Engine wear monitoring method, monitoring system, readable medium and gas turbine engine

Abstract

The invention relates to an engine wear monitoring method, a monitoring system, a readable medium, a gas turbine engine and a test system. The monitoring method comprises the following steps: S1, receiving an original signal output by a metal filing sensor for monitoring lubricating oil; s2, carrying out modulation and demodulation on the original signal to eliminate background noise and form an intermediate signal; s3, converting a signal amplitude characteristic of the intermediate signal in a unit time interval into an energy characteristic; and S4, carrying out self-adaptive sliding window model statistics on the energy characteristics so as to judge the metal filing condition of the engine lubricating oil.

Description

Technical Field

[0001] The invention relates to an engine wear monitoring method, a monitoring system, a readable medium and a gas turbine engine. Background Art

[0002] Engine wear monitoring, such as wear monitoring of gas turbine engines, can be performed using methods based on lubricating oil analysis. In the prior art, there are offline monitoring and online monitoring technologies. The physical properties of metal shavings in engine lubricating oil are monitored using optical, electrical, magnetic and other analytical methods to diagnose the wear properties, wear types and wear locations of the engine's transmission system and friction pairs with mutual motion.

[0003] In a comparative method for identifying metal chip particles in engine lubricating oil, a lubricating oil metal chip sensor output signal processing method based on the principle of amplitude modulation wave demodulation is used. This method weakens the interference in the sensor output signal through a bandpass filter; then demodulates and amplifies the signal, collects the demodulated and amplified signal, and converts it into a digital signal; metal chip calibration is achieved by recording the positive maximum value, negative minimum value and zero point position between the digital signal within a certain time range, and the particle size is calculated.

[0004] However, the inventors found that although the above comparison scheme can filter noise to a certain extent and identify metal chip particles through digital signals. But in the actual engine operation process, the working conditions are more complicated, and there is a situation where the background noise is too large. At this time, the amplitude of the digital signal segment containing metal chip particles is relatively close to the background noise signal segment, resulting in a decrease in the difference between metal chips and background noise, which leads to the risk of false alarms and missed detections, affecting the accuracy of metal chip detection. In addition, since the above comparison scheme needs to record the positive maximum value, negative minimum value and the zero point position between the two within a certain time range, under different lubricating oil flow rates, there are higher requirements for the selection of the time range. If the selection is inappropriate, the positive maximum value, negative minimum value or zero point may be missed or selected incorrectly, and the complete metal chip signal waveform cannot be recorded, affecting the identification of metal chip particles.

[0005] Therefore, the art needs a more accurate and reliable engine wear monitoring method that is more reliable for monitoring lubricating oil metal chips, especially when the engine operating conditions change or the background noise is large, and can still ensure the difference between the metal chip signal segment and the noise signal segment as much as possible, thereby achieving higher accuracy metal chip monitoring. Summary of the invention

[0006] An object of the present invention is to provide a method for monitoring engine wear.

[0007] An object of the present invention is to provide a computer readable medium.

[0008] An object of the present invention is to provide an engine wear monitoring system.

[0009] An object of the present invention is to provide a gas turbine engine.

[0010] An object of the present invention is to provide a test system for a gas turbine engine.

[0011] According to the first aspect of the present invention, an engine wear monitoring method includes S1. receiving an original signal output by a metal chip sensor used to monitor lubricating oil; S2. modulating and demodulating the original signal to eliminate background noise and form an intermediate signal; S3. the signal amplitude characteristics of the intermediate signal within a unit time interval are converted into energy characteristics; S4. the energy characteristics are subjected to adaptive sliding window model statistics to determine the metal chip condition of the engine lubricating oil.

[0012] The monitoring method introduced in the above embodiment converts the intermediate signal after the original signal is denoised, modulated and demodulated into an energy signal, converts the amplitude characteristics of the digital signal within a unit time interval into an energy characteristic, and detects metal chips in combination with an adaptive sliding window model, and uses the distribution of signal energy as a basis for identifying metal chips, thereby increasing the distinction between metal chip signals and noise signals, so that under variable operating conditions or when the background noise is large, the difference between the metal chip signal segment and the noise signal segment can still be ensured, thereby achieving high-accuracy metal chip monitoring, thereby improving engine wear monitoring, especially the accuracy of online wear monitoring results.

[0013] In one or more embodiments, in S2, an envelope detection method is used to perform amplitude modulation on the original signal, and the intermediate signal is obtained by demodulation and restoration.

[0014] In one or more embodiments, in S3, the energy characteristic of the intermediate signal is the sum of squares of discrete values. For a discrete signal x=(x1, x2, ..., x n ), the corresponding energy characteristics satisfy the following formula:

[0015]

[0016] Wherein, n is the unit time interval ΔT corresponding to the original signal multiplied by the sampling frequency f.

[0017] In one or more embodiments, in said S4, it includes: S41. Setting the sliding window length: used to count the data in the sliding window; S42. Setting the number of intervals; S43. Obtaining the maximum and minimum values ​​of the data in the sliding window, and dividing the data in the sliding window into intervals with upper and lower bounds of the maximum and minimum values ​​respectively, and counting the number of data points in each interval; S44. Performing metal chip energy concentration judgment on the data in each sliding window, if the amount of data contained in the energy minimum interval in the sliding window is greater than the energy concentration threshold, it is considered that the data in the sliding window belongs to the data of metal chip energy concentration, and the position index of the sliding window is marked as the metal chip position index; S45. If among the multiple metal chip position indexes, the number of the multiple continuous metal chip position indexes is not less than the metal chip particle judgment threshold, it is judged that among the multiple continuous metal chip position indexes, metal chip particles appear within the range of the first metal chip position index and the last metal chip position index.

[0018] In one or more embodiments, in said S4, it further includes: S46. For the metal chip particle found in S45, according to the first metal chip position index in the continuous plurality of metal chip position indexes, determining the appearance time of the metal chip, satisfying the following formula:

[0019] T = ID * △ T / f;

[0020] Wherein, ΔT and f are the unit time interval ΔT and sampling frequency f corresponding to the original signal, ID is the first metal chip position index, and is the sampling number corresponding to the metal chip position index.

[0021] In one or more embodiments, in said S4, it further includes: S47. For the metal chip particles found in S45, the equivalent particle size of the metal chip particles is obtained according to the voltage peak sewing corresponding to the continuous plurality of metal chip position indexes.

[0022] In one or more embodiments, the interval is a histogram interval.

[0023] A computer readable medium according to a second aspect of the present invention has a computer program thereon, and the program is executed by a processor to implement the steps of the monitoring method as described in the first aspect.

[0024] According to a third aspect of the present invention, an engine wear monitoring system comprises: a memory for storing instructions executable by a processor; and a processor for executing the instructions to implement the steps of the monitoring method as described in the first aspect.

[0025] In one or more embodiments, the monitoring system further comprises a filtering circuit for modulating the original signal.

[0026] In one or more embodiments, the monitoring system is connected to a display module for displaying the metal chip condition of the engine lubricating oil and / or the wear condition of the engine determined by the processor.

[0027] In one or more embodiments, the processor and / or memory are integrated into a full authority digital engine controller.

[0028] According to a fourth aspect of the present invention, a gas turbine engine has a metal chip sensor for monitoring lubricating oil, and during the operation of the gas turbine engine, the monitoring method as described in the first aspect is performed; or, the gas turbine engine also includes an engine wear monitoring system as described in the third aspect.

[0029] According to a gas turbine engine test system of a fifth aspect of the present invention, during a test of the gas turbine engine, the monitoring method as described in the first aspect is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and other features, properties and advantages of the present invention will become more apparent through the following description in conjunction with the accompanying drawings and embodiments, in which:

[0031] Figure 1 It is a flow chart of an engine wear monitoring method according to an embodiment of the present application.

[0032] Figure 2 It is a flow chart of an engine wear monitoring method according to another embodiment of the present application.

[0033] Figure 3 It is a schematic block diagram of the structure of an engine wear monitoring system according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] The present invention is further described below in conjunction with specific embodiments and drawings. More details are elaborated in the following description to facilitate a full understanding of the present invention. However, the present invention can obviously be implemented in a variety of other ways different from the description herein. Those skilled in the art can make similar generalizations and deductions based on actual application situations without violating the connotation of the present invention. Therefore, the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0035] At the same time, the present application uses specific words to describe the embodiments of the present application. The reference to "embodiment" herein means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0036] It is understood that flow charts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that, according to the actual situation, the previous or following operations are not necessarily performed precisely in order. Other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0037] It should be noted that in the following embodiments, the gas turbine engine described in the following embodiments takes an aircraft and its turbofan engine as an example, but is not limited to this. For example, ships and their gas turbine engines, and ground gas turbines may also be applicable to the wear monitoring method described in the following embodiments.

[0038] refer to Figure 1 as well as Figure 3 As shown, in some embodiments, the engine wear monitoring method may include the following steps:

[0039] S1. Receive the original signal output by the metal chip sensor for monitoring the lubricating oil;

[0040] S2 modulates and demodulates the original signal to eliminate background noise to form an intermediate signal;

[0041] S3. The signal amplitude characteristics of the intermediate signal within a unit time interval are converted into energy characteristics;

[0042] S4. The energy feature is statistically analyzed using an adaptive sliding window model to determine the metal chip condition of the engine lubricating oil.

[0043] In S1, the metal chip sensor can monitor the wear condition of the lubricating oil system online, and generate an original signal when metal chips appear, forming an original signal containing metal chip information. The metal chip sensor can be, for example, an inductive sensor, and the principle can be based on the electromagnetic induction principle to generate a voltage signal when metal chips pass by.

[0044] In S2, the noise of the original signal collected and output by the metal chip sensor 105 is filtered out, and its main noise factors are bubbles in the lubricating oil and vibration factors of the engine operation. In addition to the metal chip particles generated by wear, there are also bubbles suspended in the oil in the lubricating oil system. The bubbles suspended in the oil will interfere with the identification of particles. In S2, a method of unified noise filtering can be adopted, and the envelope detection signal processing method is used for unified filtering. The particle identification accuracy is further improved at the signal processing level, the false alarm rate of the detection result is lowered, and a more accurate and reliable particle identification result is obtained. For example, a corresponding filtering circuit 104 can be designed, such as a digital bandpass filter to filter the output signal of the sensor. The digital bandpass filter can be a finite impulse response filter (Finite Impulse Response, FIR, also known as a non-recursive filter), thereby modulating the original signal. The filtered signal is envelope processed and demodulated to restore the measurement signal.

[0045] In S3, preferably, the energy characteristic of the intermediate signal is the sum of squares of discrete values. For a discrete signal x=(x1, x2, ..., x n ), the corresponding energy characteristics satisfy the following formula:

[0046]

[0047] Wherein, n is the unit time interval ΔT corresponding to the original signal multiplied by the sampling frequency f. Preferably, in some embodiments, the unit time interval satisfies the following formula:

[0048] △T=L s / v;

[0049] Among them, the unit time interval △T corresponding to the original signal, L s is the axial length of the metal chip sensor, v is the speed of the metal chips passing through the sensitive space of the sensor; v changes with the flow rate of the lubricating oil.

[0050] The beneficial effect of the above embodiments is that the accuracy of online monitoring can be further improved. The principle is that the inventors have found that in actual engineering applications, the engine will experience different operating conditions. The factors of variable operating conditions will not only affect the noise floor level of the sensor output signal, but also further cause changes in the lubricating oil flow rate due to changes in the spindle speed, causing the characteristic waveform time span in the sensor output signal to change. These two changes will affect the stability of the algorithm. Generally speaking, the higher the spindle speed, the greater the lubricating oil flow rate. In the slow-running state, the lubricating oil flow rate decreases, and the two have a certain proportional relationship. The characteristic waveform time span is known, and the principle of setting the unit time interval in the signal energy threshold processing step is followed, that is, as close as possible but not less than the time it takes for the particles to pass through the sensor. Therefore, ideally, the unit time interval is set to L. s / v, and then calculate the signal energy in each time interval, then a single characteristic waveform will be converted into a single energy value data point, and the same is true for the noise signal segment. Therefore, the setting of the time interval completes the adaptability to changes in working conditions.

[0051] Preferably, in some embodiments, if the lubricating oil flow rate information is difficult to obtain in real time or import for calculation and processing, the lowest lubricating oil flow rate in the entire engine process can be used as the boundary condition to obtain the corresponding v, so as to obtain the maximum time interval to calculate the subsequent signal energy data. The inventors found that although this processing will reduce the difference between the particle signal segment and the noise signal segment to a certain extent, because the signal energy step is followed by the adaptive sliding window model statistics step of S4, it can still meet the needs of ferromagnetic particle signal detection and identification in actual engineering applications.

[0052] For S4, the "adaptive sliding window model" has a similar meaning to the definition in the field of data processing. The sliding window technology is used to segment the arriving data stream, divide the data stream into several windows and analyze them, which significantly improves the speed of mutation point detection and meets the real-time requirements of online detection. However, in the sliding window model, improper selection of window length will cause the problem of reduced mutation point detection accuracy. If the window is too long, the data fluctuations in the window will be masked, which will lead to reduced mutation point detection accuracy; if the window is too short, the amount of data is small and the information carried is small, which will also lead to reduced mutation point detection accuracy. Therefore, the selection of window length in the sliding window model is an important factor affecting the accuracy of data stream mutation point detection. In the adaptive sliding window model, the window length can be dynamically adjusted according to the detection process, so it is called an adaptive window model.

[0053] refer to Figure 2Preferably, in some embodiments, in S4, whether there are metal shaving particles can be determined by judging whether the signal energy in the sliding window has a polarization phenomenon. The principle is that the inventor found that when using histogram statistics, in the process of statistical data in the sliding window, the maximum and minimum values ​​of the data in the sliding window are used as upper and lower bounds to measure the distribution of data in the maximum range. When the sliding window contains particle signals, because its absolute value far exceeds the background noise value, the histogram statistics result will obtain that there are only a few data points in the highest interval, and most of the data points fall in the lowest interval, and the counts of several intervals in the middle are almost 0, showing an extreme polarization phenomenon; and when there is only noise in the sliding window, its histogram distribution is shown as data points in all intervals from low to high, although the proportion of the lowest interval is also large, but compared with the case of particles, this value is smaller, and the histogram statistics of noise also have a certain proportion in the middle several intervals, and will not show extreme polarization like the histogram of particles. Therefore, this extreme polarization phenomenon is used as an indicator for judging particles and noise.

[0054] The specific steps can be described as follows:

[0055] S41. Set the sliding window length: used to count the data in the sliding window;

[0056] It can be understood that the sliding window length is the amount of data in the sliding window. The length should be appropriate. It should not be too long. On the one hand, it is easy for granular signal points to be mixed in the sliding window. On the other hand, it is easy to break the extreme polarization and make the recognition result fuzzy. The sliding window length should not be too short, and the number of histogram intervals will not be small.

[0057] S42. Set the number of intervals;

[0058] It can be understood that the number of histogram intervals is set: the number of intervals directly determines the differentiation effect. If the number of intervals is small, the differentiation between particles and noise cannot be shown. If the number of intervals is too large, the intervals are divided too finely, which brings unnecessary difficulty and uncertainty to subsequent data processing.

[0059] S43. Obtain the maximum and minimum values ​​of the data in the sliding window, and divide the data in the sliding window into intervals with upper and lower bounds of the maximum and minimum values, respectively, and count the number of data points in each interval;

[0060] S44. Perform metal chip energy concentration determination on the data in each sliding window. If the amount of data contained in the energy minimum interval in the sliding window is greater than the energy concentration threshold, the data in the sliding window is considered to be data in the metal chip energy concentration, and the position index of the sliding window is marked as the metal chip position index;

[0061] Preferably, the inventors found that the energy concentration threshold generally needs to be set to 90%. The principle is that, after studying a large amount of experimental data, the inventors found that when there are no particle signal points, the data volume in the lowest interval is only 70% to 80%. Considering that the characteristic waveform under actual working conditions may be greater than the set unit time interval, resulting in the characteristic waveform being segmented, and the particle signal energy characteristic value is greater than 1, then when the histogram is counted, the data points included in the lowest interval will decrease slightly accordingly. Therefore, the threshold is set to above 90% to ensure the monitoring margin, that is, if the lowest interval meets the requirement of containing more than 90% of the data points, it is considered that there are particle signal points.

[0062] S45. If, among the plurality of metal chip position indexes, the number of the plurality of continuous metal chip position indexes is not less than the metal chip particle judgment threshold, it is determined that metal chip particles appear within the range between the first metal chip position index and the last metal chip position index among the plurality of continuous metal chip position indexes.

[0063] Preferably, in some embodiments, the time when the metal chips particles appear may be further determined by:

[0064] S46. For the metal chip particle found in S45, determine the appearance time of the metal chip according to the first metal chip position index in the continuous plurality of metal chip position indexes, satisfying the following formula:

[0065] T = ID * △ T / f;

[0066] Wherein, ΔT and f are the unit time interval ΔT and sampling frequency f corresponding to the original signal, ID is the first metal chip position index, and is the sampling number corresponding to the metal chip position index.

[0067] Preferably, in some embodiments, the equivalent particle size of the metal chip particles may be further determined by:

[0068] S47. For the metal chip particles found in S45, the equivalent particle size of the metal chip particles is obtained by sewing according to the voltage peaks corresponding to the continuous plurality of metal chip position indexes.

[0069] The principle is that the inventors have studied a large amount of test data and found that the relationship between the particle size and the peak-to-peak voltage test data of the particle characteristic waveform in the signal can be obtained through the test data, and the particle size can be solved according to the intermediate signal. The fitting formula can be in the form of y=ax b The power function form of the curve is fitted, where y represents the peak-to-peak value of the output voltage and x represents the equivalent diameter of the particle.

[0070] It can be understood that the monitoring method introduced in the above embodiment is described from the perspective of post-test data analysis for ease of understanding. It is an analysis performed on complete experimental data. Since there is a premise of known complete data, it is similar to an offline wear monitoring. The data analysis can be manual statistical analysis, or it can be automatically processed by scripting in programming languages ​​such as VBA and Python. However, it can be understood that the monitoring method introduced in the above embodiment can also be used for online wear monitoring. As described above, the length of the sliding window and the number of data intervals can be adaptively adjusted by setting the time interval, thereby ensuring that online monitoring, especially online monitoring under variable working conditions, has good accuracy.

[0071] As mentioned above, please refer to Figure 3 As shown, in some embodiments, the present application also provides an engine wear monitoring system 100, including a memory 101 and a processor 102, the memory 101 is used to store instructions executable by the processor, and the processor 102 is used to execute the instructions to implement the steps of the monitoring method introduced in the above embodiment.

[0072] In some embodiments, the monitoring system 100 may also be connected to a display module 103 for displaying the metal shavings condition of the engine lubricating oil and / or the wear condition of the engine determined by the processor 102, so that the gas turbine engine operator, generally the pilot, can know the current wear condition of the engine in real time, or the test personnel of the gas turbine engine can check the wear condition of the engine in real time during the gas turbine engine test. The display module 103 may have a variety of presentation forms, for example, in an airplane, the display module 103 may be a dashboard or a display screen, or even a head-up display (HUD) of a pilot's helmet.

[0073] The memory 101 and / or processor 102 of the monitoring system 100 described above may be integrated into a full authority digital engine controller (FADEC), so that the control system of the gas turbine engine has a high degree of integration. However, this is not a limitation, and the above-mentioned memory 101 and processor 102 are not limited to a specific memory or processor. In some cases, both the memory 101 and the processor 102 may have a distributed structure, for example, they may include a memory and a processor located on the aircraft side and the background cloud, respectively, and the aircraft side and the background cloud jointly implement the above-mentioned monitoring method. Furthermore, in an embodiment adopting a distributed structure, each step can adjust the specific execution terminal according to actual conditions, and the specific scheme for implementing each step on a specific terminal should not unduly limit the scope of protection of the present invention. It can be understood that the processor 101 in the previous embodiment is a combination of one or more of a system on a chip (SOC), a microcontroller, a microprocessor (e.g., a single-chip microcomputer), a reduced instruction set computer (RISC), an application-specific integrated circuit (ASIC), an application-specific instruction integrated processor (ASIP), a central processing unit (CPU), a graphics processing unit (GPU), a physical processing unit (PPU), a microcontroller unit, a digital signal processor (DSP), a field programmable gate array (FPGA), an advanced RISC machine (ARM), a programmable logic device (PLD), any circuit or processor capable of performing one or more functions, etc.

[0074] According to another aspect of the present invention, a computer-readable medium is also provided.

[0075] The computer-readable medium provided by the present disclosure has computer instructions thereon. When the computer instructions are executed by a processor, the program can be executed by the processor to implement the steps executed by the program in the monitoring method described in the above embodiment.

[0076] Based on the above introduction, it can be understood that the monitoring method and / or monitoring system 100 introduced in the above embodiment can be arranged in a gas turbine engine having a metal chip sensor for monitoring lubricating oil, so as to realize accurate real-time monitoring of the wear condition of the gas turbine engine during actual operation, and can also be arranged in a test system of the gas turbine engine, so as to realize accurate real-time monitoring of the wear condition during the test.

[0077] The beneficial effect of the scheme introduced in the above embodiment is that by converting the intermediate signal after the original signal is de-noised, modulated and demodulated into an energy signal, converting the digital signal amplitude characteristics within a unit time interval into energy characteristics, and combining the adaptive sliding window model to detect metal chips, the distribution of signal energy is used as the basis for identifying metal chips, thereby increasing the distinction between metal chip signals and noise signals, so that under variable working conditions or when the background noise is large, the difference between the metal chip signal segment and the noise signal segment can still be guaranteed, and metal chip monitoring with high accuracy can be achieved, so as to improve the accuracy of engine wear monitoring, especially the results of online wear monitoring. Thereby, accurate real-time monitoring of wear conditions can be achieved whether in the actual operation of the engine or in the engine test process.

[0078] The steps of the method described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0079] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one place to another. Storage media may be any available medium that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0080] Although the present invention is disclosed as above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for monitoring engine wear, characterized in that: include: S1. Receive the original signal output by the metal chip sensor for monitoring the lubricating oil; S2 modulates and demodulates the original signal to eliminate background noise to form an intermediate signal; S3. The signal amplitude characteristics of the intermediate signal within a unit time interval are converted into energy characteristics; S4. The energy feature is statistically analyzed using an adaptive sliding window model to determine the metal chip condition of the engine lubricating oil.

2. The monitoring method according to claim 1, characterized in that: In S2, the original signal is amplitude modulated by using an envelope detection method, and demodulated and restored to obtain the intermediate signal.

3. The monitoring method according to claim 1, characterized in that: In S3, the energy characteristic of the intermediate signal is the sum of squares of discrete values. For a discrete signal x=(x1, x2, ..., x n ), the corresponding energy characteristics satisfy the following formula: Wherein, n is the unit time interval ΔT corresponding to the original signal multiplied by the sampling frequency f.

4. The monitoring method according to claim 1, characterized in that: In said S4, it includes: S41. Set the sliding window length: used to count the data in the sliding window; S42. Set the number of intervals; S43. Obtain the maximum and minimum values ​​of the data in the sliding window, and divide the data in the sliding window into intervals with upper and lower bounds of the maximum and minimum values, respectively, and count the number of data points in each interval; S44. Perform metal chip energy concentration determination on the data in each sliding window. If the amount of data contained in the energy minimum interval in the sliding window is greater than the energy concentration threshold, the data in the sliding window is considered to be data in the metal chip energy concentration, and the position index of the sliding window is marked as the metal chip position index; S45. If, among the plurality of metal chip position indexes, the number of the plurality of continuous metal chip position indexes is not less than the metal chip particle judgment threshold, it is determined that metal chip particles appear within the range between the first metal chip position index and the last metal chip position index among the plurality of continuous metal chip position indexes.

5. The monitoring method according to claim 4, characterized in that: In said S4, it also includes: S46. For the metal chip particle found in S45, determine the appearance time of the metal chip according to the first metal chip position index in the plurality of continuous metal chip position indexes, satisfying the following formula: T = ID*△T / f; Wherein, ΔT and f are the unit time interval ΔT and sampling frequency f corresponding to the original signal, ID is the first metal chip position index, and is the sampling number corresponding to the metal chip position index.

6. The monitoring method according to claim 4, characterized in that: In said S4, it also includes: S47. For the metal chip particles found in S45, the equivalent particle size of the metal chip particles is obtained by sewing according to the voltage peaks corresponding to the continuous plurality of metal chip position indexes.

7. The monitoring method according to claim 4, characterized in that: The interval is a histogram interval.

8. The monitoring method according to claim 1, characterized in that: In S3, the unit time interval satisfies the following formula: △T=L s / v; Among them, the unit time interval △T corresponding to the original signal, L s is the axial length of the metal chip sensor, v is the speed of the metal chips passing through the sensitive space of the sensor; v changes with the flow rate of the lubricating oil.

9. The monitoring method according to claim 8, characterized in that: If the change in v cannot be determined, v is set to the v corresponding to the lowest oil flow rate during the entire engine operation.

10. A computer readable medium having a computer program thereon, characterized in that The program is executed by a processor to implement the steps of the monitoring method according to any one of claims 1 to 9.

11. An engine wear monitoring system (100), characterized in that: include: A memory (101) for storing instructions executable by a processor; A processor (102) is used to execute the instructions to implement the steps of the monitoring method according to any one of claims 1 to 9.

12. The engine wear monitoring system (100) according to claim 11, characterized in that: The invention also comprises a filtering circuit (104) for modulating the original signal.

13. The engine wear monitoring system (100) according to claim 11, characterized in that: A display module (103) is connected to display the metal chip condition of the engine lubricating oil and / or the wear condition of the engine determined by the processor (102).

14. The engine wear monitoring system (100) according to claim 11, characterized in that: The processor (102) and / or the memory (101) are integrated into a Full Authority Digital Engine Control (FADEC).

15. A gas turbine engine having a metal chip sensor (105) for monitoring lubricating oil, characterized in that: During the operation of the gas turbine engine, the monitoring method according to any one of claims 1 to 9 is performed; or, the gas turbine engine further comprises an engine wear monitoring system (100) according to any one of claims 11 to 14.

16. A gas turbine engine test system, characterized in that: During a test of a gas turbine engine, a monitoring method as claimed in any one of claims 1 to 9 is performed.

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