Pre-tightening force stability test system for thin-walled angular contact ball bearing after assembly

Abstract

The application discloses a thin-wall angular contact ball bearing post-assembly pre-tightening force stability test system and belongs to the technical field of precision bearing test, specifically comprises a simulation working condition assembly module, a multi-dimension test driving module, a multi-path test data acquisition module and a multi-dimension evaluation module; the application is a complete technical chain from direct sensing perception to systematic excitation to quantitative feature extraction to multi-dimension intelligent diagnosis, is based on direct integration sensing of the bearing body to realize accurate data perception, realizes multi-factor isolation evaluation and coupling analysis means in the systematic test path oriented by failure mechanism, realizes the output of diagnosis conclusion by the quantitative feature parameter system and the intelligent evaluation model as the core, finally achieves the overall technical effect of full-dimension coverage, full-process tracing and intelligent evaluation on the post-assembly pre-tightening force stability of the thin-wall angular contact ball bearing, and effectively solves the technical problem that the long-term stability of the pre-tightening force cannot be systematically evaluated.

Description

Technical Field

[0001] This invention relates to the field of precision bearing testing technology, and more specifically, to a system for testing the preload stability of thin-walled angular contact ball bearings after assembly. Background Technology

[0002] Thin-walled angular contact ball bearings are widely used in aerospace, precision machine tools, robotics and other fields due to their advantages such as lightweight, high rigidity and high speed. Their technical performance is highly dependent on the preload applied during assembly. Insufficient preload will lead to a decrease in rigidity and loss of precision, while excessive preload will increase temperature rise and wear, and reduce life.

[0003] However, the preload is not a fixed value. During the long-term service of the bearing after assembly, it will decay or fluctuate due to the coupling effect of various factors such as material stress relaxation, micro creep, temperature cycling, and dynamic alternating load. In other words, there is a problem with the stability of the preload. This stability directly determines the long-term accuracy and reliability of the equipment.

[0004] For bearing performance testing, existing technologies have made some progress. For example, Chinese patent application CN117451356A discloses a "service performance testing system for angular contact ball bearings based on fiber optic gratings." This system involves setting a measuring spacer with an integrated fiber optic grating sensor between two sets of test bearings. It can indirectly measure the preload force of the bearing during operation and simultaneously monitor temperature rise and vibration. This solution applies fiber optic grating technology to the performance testing of angular contact ball bearings and has certain advantages. However, it still has the following shortcomings:

[0005] On the one hand, in terms of sensing method, only the measuring spacer is used as the carrier of the sensing element, and the bearing preload is indirectly calculated by measuring the deformation of the spacer. This indirect measurement method has the loss and error of force transmission path, and the measuring spacer, as an additional component, is difficult to truly reflect the preload state inside the bearing.

[0006] On the other hand, in terms of the test path, although axial and radial forces are applied and the spindle is driven to rotate, the test process lacks a systematic test path system designed according to the failure mechanism: it simply applies load and runs the test, which cannot isolate, evaluate and couple the factors such as time, temperature, axial dynamic load, and radial dynamic load, making it difficult to reveal the internal causes and evolution laws of the preload change.

[0007] Additionally, in terms of data processing, it only stays at the level of collecting raw strain signals, wavelength signals, and spectrum signals, lacking a clearly defined and quantifiable multi-dimensional stability characteristic parameter system: its output is raw test data, rather than refined stability indicators with clear physical meaning, which cannot be directly used for quantitative evaluation of bearing stability, nor can it fuse the collected multi-source data to output a comprehensive stability conclusion. Its function stops at "data acquisition" and has not yet entered the level of "intelligent diagnosis".

[0008] In summary, to address the aforementioned technical deficiencies, a preload stability testing system for thin-walled angular contact ball bearings is proposed. This system enables direct sensing of the bearing body, execution of tests according to a systematic testing path, extraction of multi-dimensional quantitative feature parameters, and intelligent comprehensive evaluation. Summary of the Invention

[0009] The purpose of this invention is to solve practical problems. It provides a preload stability testing system for thin-walled angular contact ball bearings after assembly. The system enables direct sensing of the bearing body, execution of tests according to a systematic test path designed according to the failure mechanism, extraction of quantitative stability characteristic parameters with clear physical meaning, and intelligent comprehensive evaluation.

[0010] The objective of this invention can be achieved through the following technical solution: a preload stability testing system for thin-walled angular contact ball bearings after assembly, comprising: a simulated working condition assembly module, used to provide and fix a test fixture that simulates an actual support structure, wherein the thin-walled angular contact ball bearing to be tested and integrated with the sensing unit of the bearing body is installed in the test fixture according to a preset assembly process and preload requirements to form a bearing assembly under test;

[0011] The multi-dimensional test drive module connects to and acts on the bearing assembly under test. It is used to apply controllable physical field excitation to the assembly according to the failure mechanism through a multi-test path matrix. The multi-test path matrix includes a single-factor basic test path set and a multi-factor composite test path set. The test path set is executed with preset collaborative logic. The single-factor basic test path set includes at least long-term static relaxation test, axial dynamic load test, radial dynamic load test and temperature cycle test. The multi-factor composite test path set includes at least dynamic composite load test and thermo-mechanical coupling test.

[0012] The multi-path test data acquisition module is used to collect and process sensor signals responding to different test paths in real time, and output standardized test data packets for each test path.

[0013] The multi-dimensional evaluation module receives standardized test data packets, executes the feature extraction algorithm corresponding to the data packet to obtain stability feature parameters, performs a comprehensive stability evaluation, and outputs the stability evaluation results.

[0014] Furthermore, the multi-dimensional test drive module includes an axial loading unit, a radial loading unit, a rotary drive unit, and an environmental simulation unit. These multiple units work together to apply controllable physical field excitation to the bearing assembly under test. Specifically, the axial loading unit applies an initial static axial preload and a dynamic alternating axial load to the spindle of the bearing assembly under test; the radial loading unit applies a static radial force or a dynamic alternating radial load to the bearing housing of the bearing assembly under test; the rotary drive unit drives the spindle of the bearing assembly under test to rotate; and the environmental simulation unit provides a high-low temperature cycling environment or a constant temperature environment for the bearing assembly under test by setting up a temperature control chamber.

[0015] Furthermore, the multi-dimensional test-driven module executes a set of single-factor basic test paths using pre-defined collaborative logic, which includes:

[0016] When performing a long-term static relaxation test, the axial loading unit is controlled to apply and lock an initial static axial preload to the spindle of the bearing assembly under test, the rotary drive unit is controlled to keep the spindle of the bearing assembly under test stationary, the environmental simulation unit is controlled to maintain a constant temperature, and the radial loading unit is controlled to either not load or apply and lock a static radial force.

[0017] When performing axial dynamic load test, the axial loading unit is controlled to superimpose dynamic axial alternating load on the initial static axial preload, while the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate, the environmental simulation unit is controlled to maintain constant temperature, and the radial loading unit is controlled not to load.

[0018] When performing radial dynamic load tests, the radial loading unit is controlled to apply dynamic radial alternating loads, while the rotary drive unit is controlled to drive the spindle to rotate, the axial loading unit is controlled to apply and lock the initial static axial preload, and the environmental simulation unit is controlled to maintain a constant temperature.

[0019] During temperature cycling tests, the axial loading unit applies and locks the initial static axial preload, while the environmental simulation unit performs temperature cycling, and the rotary drive unit keeps the spindle of the bearing assembly under test stationary or rotating at low speed.

[0020] Furthermore, the multi-dimensional test-driven module executes a set of multi-factor composite test paths according to a preset collaborative logic, which includes:

[0021] When performing dynamic composite load testing, the axial loading unit and the radial loading unit are controlled synchronously to apply dynamic axial alternating load and dynamic radial alternating load with preset amplitude, frequency and phase relationship, respectively, and the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate.

[0022] When performing thermo-mechanical coupling tests, while the environmental simulation unit performs temperature cycling or maintains high temperature, the axial loading unit and / or radial loading unit are simultaneously controlled to apply dynamic mechanical loads, and optionally the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate.

[0023] Furthermore, the process of obtaining standardized test data packets for each test path includes:

[0024] The multi-path test data acquisition module synchronously collects raw sensing signals from the sensing unit, as well as working condition feedback signals from the axial loading unit, radial loading unit, rotary drive unit, and environmental simulation unit. Based on the built-in preset preload calibration model, it calculates and outputs the preload data sequence of the raw sensing signals of each test path in real time.

[0025] The preload data sequence is aligned with the synchronously acquired working condition feedback signal by timestamp and the corresponding test path identifier is marked to form a standardized test data package, which specifically includes long-term static relaxation test data package, axial dynamic load test data package, radial dynamic load test data package, temperature cycle test data package, dynamic composite load test data package and thermo-mechanical coupling test data package.

[0026] Furthermore, the process by which the multi-dimensional evaluation module obtains stability characteristic parameters includes:

[0027] For long-term static relaxation testing, a long-term static relaxation test data packet is received, which contains preload force data and constant temperature data based on a first time series. Static time dimension stability feature parameters are extracted based on this data packet.

[0028] For axial dynamic load testing, an axial dynamic load test data packet is received. This data packet contains preload data, axial load data, and spindle speed data based on a second time series. Based on this data packet, stability feature parameters of the axial dynamic dimension are extracted.

[0029] For radial dynamic load testing, a radial dynamic load test data packet is received. This data packet contains preload data, radial load data, and spindle speed data based on a third time series. Based on this data packet, radial dynamic dimension stability feature parameters are extracted.

[0030] For temperature cycling tests, a temperature cycling test data packet is received, which contains preload force data and ambient temperature data based on a fourth time series. Based on this data packet, thermodynamic stability feature parameters are extracted.

[0031] For dynamic composite load testing, a dynamic composite load test data packet is received. This data packet contains preload data, axial load data, radial load data, and spindle speed data based on the fifth time series. Composite load coupling characteristic parameters are extracted based on this data packet.

[0032] For performing thermo-mechanical coupling tests, a thermo-mechanical coupling test data packet is received. This data packet contains preload data, dynamic mechanical load data, and ambient temperature data based on a sixth time series. The thermo-mechanical coupling characteristic parameters are extracted based on this data packet.

[0033] Furthermore, the process of conducting a comprehensive stability assessment based on stability characteristic parameters includes:

[0034] The system receives multiple stability feature parameters extracted from each test data packet, which form a multi-dimensional feature vector for the corresponding test path. The multi-dimensional feature vector is then input into a preset comprehensive stability evaluation model, which outputs a quantified comprehensive stability score. The comprehensive evaluation model is either a weighted scoring model based on expert rules and thresholds, or a machine learning model trained based on historical test data and known stability state labels.

[0035] Compared with the prior art, the advantages of this invention are:

[0036] 1. This solution integrates fiber optic grating sensors or micro-thin film strain gauges directly into the body of a thin-walled angular contact ball bearing. By directly integrating the sensor into the bearing body and incorporating a preload calibration model, the sensor signal is inverted and calculated in real time, enabling direct, real-time, and accurate measurement of the preload. This achieves the goal of eliminating transmission errors and accurately reflecting the internal preload state of the bearing.

[0037] 2. This scheme also designs a single-factor basic test path set and a multi-factor composite test path set according to the failure mechanism of bearing preload decay, and defines the collaborative logic of axial loading unit, radial loading unit, rotary drive unit and environmental simulation unit under each test path, so as to realize the isolated evaluation and coupled analysis of the influence of different factors such as time, temperature, axial dynamics and radial dynamics, reveal the root cause of preload change, and effectively improve the accuracy of attribution analysis.

[0038] 3. This solution also defines quantitative stability characteristic parameters with clear physical meaning for different test paths, and integrates and analyzes multi-dimensional characteristic parameters by constructing a comprehensive stability evaluation model, so as to realize the transformation from raw test data to intelligent diagnostic conclusions, and provide direct and accurate criteria for bearing selection, assembly process optimization and predictive maintenance decisions. Attached Figure Description

[0039] Figure 1 This is a system principle block diagram of the present invention;

[0040] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0042] Example 1: This invention discloses a preload stability testing system for thin-walled angular contact ball bearings after assembly. Please refer to [link / reference]. Figures 1-2 It includes a simulated working condition assembly module, a multi-dimensional test-driven module, a multi-path test data acquisition module, and a multi-dimensional evaluation module;

[0043] The simulated working condition assembly module is used to provide and fix a test fixture that simulates the actual support structure. The thin-walled angular contact ball bearing to be tested, which integrates a sensing unit with the bearing body, is installed in the test fixture according to the preset assembly process and preload requirements to form a bearing assembly under test.

[0044] At least one set of thin-walled angular contact ball bearings in the bearing assembly under test is an integrated sensing bearing. Precision grooves are provided in its outer ring or end face for embedding strain sensing units. The strain sensing units are fiber optic grating sensors or micro thin-film strain gauges. The outer ring of the integrated sensing bearing is also provided with signal lead microchannels, so as to realize the sensing function without compromising the strength and accuracy of the bearing body.

[0045] The multi-dimensional test drive module connects to and acts on the bearing assembly under test. It includes an axial loading unit, a radial loading unit, a rotation drive unit, and an environmental simulation unit. The multi-unit cooperation applies controllable physical field excitation to the bearing assembly under test.

[0046] The axial loading unit is used to apply an initial static axial preload and a dynamic axial alternating load to the spindle of the bearing assembly under test; the radial loading unit is used to apply a static radial force or a dynamic radial alternating load to the bearing housing of the bearing assembly under test; the rotary drive unit is used to drive the spindle of the bearing assembly under test to rotate; and the environmental simulation unit is used to provide a high and low temperature cycling environment or a constant temperature environment for the bearing assembly under test by setting a temperature control chamber.

[0047] The multi-dimensional test-driven module is used to apply controllable physical field excitation to the multi-test path matrix designed according to the failure mechanism. The multi-test path matrix includes a single-factor basic test path set and a multi-factor composite test path set.

[0048] Among them, the single-factor basic test path set includes at least long-term static relaxation test, axial dynamic load test, radial dynamic load test and temperature cycle test, which are used to isolate and evaluate the influence of a single factor on the stability of preload. The multi-factor composite test path set includes at least dynamic composite load test and thermo-mechanical coupling test, which are used to evaluate the influence of multi-factor coupling effect on the stability of preload.

[0049] The multi-dimensional test-driven module executes a set of single-factor basic test paths using pre-defined collaborative logic. This collaborative logic includes:

[0050] When performing a long-term static relaxation test, the axial loading unit is controlled to apply and lock an initial static axial preload to the spindle of the bearing assembly under test, the rotary drive unit is controlled to keep the spindle of the bearing assembly under test stationary, the environmental simulation unit is controlled to maintain a constant temperature, and the radial loading unit is controlled to either not load or apply and lock a static radial force.

[0051] When performing axial dynamic load test, the axial loading unit is controlled to superimpose dynamic axial alternating load on the initial static axial preload, while the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate, the environmental simulation unit is controlled to maintain constant temperature, and the radial loading unit is controlled not to load.

[0052] When performing radial dynamic load tests, the radial loading unit is controlled to apply dynamic radial alternating loads, while the rotary drive unit is controlled to drive the spindle to rotate, the axial loading unit is controlled to apply and lock the initial static axial preload, and the environmental simulation unit is controlled to maintain a constant temperature.

[0053] During temperature cycling tests, the axial loading unit is controlled to apply and lock the initial static axial preload, while the environmental simulation unit is controlled to perform temperature cycling, and the rotary drive unit is controlled to keep the spindle of the bearing assembly under test stationary or rotating at low speed.

[0054] The multi-dimensional test-driven module executes a set of multi-factor composite test paths according to a preset collaborative logic, which includes:

[0055] When performing dynamic composite load testing, the axial loading unit and the radial loading unit are controlled synchronously to apply dynamic axial alternating load and dynamic radial alternating load with preset amplitude, frequency and phase relationship, respectively, and the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate.

[0056] When performing thermo-mechanical coupling tests, while the environmental simulation unit performs temperature cycling or maintains high temperature, the axial loading unit and / or radial loading unit are simultaneously controlled to apply dynamic mechanical loads, and optionally the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate.

[0057] By applying a series of controllable physical field excitations to the bearing assembly under test through multi-unit coordination, including at least axial mechanical load, radial mechanical load, spindle rotation of the bearing assembly under test, and temperature field changes, the test path matrix of this invention can isolate and evaluate the influence of different factors such as time, temperature, axial dynamics, and radial dynamics (through single-factor basic test paths) and perform coupled analysis (through multi-factor composite test paths), thereby revealing the root cause of preload changes.

[0058] The multi-path test data acquisition module, whose input is connected to the sensing unit of the bearing assembly under test, is used to collect and process sensing signals responding to different test paths in real time, and output standardized test data packets for each test path. The acquisition process includes:

[0059] The multi-path test data acquisition module synchronously collects raw sensing signals from the sensing unit, as well as working condition feedback signals from the axial loading unit, radial loading unit, rotary drive unit, and environmental simulation unit. Based on the built-in preset preload calibration model, it calculates and outputs the preload data sequence of the raw sensing signals of each test path in real time.

[0060] Align the preload data sequence with the synchronously acquired working condition feedback signal according to the timestamp, and mark the corresponding test path identifier to form a standardized test data package;

[0061] Specifically, it includes long-term static relaxation test data packages, axial dynamic load test data packages, radial dynamic load test data packages, temperature cycling test data packages, dynamic composite load test data packages, and thermo-mechanical coupling test data packages.

[0062] The multi-dimensional evaluation module is connected to the control end of the multi-dimensional test drive module and the data end of the multi-path test data acquisition module, respectively. It is used to receive each standardized test data packet, execute the feature extraction algorithm corresponding to the data packet to obtain stability feature parameters, perform a comprehensive stability evaluation based on the stability feature parameters, and output the stability evaluation result.

[0063] This module's functionality comprises two levels: feature extraction and comprehensive evaluation. The process of obtaining stable feature parameters includes:

[0064] For long-term static relaxation testing, a long-term static relaxation test data packet is received. This data packet contains preload data and constant temperature data based on a first time series. The preload data is static axial preload. Based on this data packet, static time dimension stability feature parameters are extracted, including static preload retention rate. The static preload retention rate is the ratio of static axial preload at a preset time to the initial static axial preload, which is used to quantitatively evaluate the degree of preload attenuation caused by material stress relaxation within a long test period.

[0065] For axial dynamic load testing, an axial dynamic load test data packet is received. This data packet contains preload data, axial load data, and spindle speed data based on a second time series. Based on this data packet, stability characteristic parameters of the axial dynamic dimension are extracted, including the standard deviation of the dynamic fluctuation of the preload and the linear decay slope of the mean preload over the test duration. The standard deviation is used to quantitatively evaluate the fluctuation intensity of the preload under axial dynamic conditions, and the linear decay slope quantifies the trend relaxation under long-term dynamic operation. The smaller the standard deviation and the closer the linear decay slope is to 0, the better the stability of the bearing under axial dynamic conditions.

[0066] The stability characteristic parameters of the axial dynamic dimension are indirectly related to the spindle speed data, but the speed data is mainly used as the control parameters of the test conditions and the verification conditions for the validity of the data.

[0067] For radial dynamic load testing, a radial dynamic load test data packet is received. This data packet contains preload data, radial load data, and spindle speed data based on a third time series. Based on this data packet, radial dynamic dimension stability feature parameters are extracted, including the quasi-static sensitivity of preload to radial load. The quasi-static sensitivity of preload to radial load is the ratio between the preload and the radial load increment during the radial load change phase, which is used to quantitatively evaluate the sensitivity of preload to radial disturbances.

[0068] Similarly, within the time window for calculating quasi-static sensitivity, the rotational speed is constant and extremely low. The rotational speed data is not directly involved in the calculation formula for quasi-static sensitivity. Here, the spindle speed is mainly used as a control parameter for the test conditions and a verification condition for the validity of the data.

[0069] For temperature cycling tests, a temperature cycling test data packet is received. This data packet contains preload data and ambient temperature data based on a fourth time series. Based on this data packet, thermodynamic stability feature parameters are extracted, including the maximum range of preload variation in a single temperature cycle, which are used to quantitatively evaluate the preload fluctuation caused by temperature changes.

[0070] For dynamic composite load testing, a dynamic composite load test data packet is received. This data packet contains preload data, axial load data, radial load data, and spindle speed data based on the fifth time series. Based on this data packet, composite load coupling characteristic parameters are extracted, including the total preload fluctuation and the response amplitude ratio of the axial and radial loads. The total preload fluctuation is obtained by calculating the standard deviation of the preload data. The response amplitude ratio is the ratio of the spectral amplitude of the preload data at the dominant frequency of the axial load to the spectral amplitude at the dominant frequency of the radial load. This is used to quantitatively evaluate the comprehensive fluctuation characteristics and response characteristics of the preload under multi-axis dynamic load coupling.

[0071] For performing thermo-mechanical coupling tests, a thermo-mechanical coupling test data packet is received. This data packet contains preload data, dynamic mechanical load data, and ambient temperature data based on the sixth time series. Based on this data packet, thermo-mechanical coupling characteristic parameters are extracted, including the gradient of preload fluctuation intensity with temperature and the rate of change of dynamic stiffness with temperature. The gradient is obtained by calculating the value of preload fluctuation in different stable temperature ranges and linearly fitting the preload fluctuation with the corresponding temperature. The rate of change is obtained by calculating the gain of the frequency response function of preload to dynamic load in high temperature and low temperature ranges, and calculating the ratio or difference between the two to quantitatively evaluate the temperature sensitivity of preload under thermo-mechanical coupling.

[0072] For standardized test data packages for different test paths, the multi-dimensional evaluation module executes the corresponding feature extraction algorithm to obtain quantitative stability feature parameters with clear physical meaning, and transforms the original test data into quantitative indicators that can be directly used for stability evaluation.

[0073] The process of comprehensive stability evaluation based on the stability characteristic parameters of each test path includes:

[0074] The system receives multiple stability feature parameters extracted from each test data packet, which form a multi-dimensional feature vector for the corresponding test path. The multi-dimensional feature vector is then input into a preset comprehensive stability evaluation model, which outputs a quantified comprehensive stability score. The comprehensive evaluation model is either a weighted scoring model based on expert rules and thresholds, or a machine learning model trained based on historical test data and known stability state labels.

[0075] For the weighted scoring model, based on expert rules and thresholds, preset weight coefficients are added to each feature parameter, and the weighted sum is calculated after standardizing the scores of each feature parameter.

[0076] For machine learning models, based on historical test data and known stability state labels, support vector machines, random forests or neural network models are trained, and multidimensional feature vectors are directly mapped to stability levels (such as A / B / C / D levels) or remaining reliable lifetime predictions.

[0077] By constructing a comprehensive stability assessment model, a leap from "data acquisition" to "intelligent diagnosis" has been achieved, providing direct and accurate criteria for bearing reliability assessment and life prediction.

[0078] Example 2: This invention also proposes a method for testing the preload stability of thin-walled angular contact ball bearings after assembly. Please refer to [link / reference]. Figure 2 It includes the following steps:

[0079] S1: The bearing assembly under test is formed by simulating the working conditions assembly module;

[0080] The thin-walled angular contact ball bearing, which integrates various fiber optic grating sensors, is installed in the test fixture of the simulated working condition assembly module according to the preset assembly process to form the bearing assembly under test. Each test unit is initialized and the initial static axial preload is set.

[0081] S2: Through the multi-dimensional test drive module, a controllable physical field excitation is applied to the bearing assembly under test by a multi-test path matrix designed according to the failure mechanism. The multi-test path matrix includes a single-factor basic test path set and a multi-factor composite test path set. At least one single-factor basic test path and at least one multi-factor composite test path are selected.

[0082] S3: When executing each test path, execute each test path according to the corresponding collaborative logic, and generate the corresponding standardized test data package through the multi-path test data acquisition module;

[0083] S4: Based on the type of standardized test data package, call the corresponding feature extraction algorithm to extract the quantization stability feature parameters of the corresponding test path;

[0084] S5: Input the extracted multiple quantitative stability feature parameters into the stability comprehensive evaluation model, and output a quantitative comprehensive stability evaluation result.

[0085] In summary, this invention includes a simulated working condition assembly module, a multi-dimensional test driving module, a multi-path test data acquisition module, and a multi-dimensional evaluation module.

[0086] Among them, the simulated working condition assembly module is used to install the bearing under test with integrated sensing unit in the test fixture to form the bearing under test assembly; the multi-dimensional test drive module applies physical field excitation according to the test path matrix designed according to the failure mechanism, including single-factor basic test path and multi-factor composite test path.

[0087] The multi-path test data acquisition module collects sensor signals and generates standardized test data packets; the multi-dimensional evaluation module extracts quantitative stability feature parameters with clear physical meaning from each data packet and outputs a quantitative stability score through a comprehensive evaluation model.

[0088] This invention enables direct sensing of the bearing body, multi-factor isolation assessment and coupled analysis, quantitative feature parameter extraction and intelligent comprehensive evaluation, to solve the problem of the inability to systematically assess the long-term stability of preload. It can be widely used in the reliability verification and health management of precision bearings.

[0089] The above description is merely a preferred embodiment of the present invention; however, the scope of protection of the present invention is not limited thereto; any equivalent substitutions or modifications made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solution and its improved concept, should be covered within the scope of protection of the present invention.

Claims

1. A system for testing the preload stability of thin-walled angular contact ball bearings after assembly, characterized in that: include: The simulated working condition assembly module is used to provide and fix a test fixture that simulates the actual support structure. The thin-walled angular contact ball bearing to be tested, which integrates a sensing unit with the bearing body, is installed in the test fixture according to the preset assembly process and preload requirements to form a bearing assembly under test. A multi-dimensional test drive module is connected to and acts on the bearing assembly under test. It is used to apply controllable physical field excitation to the assembly according to the failure mechanism through a multi-test path matrix. The multi-test path matrix includes a single-factor basic test path set and a multi-factor composite test path set. The test path set is executed with preset collaborative logic. The single-factor basic test path set includes at least long-term static relaxation test, axial dynamic load test, radial dynamic load test and temperature cycle test. The multi-factor composite test path set includes at least dynamic composite load test and thermo-mechanical coupling test. The multi-path test data acquisition module is used to collect and process sensor signals responding to different test paths in real time, and output standardized test data packets for each test path. The multi-dimensional evaluation module receives standardized test data packets, executes the feature extraction algorithm corresponding to the data packet to obtain stability feature parameters, performs a comprehensive stability evaluation, and outputs the stability evaluation results.

2. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 1, characterized in that: The multi-dimensional test drive module includes an axial loading unit, a radial loading unit, a rotary drive unit, and an environmental simulation unit. These multiple units work together to apply controllable physical field excitation to the bearing assembly under test. Specifically, the axial loading unit applies an initial static axial preload and a dynamic alternating axial load to the spindle of the bearing assembly under test; the radial loading unit applies a static radial force or a dynamic alternating radial load to the bearing housing of the bearing assembly under test; the rotary drive unit drives the spindle of the bearing assembly under test to rotate; and the environmental simulation unit provides a high-low temperature cycling environment or a constant temperature environment for the bearing assembly under test by setting up a temperature control chamber.

3. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 2, characterized in that: The multi-dimensional test-driven module executes a set of single-factor basic test paths using pre-defined collaborative logic. This collaborative logic includes: When performing a long-term static relaxation test, the axial loading unit is controlled to apply and lock an initial static axial preload to the spindle of the bearing assembly under test, the rotary drive unit is controlled to keep the spindle of the bearing assembly under test stationary, the environmental simulation unit is controlled to maintain a constant temperature, and the radial loading unit is controlled to either not load or apply and lock a static radial force. When performing axial dynamic load test, the axial loading unit is controlled to superimpose dynamic axial alternating load on the initial static axial preload, while the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate, the environmental simulation unit is controlled to maintain constant temperature, and the radial loading unit is controlled not to load. When performing radial dynamic load tests, the radial loading unit is controlled to apply dynamic radial alternating loads, while the rotary drive unit is controlled to drive the spindle to rotate, the axial loading unit is controlled to apply and lock the initial static axial preload, and the environmental simulation unit is controlled to maintain a constant temperature. During temperature cycling tests, the axial loading unit applies and locks the initial static axial preload, while the environmental simulation unit performs temperature cycling, and the rotary drive unit keeps the spindle of the bearing assembly under test stationary or rotating at low speed.

4. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 3, characterized in that: The multi-dimensional test-driven module executes a set of multi-factor composite test paths according to preset collaborative logic. The collaborative logic includes: When performing dynamic composite load testing, the axial loading unit and the radial loading unit are controlled synchronously to apply dynamic axial alternating load and dynamic radial alternating load with preset amplitude, frequency and phase relationship, respectively, and the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate. When performing thermo-mechanical coupling tests, while the environmental simulation unit performs temperature cycling or maintains high temperature, the axial loading unit and / or radial loading unit are simultaneously controlled to apply dynamic mechanical loads, and optionally the rotary drive unit is controlled to drive the spindle of the bearing assembly under test to rotate.

5. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 4, characterized in that: The process of obtaining standardized test data packages for each test path includes: The multi-path test data acquisition module synchronously collects raw sensing signals from the sensing unit, as well as working condition feedback signals from the axial loading unit, radial loading unit, rotary drive unit, and environmental simulation unit. Based on the built-in preset preload calibration model, it calculates and outputs the preload data sequence of the raw sensing signals of each test path in real time. The preload data sequence is aligned with the synchronously acquired working condition feedback signal by timestamp and the corresponding test path identifier is marked to form a standardized test data package, which specifically includes long-term static relaxation test data package, axial dynamic load test data package, radial dynamic load test data package, temperature cycle test data package, dynamic composite load test data package and thermo-mechanical coupling test data package.

6. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 5, characterized in that: The process by which the multi-dimensional evaluation module obtains stability feature parameters includes: For long-term static relaxation testing, a long-term static relaxation test data packet is received, which contains preload force data and constant temperature data based on a first time series. Static time dimension stability feature parameters are extracted based on this data packet. For axial dynamic load testing, an axial dynamic load test data packet is received. This data packet contains preload data, axial load data, and spindle speed data based on a second time series. Based on this data packet, stability feature parameters of the axial dynamic dimension are extracted. For radial dynamic load testing, a radial dynamic load test data packet is received. This data packet contains preload data, radial load data, and spindle speed data based on a third time series. Based on this data packet, radial dynamic dimension stability feature parameters are extracted. For temperature cycling tests, a temperature cycling test data packet is received, which contains preload force data and ambient temperature data based on a fourth time series. Based on this data packet, thermodynamic stability feature parameters are extracted. For dynamic composite load testing, a dynamic composite load test data packet is received. This data packet contains preload data, axial load data, radial load data, and spindle speed data based on the fifth time series. Composite load coupling characteristic parameters are extracted based on this data packet. For performing thermo-mechanical coupling tests, a thermo-mechanical coupling test data packet is received. This data packet contains preload data, dynamic mechanical load data, and ambient temperature data based on a sixth time series. The thermo-mechanical coupling characteristic parameters are extracted based on this data packet.

7. The preload stability testing system for thin-walled angular contact ball bearings after assembly according to claim 6, characterized in that: The process of comprehensive stability assessment based on stability characteristic parameters includes: The system receives multiple stability feature parameters extracted from each test data packet, which form a multi-dimensional feature vector for the corresponding test path. The multi-dimensional feature vector is then input into a preset comprehensive stability evaluation model, which outputs a quantified comprehensive stability score. The comprehensive evaluation model is either a weighted scoring model based on expert rules and thresholds, or a machine learning model trained based on historical test data and known stability state labels.

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