Aero-engine blade impact monitoring system based on piezoelectric sensing

Abstract

The invention discloses an aero-engine blade impact monitoring system based on piezoelectric sensing, which relates to the technical field of aero-engine blade monitoring and comprises a sensing network intelligent layer, a conductive slip ring, a data acquisition card and an upper computer system. The sensing network intelligent layer is arranged on the surface of the blade, the sensing network intelligent layer comprises a plurality of piezoelectric sensors, the piezoelectric sensors convert stress waves generated when the blade is impacted into electric signals, signal transmission is conducted through the conductive slip ring, signal collection is conducted through the data collection card, and signal analysis is conducted through the upper computer system in sequence, so that blade impact data are obtained. Stress waves generated when the blade is impacted are converted into electric signals through the piezoelectric sensors arranged on the sensing network intelligent layer on the surface of the blade, the electric signals are transmitted, collected and processed, the impact condition of the aero-engine blade can be monitored in real time, the monitoring precision is high, and the performance of the blade cannot be affected.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft engine blade monitoring, and in particular to an aircraft engine blade impact monitoring system based on piezoelectric sensing. Background Art

[0002] As complex, thin-walled, curved components, aircraft engine blades are a critical and typical part in aircraft engines. During service, they may be struck by foreign objects such as hail, birds, and gravel, which can cause damage, performance degradation, and even serious safety accidents. Therefore, impact monitoring of aircraft engine blades is of great significance.

[0003] To monitor aeroengine blade impacts and thereby monitor their operating condition and predict their health, many researchers have proposed and studied various methods. These include measurement techniques such as blade tip timing and infrared thermal imaging. Blade tip timing analyzes the blade tip displacement response during impact to reconstruct the impact location and load. However, currently used blade models are mostly simplified. Due to technical limitations, these techniques only consider the vibration of a single blade, neglecting the coupling effects of the entire blade stage and the influence of aerodynamic forces. Infrared thermal imaging, on the other hand, is susceptible to environmental interference, affecting its accuracy and stability. Therefore, it is difficult to obtain accurate monitoring results under the complex operating conditions of aeroengines. Structural health monitoring (SHM) technology utilizes integrated sensor networks mounted on target structures to collect and process structural status information, enabling real-time impact monitoring of objects. Within SHM, passive impact monitoring based on piezoelectric sensors offers the advantages of low cost, strong real-time performance, and high accuracy. It can effectively assess the operating condition and predict the health of the monitored object using impact information, and thus holds great potential for impact monitoring of aeroengine blades. Impact identification is a typical inverse problem, requiring the determination of the impact location and energy from the structural stress waves. Piezoelectric sensors can sensitively extract the stress wave signals propagating through the blades, analyze and reconstruct them, and ultimately identify the impact location and energy. Summary of the Invention

[0004] In response to the above problems, the present invention proposes an aircraft engine blade impact monitoring system based on piezoelectric sensing, which provides a high-precision and strong stability impact monitoring system and realizes real-time monitoring of aircraft engine blades during flight.

[0005] An aero-engine blade impact monitoring system based on piezoelectric sensing includes a sensor network intelligence layer, a conductive slip ring, a data acquisition card and a host computer system;

[0006] The sensor network intelligent layer includes a substrate, a printed circuit, a plurality of piezoelectric sensors, a ground contact, and a plurality of positive electrode contacts; the substrate carries and protects the dispersed piezoelectric sensors; the printed circuit is etched on the substrate; the piezoelectric sensors convert stress waves generated when the aircraft engine rotor blades are impacted into electrical signals; the printed circuit electrically connects the negative electrodes of all piezoelectric sensors to the ground contact; the printed circuit electrically connects the positive electrodes of all piezoelectric sensors to the corresponding positive electrode contacts; the sensor intelligent layer is disposed on the surface of the aircraft engine rotor blades;

[0007] The conductive slip ring is arranged on the aero-engine shaft to realize the electrical connection between the conductor moving with the blade and the stationary data line; the conductive slip ring transmits the electrical signal in the conductor to the data acquisition card through the data line;

[0008] The electrical signals output by the intelligent layer of the sensor network are sequentially transmitted through the wires, conductive slip rings and data lines, collected in the data acquisition card, and analyzed by the host computer system to obtain the aircraft engine blade impact data in real time.

[0009] Preferably, the impact data includes impact position and impact energy.

[0010] Preferably, the analysis of the collected electrical signals by the host computer system specifically includes:

[0011] Use stress wave signal decomposition algorithm to decompose stress waves in collected electrical signals;

[0012] Use feature extraction algorithm to extract features from the decomposed stress wave signal;

[0013] Based on the feature-extracted stress wave signal, the impact location is calculated using the impact location algorithm;

[0014] Based on the feature-extracted stress wave signal, the impact energy is calculated using an impact quantification algorithm.

[0015] Preferably, the impact location algorithm is a weighted centroid method.

[0016] Preferably, the impact quantification algorithm is a system identification method; the system identification method establishes a model through experiments, calculates the transfer function of the model through an inversion algorithm, and reconstructs the impact load signal in the feature-extracted stress wave signal.

[0017] Preferably, the sensor network intelligent layer can withstand a maximum temperature of 350°C.

[0018] Preferably, the piezoelectric sensor is made of lithium niobate.

[0019] Preferably, the substrate is made of polyimide.

[0020] Preferably, the thickness of the network intelligence layer does not exceed the allowable error of the roughness of the monitored aircraft engine blade; the weight of the network intelligence layer does not exceed the allowable error of the manufacturing of the monitored aircraft engine blade.

[0021] Preferably, the data acquisition card is a programmable data acquisition card.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] (1) The present invention utilizes a network of piezoelectric sensors to monitor engine blade impact with higher monitoring accuracy and can achieve high-precision impact monitoring under harsh conditions of high temperature and high speed;

[0024] (2) The thickness of the sensor network intelligent layer used in the present invention is within the range of the blade surface roughness error, and the weight is within the manufacturing error of the blade, and will not affect the aerodynamic performance and mechanical performance of the blade during the monitoring process;

[0025] (4) The conductive slip ring used in the present invention has strong stability, high speed and anti-interference performance in data transmission; a programmable data acquisition card is selected for signal acquisition, which takes into account both portability and functional flexibility;

[0026] (3) The system proposed in the present invention is easy to install and solves the problem of monitoring the internal components of the engine. Through real-time monitoring of the system, the hidden dangers caused by the collision of the aircraft engine blades can be timely known, thereby improving the safety of engine operation. The design significantly improves the continuity of the blade structural integrity assessment, supports the complete life cycle monitoring from static maintenance to dynamic operation, and provides a new solution for the health management of aviation equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be described in further detail below with reference to the accompanying drawings;

[0028] Figure 1 This is an architectural diagram of an aero-engine blade impact monitoring method based on piezoelectric sensing according to an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the composition of an aircraft engine blade impact monitoring system of an aircraft engine blade impact monitoring device based on piezoelectric sensing according to an embodiment of the present invention;

[0030] Figure 3 This is a signal acquisition program diagram of an aircraft engine blade impact monitoring device based on piezoelectric sensing according to an embodiment of the present invention;

[0031] Figure 4Schematic diagram of a blade impact monitoring signal of an aircraft engine blade impact monitoring device based on piezoelectric sensing according to an embodiment of the present invention;

[0032] Figure numbers: 1. substrate; 2. printed circuit; 3. piezoelectric sensor; 4. positive electrode contact; 5. ground contact; 6. wire; 7. sensor network intelligent layer; 8. engine main shaft; 9. rotor blade; 10 dynamic end; 11. conductive slip ring; 12. static end; 13. signal acquisition card; 14. acquisition interface; 15. USB port; 16. host computer system. DETAILED DESCRIPTION

[0033] The present invention is further described below through specific embodiments.

[0034] To address the challenges of blade impact monitoring in high-speed, high-temperature environments of aircraft engines, and to address the limitations of existing monitoring methods in terms of accuracy and real-time performance, this paper has developed a piezoelectric sensing-based impact monitoring system. The core of this system lies in the use of a specialized sensor network intelligence layer to provide real-time sensing of potential blade impacts. During installation and use, the system does not interfere with the normal operation of the power system. The monitoring system primarily comprises a sensor network intelligence layer capable of acquiring stress wave signals, conductive slip rings for transmitting dynamic and static signals, a data acquisition card for signal acquisition and storage, and a host computer module for signal analysis and processing. The coordinated operation of these units enables the system to provide real-time and accurate impact monitoring.

[0035] Figure 1 This is a schematic diagram of the monitoring system architecture. It illustrates the basic components and working mechanism of the invented impact monitoring system, including the capture, transmission, collection, analysis, and processing of impact signals, forming a complete monitoring system.

[0036] Figure 2 The following is a schematic diagram of the system components used for aircraft engine blade impact monitoring. The monitored object is an aircraft engine rotor blade 9. The entire monitoring system includes a blade stress wave signal sensing module, a signal transmission module, a signal acquisition module, and a signal analysis module. Specifically, in this embodiment, the blade stress wave signal sensing module is the sensor network intelligent layer 7, the signal transmission module includes wires 6 and conductive slip rings 11, the signal transmission module is a data acquisition card 13, and the signal analysis module is a host computer system.

[0037] The design principles of the monitoring system are as follows:

[0038] High-temperature resistance and stable performance are the key factors in sensor selection to ensure proper function under the harsh operating conditions of aircraft engine blades. The thickness and weight of the sensor network intelligent layer 7 generally do not exceed the manufacturing tolerances of the monitored blades to avoid affecting the blades' aerodynamic balance and mechanical properties. Regarding the selection of conductive slip rings, the number of paths should be determined based on the number of sensors on the blades, while the rated speed of the slip rings should be selected based on the impeller speed to ensure they meet operational requirements. Regarding algorithm selection, the selection of positioning and quantification algorithms should be based on the accuracy requirements of blade monitoring, or the algorithm currently performing best in terms of impact performance should be selected.

[0039] The stress wave signal sensing module of this embodiment is a sensor network intelligent layer 7, comprising a substrate 1, a printed circuit 2, a piezoelectric sensor 3, a positive electrode contact 4, and a ground contact 5. The substrate 1 is made of polyimide and serves to support and protect the sensor. Its thickness can be adjusted based on the surface flatness requirements of the aircraft engine blade, with a minimum thickness of 15 mm. The piezoelectric sensor 3 is made of lithium niobate and serves to receive and convert stress wave signals into electrical signals. Its minimum thickness can reach 25 mm and is resistant to high temperatures. The printed circuit 2 is etched onto the substrate 1 and is responsible for connecting the piezoelectric sensor 3 to its corresponding electrode contacts and transmitting the electrical signals generated by the piezoelectric sensor. The positive electrode contact 4 is connected to the positive electrode of the corresponding piezoelectric sensor 3 through the printed circuit 2, and the ground contact 5 is connected to the negative electrodes of all piezoelectric sensors 3 through the printed circuit 2. To achieve comprehensive monitoring of the rotor blade 9, the sensor network intelligent layer is designed based on the shape of the rotor blade 9, with the piezoelectric sensors 3 positioned at the four corners of the blade to achieve full coverage. The entire sensor network intelligent layer 7 can withstand temperatures up to 350°C and is fully adhered to the surface of the blade to be monitored through a high-temperature resistant and high-strength adhesive film to withstand high temperature and high speed conditions.

[0040] When the engine is operating, its rotor blades 9 can rotate at speeds of 8,000-16,000 rpm. A sensor network intelligent layer 7 is bonded to the surface of the rotor blades 9 using a high-temperature-resistant adhesive. When an impact strikes the blades, stress waves are generated on the blade surface, which are then detected by the piezoelectric sensor 3 on the sensor network intelligent layer 7. The piezoelectric sensor 3 converts the detected stress wave signal into an electrical signal, which is then transmitted via electrode contacts 4 and 5 to a wire 6. The wire 6 is guided along the blade root into the cavity of the engine main shaft 8 and extends along the shaft's tail to connect to the dynamic end 10 of a conductive slip ring 11. The signal is converted from dynamic to static through the conductive slip ring 11. The static end 12 of the conductive slip ring 11 is connected to the acquisition interface 14 of a signal acquisition card 13. The signal acquisition card 13, under program control, filters, amplifies, and stores the signal. The signal acquisition card 13 is connected to a host computer system 16 via a USB port 15. The host computer system 16 includes a stress wave signal decomposition algorithm, a feature extraction algorithm, an impact location algorithm, and a quantitative algorithm. These algorithms determine the impact location and force of the impacted engine blade, as well as the approximate material of the impacting object. Based on the analysis results, it determines whether the impacted blade can continue to operate and whether it requires timely repair.

[0041] The monitoring system of this embodiment transcends the limitations of traditional detection modes, enabling monitoring of aircraft engines both in idle and operating states. By permanently integrating the intelligent sensor network layer 7 onto the surface of the engine blades, a real-time online monitoring system covering all operating conditions is established. This solution is not limited to impact monitoring of engine blades; it can be modified as needed to monitor other structures.

[0042] Figure 3 Figure 2 shows the signal acquisition program. This embodiment uses the NI USB-6210 data acquisition card. A signal acquisition program is written using LabVIEW software as needed. During operation of the impact monitoring system, the host computer system 16 uses this program to control the signal acquisition card 13 to filter, amplify, and store signals. The signal acquisition program is modular in design and primarily consists of a signal input and configuration module, a dynamic parameter control module, a signal processing and visualization module, and a data storage and output module.

[0043] The operation process is as follows:

[0044] Initial setup: Select the physical channel and configure the terminal protocol, set the input range and sampling parameters (sampling frequency and buffer size).

[0045] Signal acquisition and preprocessing: After starting acquisition, the program loops to capture the signal, generating the original waveform and performing real-time filtering and amplification. The "Refresh" module updates the interface display and simultaneously detects signal anomalies (overrange and noise interference).

[0046] Data storage and management: After the user triggers the "Save Data" command, the original waveform, processing results, and metadata are written to the measurement file, supporting breakpoint resumption and overwrite protection.

[0047] Termination and maintenance: After completing the collection, exit safely through the "TERM" command or clear the historical configuration through the "Reset" module to prepare for the next monitoring task.

[0048] This signal acquisition program uses analog voltage signals received at acquisition port 14 of a signal acquisition card 13 as input. It has 16 input channels, capable of connecting up to 16 piezoelectric sensors 3. The sampling frequency is typically set at 10 times the maximum frequency of the voltage signal to ensure signal integrity. The program supports both stopped and running acquisition modes. Through dynamic range calibration and buffer management, it adapts to the full range of aircraft engine operating conditions, from low-temperature startup to high-temperature and high-speed monitoring.

[0049] This example uses the NIUSB-6210 data acquisition card as an example and writes the corresponding program. However, actual applications are not limited to this model. The modular design also supports functional expansion and compatibility with existing sensor networks in aviation equipment. By modifying parameters such as the number of signal channels, sampling frequency, signal type, and signal preprocessing, different monitoring requirements can be met.

[0050] Figure 4 Figure 3 shows an impact signal detected by a piezoelectric sensor 3 in the blade impact monitoring system. When no impact occurs, the voltage signal collected by piezoelectric sensor 3 is essentially zero, fluctuating only slightly due to environmental interference. When an impact occurs, the generated stress wave signal propagates to piezoelectric sensor 3, is captured, and then transmitted to the host computer system 16 for impact analysis.

[0051] The monitoring algorithm can use the weighted centroid method for positioning and the system identification method for quantification. The centroid method of impact positioning is based on the attenuation of the impact energy, which is determined by Figure 4 The impact signal is obtained, and the attenuation coefficient is measured experimentally or calculated based on material properties. Impact quantification is obtained through load reconstruction, that is, a system model is established through experiments, and the system transfer function is calculated using an inversion algorithm to reconstruct the impact load signal.

[0052] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited to this. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. An aircraft engine blade impact monitoring system based on piezoelectric sensing, characterized in that: Including conductive slip ring, sensor network intelligent layer, data acquisition card and host computer system; The conductive slip ring is arranged on the aero-engine shaft to realize the electrical connection between the conductor moving with the blade and the stationary data line; The sensor network intelligent layer includes a substrate, a printed circuit, a plurality of piezoelectric sensors, a ground contact, and a plurality of positive electrode contacts; the substrate carries and protects the dispersedly arranged piezoelectric sensors; the printed circuit is etched on the substrate; the piezoelectric sensors convert stress waves generated when the aircraft engine rotor blades are impacted into electrical signals; the printed circuit electrically connects the negative electrodes of all piezoelectric sensors to the ground contact, and the printed circuit electrically connects the positive electrodes of all piezoelectric sensors to the corresponding positive electrode contacts, the ground contact and the positive electrode contact are electrically connected to the wire, and the electrical signal of each piezoelectric sensor is transmitted to the wire through the printed circuit, the positive electrode contact, and the ground contact; the sensor intelligent layer is arranged on the surface of the aircraft engine rotor blade; the electrical signal output by the sensor network intelligent layer is sequentially transmitted to the acquisition card through the wire, the conductive slip ring, and the data cable; The acquisition card sends the collected electrical signals to the host computer system; The host computer system analyzes the collected electrical signals and obtains the aero-engine blade impact data in real time.

2. The piezoelectric sensing-based aircraft engine blade impact monitoring system according to claim 1, characterized in that: The impact data includes an impact position and an impact energy.

3. The piezoelectric sensing-based aircraft engine blade impact monitoring system according to claim 2, characterized in that: The analysis of the collected electrical signals by the host computer system specifically includes: Use stress wave signal decomposition algorithm to decompose stress waves in collected electrical signals; Use feature extraction algorithm to extract features from the decomposed stress wave signal; Based on the feature-extracted stress wave signal, the impact location is calculated using the impact location algorithm; Based on the feature-extracted stress wave signal, the impact energy is calculated using an impact quantification algorithm.

4. The piezoelectric sensing-based aircraft engine blade impact monitoring system according to claim 3, characterized in that: The collision location algorithm is a weighted centroid method.

5. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 3, characterized in that: The impact quantification algorithm is a system identification method; the system identification method establishes a model through experiments, calculates the transfer function of the model through an inversion algorithm, and reconstructs the impact load signal in the feature-extracted stress wave signal.

6. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 1, characterized in that: The sensor network intelligent layer can withstand a maximum temperature of 350°C.

7. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 1, characterized in that: The material of the piezoelectric sensor is lithium niobate.

8. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 1, characterized in that: The material of the substrate is polyimide.

9. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 1, characterized in that: The thickness of the network intelligence layer does not exceed the allowable error of the roughness of the monitored aircraft engine blade; the weight of the network intelligence layer does not exceed the allowable error of the manufacturing of the monitored aircraft engine blade.

10. The aero-engine blade impact monitoring system based on piezoelectric sensing according to claim 1, characterized in that: The data acquisition card is a programmable data acquisition card.

Images