Method and system for testing reliability of small general engine

Abstract

The invention relates to the technical field of engine testing, and discloses a reliability test method and system for a small general engine, and the method comprises the steps: collecting an engine vibration signal through a superconducting quantum interferometer, and collecting a temperature distribution parameter through a quantum dot temperature sensor; performing combined testing of cold and hot shock, high-load operation and random working conditions, and synchronously monitoring dynamic response characteristic data; constructing a Weibull probability model, and determining key influence factors through a global sensitivity analysis method; acquiring a surface roughness parameter by adopting a field emission scanning electron microscope, obtaining a material component parameter through energy spectrum analysis, and establishing a parameter mapping relation; establishing a vibration and temperature early warning system, executing a graded sweep frequency excitation and abrasive particle acceleration test, and recording a parameter degradation process; and generating a three-dimensional parameter cloud picture, and outputting a reliability test report. According to the method, the reliability of the small general engine can be comprehensively and efficiently evaluated, and a scientific basis is provided for design, maintenance and improvement of the engine.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engine testing, and in particular to a reliability test method and system for small general-purpose engines. BACKGROUND

[0002] Small general-purpose engines are widely used in generator sets, garden machinery, and small engineering machinery fields, and their reliability directly affects the service life and operating efficiency of the equipment. However, existing reliability test methods have the following problems: first, the test conditions are single and cannot fully simulate the actual use environment of the engine; second, the test process is complex, time-consuming, and difficult to monitor and analyze the performance changes of the engine in real time; third, there is a lack of detection means for microscopic damage of engine parts, making it difficult to detect potential fault hazards in advance. These problems result in the existing methods being unable to effectively evaluate the reliability of the engine, affecting the maintenance and improvement of the equipment.

[0003] Currently, although there are some reliability test methods for automotive engines and aero engines, these methods are not completely applicable to small general-purpose engines. For example, the reliability test of automotive engines usually focuses on high-speed operation and high-load conditions, while small general-purpose engines are more commonly used in low-speed, low-load conditions. In addition, existing methods have deficiencies in data acquisition and analysis, and cannot provide comprehensive multi-physical field parameter monitoring and fusion analysis, resulting in inaccurate evaluation of the engine operating state.

[0004] In order to improve the reliability of small general-purpose engines, a reliability test method is needed that can fully simulate the actual use environment, monitor and analyze the performance changes of the engine in real time, and detect microscopic damage of parts. Existing methods have deficiencies in the accuracy of data acquisition, diversity of test conditions, and depth of data analysis, and need to be further improved and optimized.

[0005] Therefore, the present application proposes a reliability test method and system for small general-purpose engines, which comprehensively evaluates the reliability of the engine, detects potential fault hazards in advance, and improves the service life and operating efficiency of the engine through multiple condition simulation, real-time data monitoring and analysis, and microscopic damage detection of parts. SUMMARY

[0006] The purpose of the present application is to solve the problems of single test condition, incomplete data acquisition, and insufficient microscopic damage detection in the prior art, and to propose a reliability test method and system for small general-purpose engines.

[0007] In order to achieve the above-mentioned purpose, the present application adopts the following technical solution: a reliability test method for small general-purpose engines, comprising the following steps:

[0008] Step S1, collect engine surface vibration signals using a superconducting quantum interferometer, and collect engine cylinder, piston and exhaust manifold temperature distribution parameters using a quantum dot temperature sensor;

[0009] Step S2, perform cold and hot impact, high load operation and random working condition combined testing on the engine, and synchronously monitor the dynamic response characteristic data of temperature, speed, torque and vibration spectrum parameters;

[0010] Step S3, based on the vibration signal and the temperature distribution parameter, extract the vibration spectrum characteristic parameter and the temperature gradient parameter to construct a Weibull probability model, and determine the key influence factor by the Sobol global sensitivity analysis method;

[0011] Step S4, obtain the engine surface roughness parameter by field emission scanning electron microscopy, and obtain the material composition parameter by energy spectrum analysis, and establish the parameter mapping relationship between the surface roughness parameter, the material composition parameter and the vibration spectrum characteristic parameter;

[0012] Step S5, establish a vibration and temperature early warning system and perform a hierarchical sweep frequency excitation and abrasive particle accelerated test, construct a multi-dimensional evaluation index system of parameter degradation process, and record the failure process by a camera throughout the process;

[0013] Step S6, integrate the vibration spectrum characteristic parameter, the temperature distribution parameter and the wear morphology parameter to generate a three-dimensional parameter cloud map, and output a reliability test report.

[0014] Further, in step S1, the following sub-steps are further included:

[0015] S1-1, arrange a superconducting quantum interferometer sensor array, set up ≥12 measuring points on the surface of the engine cylinder, crankcase and exhaust manifold, continuously collect vibration signals in the range of 0-50 kHz at a sampling frequency of 100 kHz;

[0016] S1-2, use quantum Fourier transform algorithm to process the original vibration signal, convert the time domain signal to the frequency domain signal, and extract the ground-state-excitation-state probability amplitude ratio characteristic parameter, and calculate the vibration amplitude parameter, the vibration amplitude parameter represents the fluctuation value of the collected vibration signal;

[0017] S1-3, arrange quantum dot temperature sensors on the top of the engine cylinder, the piston skirt and the surface of the exhaust manifold to measure the temperature change, the quantum dot temperature sensor array contains 16 quantum dot temperature sensors, forming a 4×4 grid layout, the spacing of the sensors is 5mm;

[0018] S1-4, calibrate the quantum dot temperature sensor data using an infrared camera with a wavelength range of 0.7-2.5μm by multi-spectral radiation thermometry technology, the calibration is automatically performed every 10 minutes;

[0019] S1-5, acquiring temperature distribution parameters by a quantum dot temperature sensor array, combining a finite element analysis method, constructing a three-dimensional temperature field parameter model, and reflecting the temperature distribution inside the engine.

[0020] Further, in step S2, further comprising the following sub-steps:

[0021] S2-1, performing cold and hot impact test, placing the engine in a programmable cold and hot impact box, cycling between -20℃ and 50℃ at a rate of 10℃ / min, keeping each temperature platform for 60 minutes, and recording the temperature parameter dynamic response of the engine cylinder, piston and lubrication system by embedded PT100 temperature sensor at a frequency of 1Hz;

[0022] S2-2, performing high load operation test, increasing the engine load to 80%-100% of rated power by electromagnetic dynamometer at a gradient of 10% rated load / min, synchronously collecting output signals by built-in speed sensor and torque sensor at a sampling interval of 100ms during the linear change of engine speed from idle to rated value, and recording the parameter coupling characteristics of speed and torque in real time;

[0023] S2-3, performing random working condition test, simulating random working conditions in actual use by computer controlling the speed and load of the engine, the change range of speed and load being 20%-100% of rated speed and 10%-100% of rated load respectively, the test time being 50-100 hours, and synchronously enabling a random vibration table to apply a random vibration spectrum to the engine body, crankcase and exhaust manifold to continuously obtain vibration spectrum parameters;

[0024] S2-4, during the tests of cold and hot impact, high load operation and random working condition, synchronously monitoring the dynamic response characteristic data of temperature, speed, torque and vibration spectrum parameters of the engine by IEEE 1588v2 precision time protocol for clock synchronization of embedded PT100 temperature sensor, speed sensor, torque sensor and vibration signal acquisition link;

[0025] S2-5, performing time-frequency analysis on the collected dynamic response characteristic data to extract characteristic values, the characteristic values including temperature change rate, speed fluctuation amplitude, torque fluctuation amplitude and first 5 order resonance frequency offset of vibration spectrum.

[0026] Further, in step S3, further comprising the following sub-steps:

[0027] S3-1, wavelet packet decomposition is performed on the collected vibration signal, the energy entropy parameters of 32 sub-bands in the frequency band of 0-50 kHz are calculated, and the dimension is reduced to 5 vibration spectrum characteristic parameters through principal component analysis, the vibration spectrum characteristic parameters include energy entropy, main frequency, frequency center, bandwidth and kurtosis;

[0028] S3-2, based on the temperature distribution parameters collected by the quantum dot temperature sensor, the axial and radial temperature gradient parameters between the cylinder, the piston and the exhaust manifold are calculated, and the thermodynamic characteristic parameters are extracted, the thermodynamic characteristic parameters include the maximum gradient value, the gradient change rate, the average gradient value, the gradient standard deviation, the heat flux and the thermal diffusivity;

[0029] S3-3, a Weibull probability model is established with the vibration spectrum characteristic parameters as the observation variables and the axial and radial temperature gradient parameters as the state variables, the formula of the Weibull probability model is:

[0030]

[0031] Where P(∣) is the probability density function, T represents the temperature state vector, V represents the vibration characteristic vector, β is the shape parameter, η is the scale parameter, Y is the location parameter, n represents the number of sub-bands of the vibration spectrum characteristic parameters, i represents the sub-band index of the vibration spectrum characteristic parameters, and e represents the base number of natural logarithm;

[0032] S3-4, Sobol global sensitivity analysis method is used to calculate the variance contribution rate of each input parameter to the model output, and the vibration spectrum characteristic parameters and the axial and radial temperature gradient parameters with a contribution rate greater than 15% are selected as the key influencing factors.

[0033] Further, in step S4, the following sub-steps are further included:

[0034] S4-1, selecting the key wear area of the engine as the target site for field emission scanning electron microscope detection, the key wear area includes piston ring, cylinder liner, crankshaft, connecting rod, valve, exhaust manifold, intake valve seat and fuel nozzle;

[0035] S4-2, using field emission scanning electron microscope to scan the surface morphology of the target site, obtaining the surface roughness parameters, the surface roughness parameters include average roughness, root mean square roughness and maximum height roughness;

[0036] S4-3, using energy spectrum analyzer to perform surface scanning on the target site, obtaining material composition parameters, the material composition parameters include base iron element concentration, chromium element loss rate, oxidation wear index and lubricating film residual amount;

[0037] S4-4, performing partial least squares regression analysis on the surface roughness parameters, material composition parameters and vibration frequency spectrum characteristic parameters to establish the following mapping relationship matrix:

[0038]

[0039] wherein the matrix A is a weight coefficient and b is a bias term.

[0040] Further, in step S5, the following sub-steps are further included:

[0041] S5-1, establishing a three-level early warning threshold system for the vibration amplitude parameter, including a low warning threshold of 0.5mm / s, a medium warning threshold of 1.0mm / s and a high warning threshold of 1.5mm / s, when the engine vibration amplitude exceeds the low warning threshold, the monitoring frequency of the superconducting quantum interferometer is increased, when the medium warning threshold is exceeded, the magneto-rheological excitation device is started for frequency sweeping excitation, and when the high warning threshold is exceeded, the full-power frequency sweeping excitation is activated;

[0042] S5-2, constructing an adaptive diagnosis algorithm for temperature anomalies, real-time calculating the axial temperature gradient parameter between the engine cylinder, piston and exhaust manifold, when the temperature gradient value exceeds 5℃ / mm, triggering the abrasive particle injection system to inject abrasive particles with a particle size range of 10-50 microns for abrasive particle accelerated testing;

[0043] S5-3, constructing a multi-dimensional evaluation index system for parameter degradation process, including vibration amplitude change rate, temperature change rate, torque fluctuation amplitude and wear depth;

[0044] S5-4, using a camera with a frame rate >1000fps to continuously shoot the evolution process of the engine from the appearance of initial abnormal signs to complete failure, and marking the time stamp of each frame of image through a time synchronizer.

[0045] Further, in step S6, the following sub-steps are further included:

[0046] S6-1, using timestamp backtracking technology to align the vibration frequency spectrum characteristic parameters, temperature distribution parameters and wear morphology parameters to the same time reference, with a time synchronization accuracy better than 10μs, the temperature distribution parameters include three-dimensional temperature distribution data of the cylinder, piston and exhaust manifold collected by the quantum dot temperature sensor array, and the wear morphology parameters represent the surface roughness parameters and material composition parameters;

[0047] S6-2, based on the Kriging interpolation algorithm, mapping the discrete vibration and temperature parameters to the surface of the engine three-dimensional CAD model to generate a 0.1mm resolution parameter distribution cloud map, supporting transparent superimposed display of multi-physical field data;

[0048] S6-3, three-dimensional topography reconstruction is carried out on the micro morphology obtained by the field emission scanning electron microscope, and the wear morphology parameters of the corresponding position of the engine are mapped to the whole machine model through a feature matching algorithm;

[0049] S6-4, the data of the Weibull probability model output and the parameter degradation process are integrated, and the reliability index is calculated, the reliability index includes mean time between failures, reliability, failure rate, wear rate, parameter degradation rate, remaining service life, failure probability and maintenance interval;

[0050] S6-5, the reliability test report is automatically generated based on the XML template, including parameter evolution animation, three-dimensional interactive model and original data block chain hash value.

[0051] Further, a reliability test system of a small general-purpose engine comprises:

[0052] The parameter acquisition module is composed of a superconducting quantum interference vibration detection unit and a quantum dot temperature sensor array, and is used for collecting vibration signals and temperature distribution parameters;

[0053] The working condition test module comprises a programmable cold and hot impact box, an electromagnetic dynamometer, a computer and a random vibration table, and is used for performing multi-working condition parameter test and obtaining dynamic response parameters;

[0054] The modeling analysis module is a computing unit loaded with Weibull probability model algorithm and parameter sensitivity analysis program, and is used for completing reliability modeling;

[0055] The microscopic detection module is a combined system integrating a field emission scanning electron microscope and an energy spectrum analyzer, and is used for performing engine surface roughness parameter and material composition parameter detection;

[0056] The accelerated test module is composed of a magneto-rheological excitation device, a abrasive particle injection system, a camera and a time synchronizer, and is used for implementing parameter threshold triggered sweep frequency excitation and abrasive particle injection test;

[0057] The report generation module comprises a three-dimensional visualization workstation and a block chain storage terminal, and is used for creating a three-dimensional parameter cloud chart and outputting a reliability test report.

[0058] The technical scheme provided by the application has at least the following beneficial effects:

[0059] The cold and hot impact, high load operation and random working condition combined test can comprehensively simulate various working conditions of the engine in actual use, not only improve the comprehensiveness and accuracy of the test, but also more truly reflect the running state of the engine under different environments.

[0060] The application can realize real-time monitoring and analysis of the running state of the engine, discover potential faults in time, and improve the efficiency and reliability of the test by collecting engine parameters through a high-precision sensor array and performing time-frequency analysis and feature extraction.

[0061] The application can discover and evaluate micro-damage in time by acquiring surface roughness and material composition parameters of key components of the engine through field emission scanning electron microscopy and energy spectrum analysis, and performing three-dimensional morphology reconstruction, thereby providing a scientific basis for maintenance and improvement of the engine.

[0062] The application can comprehensively evaluate the reliability of the engine by generating a three-dimensional parameter cloud and calculating reliability indicators based on a Weibull probability model, thereby providing comprehensive data support for maintenance and improvement of the equipment. BRIEF DESCRIPTION OF DRAWINGS

[0063] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0064] Figure 1 The method flowchart provided for the embodiments of the present application;

[0065] Figure 2 The system architecture diagram provided for the embodiments of the present application. DETAILED DESCRIPTION

[0066] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following describes the reliability test method and system of a small general-purpose engine according to the present application, its specific implementation, structure, features and effects in detail in combination with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0068] The following embodiments are only for illustrative purposes, and are not intended to limit the scope of the present application.

[0069] The following describes the specific scheme of the reliability test method and system of a small general-purpose engine provided by the present application in combination with the drawings.

[0070] Referring to Figure 1 It shows a method flow chart of a reliability test method of a small general-purpose engine provided by an embodiment of the application, comprising the following steps:

[0071] Step S1, using a superconducting quantum interferometer to collect engine surface vibration signals, and using a quantum dot temperature sensor to collect temperature distribution parameters of the engine cylinder, piston and exhaust manifold;

[0072] In step S1, the following sub-steps are further included:

[0073] S1-1, arranging a superconducting quantum interferometer sensor array, setting ≥12 measuring points on the surface of the engine cylinder, crankcase and exhaust manifold, and continuously collecting vibration signals in the range of 0-50 kHz at a sampling frequency of 100 kHz;

[0074] S1-2, using a quantum Fourier transform algorithm to process the original vibration signals, converting the time domain signals into frequency domain signals, and extracting the ground-state-excitation-state probability amplitude ratio characteristic parameters, while calculating the vibration amplitude parameters, which represent the fluctuation value of the collected vibration signals;

[0075] S1-3, arranging quantum dot temperature sensors on the top of the engine cylinder, the piston skirt and the surface of the exhaust manifold to measure temperature changes, the quantum dot temperature sensor array contains 16 quantum dot temperature sensors, forming a 4x4 grid layout, and the spacing between the sensors is 5mm;

[0076] S1-4, using a multispectral radiation thermometry technique, using an infrared camera with a wavelength range of 0.7-2.5 μm to calibrate the quantum dot temperature sensor data, and calibrating every 10 minutes automatically;

[0077] S1-5, collecting temperature distribution parameters through the quantum dot temperature sensor array, combining with the finite element analysis method, constructing a three-dimensional temperature field parameter model, and reflecting the temperature distribution inside the engine.

[0078] It should be noted that the superconducting quantum interferometer is a high-sensitivity magnetic sensor based on the principle of superconducting quantum interference, which can detect extremely weak magnetic field changes, and is usually used for high-precision physical quantity measurement, including vibration, magnetic field and current.

[0079] The quantum Fourier transform algorithm is a signal processing algorithm based on quantum computing, which can convert time domain signals into frequency domain signals. Compared with the traditional Fourier transform, the quantum Fourier transform has higher efficiency and accuracy when processing quantum state signals.

[0080] Multispectral radiation thermometry is a method of determining the temperature of an object by measuring its radiation intensity in multiple wavelength ranges, which can utilize the radiation characteristics of different wavelengths to improve the accuracy and reliability of temperature measurement.

[0081] Infrared camera calibration: The high resolution and high sensitivity of the infrared camera enable it to provide accurate temperature reference data for calibrating the quantum dot temperature sensor, and this calibration method can ensure the measurement accuracy of the quantum dot temperature sensor under different environmental conditions.

[0082] Finite element analysis (FEA) is a numerical analysis method used to solve complex engineering problems, which can accurately simulate the temperature distribution inside the engine, and combined with the temperature distribution parameters collected by the quantum dot temperature sensor, a high-precision three-dimensional temperature field parameter model can be constructed. This helps to comprehensively evaluate the thermal state of the engine and predict potential thermal failures.

[0083] Step S2, cold and hot impact, high load operation and random working condition combined test of engine, synchronous monitoring of temperature, speed, torque and vibration spectrum parameter dynamic response characteristics;

[0084] In step S2, the following sub-steps are included:

[0085] S2-1, cold and hot impact test, the engine is placed in a programmable cold and hot impact box, and the temperature is changed between-20℃ and 50℃ at a rate of 10℃ / min, each temperature platform is maintained for 60 minutes, and the temperature parameter dynamic response of the engine cylinder, piston and lubrication system is recorded by embedded PT100 temperature sensor at a frequency of 1Hz;

[0086] S2-2, high load operation test, the engine load is increased to 80%-100% of rated power by electromagnetic dynamometer at a gradient of 10% rated load / minute, and the output signal is synchronously collected by built-in speed sensor and torque sensor at a sampling interval of 100ms during the linear change of engine speed from idle to rated value, and the parameter coupling characteristics of speed and torque are recorded in real time;

[0087] S2-3, random working condition test, the speed and load of the engine are controlled by computer to simulate the random working conditions in actual use, the change range of speed and load is 20%-100% of rated speed and 10%-100% of rated load respectively, the test time is 50-100 hours, and the random vibration table is started synchronously to apply random vibration spectrum to the engine body, crankcase and exhaust manifold, and the vibration spectrum parameters are continuously obtained;

[0088] S2-4, During the cold-heat shock, high-load operation, and random working condition test, the IEEE 1588v2 precision time protocol is used to synchronize the clock of the embedded PT100 temperature sensor, the speed sensor, the torque sensor, and the vibration signal acquisition link, and the dynamic response characteristic data of the engine's temperature, speed, torque, and vibration spectrum parameters are synchronously monitored.

[0089] S2-5, The dynamic response characteristic data collected is subjected to time-frequency analysis, and the characteristic values including the temperature change rate, the speed fluctuation amplitude, the torque fluctuation amplitude, and the first five-order resonance frequency offset of the vibration spectrum are extracted.

[0090] It should be noted that the cold-heat shock test: the purpose is to simulate the engine's operation under extreme temperature changes and evaluate the engine's thermal stability and heat shock resistance.

[0091] The programmable cold-heat shock box is a device that can accurately control and adjust the internal temperature, and can automatically adjust the temperature according to the preset program to achieve the cyclic change of temperature.

[0092] Each temperature platform is maintained for 60 minutes: the 60-minute holding time is long enough to ensure that the engine reaches thermal equilibrium at each temperature platform, thereby accurately recording the dynamic response of the temperature parameters.

[0093] Temperature platform: the duration of maintaining the target temperature constant in the cold-heat shock cycle, when the temperature fluctuation is continuously ≤±0.5℃ for 5 minutes, it is considered to enter the platform period; the cold-heat shock test includes two platforms: the -20℃ platform is the low-temperature constant temperature segment (maintained for 60 minutes); the +50℃ platform is the high-temperature constant temperature segment (maintained for 60 minutes).

[0094] Embedded PT100 temperature sensor: PT100 temperature sensor is a high-precision temperature sensor based on platinum resistance, whose resistance changes with temperature, and the embedded design means that the sensor is installed inside the key parts of the engine, which can directly measure the local temperature.

[0095] Electromagnetic dynamometer: a device for measuring the output power and torque of the engine, which converts the mechanical energy of the engine into electrical energy through electromagnetic induction and measures its output power.

[0096] 10% rated load / minute gradient: the 10% rated load / minute gradient can simulate the smooth transition of the engine from low load to high load, ensuring the gradualness and safety of the test.

[0097] Synchronous acquisition: synchronous acquisition of speed and torque signals can ensure the consistency and relevance of the data, facilitating subsequent comprehensive analysis.

[0098] Both the speed sensor and the torque sensor are integrated inside the electromagnetic dynamometer, which is a standard configuration. When the dynamometer is loading the engine, it outputs the speed and torque signals in real time through its built-in encoder (as a speed sensor) and torque flange (as a torque sensor), without the need for additional installation.

[0099] Parameter coupling characteristics: refers to the mutual relationship and influence between two or more parameters. In engine testing, the coupling characteristics of speed and torque can reflect the dynamic performance of the engine.

[0100] Random operating condition test: aims to simulate the random operating conditions of the engine in actual use, and evaluate the performance and reliability of the engine under complex operating conditions.

[0101] Test time is 50-100 hours: 50-100 hours of test time can fully capture the long-term performance changes of the engine under random operating conditions, and evaluate its reliability and durability.

[0102] IEEE 1588v2 Precision Time Protocol is a protocol for synchronizing clocks between network devices, which can achieve high-precision time synchronization and ensure that the data collected by different sensors is comparable and related in time.

[0103] Vibration signal acquisition link: refers to the complete process of continuously acquiring 0-50kHz vibration signals at a sampling frequency of 100kHz by a superconducting quantum interference sensor array, then processing the acquired vibration signals using quantum Fourier transform algorithm, and finally outputting the vibration spectrum parameters.

[0104] Dynamic response characteristic data refers to all original and derived data that can reflect the dynamic behavior of the engine, which are recorded in real time under three test conditions: cold and hot shock, high load operation and random operating conditions. Specifically, it includes:

[0105] Temperature: instantaneous temperature sequence (1Hz sampling) of each measuring point of the cylinder, piston and lubrication system.

[0106] Speed: instantaneous speed sequence (100ms sampling) output by the engine shaft.

[0107] Torque: instantaneous torque sequence (100ms sampling) measured by the electromagnetic dynamometer.

[0108] Vibration spectrum parameters: refers to the 0-50kHz frequency domain data obtained by sampling the vibration signals collected during the random operating condition combination test of the engine at a frequency of 100kHz by a superconducting quantum interference sensor array and processing them using quantum Fourier transform algorithm.

[0109] Time-frequency analysis is a signal processing method that analyzes the characteristics of a signal in both time and frequency domains, providing the time-frequency distribution of the signal and helping to identify the frequency components and time variations in the signal.

[0110] Temperature rate of change: the rate of change of temperature over time, reflecting the dynamic change of temperature.

[0111] Speed fluctuation amplitude: the amplitude of the speed change in a short period of time, reflecting the stability of the speed.

[0112] Torque fluctuation amplitude: the amplitude of the torque change in a short period of time, reflecting the stability of the torque.

[0113] The first 5 order resonance frequency offset of the vibration spectrum: the change of the first 5 order resonance frequency in the vibration signal, reflecting the change of the vibration characteristics.

[0114] Step S3, based on the vibration signal and the temperature distribution parameter, extract the vibration spectrum feature parameter and the temperature gradient parameter to construct the Weibull probability model, and determine the key influence factor by Sobol global sensitivity analysis method;

[0115] In step S3, it further includes the following sub-steps:

[0116] S3-1, wavelet packet decomposition is performed on the collected vibration signal, the energy entropy parameters of 32 sub-bands in the frequency band of 0-50kHz are calculated, and the dimension is reduced to 5 vibration spectrum feature parameters through principal component analysis, the vibration spectrum feature parameters include energy entropy, main frequency, frequency center, bandwidth and kurtosis;

[0117] S3-2, based on the temperature distribution parameter collected by the quantum dot temperature sensor, the axial and radial temperature gradient parameters between the cylinder, piston and exhaust manifold are calculated, and the thermodynamic characteristic parameters are extracted, including the maximum gradient value, gradient change rate, average gradient value, gradient standard deviation, heat flux and thermal diffusivity;

[0118] S3-3, taking the vibration spectrum feature parameter as the observation variable and the axial and radial temperature gradient parameter as the state variable, a Weibull probability model is established, and the formula of the Weibull probability model is:

[0119]

[0120] Where P(∣) is the probability density function, T represents the temperature state vector, V represents the vibration feature vector, β is the shape parameter, η is the scale parameter, Υ is the location parameter, n represents the sub-band number of the vibration spectrum feature parameter, i represents the sub-band index of the vibration spectrum feature parameter, and e represents the base number of natural logarithm;

[0121] S3-4, Sobol global sensitivity analysis method is used to calculate the variance contribution rate of each input parameter to the model output, and the vibration frequency spectrum characteristic parameters with contribution rate > 15% and the axial and radial temperature gradient parameters are selected as the key influence factors.

[0122] It should be noted that wavelet packet decomposition is a multi-resolution analysis method used to decompose signals into sub-bands of different frequency bands. Through wavelet transform, signals can be decomposed in both time and frequency domains, providing time-frequency distribution of signals.

[0123] Calculate the energy entropy parameters of 32 sub-bands in the frequency range of 0-50 kHz: through wavelet packet decomposition, the vibration signal is decomposed into 32 sub-bands, each covering a specific frequency range.

[0124] Principal component analysis: a statistical method used to map high-dimensional data to low-dimensional space while preserving the main features of the data. Through linear transformation, data is projected into a new coordinate system, with the first principal component direction having the maximum variance, the second principal component next, and so on.

[0125] Dimension reduction to 5 vibration frequency spectrum characteristic parameters: reduce the energy entropy parameters of 32 sub-bands to 5 core vibration frequency spectrum characteristic parameters, reduce the data dimension, and improve the calculation efficiency.

[0126] Energy entropy: describes the energy distribution of vibration signals in different frequency bands. By calculating the energy entropy of each sub-band, the distribution characteristics of vibration energy in the frequency domain can be understood.

[0127] Dominant frequency: the frequency component with the highest energy in the vibration signal. The dominant frequency reflects the main frequency characteristics of the vibration signal, which is usually related to the main operating state of the engine.

[0128] Frequency center: describes the frequency distribution center position of the vibration signal. The frequency center can reflect the frequency distribution characteristics of the vibration signal, which helps to distinguish different types of vibration modes.

[0129] Bandwidth: describes the width of the frequency range of the vibration signal. Bandwidth reflects the frequency distribution range of the vibration signal, which can be used to evaluate the complexity of the vibration signal.

[0130] Kurtosis: describes the peak characteristics of the vibration signal. Kurtosis reflects the sharpness of the vibration signal, which is usually used to detect anomalies or impact components in the signal.

[0131] Axial and radial temperature gradient parameters: axial temperature gradient refers to the rate of temperature change along the engine axis direction, and radial temperature gradient refers to the rate of temperature change along the engine radial direction; by calculating the axial and radial temperature gradient parameters, the thermal distribution inside the engine can be comprehensively evaluated, and potential thermal fault areas can be identified.

[0132] Gradient rate of change: Describes the rate of change of temperature gradient over time. The gradient rate of change reflects the dynamic change characteristics of the temperature distribution, which helps to evaluate the thermal stability of the engine.

[0133] Average gradient value: Describes the average value of the temperature gradient in the temperature field. The average gradient value reflects the overall trend of the temperature distribution, which can be used to evaluate the thermal efficiency of the engine.

[0134] Gradient standard deviation: Describes the dispersion of the temperature gradient. The gradient standard deviation reflects the fluctuation characteristics of the temperature distribution, which helps to evaluate the thermal uniformity of the engine.

[0135] Heat flux: Describes the heat per unit area per unit time. The heat flux reflects the heat transfer efficiency inside the engine, which can be used to evaluate the cooling performance of the engine.

[0136] Thermal diffusivity: Describes the diffusion speed of heat in the engine material. The thermal diffusivity reflects the heat conduction characteristics of the engine material, which helps to evaluate the thermal management performance of the engine.

[0137] Shape parameter (β): Describes the shape of the Weibull distribution, indicating a decreasing failure rate when β<1, a constant failure rate when β=1, and an increasing failure rate when β>1.

[0138] Scale parameter (η): Describes the width of the Weibull distribution, affecting the dispersion of the data, and representing the characteristic life.

[0139] Location parameter (γ): Describes the starting point of the Weibull distribution, affecting the horizontal position of the distribution, and representing the minimum life, i.e., before this life, the cumulative distribution function of failure is 0.

[0140] Weibull probability model refers to the joint probability model of three-parameter Weibull distribution and hidden Markov chain. The three-parameter Weibull distribution is a commonly used reliability analysis model, which can describe the failure time distribution of equipment; the hidden Markov chain is a statistical model used to describe the transition probability of the system between different states; the joint probability model combines the three-parameter Weibull distribution and the hidden Markov chain, which can consider both the static and dynamic characteristics of the equipment, and more comprehensively evaluate the reliability of the equipment.

[0141] Sobol global sensitivity analysis method: Sobol global sensitivity analysis is a global sensitivity analysis method based on variance decomposition, which is used to evaluate the contribution of each input parameter to the output of the model; by calculating the variance contribution rate of each input parameter to the output of the model, the parameters with greater influence on the output of the model are identified, and the input parameters of the model are optimized.

[0142] Variance contribution rate: the variance contribution rate refers to the contribution proportion of a certain input parameter to the model output variance, which is used to measure the influence degree of the parameter on the model output; by calculating the variance contribution rate, the key parameters which have greater influence on the model output can be identified, thereby providing a basis for model optimization and parameter selection.

[0143] In step S4, the surface roughness parameters of the engine are obtained by using a field emission scanning electron microscope, the material composition parameters are obtained by energy spectrum analysis, and a parameter mapping relationship between the surface roughness parameters, the material composition parameters and the vibration frequency spectrum characteristic parameters is established.

[0144] In step S4, the following sub-steps are further included:

[0145] S4-1, a key wear area of the engine is selected as a target part for field emission scanning electron microscope detection, and the key wear area includes a piston ring, a cylinder sleeve, a crankshaft, a connecting rod, a valve, an exhaust manifold, an intake valve seat and a fuel nozzle.

[0146] S4-2, surface morphology scanning is performed on the target part by using a field emission scanning electron microscope to obtain surface roughness parameters, and the surface roughness parameters include average roughness, root mean square roughness and maximum height roughness.

[0147] S4-3, surface scanning is performed on the target part by using an energy spectrum analyzer to obtain material composition parameters, and the material composition parameters include base body iron element concentration, chromium element loss rate, oxidation wear index and lubricating film residual amount.

[0148] S4-4, partial least squares regression analysis is performed on the surface roughness parameters, the material composition parameters and the vibration frequency spectrum characteristic parameters, and the following mapping relationship matrix is established:

[0149]

[0150] In the formula, matrix A is a weight coefficient, and b is a bias term.

[0151] It should be noted that the key wear area refers to a part in the engine which is prone to wear and failure during operation, and the wear condition of these areas directly affects the performance and reliability of the engine.

[0152] Piston ring: the piston ring directly contacts the cylinder wall and bears the action of high-temperature and high-pressure gas, and is prone to wear, which leads to a decrease in the sealing performance of the cylinder.

[0153] Cylinder sleeve: the cylinder sleeve directly contacts the piston and bears the action of high-temperature and high-pressure gas, and is prone to wear, which leads to a decrease in the surface quality of the inner wall of the cylinder.

[0154] Crankshaft: the crankshaft is a core component of the engine, bears complex mechanical stress and thermal stress, and is prone to wear, which leads to a decrease in the surface quality of the journal.

[0155] Connecting rod: The connecting rod connects the piston and the crankshaft, and is subjected to high-frequency reciprocating motion and alternating stress. It is prone to loosening due to wear.

[0156] Valve: The valve controls the intake and exhaust of the engine and withstands the impact of high-temperature and high-pressure gases.

[0157] Exhaust manifold: The exhaust manifold is subjected to the impact and corrosion of high-temperature exhaust gas.

[0158] Intake valve seat: The intake valve seat controls the flow and pressure of the intake air and withstands the impact of high-frequency airflow.

[0159] Fuel nozzles: Fuel nozzles control the direction and atomization effect of fuel injection and withstand the impact of high-pressure fuel. Their injection performance is easily reduced due to wear.

[0160] A field emission scanning electron microscope (FET) is a high-resolution scanning electron microscope that uses a field emission electron source to provide high-brightness and high-resolution images.

[0161] Average roughness: Reflects the average surface roughness and is an important indicator for evaluating surface smoothness.

[0162] Root mean square roughness: reflects the standard deviation of surface roughness and can more comprehensively describe the unevenness of the surface.

[0163] Maximum height roughness: Reflects the maximum peak-to-valley height of a surface and is used to assess the extreme unevenness of a surface.

[0164] An energy dispersive X-ray spectroscopy (EDS) analyzer is an instrument used to analyze the composition of materials by detecting the characteristic energies of X-rays to determine the elemental composition of a sample.

[0165] Matrix iron concentration: reflects the matrix composition of the material and is an important indicator for assessing the wear condition of the material.

[0166] Chromium loss rate: This reflects the wear and tear of chromium, which is commonly used to improve the wear resistance and corrosion resistance of materials.

[0167] Oxidative wear index: Reflects the degree of oxidative wear of a material and is an important indicator for assessing material aging and wear.

[0168] Lubricating film residue: This reflects the coverage of the lubricating film. The amount of residual lubricating film directly affects the lubrication effect and wear condition of the engine.

[0169] Weighting coefficients (matrix A): represent the degree of contribution of the input variables to the output variables.

[0170] Bias term (b): Represents the model offset, used to adjust the model's fit.

[0171] Step S5, establish a warning system for vibration and temperature and perform a graded frequency sweep excitation and abrasive particle accelerated test, construct a multi-dimensional evaluation index system of parameter degradation process, and record the failure process by camera throughout the process;

[0172] In step S5, the following sub-steps are also included:

[0173] S5-1, establish a three-level warning threshold system for vibration amplitude parameters, with low warning threshold of 0.5 mm / s, medium warning threshold of 1.0 mm / s and high warning threshold of 1.5 mm / s. When the engine vibration amplitude exceeds the low warning threshold, the monitoring frequency of the superconducting quantum interference device is increased, when it exceeds the medium warning threshold, the magneto-rheological excitation device is started for frequency sweep excitation, and when it exceeds the high warning threshold, the full-power frequency sweep excitation is activated;

[0174] S5-2, construct a self-adaptive diagnosis algorithm for temperature anomalies, calculate the axial temperature gradient parameter between the engine cylinder, piston and exhaust manifold in real time, when the temperature gradient value exceeds 5℃ / mm, trigger the abrasive particle injection system to inject abrasive particles with particle size range of 10-50 microns for abrasive particle accelerated test;

[0175] S5-3, construct a multi-dimensional evaluation index system of parameter degradation process, including vibration amplitude change rate, temperature change rate, torque fluctuation amplitude and wear depth;

[0176] S5-4, use a camera with frame rate >1000fps to continuously shoot the evolution process of the engine from the appearance of initial abnormal signs to complete failure, and mark the time stamp of each frame of image through a time synchronizer.

[0177] It should be noted that the low warning threshold of 0.5 mm / s: the low warning threshold of 0.5 mm / s is set based on the background level of vibration amplitude when the engine is running normally. When the vibration amplitude exceeds this threshold, it indicates that the engine may have slight abnormalities, and the monitoring frequency needs to be increased to obtain more detailed data for further analysis and evaluation.

[0178] The medium warning threshold of 1.0 mm / s: the medium warning threshold of 1.0 mm / s is set according to the vibration amplitude of the engine under moderate abnormal conditions. When the vibration amplitude exceeds this threshold, it indicates that the abnormal condition of the engine may be more significant, and the magneto-rheological excitation device needs to be started for frequency sweep excitation to prepare for more in-depth testing and analysis.

[0179] The high warning threshold of 1.5 mm / s: the high warning threshold of 1.5 mm / s is set for the possible serious abnormal conditions of the engine. When the vibration amplitude exceeds this threshold, it indicates that the engine may have significant risk of failure, and full-power frequency sweep excitation needs to be activated to simulate the vibration response under extreme conditions and accelerate the exposure of potential faults.

[0180] Full power sweep excitation: When the engine vibration amplitude exceeds the high alert threshold, full power sweep excitation is activated to simulate the vibration response under extreme conditions, accelerating the exposure of potential faults. Full power sweep excitation can cover a wider frequency range, helping to identify the dynamic response characteristics of the engine at different frequencies.

[0181] Adaptive diagnosis algorithm for temperature anomalies: The adaptive diagnosis algorithm is an algorithm that can automatically adjust the diagnosis strategy based on real-time data. By calculating the temperature gradient parameter in real time, it identifies temperature anomalies and takes timely measures such as triggering the abrasive particle injection system.

[0182] Temperature gradient value: The specific value of the temperature gradient, indicating the rate of change of temperature at a certain point in space, used to describe the degree of temperature change along the axial direction between the engine block, piston and exhaust manifold. The gradient value reflects the rate of temperature change per unit distance in a particular direction.

[0183] Trigger abrasive particle injection system when gradient value exceeds 5℃ / mm: The gradient value of 5℃ / mm is a preset threshold for determining whether the temperature change is abnormal. When the gradient value exceeds this threshold, it indicates that the engine may have a risk of thermal failure, so the abrasive particle injection system is triggered to simulate the wear condition in actual operation and accelerate fault exposure.

[0184] Abrasive particle injection system: The abrasive particle injection system is used to inject abrasive particles into the engine to simulate the wear condition in actual operation. By injecting abrasive particles, it can accelerate fault exposure and identify potential fault points in advance.

[0185] Abrasive particles with a particle size range of 10-50 microns: The particle size range of 10-50 microns is selected based on the actual wear condition inside the engine. Abrasive particles with this particle size range can effectively simulate the wear condition in actual operation without causing excessive damage to the engine.

[0186] Parameter degradation process: Refers to the process of gradual decline in engine performance parameters due to various factors such as wear, fatigue and aging. Changes in these parameters reflect the deterioration of engine state and are an important basis for evaluating engine reliability and remaining service life.

[0187] Multi-dimensional evaluation index system: The multi-dimensional evaluation index system includes vibration amplitude change rate, temperature change rate, torque fluctuation amplitude and wear depth. These indicators can comprehensively evaluate the engine parameter degradation process and identify potential fault modes.

[0188] High-speed camera with frame rate >1000fps: Using high-speed camera with frame rate >1000fps is to capture the whole process from initial abnormality to final failure of the engine, ensure the continuity and traceability of the recording, high frame rate can provide more detailed dynamic information, which is helpful for subsequent detailed analysis and fault diagnosis.

[0189] Time synchronizer: Time synchronizer is used to mark the timestamp of each frame of image, to ensure the continuity and traceability of the recording, through the time synchronizer, the shooting time of each frame of image can be accurately known, which is convenient for subsequent detailed analysis and fault diagnosis.

[0190] Step S6, integrating vibration spectrum characteristic parameters, temperature distribution parameters and wear morphology parameters, generating three-dimensional parameter cloud picture, outputting reliability test report;

[0191] In step S6, the following sub-steps are further included:

[0192] S6-1, using timestamp backtracking technology, aligning vibration spectrum characteristic parameters, temperature distribution parameters and wear morphology parameters to the same time reference, time synchronization accuracy is better than 10μs, temperature distribution parameters include three-dimensional temperature distribution data of cylinder, piston and exhaust manifold collected by quantum dot temperature sensor array, wear morphology parameters represent surface roughness parameters and material composition parameters;

[0193] S6-2, based on Kriging interpolation algorithm, mapping discrete vibration and temperature parameters to the surface of engine three-dimensional CAD model, generating 0.1mm resolution parameter distribution cloud picture, supporting transparency superimposed display of multi-physical field data;

[0194] S6-3, three-dimensional morphology reconstruction of micro-morphology obtained by field emission scanning electron microscope, mapping wear morphology parameters of corresponding position of engine to the whole machine model through feature matching algorithm;

[0195] S6-4, combining Weibull probability model output and data of parameter degradation process, calculating reliability index, reliability index includes mean time between failures, reliability, failure rate, wear rate, parameter degradation rate, remaining useful life, failure probability and maintenance interval;

[0196] S6-5, based on XML template, automatically generating reliability test report, including parameter evolution animation, three-dimensional interactive model and original data block chain hash value.

[0197] It should be noted that the timestamp backtracking technology: timestamp backtracking technology is a technology for synchronizing and aligning multi-source data, by attaching high-precision timestamp to each data point, and aligning data according to these timestamps in subsequent processing.

[0198] Kriging interpolation algorithm: Kriging interpolation algorithm is a geostatistical method used to estimate the value of unknown locations by calculating spatial autocorrelation, generating high-resolution parameter distribution maps, suitable for complex spatial data interpolation.

[0199] Feature matching algorithm: Feature matching algorithm is an image processing technique used to find corresponding feature points between different images or models, and can accurately map local wear parameters to corresponding positions on the whole machine model.

[0200] Roughness: Reflects the microscopic unevenness of the surface, is an important indicator for evaluating the wear state of the surface.

[0201] Crack length: Reflects the crack situation of the material, is an important indicator for evaluating the fatigue and wear of the material.

[0202] Reliability (R(t)): The probability that the engine does not fail within a certain time t.

[0203] Failure rate (λ(t)): The instantaneous probability of engine failure within a certain time t.

[0204] Wear rate: The wear rate of the key components of the engine.

[0205] Remaining useful life: The time that the engine is expected to operate normally under the current state.

[0206] Failure probability: The probability of engine failure within a certain time.

[0207] Maintenance interval: The recommended maintenance period to ensure the reliable operation of the engine within that period.

[0208] XML template: XML template is a template based on XML format, used to define the structure and content of the report.

[0209] Raw data blockchain hash value: The hash value of the data generated by the blockchain technology, to ensure the authenticity and non-tamperability of the data.

[0210] Please refer to Figure 2 , which shows the system architecture diagram of a reliability verification system for a small general-purpose engine provided by an embodiment of the present application, comprising:

[0211] Parameter acquisition module: composed of superconducting quantum interferometer vibration detection unit and quantum dot temperature sensor array, used to realize the acquisition of vibration signal and temperature distribution parameters;

[0212] It should be noted that the superconducting quantum interferometer vibration detection unit: arranged on the surface of the engine cylinder, crankcase and exhaust manifold, continuously collects vibration signals in the range of 0-50kHz with a sampling frequency of 100kHz.

[0213] Quantum dot temperature sensor array: arranged on the cylinder head, piston skirt and exhaust manifold surface, forming a 4x4 grid layout, with a sensor spacing of 5mm, capable of measuring temperature changes.

[0214] Working condition test module: contains programmable cold and hot shock box, electromagnetic dynamometer, computer and random vibration table, used to perform multi-working condition parameter test and obtain dynamic response parameters;

[0215] Note that the programmable cold and hot shock box: cycles between -20℃ and 50℃ at a rate of 10℃ / min, each temperature platform is maintained for 60 minutes, and the temperature parameter dynamic response is recorded by embedded PT100 temperature sensor at a frequency of 1Hz.

[0216] Electromagnetic dynamometer: the engine load is increased to 80%-100% of rated power at a gradient of 10% rated load / minute, and the output signals of the speed sensor and torque sensor are synchronously collected at a sampling interval of 100ms during the linear change of the speed from idle to rated value.

[0217] Computer: controls the speed and load of the engine, simulates random working conditions in actual use, the change range of speed and load is 20%-100% of rated speed and 10%-100% of rated load respectively, and the test time is 50-100 hours.

[0218] Random vibration table: applies random vibration spectrum (10-1000Hz, RMS acceleration 0.5-5g) to the engine body, crankcase and exhaust manifold to continuously obtain vibration spectrum parameters.

[0219] Modeling analysis module: a computing unit equipped with Weibull probability model algorithm and parameter sensitivity analysis program, used to complete reliability modeling;

[0220] Note that the Weibull probability model algorithm: based on vibration spectrum characteristic parameters and temperature gradient parameters, a joint probability model of three-parameter Weibull distribution and hidden Markov chain is constructed.

[0221] Parameter sensitivity analysis program: uses Sobol global sensitivity analysis method to calculate the variance contribution rate of each input parameter to the model output, and selects vibration spectrum sub-band and temperature gradient parameters with contribution rate >15% as key influencing factors.

[0222] Microscopic detection module: a combined system integrating field emission scanning electron microscope and energy spectrometer, used to perform engine surface roughness parameter and material composition parameter detection;

[0223] Need to explain, field emission scanning electron microscope: the key wear area of the engine (piston ring, cylinder sleeve, crankshaft) surface morphology scanning, get the surface roughness parameters, including the average roughness, root mean square roughness and maximum height roughness.

[0224] Energy spectrum analyzer: surface scanning of key wear area, obtaining material composition parameters, including matrix iron element concentration, chromium element loss rate, oxidation wear index and lubricating film residual amount.

[0225] Acceleration test module: composed of magneto rheological excitation device, abrasive particle injection system, camera and time synchronizer, used for implementing parameter threshold triggered sweep frequency excitation and abrasive particle injection test;

[0226] Need to explain, magneto rheological excitation device: when the vibration amplitude exceeds the medium warning threshold (1.0mm / s), start the magneto rheological excitation device for sweep frequency excitation.

[0227] Abrasive particle injection system: when the temperature gradient value exceeds 5℃ / mm, trigger the abrasive particle injection system, inject abrasive particles with particle size range of 10-50 microns.

[0228] Camera: use high-speed camera with frame rate >1000fps to continuously shoot the whole process of engine from initial abnormality to final failure.

[0229] Time synchronizer: mark the time stamp of each frame of image through time synchronizer, ensure the continuity and traceability of the record.

[0230] Report generation module: contains three-dimensional visualization workstation and block chain storage terminal, used for creating three-dimensional parameter cloud picture and outputting reliability test report.

[0231] Need to explain, three-dimensional visualization workstation: based on Kriging interpolation algorithm, map the discrete vibration and temperature parameters to the surface of engine three-dimensional CAD model, generate 0.1mm resolution parameter distribution cloud picture, support transparency superposition display of multi-physical field data.

[0232] Block chain storage terminal: based on XML template to automatically generate reliability test report, including parameter evolution animation, three-dimensional interactive model and original data block chain hash value, ensure the authenticity and non-tamperability of the report.

[0233] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A reliability verification method for a small general-purpose engine, characterized by comprising: The method comprises: Step S1, collecting engine surface vibration signals using a superconducting quantum interferometer, and collecting temperature distribution parameters of the engine cylinder, piston and exhaust manifold using a quantum dot temperature sensor; Step S2, performing cold and hot impact, high load operation and random working condition combined testing on the engine, and synchronously monitoring the dynamic response characteristic data of temperature, speed, torque and vibration spectrum parameters; Step S3, based on the vibration signals and temperature distribution parameters, extracting vibration spectrum characteristic parameters and temperature gradient parameters to construct a Weibull probability model, and determining key influencing factors by a Sobol global sensitivity analysis method; Step S4, obtaining engine surface roughness parameters using a field emission scanning electron microscope, and obtaining material composition parameters through energy spectrum analysis, and establishing a parameter mapping relationship among the surface roughness parameters, material composition parameters and vibration spectrum characteristic parameters; Step S5, establishing a vibration and temperature early warning system and performing hierarchical sweep frequency excitation and abrasive particle accelerated testing, constructing a multi-dimensional evaluation index system of parameter degradation process, and recording the failure process through a camera throughout; Step S6, integrating vibration spectrum characteristic parameters, temperature distribution parameters and wear morphology parameters to generate a three-dimensional parameter cloud chart, and outputting a reliability test report.

2. The reliability test method of a small general-purpose engine according to claim 1, characterized in that: wherein in step S1, further comprising the following sub-steps: S1-1, arranging a superconducting quantum interferometer sensor array, setting ≥12 measuring points on the surface of the engine cylinder, crankcase and exhaust manifold, and continuously collecting vibration signals in the range of 0-50 kHz at a sampling frequency of 100 kHz; S1-2, processing the original vibration signals using a quantum Fourier transform algorithm, converting the time domain signals into frequency domain signals, and extracting the ground-state-excitation-state probability amplitude ratio characteristic parameters, while calculating the vibration amplitude parameters, which represent the fluctuation value of the collected vibration signals; S1-3, arranging quantum dot temperature sensors on the top of the engine cylinder, the piston skirt and the surface of the exhaust manifold to measure temperature changes, the quantum dot temperature sensor array includes 16 quantum dot temperature sensors, forming a 4×4 grid layout, and the spacing between the sensors is 5 mm; S1-4, calibrating the quantum dot temperature sensor data using an infrared camera with a wavelength range of 0.7-2.5 μm through multi-spectral radiation thermometry technology, and the calibration is automatically performed every 10 minutes; S1-5, collecting temperature distribution parameters through the quantum dot temperature sensor array, combining with the finite element analysis method, and constructing a three-dimensional temperature field parameter model to reflect the temperature distribution inside the engine.

3. The reliability test method of a small general-purpose engine according to claim 1, characterized in that: wherein in step S2, further comprising the following sub-steps: S2-1, performing cold and hot impact testing, placing the engine in a programmable cold and hot impact box, cycling between -20℃ and 50℃ at a rate of 10℃ / min, maintaining each temperature platform for 60 minutes, and recording the temperature parameter dynamic response of the engine cylinder, piston and lubrication system through an embedded PT100 temperature sensor at a frequency of 1 Hz; S2-2, high load operation test is performed, the engine load is raised to 80%-100% of the rated power by the electromagnetic dynamometer at a gradient of 10% rated load / minute, the output signals are synchronously collected by the built-in speed sensor and torque sensor at a sampling interval of 100 ms during the linear change of the engine speed from idle to rated value, and the parameter coupling characteristics of the speed and torque are recorded in real time; S2-3, random working condition test is performed, the speed and load of the engine are controlled by the computer to simulate the random working condition in actual use, the change ranges of the speed and load are 20%-100% of the rated speed and 10%-100% of the rated load respectively, the test time is 50-100 hours, the random vibration table is synchronously started to apply a random vibration spectrum to the engine body, the crankcase and the exhaust manifold, and the vibration frequency spectrum parameters are continuously obtained; S2-4, during the tests of cold and hot impact, high load operation and random working condition, the IEEE 1588v2 precision time protocol is used to synchronize the clocks of the embedded PT100 temperature sensor, the speed sensor, the torque sensor and the vibration signal acquisition link, and the dynamic response characteristic data of the temperature, the speed, the torque and the vibration frequency spectrum parameters of the engine are synchronously monitored; S2-5, the dynamic response characteristic data collected are subjected to time-frequency analysis, and characteristic values are extracted, the characteristic values including the temperature change rate, the speed fluctuation amplitude, the torque fluctuation amplitude and the first 5 order resonance frequency offset of the vibration frequency spectrum.

4. The reliability verification method of the small general-purpose engine according to claim 1, characterized in that: wherein in step S3, the following sub-steps are further included: S3-1, the collected vibration signals are subjected to wavelet packet decomposition, the energy entropy parameters of 32 sub-bands in the 0-50 kHz frequency band are calculated, and the dimension is reduced to 5 vibration frequency spectrum characteristic parameters through principal component analysis, the vibration frequency spectrum characteristic parameters including the energy entropy, the main frequency, the frequency center, the bandwidth and the kurtosis; S3-2, based on the temperature distribution parameters collected by the quantum dot temperature sensor, the axial and radial temperature gradient parameters between the cylinder body, the piston and the exhaust manifold are calculated, and the thermodynamic characteristic parameters are extracted, the thermodynamic characteristic parameters including the maximum gradient value, the gradient change rate, the average gradient value, the gradient standard deviation, the heat flux and the thermal diffusivity; S3-3, the Weibull probability model is established with the vibration frequency spectrum characteristic parameters as the observation variables and the axial and radial temperature gradient parameters as the state variables, the formula of the Weibull probability model being: wherein P(∣) is the probability density function, T represents the temperature state vector, V represents the vibration characteristic vector, β is the shape parameter, η is the scale parameter, Y is the location parameter, n represents the sub-band number of the vibration frequency spectrum characteristic parameters, i represents the sub-band index of the vibration frequency spectrum characteristic parameters, and e represents the base number of the natural logarithm; S3-4, the Sobol global sensitivity analysis method is used to calculate the variance contribution rate of each input parameter to the model output, and the vibration frequency spectrum characteristic parameters and the axial and radial temperature gradient parameters with a contribution rate >15% are selected as the key influencing factors.

5. The reliability verification method of a small general-purpose engine according to claim 1, characterized in that: wherein in step S4, further comprising the following sub-steps: S4-1, selecting the key wear area of the engine as the target site for field emission scanning electron microscope detection, the key wear area including piston ring, cylinder sleeve, crankshaft, connecting rod, valve, exhaust manifold, intake valve seat and fuel nozzle; S4-2, using field emission scanning electron microscope to scan the surface morphology of the target site, obtaining surface roughness parameters, including average roughness, root mean square roughness and maximum height roughness; S4-3, using energy spectrum analyzer to scan the target site, obtaining material composition parameters, including matrix iron element concentration, chromium element loss rate, oxidation wear index and lubricating film residual amount; S4-4, performing partial least squares regression analysis on the surface roughness parameters, material composition parameters and vibration frequency spectrum characteristic parameters, and establishing the following mapping relationship matrix: wherein, matrix A is the weight coefficient, and b is the bias term.

6. The reliability verification method of a small general-purpose engine according to claim 2, characterized in that: wherein in step S5, further comprising the following sub-steps: S5-1, establishing a three-level early warning threshold system for vibration amplitude parameters, respectively 0.5mm / s low warning threshold, 1.0mm / s medium warning threshold and 1.5mm / s high warning threshold, when the engine vibration amplitude exceeds the low warning threshold, the monitoring frequency of the superconducting quantum interference device is increased, when the medium warning threshold is exceeded, the magnetic rheological excitation device is started for frequency sweeping excitation, and when the high warning threshold is exceeded, the full power frequency sweeping excitation is activated; S5-2, constructing an adaptive diagnosis algorithm for temperature anomalies, real-time calculating the axial temperature gradient parameters between the engine cylinder, piston and exhaust manifold, when the temperature gradient value exceeds 5℃ / mm, triggering the abrasive particle injection system to inject abrasive particles with particle size range of 10-50 microns for abrasive particle accelerated test; S5-3, constructing a multi-dimensional evaluation index system for parameter degradation process, including vibration amplitude change rate, temperature change rate, torque fluctuation amplitude and wear depth; S5-4, using a camera with frame rate >1000fps to continuously shoot the evolution process of the engine from the appearance of initial abnormal signs to complete failure, and marking the time stamp of each frame of image through a time synchronizer.

7. The reliability verification method of a small general-purpose engine according to claim 1, characterized in that: wherein in step S6, further comprising the following sub-steps: S6-1, using timestamp backtracking technology, aligning the vibration frequency spectrum characteristic parameters, temperature distribution parameters and wear morphology parameters to the same time reference, the time synchronization accuracy is better than 10μs, the temperature distribution parameters include three-dimensional temperature distribution data of cylinder, piston and exhaust manifold collected by quantum dot temperature sensor array, and the wear morphology parameters represent surface roughness parameters and material composition parameters; S6-2, based on the Kriging interpolation algorithm, the discrete vibration, temperature parameters are mapped to the engine three-dimensional CAD model surface, generating 0.1mm resolution parameter distribution cloud, supporting transparency superimposed display of multi-physical field data; S6-3, three-dimensional morphology reconstruction is performed on the micro morphology obtained by field emission scanning electron microscope, and the wear morphology parameters of the corresponding position of the engine are mapped to the whole machine model through feature matching algorithm; S6-4, the data of Weibull probability model output and parameter degradation process are integrated to calculate the reliability index, including mean time between failures, reliability, failure rate, wear rate, parameter degradation rate, remaining useful life, failure probability and maintenance interval; S6-5, based on XML template, reliability test report is automatically generated, including parameter evolution animation, three-dimensional interactive model and original data blockchain hash value.

8. A reliability testing system for a small general-purpose engine, characterized in that, It includes: Parameter acquisition module: composed of superconducting quantum interference vibration detection unit and quantum dot temperature sensor array, used for realizing the acquisition of vibration signal and temperature distribution parameters; Working condition test module: including programmable cold and hot shock box, electromagnetic dynamometer, computer and random vibration table, used for performing multi-working condition parameter test and obtaining dynamic response parameters; Modeling analysis module: the calculation unit loaded with Weibull probability model algorithm and parameter sensitivity analysis program, used for completing reliability modeling; Microscopic detection module: integrated field emission scanning electron microscope and energy spectrum analyzer combined system, used for performing engine surface roughness parameter and material composition parameter detection; Accelerated test module: composed of magneto rheological excitation device, abrasive particle injection system, camera and time synchronizer, used for implementing parameter threshold triggered sweep excitation and abrasive particle injection test; Report generation module: including three-dimensional visualization workstation and blockchain storage terminal, used for creating three-dimensional parameter cloud and outputting reliability test report.

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