An engine condition detection system and method

Abstract

An engine condition detection system includes a data processing system and multiple microphone arrays. Each microphone array includes multiple microphones, and the arrays are arranged around the detection station to collect vector information of sound. The data processing system pre-stores a digital model of the engine under test and converts the sound signals collected by the microphone arrays into image information, projecting it onto the outline of the digital model as a noise cloud map. This invention enables non-contact detection of abnormal engine noise, which is convenient, accurate, and fast, improving the efficiency of engine fault detection and diagnosis. This invention also provides an engine condition detection method.

Description

Technical Field

[0001] This invention belongs to the field of aero-engines, specifically relating to an engine condition detection system and method. Background Technology

[0002] With the development of the aviation industry, the research and development of civil high-bypass turbofan engines has received increasing attention. During the testing phase of aero-engine development, frequent failures occur, requiring real-time monitoring of key parameters and timely diagnosis of faults to facilitate analysis, troubleshooting, and technological optimization. Civil high-bypass turbofan engines operate in harsh environments—high temperature, high pressure, high speed, and high load—making their components highly susceptible to wear, cracks, deformation, and other failures, leading to typical faults such as stall and surge. Failure to detect these faults in a timely manner not only hinders testing but also increases the risk of safety accidents. Current technologies typically monitor engine status by detecting aerodynamic parameters such as temperature and pressure at compressor and combustion chamber outlets, often lacking specificity and immediacy; or they use contact testing methods to detect localized vibrations or stress states, which often involve complex equipment and poor repeatability.

[0003] The inventors recognized that noise measurement-based condition detection technology can identify and locate sound sources in a non-contact manner, which is of positive significance for improving the efficiency and accuracy of engine condition detection. Summary of the Invention

[0004] The purpose of this invention is to provide an engine condition detection system and method that can detect engine noise in a non-contact manner, conveniently, quickly and accurately locate the source of abnormal engine noise in space, so as to achieve the purpose of detecting the engine operating status and improve the efficiency of detecting and diagnosing aero-engine faults.

[0005] According to one aspect of the present invention, an engine condition detection system is provided, comprising a data processing system, multiple microphone arrays, and a detection station. The microphone arrays include multiple microphones arranged at different angles around the detection station, each microphone array facing the detection station, for acquiring vector signals of sound. The data processing system stores a digital model of the engine under test and is signal-connected to each of the microphone arrays, for converting the sound vector signals acquired by the microphone arrays into image information and projecting them onto the outline of the digital model of the engine under test as a noise cloud map.

[0006] The condition detection system can collect vector information of abnormal noise in a non-contact manner, without the need for lead wires or drilling. It is convenient and instantaneous, and can accurately match the location of abnormal noise sources with the contours of the engine surface, thus improving the efficiency of fault detection and diagnosis.

[0007] Furthermore, the microphone includes a sound pressure sensor and a sound intensity sensor. By recording the sound pressure and sound intensity of the sound signal respectively, the vector information of the noise can be recorded more accurately.

[0008] Furthermore, the microphones in the microphone array are arranged at different horizontal positions and / or vertical heights. The microphones at different positions improve the detection performance of the microphone array.

[0009] Preferably, the microphone is mounted on an adjustable slide rail arranged along the normal direction of the microphone array to allow for microphone movement. The slide rail simplifies microphone position adjustment and facilitates optimization of the microphone array's detection performance during system setup.

[0010] Preferably, the engine condition detection system further includes a sound shield, the shell of which is made of sound-insulating material and includes an opening facing the engine under test. The microphone is arranged inside the sound shield. The sound shield helps to isolate interference signals such as ambient noise and reverberation, improving the quality of sound signal acquisition.

[0011] According to another aspect of the present invention, an engine condition detection method is provided. This method utilizes any of the aforementioned engine condition detection systems to locate noise sources by acquiring vector signals of engine noise, and includes the following steps:

[0012] 1) Data preparation: Based on the size and performance characteristics of the engine to be tested, the microphone array is arranged, and acoustic signals from a standard engine sound source installed at the testing station are collected.

[0013] 2) Model preparation: The acoustic signals collected in step 1) are processed using the data processing system. Feature data is selected to establish a data model. The feature data is converted into image information and projected onto the outline of the digital model of the engine under test to establish a standard spectrum of engine noise cloud under normal operating conditions.

[0014] 3) Test run detection: Acoustic signals of the engine under test running at the test station are collected, the corresponding feature data are extracted and substituted into the data model, and the data processing system is used to convert them into image information and project them onto the outline of the digital model of the engine under test to obtain the engine noise cloud map detection spectrum.

[0015] 4) Analysis and comparison: Compare the standard spectrum with the detection spectrum. If the difference in noise signal in the engine area exceeds the allowable value, then the presence of an abnormal noise source in the area is identified, and the three-coordinate information of the abnormal noise source on the surface of the engine under test is obtained.

[0016] Engine condition detection methods can quickly locate abnormal noises that occur during engine operation in a non-contact manner, which helps to detect and diagnose faults in a timely and rapid manner, reduce testing costs, and improve testing efficiency and safety.

[0017] Furthermore, step 2) also includes a model optimization step, which processes the acoustic signals acquired in multiple steps 1), filters out environmental noise and bad data, and performs at least one round of debugging and training on the data model. Optimizing the data model can improve detection accuracy and reduce detection errors.

[0018] Furthermore, step 1) also includes an adjustment step for the microphone array. This adjustment step involves moving individual microphones within the microphone array along the normal direction of the plane containing the microphone array during signal acquisition, until the sound signal acquired by the microphone array reaches its strongest value. The distance moved in this adjustment step does not exceed the original spacing length between adjacent microphones in the microphone array. Adjusting the structure of the microphone array based on the actual acoustic effects at the test site can achieve better test results. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the structure of an engine condition detection system in one embodiment;

[0020] Figure 2 This is a schematic diagram of the microphone and slide rail in one embodiment;

[0021] Figure 3 This is a schematic diagram of the soundproof enclosure in one embodiment;

[0022] Figure 4 This is a schematic diagram illustrating the analysis and comparison results of noise source localization methods in one embodiment.

[0023] The purpose of the above-described drawings is to provide a detailed description of the invention so that those skilled in the art can understand its technical concept, and not to impose specific limitations on the embodiments of the invention. The above-described drawings only schematically depict the parts related to the technical features of the invention and do not depict all details or all parts and equipment strictly according to actual scale. Detailed Implementation

[0024] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, so that those skilled in the art can understand the technical concept of the present invention. The following embodiments are not intended to specifically limit the scope of protection of the present invention.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art; the technical terms used herein are intended only to describe particular embodiments and are not intended to limit the application; the terms “comprising” and “having” and any equivalent expressions thereof in the specification, claims and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in different places in the specification does not necessarily refer to the same specific embodiment, nor is it an exclusive or alternative embodiment to other embodiments. Those skilled in the art will understand, in light of the specific circumstances, that the embodiments described herein can be combined with other embodiments without causing structural or principle conflicts.

[0027] In the description of the embodiments in this application, "and / or" is merely a way of describing the relationship between related objects, indicating that there can be three relationships, such as A and / or B, which means that A exists alone, B exists simultaneously, or B exists alone. The character " / " indicates that the related objects before and after are in an "or" relationship.

[0028] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation", "connection", "fixing" and terms describing position and orientation should be interpreted broadly, and those skilled in the art can understand the actual meaning of the above terms in specific embodiments according to specific circumstances.

[0029] The development of aero-engines is one of the core topics of the civil aviation industry. Civil high-bypass turbofan engines have complex structures, long development cycles, require various verification tests, involve numerous parameters, complex logic, and are costly. Engine components operate under harsh conditions—high temperature, high pressure, high speed, and long operating time—making various parts highly susceptible to wear, cracks, deformation, and other failures, leading to typical malfunctions such as stall and surge. These malfunctions are particularly frequent during the development process, not only affecting the progress of verification tests but also creating safety hazards. Existing technologies often use contact sensors to detect vibration and strain information in different parts of the engine, requiring complex wiring and frequent drilling and disassembly, resulting in low efficiency and a lack of specificity. The inventors recognized that acquiring vector information of engine operating noise in a non-contact manner and locating the noise source can promptly and accurately determine the location of abnormal noise, thereby improving the efficiency of engine fault detection and diagnosis.

[0030] According to one embodiment of the present invention, an engine condition detection system such as Figure 1As shown. The system includes a data processing system 1 and multiple microphone arrays 2. The data processing system 1 typically includes a high-performance computer and its database storage module. The microphone arrays 2 are arranged in the engine test chamber 5, surrounding the test station 4 at different angles, facing the test station 4, to collect sound vector information. One end of the engine test chamber 5 has an air inlet 6, and the opposite end has an exhaust outlet 7. Air flows in the direction indicated by arrow 8. The engine under test 3 is installed on the test station 4, with its axis aligned with the airflow direction 8, allowing the air flowing in through the air inlet 6 to naturally enter through the intake end of the engine under test 3, exit through the exhaust end, and flow out of the room through the exhaust outlet 7. The data processing system 1 is signal-connected to each microphone array 2, converting the sound vector signals collected by the microphone arrays 2 into image information and projecting it onto the outline of its stored digital engine model, outputting a noise cloud map.

[0031] Each microphone array 2 includes multiple microphones, each containing a sound pressure sensor and a sound intensity sensor, further enhancing the ability to record sound vector information. These microphones are positioned at different horizontal locations or different vertical heights to collect sound signals from the detection station from different directions.

[0032] like Figure 2 As shown, in a preferred embodiment, the microphones 9 in each array are mounted on slide rails 10, which are installed along the normal direction of plane 11, allowing each microphone 9 to be adjusted within a certain range of position relative to the plane 11 where the microphone array 2 is located. If necessary, the microphones 9 can also be fixed in the desired position using a locking device. The presence of slide rails 10 makes adjusting the microphone arrays more convenient and quick, enhancing the flexibility of the engine condition monitoring system. In some other embodiments, slide rails 10 are not essential for the engine condition monitoring system.

[0033] like Figure 3 As shown, as a preferred embodiment, each microphone 9 can be installed within a sound shield 12. The housing of the sound shield 12 is made of sound-insulating material and includes walls abc, acd, and bcd, and an opening abd, with the opening abd facing the testing station 4. The microphone 9 is installed inside the sound shield 12, and its sound sensor points outward through the opening abd. The sound shield 12 can filter out reverberation interference from environmental noise inside the engine test chamber 5 and sound reflections from the walls, thereby improving the quality of sound signal acquisition. In other embodiments, the geometry of the sound shield 12 does not necessarily have to be a triangular pyramid; it can also be a hemispherical, conical, or other shell structure with an opening.

[0034] An embodiment of the present invention also provides an engine condition detection method, which applies the above-described engine condition detection system and locates the noise source by collecting vector information of the noise, including the following steps:

[0035] Step 1) Data preparation: Based on the size and performance characteristics of the engine under test, arrange each microphone array 2 and collect the acoustic vector signal of the standard engine sound source installed on the testing station 4.

[0036] Preferably, the acoustic signal acquisition process includes an adjustment step for the microphone array 2. This step involves moving individual microphones 9 in the microphone array along the slide rail 10, with the movement distance not exceeding the original spacing length of adjacent microphones in the microphone array 2. The acoustic characteristics of the test site may cause significant differences in the quality of sound signals acquired at adjacent spatial locations. The microphone positions are adjusted until the sound signal acquired by the microphone array reaches its strongest within the adjustment range. Optimizing the arrangement of the microphone array can improve signal acquisition quality and reduce the number of arrays required.

[0037] Step 2) Model preparation: Digitize the test scenario, establish a digital model of the test site and the engine under test, process the acoustic vector signal collected in Step 1) using the data processing system 1, classify the noise signal, structure the data, select feature data to establish a data model and convert it into image information and project it onto the outline of the digital model of the engine under test, and establish a standard spectrum of engine noise cloud under normal operating conditions.

[0038] After the data model is established, it is preferable to perform a model optimization step. This can be done by comprehensively processing the acoustic signals and historical data collected in step 1) multiple times, verifying the model, filtering out environmental noise and bad data, and performing at least one round of debugging and training on the data model. The data model can then be corrected and optimized through simulation calculations.

[0039] Step 3) Test run test: Replace the standard engine sound source on the test station 4 with the engine under test 3, collect the acoustic signal of the engine under test 3 running, extract the corresponding feature data and substitute it into the data model established in step 2), and use the data processing system 1 to convert it into image information and project it onto the outline of the digital model of the engine under test to obtain the engine noise cloud map detection spectrum.

[0040] Step 4) Analysis and comparison: Compare the standard spectrum and the test spectrum. If the difference in noise signal in the same engine area exceeds the allowable value, then the presence of an abnormal noise source in the area is identified, and the three-coordinate information of the abnormal noise source on the surface of the engine under test is obtained.

[0041] The data and analysis results generated in the above steps, combined with the actual maintenance results of the engine under test, will be stored as historical data in the database of data processing system 1 for use in the establishment and optimization of the model in subsequent tests.

[0042] by Figure 4 For example, the diagram shows a schematic of the virtual feature value surface mnop on the left side of the engine. This plane is divided into 16 regions, corresponding to different locations on the left side of the engine. The color of each region represents the noise intensity in its noise cloud spectrum, with darker colors indicating higher noise levels. Comparing the collected detection spectrum with the standard spectrum revealed an abnormally elevated noise signal 13. It can be determined that regions 2j and 4i on the left side of the engine are the corresponding noise sources, indicating abnormalities in the corresponding parts. For example, the contact between the casing accessory guide and the casing caused unexpected abnormal vibrations.

[0043] The engine status detection method described in this embodiment enables rapid and timely detection of engine operating status in a non-contact manner, facilitates and accurately locates engine noise sources in space, and improves the efficiency of detecting and diagnosing aero-engine faults.

[0044] It should be noted that the purpose of the above embodiments is to provide a detailed description of the technical solution of the present invention, so as to facilitate understanding by those skilled in the art. Within the scope of the claims of the present invention, improvements or equivalent substitutions to the parts or methods involved in the above embodiments, as well as combinations of different embodiments without conflict, all fall within the protection scope of the present invention.

Claims

1. An engine condition detection system, characterized in that: Includes a data processing system, multiple microphone arrays, and inspection stations. The microphone array includes multiple microphones arranged at different angles around the detection station and facing the detection station respectively, for collecting vector signals of sound; the microphones are mounted on an adjustable slide rail, which is arranged along the normal direction of the microphone array to allow the microphones to move. The data processing system stores a digital model of the engine and is connected to the signal of each of the microphone arrays. It is used to convert the sound vector signals collected by the microphone arrays into image information and project them onto the outline of the digital model of the engine under test as a noise cloud map.

2. The engine condition detection system according to claim 1, characterized in that, The microphone includes a sound pressure sensor and a sound intensity sensor.

3. The engine condition detection system according to claim 1, characterized in that, The microphones in the microphone array are arranged at different horizontal positions and / or vertical heights.

4. The engine condition detection system according to any one of claims 1 to 3, characterized in that, It also includes a sound shield, the shell of which is made of sound-insulating material and includes an opening facing the engine under test, and the microphone is arranged inside the sound shield.

5. An engine condition detection method, utilizing the engine condition detection system according to any one of claims 1 to 4, to locate the noise source by acquiring vector signals of engine noise, characterized in that, Includes the following steps: Step 1) Data preparation: Based on the size and performance characteristics of the engine to be tested, arrange the microphone array and collect the acoustic signals of the standard engine sound source installed at the testing station. Step 2) Model preparation: The acoustic signals collected in Step 1) are processed using the data processing system. Feature data is selected to build a model. The feature data is converted into image information and projected onto the outline of the digital model of the engine under test to establish a standard spectrum of engine noise cloud under normal operating conditions. Step 3) Test run and testing: Acoustic signals of the engine under test running at the test station are collected, the corresponding feature data are extracted and substituted into the data model, and the data processing system is used to convert them into image information and project them onto the outline of the digital model of the engine under test to obtain the engine noise cloud map detection spectrum. Step 4) Analysis and comparison: Compare the standard spectrum with the detection spectrum. If the difference in noise signal in the same engine area exceeds the allowable value, then the area is identified as having an abnormal noise source, and the three-coordinate information of the abnormal noise source on the surface of the engine under test is obtained.

6. The engine condition detection method according to claim 5, characterized in that, Step 2) further includes a model optimization step, which processes the acoustic signals collected in multiple steps 1) to filter out environmental noise and bad data points, and performs at least one round of debugging and training on the data model.

7. The engine condition detection method according to claim 5, characterized in that, Step 1) further includes an adjustment step for the microphone array. In the signal acquisition process, the individual microphones in the microphone array are moved in the normal direction of the plane in which the microphone array is located until the sound signal acquired by the microphone array reaches its strongest. The distance moved in the adjustment step does not exceed the original interval length between adjacent microphones in the microphone array.

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