Airborne plunger pump return oil filter residual life prediction method based on pressure difference and temperature signals

Abstract

The invention provides an airborne plunger pump return oil filter residual life prediction method based on pressure difference and temperature signals, and belongs to the field of fluid, and the method mainly comprises the following steps: (A) return oil filter pressure difference characteristic modeling; (B) temperature and pressure difference data of the return oil filter are corrected and put in storage; (C) designing an oil return filter life prediction algorithm; and (D) developing an intelligent monitoring and diagnosis system. According to the method, the oil return filter is subjected to pressure difference characteristic modeling and calculation based on the working principle of the oil return filter, the blockage state of the oil return filter is represented by using the change rule of the pressure difference delta P, the service life of the oil return filter is monitored and diagnosed by developing an intelligent prediction algorithm, and the problem that the oil return filter of the aviation plunger pump cannot be monitored and is difficult to diagnose under the condition of no flow signal is solved.

Description

Technical Field

[0001] The invention belongs to the field of fluids and relates to a method for predicting the remaining service life of an airborne plunger pump return oil filter based on pressure difference and temperature signals. Background Art

[0002] The aviation plunger pump is the "heart" of the airborne hydraulic system, and its performance and reliability directly affect the safety and reliability of the aircraft. The return oil filter of the aviation plunger pump is used to filter metal debris, impurities, pollutants, etc. caused by wear during the operation of the plunger pump. As the aircraft's operating time increases, the return oil filter will inevitably deposit particulate pollutants. When the return oil filter is blocked to a certain extent, the pressure difference before and after the return oil filter will increase, and the shell return oil back pressure will continue to increase. At this time, if the bypass valve is not opened, the excessive return oil back pressure will cause the oil film of the internal friction pair of the plunger pump to become unstable, the wear will increase, and even the shell will rupture; if the bypass valve is opened, the particulate pollutants will directly enter the hydraulic system, causing the internal precision-matched running parts to get stuck, the lubrication performance will decrease, and the wear will increase. It can be seen that the return oil filter is crucial to the safe operation of the aviation plunger pump. At present, if the engine oil filter is blocked during the operation of the aircraft, according to the "Civil Aircraft Symptom Level Classification Method", the crew must stop the aircraft for inspection and replace the return oil filter, which directly affects the operating economy. According to statistics, engine maintenance costs account for about 40% of aircraft maintenance costs. Shutdowns to replace return oil filters will undoubtedly increase costs for airlines and reduce economic efficiency. Therefore, in order to address the problem that the status of aviation plunger pump return oil filters cannot be monitored and is difficult to diagnose, an intelligent monitoring and diagnosis system for aviation plunger pump return oil filters based on oil filter pressure difference is proposed. The system uses existing onboard sensors to monitor and evaluate the status of return oil filters without the need to install additional equipment. It can repair or replace return oil filters that are about to fail as needed, prevent and resolve potential failure risks, and ensure the reliability and safety of aviation plunger pump operations. Summary of the invention

[0003] (I) Purpose of the invention

[0004] The purpose of this invention is to propose an intelligent monitoring and diagnosis system based on the measurement signal of the oil filter of an airborne piston pump, in response to the urgency of monitoring the oil return filter and the difficulty of diagnosis. The inherent law between the pressure difference before and after the oil return filter and the degree of internal blockage of the oil return filter is explored, and the pressure difference characteristic modeling of the oil return filter, the contribution of the return oil temperature to the pressure difference, the intelligent identification of the maximum flow rate and the maximum pressure difference of a single flight, and the prediction method of the oil return filter life are carried out. An intelligent monitoring and diagnosis system for the maximum pressure difference of the oil return filter is developed, and an intelligent monitoring and diagnosis system based on the measurement signal of the oil filter of an airborne piston pump is proposed to provide support for the safe operation and maintenance of aviation plunger pumps.

[0005] (II) Technical solution

[0006] The technical solution of the present invention is: a method for predicting the remaining life of an airborne plunger pump return oil filter based on pressure difference and temperature signals, comprising the following steps:

[0007] (A) Modeling of oil return filter pressure difference characteristics;

[0008] (B) The return oil filter temperature and pressure difference data are corrected and stored;

[0009] (C) Design of oil return filter life prediction algorithm;

[0010] (D) Development of intelligent monitoring and diagnostic systems;

[0011] The method for modeling the differential pressure characteristics of the oil return filter described in step (A) is as follows:

[0012] (1) Analyze the oil filter pore size and oil filter length of the oil return filter to obtain the maximum oil filtering capacity;

[0013] (2) Establish an equivalent mathematical model of the oil return filter based on the equivalent throttling theory;

[0014] (3) Derive the oil return filter pressure difference relationship;

[0015] ΔP=k(Q,T)f(d) (Formula 1) In the formula, k(Q,T) is the determinable pressure difference coefficient, and f(d) is a function related to the oil pore size of the return oil filter, which is used to characterize the degree of blockage of the oil filter.

[0016] The method for correcting and storing the return oil filter temperature and pressure difference data in step (B) is as follows:

[0017] (1) Preliminarily set the pressure difference coefficient k(Q, T) based on the plunger pump onboard pressure difference and temperature sensor data;

[0018] (2) Calculate the return oil filter working time T for a single flight based on the pressure difference data;

[0019] (3) Based on the viscosity-temperature characteristics of the plunger pump hydraulic oil, the pressure difference coefficient k(Q, T) is corrected, and the pressure difference and flow rate change curves over time are drawn;

[0020] (5) Intelligently identify the maximum pressure difference value corresponding to the maximum flow rate, and enter the maximum pressure difference ΔP and working time T in each flight into the database.

[0021] The design method of the oil return filter life prediction algorithm described in step (C) is as follows:

[0022] (1) Set the maximum allowable pressure difference ΔP according to the oil return filter's oil filtering capacity max ;

[0023] (2) Extract the historical maximum pressure difference-flight duration point set (ΔP, T) based on the established database;

[0024] (3) Intelligent law recognition is performed on the maximum pressure difference-flight duration point set, the maximum pressure difference change law is analyzed, and the maximum pressure difference distribution outside the database point set (ΔP m , t m );

[0025] (4) Based on the predicted maximum pressure difference variation law, calculate the maximum allowable pressure difference value ΔP of the return oil filter max The corresponding flight time t max , calculate the remaining life of the return oil filter t res ;

[0026] The method for developing the intelligent monitoring and diagnostic system described in step (D) is as follows:

[0027] (1) Analyze the characteristics of the return oil filter and hydraulic oil, and establish a pressure difference characteristic model within the system;

[0028] (2) Develop a data processing system that generates a corrected pressure difference and flow rate curve based on the viscosity-temperature characteristics, intelligently identifies the maximum pressure difference and enters it into the database;

[0029] (3) Design an algorithm to predict the life of the oil return filter, perform intelligent diagnosis on the point set in the database, predict the change law of the maximum pressure difference of the oil return filter, and calculate the remaining life;

[0030] (4) Develop a return oil filter life monitoring and diagnosis system. After the flight, the system provides the remaining life based on a prediction algorithm. The user inputs the next flight duration, predicts the future maximum pressure difference value, and determines whether the return oil filter needs to be replaced.

[0031] (5) Test / simulate the system and repeat steps (B) and (C) after each flight to verify the monitoring and diagnosis effects of the maximum pressure difference and the remaining life. If the accuracy requirements are not met, optimize and modify the model.

[0032] (III) Beneficial effects of the present invention

[0033] The beneficial effects of the present invention are as follows: the present invention provides a method for predicting the remaining life of an airborne plunger pump return oil filter based on pressure difference and temperature signals. The method takes the status monitoring of the return oil filter of the airborne hydraulic system as the starting point, analyzes the relationship between the remaining life of the return oil filter and the maximum pressure difference according to the pressure difference characteristics of the return oil filter, optimizes the design of the return oil filter status monitoring and diagnosis system, and finally verifies the reliability of the system through simulation. The current shortcomings of aviation plunger pump return oil filters, such as difficulty in monitoring and inability to diagnose, are solved. The present invention effectively utilizes existing airborne sensors to realize return oil filter status monitoring and diagnosis without flow signals. The remaining life prediction accuracy can reach half a flight sortie, and it is applicable to a wide range of scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flowchart of the remaining service life prediction method of the return oil filter of an airborne plunger pump based on pressure difference and temperature signals.

[0035] Figure 2 It is a schematic diagram of an airborne sensor of the method for predicting the remaining life of an airborne plunger pump return oil filter based on pressure difference and temperature signals of the present invention.

[0036] Figure 3 This is a schematic diagram of the remaining service life prediction method of an airborne plunger pump return oil filter based on pressure difference and temperature signals of the present invention.

[0037] Figure 4 It is a pressure difference and flow rate change curve of a single flight in an embodiment of the present invention.

[0038] Figure 5 It is a schematic diagram of oil return filter life prediction based on interpolation in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention is specifically described below in conjunction with a simulation example.

[0040] This embodiment takes the oil return filter of a certain aviation plunger pump as the research object. The oil return system consists of an oil return pipeline, an oil return filter, an oil return sensor and an oil return radiator. The intelligent prediction method of the oil return filter in this embodiment adopts the Lagrange interpolation method, which is only a special case of the intelligent prediction of the maximum pressure difference of the oil return filter. Figure 1 The following is a working diagram of the intelligent monitoring and diagnosis system based on the airborne plunger pump oil filter measurement signal of the present invention. The specific implementation steps are as follows:

[0041] (A) Modeling of oil return filter pressure difference characteristics;

[0042] Based on the operating conditions of the aviation plunger pump return oil filter (temperature range 10℃-110℃, return oil pressure 0.45-0.65MPa), a suitable type of return oil filter is selected, and the return oil filter is equivalent to a throttling hole. The equivalent filter inner diameter d and the equivalent filter length L of this type of return oil filter are measured experimentally; then, according to the equivalent throttling hole flow formula, a mathematical model of the return oil filter pressure difference is established, and the relationship between the qualitative pressure difference and the return oil flow, return oil temperature, and oil flow area is analyzed, and the return oil pressure difference coefficient is preliminarily calculated.

[0043] (B) The return oil filter temperature and pressure difference data are corrected and stored;

[0044] The existing onboard sensors of aviation piston pumps are return oil filter pressure difference sensor and return oil temperature sensor, and their installation positions are as follows: Figure 2 As shown. Calculate the working time t according to the start and end points of the return oil filter pressure difference; enter the temperature and pressure difference data into the database, correct the return oil pressure difference coefficient based on the viscosity-temperature characteristics of the hydraulic oil, draw the flow change curve and the pressure difference change curve, and extract the maximum flow Qmax The corresponding maximum return oil pressure difference AP is as follows: Figure 3 , Figure 4 shown.

[0045] (C) Design of oil return filter life prediction algorithm;

[0046] Based on the selection of the return oil filter, 1MPa is set as the critical value of the return oil filter failure: ΔP max =1MPa; perform Lagrange interpolation on the point set (ΔP, T) of the maximum return oil pressure difference and the working time under different sorties to obtain an interpolation curve. Based on the interpolation curve, analyze the rules between the elements in the point set, and predict the elements outside the point set. The flight time corresponding to the failure pressure difference is 873 hours, which is subtracted from the current flight time to obtain a remaining life of 273 hours.

[0047] (D) Development of intelligent monitoring and diagnostic systems;

[0048] An intelligent monitoring and diagnosis system is developed based on the life prediction algorithm of the return oil filter. The system automatically records the sensor data after each flight, intelligently extracts the corresponding pressure difference value at the maximum flow rate, and then adds the current flight data (ΔP n , t n ), and update the Lagrange interpolation equation to re-predict the remaining life. Figure 5 As shown in the figure, the blue line is the maximum pressure difference change curve of the j-th interpolation, which is somewhat different from the change law of the n-th interpolation. By comparing the prediction curves of adjacent flight sorties, the pressure difference coefficient and the interpolation constant term are corrected based on the deviation value to optimize the system accuracy.

Claims

1. A method for predicting the remaining life of an airborne plunger pump return oil filter based on pressure difference and temperature signals, characterized in that: The steps include: (A) Modeling of the differential pressure characteristics of the oil return filter; (B) The return oil filter temperature and pressure difference data are corrected and stored; (C) Design of oil return filter life prediction algorithm; (D) Development of intelligent monitoring and diagnostic systems.

2. The method for predicting the remaining life of an onboard plunger pump return oil filter based on pressure difference and temperature signals according to claim 1 is characterized in that: The pressure differential characteristic of the return oil filter described in step (A) is modeled as follows: the pressure differential before and after the return oil filter is affected by the size of its equivalent oil-passing pore size during operation. As the blockage degree of the return oil filter increases, the return oil pressure differential at the same flow rate continues to increase. It can be regarded as an equivalent throttling hole to calculate its pressure differential characteristic. The specific method is as follows: (1) Calculate the size parameters of the return oil filter. The diameter and on-off of the oil-passing pores inside the return oil filter determine the filtering capacity of the oil filter. Model the equivalent oil filter diameter d and the equivalent oil filter length L to determine the flow state of the fluid passing through; (2) Establish the relationship between the pressure difference before and after the return oil filter, and rewrite the pressure difference relationship into a relationship that represents the degree of blockage of the return oil filter. Based on the viscosity-temperature characteristics of hydraulic oil, it is known that the dynamic viscosity of hydraulic oil decreases as the temperature increases. Rewriting the pressure difference relationship yields: ΔP=k(Q,T)f(d) (Formula 1) Where ΔP is the pressure difference before and after the return oil filter, k(Q,T) is the determinable pressure difference coefficient, which is used to characterize the relationship between the pressure difference and the flow rate, and f(d) is a function related to the oil pore size of the return oil filter, which is used to characterize the degree of blockage of the oil filter. (3) Establish the flow-pressure difference characteristic of the return oil filter. Equivalently convert the return oil filter into a throttling elongated hole, and obtain the relationship between the flow and pressure difference through the return oil filter: In the formula, μ is the dynamic viscosity of the oil, and l is the length of the orifice, i.e., the equivalent length. It can be seen that the factors that affect the maximum pressure difference of the return oil filter are the maximum flow rate q max , dynamic viscosity μ and the diameter of the oil-passing hole d.

3. The method for predicting the remaining life of an onboard plunger pump return oil filter based on pressure difference and temperature signals according to claim 1 is characterized in that: The correction and storage of the return oil filter temperature and pressure difference data in step (B) is as follows: during different flights of the aircraft, the return oil temperature, return oil flow rate and oil filtering time through the return oil filter are considered to affect the pressure difference. In order to make an accurate life prediction, the flight data of the return oil filter is stored in the database. The specific method is as follows: (1) Modeling the differential pressure characteristics of the oil return filter according to claim 2, analyzing the expected operating conditions of the oil return filter, and initially setting its differential pressure coefficient k(Q,T); (2) Read and input the return oil filter pressure differential sensor data of different flight sorties, determine the working time of the return oil filter of each sortie based on the pressure differential, and draw a curve of pressure differential change over time; (3) Read and input the return oil filter temperature sensor data of different flight sorties, and based on the viscosity-temperature characteristics of the hydraulic oil of this model, correct the pressure difference coefficient k(Q,T) and the pressure difference curve; (4) Identify the maximum differential pressure value during the flight. Based on the working principle of the return oil filter, the maximum differential pressure generally occurs at the maximum flow rate. The return oil filter flow change curve is drawn based on the corrected differential pressure coefficient k(Q,T), and the maximum differential pressure ΔP corresponding to the maximum flow rate is intelligently identified; (5) The maximum pressure difference Δp and working time T of the return oil filter in each flight are entered into the database.

4. The method for predicting the remaining life of an onboard plunger pump return oil filter based on pressure difference and temperature signals according to claim 1 is characterized in that: The life prediction algorithm of the return oil filter described in step (C) is designed as follows: using the maximum pressure difference ΔP-operating time T curve in historical flight sorties, predicting the maximum pressure difference change trend, and judging the remaining life of the return oil filter based on the maximum allowable pressure difference. The specific method is as follows: (1) Based on the return oil filter pressure differential characteristic modeling in claim 2, the maximum pressure differential ΔP that the return oil filter can withstand is set max ; (2) According to the flight pressure difference-temperature data in claim 3, the maximum pressure difference ΔP and working time T data in different flights are extracted to form the maximum pressure difference-flight duration point set: (ΔP,T): (ΔP1,t1), (ΔP2,t2), (ΔP3,t3),…, (ΔP n ,t n ); (3) Use intelligent algorithms to diagnose the (ΔP, T) point set, find the change rules of the elements in the point set based on the intelligent algorithm, and diagnose the points t between the elements in the point set and outside the point set. m Make a prediction and calculate the maximum pressure difference ΔP that will occur under this flight sortie m ; (4) Predict the remaining life of the return oil filter. Based on the predicted (ΔP, T) law, predict the limit pressure difference ΔP of the return oil filter. max The flight time is t max , calculate the remaining life of the return oil filter: t res =t max -t m。 5. The method for predicting the remaining service life of an onboard plunger pump return oil filter based on pressure difference and temperature signals according to claim 1, characterized in that: The intelligent monitoring and diagnosis system described in step (D) is developed as follows: (1) According to the return oil filter pressure difference characteristic modeling required by claim 2, based on the return oil filter configuration parameters, hydraulic oil model and rated operating conditions of the aviation piston pump, the return oil filter mathematical model and oil viscosity-temperature characteristics are established in the system, and the return oil filter pressure difference coefficient k(Q,T) is preliminarily calculated; (2) Correcting and storing the return oil filter temperature and pressure difference data in accordance with claim 3, correcting the pressure difference based on the temperature data, drawing a pressure difference and return oil flow rate change curve, intelligently identifying the maximum pressure difference ΔP, and entering it and the flight duration T into the system database; (3) According to the design of the oil return filter life prediction algorithm in claim 4, an intelligent prediction algorithm is developed to identify the rules of the maximum pressure difference-flight duration point set (ΔP, T) and predict the maximum pressure difference (ΔP) corresponding to the flight duration outside the point set. m ,t m ); Based on the predicted maximum pressure difference change law, evaluate the blockage degree of the return oil filter and calculate the remaining life t res ; (4) Develop an intelligent diagnostic system. After each flight, the system updates the database and corrects the maximum pressure difference change pattern. The user enters the flight time t of the next flight. m , intelligently predict the maximum pressure difference ΔP of the return oil filter for the next flight m , if the critical pressure difference ΔP is exceeded max , it will prompt to replace the return oil filter; otherwise, it will provide the remaining life t predicted based on the maximum pressure difference law res For reference; (5) Continuously optimize the intelligent algorithm based on updated data. After each flight, the intelligent diagnosis and monitoring system repeats steps (B) and (C), compares the maximum pressure difference predicted by the system with the maximum pressure difference during the actual flight, and corrects the system pressure difference coefficient based on the residual to optimize the prediction accuracy.

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