maintenance flow diagram in accordance with an embodiment of the invention;
FIG. 6 is a simulation flow diagram based on a discrete event driven method disclosed in an embodiment of the present invention;
FIG. 7 is a flow chart of Monte Carlo sampling as disclosed in an embodiment of the present invention;
FIG. 8 is a schematic diagram of an aircraft prediction and health management performance index determination apparatus according to an embodiment of the present invention;
fig. 9 is a schematic diagram of another apparatus for determining performance indicators of aircraft prediction and health management according to an embodiment of the present invention.
Detailed Description
In order to make the present invention better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include other steps or elements not expressly listed or inherent to such process, method, article, or device.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Example 1
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for determining performance indexes of prediction and health management of an aircraft according to an embodiment of the present invention. The method for determining the performance index of the prediction and health management of the aircraft described in fig. 1 is applied to the simulation and evaluation of the performance evaluation of the operation guarantee process of the aircraft, which is not limited in the embodiment of the invention. As shown in fig. 1, the aircraft prediction and health management performance index determination method may include the following operations:
s1, acquiring data information of an aircraft guarantee process and an aircraft guarantee process workflow;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
The performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
the aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
s2, constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
s3, simulating the work flow of the aircraft guarantee process by using a preset system simulation method to obtain simulation process data information;
the simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
S4, processing the simulation process data information by using a mathematical statistics method to obtain aircraft guarantee efficiency indexes;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
s5, adjusting the performance index information of the prediction and health management in the airplane operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and health management on the guarantee efficiency;
s6, combining the predicted and health-managed performance index information according to the influence degree information to obtain a predicted and health-managed performance index information combination;
s7, evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
Optionally, the task model is used for describing task profile information executed by the aircraft and driving the aircraft to run and guarantee activities;
the aircraft configuration model is used for describing basic composition information of an aircraft and failure rates, average maintenance time, failure detection rate, failure isolation rate, life prediction advance, life prediction precision and preventive maintenance interval parameters of various subsystems;
The maintenance model is used for describing how the aircraft performs repair maintenance, preventive maintenance and predictive maintenance under the support of prediction and health management;
the guarantee resource model is used for describing a storage and supply mode and a scheduling rule of various aviation material spare parts required by guaranteeing normal flight of an aircraft;
the guarantee organization model is used for describing various guarantee entities and interaction relations among the various guarantee entities involved in the operation process of the aircraft.
Optionally, the simulating the workflow of the aircraft security process by using a preset system simulation method to obtain simulation process data information includes:
s31, simulating the work flow of the aircraft guarantee process by using a discrete event driving method to obtain a task list;
s32, generating the initial state of the aircraft and the fault occurrence time through random sampling according to the task list, and obtaining simulation process data information.
Optionally, the processing the simulation process data information by using a mathematical statistics method to obtain an aircraft guarantee efficiency index includes:
s41, processing the aircraft security process data information by using an availability calculation model to obtain availability;
The usage availability calculation model is as follows:
wherein A is O For availability, OT is working time, ST is standby time, TCM is repair maintenance time, TPM is preventive maintenance time, ALDT is management and guarantee delay time;
s42, processing the aircraft guarantee process data information by using a lifting rate calculation model to obtain lifting rate;
the overhead rate calculation model is as follows:
wherein SGR is the overhead rate, D i For the total number of days of play, n is the total number of days of play, m i For the number of aircraft to be launched per day, T FL For the number of hours an aircraft can fly per day, T DU Average number of hours per flight for aircraft, T GM The ground taxi time per time is averaged for the aircraft,T TA preparation time for aircraft to restart, T CM For average repairable repair time per take-out of aircraft, T PM For average preventive maintenance time per outgoing train of aircraft, T AB For the average fight damage repair time per moving frame time, T SM Average replenishment time per overhead;
s43, processing the aircraft security process data information by using a task success rate calculation model to obtain a task success rate;
the task success rate calculation model is as follows:
Where MCSP is the task success rate.
Optionally, the adjusting the performance index information of the prediction and the health management to obtain the influence degree information of the performance index information of each prediction and the health management on the guarantee efficiency includes:
s51, setting a change range and a change step length of the fault detection rate, the fault isolation rate, the life prediction advance, the life prediction precision and the preventive maintenance interval information;
s52, changing the performance index information of prediction and health management according to the change step length each time, fixing the performance index information of other prediction and health management, and obtaining the guarantee performance index of the airplane by using a sensitivity analysis method;
and S53, calculating the average change rate of the performance indexes of the aircraft on different predictions and health management, and sorting from large to small according to the average change rate to obtain the influence degree information of the performance index information of each prediction and health management on the performance.
Example two
Referring to fig. 2, fig. 2 is a flowchart illustrating another method for determining performance indexes of prediction and health management of an aircraft according to an embodiment of the invention. The method for determining the performance index of the prediction and health management of the aircraft described in fig. 2 is applied to the simulation and evaluation of the performance evaluation of the operation guarantee process of the aircraft, which is not limited in the embodiment of the invention. As shown in fig. 2, the aircraft prediction and health management performance index determination method may include the following operations:
Step one: and building a task model according to the task planning data of the aircraft. In this embodiment, a total of 12 aircraft are required to perform tasks, at least 4 aircraft are required to be continuously located in a designated task area within 30 days, wherein a single trip is left for 5 hours, each of the trip and return times is 1 hour, and the task execution time is 3 hours. Therefore, in order to keep 4 airplanes in place in the mission area, the next airplane will start 3 hours after the former airplane starts to ensure that the next airplane enters the mission area to execute the mission in relay when the former airplane returns from the mission area. The task requires the availability not to be lower than 90% and the task success rate not to be lower than 85%.
Step two: and building an aircraft configuration model according to the unit composition information, the general quality characteristics and the PHM performance parameters of the aircraft. In this embodiment, a system-level configuration model is established, including an avionics system, a flight control system, a power system, an electromechanical system, and a structure, and performance parameter values such as failure rate, average maintenance time, failure detection rate, failure isolation rate, life prediction advance, life prediction accuracy, and preventive maintenance interval of these systems are given.
Step three: and establishing a guarantee organization model of the airplane. In this embodiment, three solid models of a maintenance station, an aerial material warehouse, and a supplier are established. Wherein the repair station is a location for performing aircraft repair, the aircraft supplies aircraft with spare parts, and the suppliers are for repair of faulty parts and replenishment of spare parts.
Step four: and establishing a guarantee resource model of the aircraft. In this embodiment, a system-level spare part model is built, including avionics system spare parts, flight control system spare parts, power system spare parts, electromechanical system spare parts, and structural spare parts.
Step five: and (5) establishing repair models for repairing, preventing, predicting and the like. The flow of repair, preventive and predictive repair is shown in figures 3, 4 and 5.
Step six: and establishing a PHM initial scheme, performing guarantee simulation by a discrete event driving method and a Monte Carlo sampling method, obtaining statistical results of the availability, the overhead rate and the task success rate, and forming an initial capacity benchmark. The simulation flow based on the discrete event driven method is shown in fig. 6, and the monte carlo sampling flow is shown in fig. 7. In this embodiment, PHM initial protocol: the fault detection rate is 0.8, the fault isolation rate is 0.8, the life prediction advance is 30 flight hours, the life prediction precision is 80%, and the preventive maintenance interval is more than or equal to 50 hours. Simulation results: the availability is 0.72, the overhead rate is 0.82, the task success rate is 0.75, and the task requirements are not met.
Step seven: and obtaining the influence degree of performance parameters such as fault detection rate, fault isolation rate, life prediction advance, life prediction precision, preventive maintenance interval and the like on the utilization availability, the overhead rate and the task success rate index of the aircraft through sensitivity analysis. Taking the fault detection rate pair as an example, in the embodiment, the change range of the fault detection rate is set to be 0.8-0.98, and the change step length is set to be 0.06; the change range of the fault isolation rate is 0.8-0.98, and the change step length is 0.06; the variation range of the life prediction advance is 30-210, and the variation step length is 60; the variation range of the life prediction precision is 80% -90%, and the variation step length is 5%; the preventive maintenance intervals vary from 50, 100, 300. Based on the PHM initial scheme, changing one PHM performance index and fixing other PHM performance indexes according to the specified step length each time, and obtaining the guarantee performance index of the aircraft through simulation analysis. Then, calculating the average change rate of the guarantee efficiency index based on different PHM performance indexes, and sorting according to the average change rate from large to small, wherein the sensitivity sorting of the PHM performance indexes is as follows: fault isolation rate > fault detection rate > life prediction accuracy > preventive maintenance interval > life prediction advance.
Step eight: based on the variation range of the PHM performance index, a total of 4 x 3 = 576 PHM performance index combinations were simulated, PHM performance index combinations satisfying the use availability of not less than 90% and task success rate of not less than 85% were selected as shown in Table 1.
TABLE 1 guarantee efficacy under different PHM Performance index combinations
Example III
Referring to fig. 8, fig. 8 is a schematic structural diagram of an apparatus for determining performance index of prediction and health management of an aircraft according to an embodiment of the invention. The device for determining the performance index of the prediction and health management of the aircraft described in fig. 8 is applied to the simulation and evaluation of the performance evaluation of the operation guarantee process of the aircraft, which is not limited in the embodiment of the invention. As shown in fig. 8, the aircraft prediction and health management performance index determination apparatus may include the following operations:
s301, a data acquisition module is used for acquiring data information of an aircraft guarantee process and a workflow of the aircraft guarantee process;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
the performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
The aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
s302, a simulation model construction module is used for constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
s303, a workflow simulation module simulates the workflow of the aircraft guarantee process by using a preset system simulation method to obtain simulation process data information;
the simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
S304, a data processing module is used for processing the simulation process data information by using a mathematical statistics method to obtain an aircraft guarantee efficiency index;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
s305, an index evaluation module is used for adjusting the performance index information of prediction and health management in the aircraft operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and health management on the guarantee efficiency;
s306, an index combination module is used for combining the performance index information of the prediction and the health management according to the influence degree information to obtain a performance index information combination of the prediction and the health management;
s307, an index evaluation module is used for evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
Example IV
Referring to fig. 9, fig. 9 is a schematic structural diagram of another apparatus for determining performance index of prediction and health management of an aircraft according to an embodiment of the invention. The device for determining the performance index of the prediction and health management of the aircraft described in fig. 9 is applied to the simulation and evaluation of the performance evaluation of the operation guarantee process of the aircraft, which is not limited in the embodiment of the invention. As shown in fig. 9, the aircraft prediction and health management performance index determination apparatus may include the following operations:
A memory S401 storing executable program codes;
a processor S402 coupled with the memory S401;
the processor S402 invokes the executable program code stored in the memory S401 for performing the aircraft prediction and health management performance index determination methods as described in embodiments one and two.
Example five
The embodiment of the invention discloses a computer-readable storage medium storing computer instructions for electronic data exchange, wherein the computer instructions, when invoked, are used for executing the aircraft prediction and health management performance index determination methods as described in the first and second embodiments.
The apparatus embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.
Finally, it should be noted that: the embodiment of the invention discloses a method and a device for determining performance indexes of airplane prediction and health management, which are disclosed by the embodiment of the invention only as a preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (8)
1. A method for determining performance indicators of prediction and health management of an aircraft, the method comprising:
s1, acquiring data information of an aircraft guarantee process and an aircraft guarantee process workflow;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
the performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
The aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
s2, constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
s3, simulating the work flow of the aircraft guarantee process to obtain simulation process data information;
the simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
S4, processing the simulation process data information to obtain airplane guarantee efficiency indexes;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
s5, adjusting the performance index information of the prediction and health management in the airplane operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and health management on the guarantee efficiency;
s6, combining the predicted and health-managed performance index information according to the influence degree information to obtain a predicted and health-managed performance index information combination;
s7, evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
2. The method for determining performance indexes of prediction and health management of an aircraft according to claim 1, wherein the task model is used for describing task profile information of the aircraft, and driving operation guarantee activities of the aircraft;
The aircraft configuration model is used for describing basic composition information of an aircraft and failure rates, average maintenance time, failure detection rate, failure isolation rate, life prediction advance, life prediction precision and preventive maintenance interval parameters of various subsystems;
the maintenance model is used for describing how the aircraft performs repair maintenance, preventive maintenance and predictive maintenance under the support of prediction and health management;
the guarantee resource model is used for describing a storage and supply mode and a scheduling rule of various aviation material spare parts required by guaranteeing normal flight of an aircraft;
the guarantee organization model is used for describing various guarantee entities and interaction relations among the various guarantee entities involved in the operation process of the aircraft.
3. The method for determining performance index of prediction and health management of an aircraft according to claim 1, wherein the simulating the workflow of the aircraft security process to obtain the simulated process data information comprises:
s31, simulating the work flow of the aircraft guarantee process to obtain a task list;
s32, generating the initial state of the aircraft and the fault occurrence time through random sampling according to the task list, and obtaining simulation process data information.
4. The method for determining performance index of prediction and health management of an aircraft according to claim 1, wherein the processing the simulation process data information to obtain performance index of guarantee of the aircraft comprises:
s41, processing the aircraft security process data information by using an availability calculation model to obtain availability;
the usage availability calculation model is as follows:
wherein A is O For availability, OT is working time, ST is standby time, TCM is repair maintenance time, TPM is preventive maintenance time, ALDT is management and guarantee delay time;
s42, processing the aircraft guarantee process data information by using a lifting rate calculation model to obtain lifting rate;
the overhead rate calculation model is as follows:
wherein SGR is the overhead rate, D i For the total number of days of play, n is the total number of days of play, m i For the number of aircraft to be launched per day, T FL For the number of hours an aircraft can fly per day, T DU Average number of hours per flight for aircraft, T GM For average ground taxi time of aircraft, T TA Preparation time for aircraft to restart, T CM For average repairable repair time per take-out of aircraft, T PM For average preventive maintenance time per outgoing train of aircraft, T AB For the average fight damage repair time per moving frame time, T SM Average replenishment time per overhead;
s43, processing the aircraft security process data information by using a task success rate calculation model to obtain a task success rate;
the task success rate calculation model is as follows:
where MCSP is the task success rate.
5. The method for determining performance indexes of prediction and health management of an aircraft according to claim 1, wherein the adjusting the performance index information of prediction and health management to obtain the influence degree information of the performance index information of prediction and health management on the guarantee efficiency comprises:
s51, setting a change range and a change step length of the fault detection rate, the fault isolation rate, the life prediction advance, the life prediction precision and the preventive maintenance interval information;
s52, changing the performance index information of prediction and health management according to the change step length each time, fixing the performance index information of other prediction and health management, and obtaining the guarantee performance index of the airplane by using a sensitivity analysis method;
and S53, calculating the average change rate of the performance indexes of the aircraft on different predictions and health management, and sorting from large to small according to the average change rate to obtain the influence degree information of the performance index information of each prediction and health management on the performance.
6. An aircraft predictive and health management performance index determination apparatus, the apparatus comprising:
the data acquisition module is used for acquiring data information of the aircraft guarantee process and the workflow of the aircraft guarantee process;
the aircraft guarantee process data information comprises aircraft general quality characteristic parameter information, guarantee organization mode and management mechanism information, guarantee resource configuration information and performance index information of prediction and health management;
the performance index information of the prediction and health management comprises fault isolation rate, fault detection rate, life prediction precision, preventive maintenance interval and prediction advance;
the aircraft security process workflow comprises a pre-flight preparation, task execution, repair maintenance, preventive maintenance and predictive maintenance workflow;
the simulation model construction module is used for constructing an airplane operation guarantee simulation model according to the airplane guarantee process data information;
the aircraft operation guarantee simulation model comprises a task model, an aircraft configuration model, a maintenance model, a guarantee resource model and a guarantee organization model;
the workflow simulation module is used for simulating the workflow of the aircraft guarantee process by using a preset system simulation method to obtain simulation process data information;
The simulation process data information comprises working time, standby time, repairing maintenance time, preventive maintenance time, management and guarantee delay time, a take-off rate, total take-off times of the ith day, total take-off days, the number of aircrafts which can take off each day, the number of aircrafts which can fly each day, the average number of aircrafts per flight hours, the average ground taxi time of each aircraft, the preparation time for taking off the aircrafts again, the average repairing maintenance time of each take-off time of the aircraft, the average preventive maintenance time of each take-off time of the aircraft, the average fight damage repair time of each take-off time and the average replenishment time of each take-off time;
the data processing module is used for processing the simulation process data information by utilizing a mathematical statistics method to obtain aircraft guarantee efficiency indexes;
the aircraft guarantee efficiency index comprises use availability, a running gear rate and a task success rate;
the index evaluation module is used for adjusting the performance index information of the prediction and the health management in the airplane operation guarantee simulation model to obtain the influence degree information of the performance index information of each prediction and the health management on the guarantee efficiency;
The index combination module is used for combining the performance index information of the prediction and the health management according to the influence degree information to obtain a performance index information combination of the prediction and the health management;
the index evaluation module is used for evaluating the performance index information combination of the prediction and the health management and the aircraft guarantee efficiency index, judging whether the guarantee efficiency requirement is met, and outputting the performance index information combination of the prediction and the health management if the guarantee efficiency requirement is met; and if the requirements are not met, executing S5 until the requirements of ensuring the efficiency are met.
7. An aircraft predictive and health management performance index determination apparatus, the apparatus comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the aircraft prediction and health management performance index determination method of any one of claims 1-5.
8. A computer-storable medium storing computer instructions for use in the method of determining an aircraft prediction and health management performance index according to any one of claims 1 to 5 when called.
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