Performance degradation data processing method for machine tool stepping acceleration test

Abstract

The invention discloses a performance degradation data processing method for a machine tool stepping acceleration test, and the method comprises the steps: 1, carrying out a stepping stress acceleration performance degradation test on a test machine tool, and collecting the acceleration performance degradation test data of each stepping stress; 2, converting the stepping stress degradation data into constant stress degradation data; 3, establishing various performance degradation models of the machine tool under the constant stress and estimating parameter values of the models; 4, establishing acceleration models of the machine tool, estimating parameter values of the acceleration models, and extrapolating performance degradation failure time of working stress of the machine tool; 5, machine tool failure mechanism consistency inspection under the acceleration stress and the working stress is carried out; 6, a machine tool multi-element performance dependent competition degradation model is established, and the machine tool multi-element performance retentivity is calculated. The method has the advantages of being high in efficiency and simple in data processing.

Description

Technical Field

[0001] The invention relates to the technical field of performance testing of numerically controlled machine tools, in particular to a performance degradation data processing method for a step acceleration test of a machine tool. Background Art

[0002] For a long time, the performance retention of domestic machine tools has always been far behind that of foreign advanced machine tools. The reason is that domestic machine tools started late, and the various performances of CNC machine tools such as precision and rigidity continued to degrade and affect each other during service, and the evolution law was complex and unclear. In addition, most of the existing methods are aimed at analyzing performance degradation, that is, analyzing and predicting the life span, ignoring the analysis of factors affecting the performance retention of machine tools, resulting in slow improvement of domestic performance retention.

[0003] At present, domestic machine tools are still mainly based on traditional on-site tracking test methods, and data is obtained through long-term tracking tests. However, due to the slow performance degradation of some equipment, traditional analysis methods need to process a large amount of degradation test data, which makes data processing cumbersome and leads to low efficiency of machine tool performance degradation analysis. Moreover, most of the existing methods are based on multi-sample data for analysis, which requires more samples and longer test time. Less performance degradation data is obtained within the limited test time. At the same time, most of the existing performance degradation tests are based on the ideal state of a single influencing factor, and often ignore the influence of the interaction of multiple stress factors on the performance of machine tools. It is impossible to accurately grasp and describe the characteristics of product degradation, resulting in the inability to accurately analyze the performance retention of machine tools under accelerated degradation of multi-performance. In addition, most of the existing methods focus on analyzing and predicting the life of the equipment based on degradation data, lacking analysis of the performance retention of machine tools under stress, resulting in slow improvement of machine tool performance retention. Therefore, there is an urgent need for a performance degradation data processing method for machine tool step acceleration test to explore the evolution law of various performance degradation of machine tools and the level of multi-performance retention of machine tools. Summary of the invention

[0004] The object of the present invention is to provide a performance degradation data processing method for a step acceleration test of a machine tool to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a performance degradation data processing method for a machine tool step acceleration test, comprising the following steps:

[0006] Step 1: Perform a step stress accelerated performance degradation test on the test machine tool and collect accelerated performance degradation test data of each step stress;

[0007] Step 2: Convert the step stress degradation data to constant stress degradation data;

[0008] Step 3: Establish the performance degradation model of the machine tool under constant stress and estimate its parameter values;

[0009] Step 4: Establish various acceleration models of machine tools and estimate their parameter values, and extrapolate the failure time of various performance degradation of machine tool working stress;

[0010] Step 5: Consistency test of machine tool failure mechanism under accelerated stress and working stress;

[0011] Step 6: Establish a model of interdependent competitive degradation of multiple performances of machine tools and calculate the degree of retention of multiple performances of machine tools.

[0012] According to the above technical solution, the method steps of performing a step stress accelerated performance degradation test on a machine tool and collecting accelerated performance degradation test data of each step stress include:

[0013] The step stress acceleration performance degradation test is carried out on the test machine tool, and different step acceleration stress levels s1, s2, s3, ...s are set. k , where s1 <s2<s3,...<s k , k represents the number of step acceleration stress levels;

[0014] The test data of machine tool performance degradation under each step stress acceleration are collected.

[0015] According to the above technical solution, the method steps for converting the step stress degradation data to the constant stress degradation data include:

[0016] Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time of the test in the step stress acceleration performance degradation data, and describe the degradation process d(t) of the machine tool step acceleration test as:

[0017]

[0018] Where s1, s2, …s k represents a total of k step acceleration stress levels (s1 <s2<…<s k ),τ1,τ2,…,τ k represents the test deadline when the step acceleration stress level increases, d(t) is the performance degradation of the machine tool at time t, and w k is the stress level s k The equivalent starting time of the lower degradation test;

[0019] A coordinate system is established, and the coordinates of the performance degradation at each time t are marked in the coordinate system. The coordinates of the performance degradation at each time t are connected to construct the degradation trajectory of each performance of the machine tool. According to the degradation trajectory of each performance of the machine tool, a degradation trajectory function of each performance of the machine tool is constructed:

[0020] yilj =g(t ilj ,θ)+ε lj

[0021] In the formula, y ilj represents the jth step acceleration stress level of the machine tool, the lth performance, and the degradation increment measurement value of the ith measurement time, g(t ilj ,θ) represents the theoretical value of degradation increment at the jth step acceleration stress level, the lth performance, and the ith measurement time, and g(t ilj ,θ) is the power function of time t at each step acceleration stress level, θ is the function g(t ilj ,θ), the unknown parameters, ε lj is the measurement error, and N(*) is a normal distribution, s lj represents the standard deviation of measurement error;

[0022] Identify the degradation trajectory function images of various machine tool performances, anchor the moment when the degradation amount is equal, and obtain the formula:

[0023] d(w k |s k )=d(w k-1 +τ k-1 -τ k-2 |s k-1 )

[0024] Among them, at stress level s k Next test w k The amount of degradation produced by the time is equal to the degradation test carried out to the stress level s k-1 The accumulated degradation at the cutoff time.

[0025] According to the above technical solution, the method step of converting the step stress degradation data to the constant stress degradation data also includes:

[0026] The accelerated performance degradation test data under different progressive acceleration stress levels are transformed to obtain constant acceleration stress levels s1, s2, s3, ...s j , and the corresponding performance degradation rate a, and then fit. Without loss of generality, the power law model is used to establish the machine tool performance degradation trajectory function:

[0027]

[0028] According to the degradation process d(t) of the machine tool step acceleration test, the degradation process of the machine tool step acceleration test is further obtained:

[0029]

[0030] According to the above accelerated test degradation process, anchoring the moment when the degradation amount is equal, the formula is obtained:

[0031]

[0032] Further calculations yield the formula:

[0033]

[0034] Among them, w1=0, τ0=0, further we get:

[0035]

[0036] Where, t 11 ,t 21 ,…,t i1 represents the 1st, 2nd, ..., i-th performance test time at stress level s1, and recursively represents w3, w4, w5, ..., w k ;

[0037] Furthermore, the step-accelerated stress level s k Degradation time to constant stress s j The formula for equivalent degradation time converted from degradation time is:

[0038]

[0039] In the formula, h ij is the converted constant acceleration stress s j The equivalent degradation test time of each performance at , and the complete performance degradation data of the machine tool under k constant acceleration stress levels after conversion are calculated in sequence.

[0040] According to the above technical solution, the method steps of establishing various performance degradation models of machine tools under constant stress and estimating their parameter values ​​include:

[0041] The performance degradation model is determined according to the degradation trajectory function of each performance of the machine tool, and the machine tool performance degradation model is established according to the determined performance degradation model:

[0042]

[0043] according to Transform the degradation model:

[0044]

[0045] Furthermore, a likelihood function of the machine tool performance degradation model is established:

[0046]

[0047] The likelihood function is derived and solved to obtain the parameter estimation value a of each performance degradation model of each accelerated stress. lj ,b lj .

[0048] According to the above technical solution, the method of establishing various acceleration models of machine tools and estimating their parameter values, and extrapolating the failure time of various performance degradation of machine tool working stresses includes:

[0049] According to the machine tool performance degradation model, a multi-stress acceleration model consisting of single stress, double stress coupling terms, triple stress coupling terms, ..., K stress coupling terms is established:

[0050]

[0051] In the formula, Represents permutations and combinations, a lj (α0,α1,…,α u ) is the obtained accelerated stress level s j , the parameters of the lth performance degradation model, x1,x2,…,x K represents K stress forms in the accelerated stress level;

[0052] When the performance of the machine tool degrades by the same amount at different stress levels, l When the degradation time ratio is defined as the acceleration factor between stress levels, at the accelerated stress level s p ,s q The calculation formula of the acceleration factor is:

[0053]

[0054] Ap,q=t d,p / t d,q

[0055] Furthermore, the calculation formula of the acceleration factor is obtained according to the above two formulas:

[0056]

[0057] Where, Ap,q represents the acceleration stress level s p ,s q The acceleration factor when .

[0058] According to the above technical solution, the method of establishing various acceleration models of machine tools and estimating their parameter values, and extrapolating the failure time of various performance degradation of machine tool working stress also includes:

[0059] Set the failure threshold of machine tool performance degradation to D l , the machine tool working stress level is recorded as s0, and the corresponding performance degradation model parameters are a l0,b l0 , the machine tool is at the accelerated stress level s j The performance degradation model at time s is extrapolated to the working stress s0, and the time when the performance degradation reaches the failure threshold is ζ lj , the calculation formula is:

[0060]

[0061] Set the machine tool to work at a stress level where the performance degradation reaches the failure threshold D l The time is ζ l0 , the calculation formula is:

[0062]

[0063] Furthermore, the time when the performance degradation of the tool machine under the working stress and J accelerated stress levels reaches the failure threshold is recursively calculated in sequence: ζ l0 ,ζ l1 ,ζ l2 …,ζ lJ .

[0064] Furthermore, a coordinate system is established to set all ζ lj The values ​​of are marked in the coordinate system, identifying ζ lj The distribution characteristics of lj The normal distribution characteristics of establish the maximum likelihood function:

[0065]

[0066] Solve the maximum likelihood function to obtain all unknown parameters of the machine tool acceleration model, and calculate the time ζ when the performance degradation reaches the failure threshold. lj The calculation formula is used to calculate the performance degradation failure time of the machine tool under various stress levels.

[0067] According to the above technical solution, the method steps for consistency inspection of machine tool failure mechanism under acceleration stress and working stress include:

[0068] Set the test threshold θ and establish the test function:

[0069]

[0070] Set the parameter values ​​b0, b1, b2, …, b k The test function is injected to obtain the output test value AD. When the test value AD is greater than θ, it is marked that the failure mechanism of the machine tool under the accelerated stress of the performance degradation model is consistent with the failure mechanism under the working stress.

[0071] According to the above technical solution, the method steps of establishing a machine tool multi-performance interdependent competitive degradation model and calculating the multi-performance retention degree of the machine tool include:

[0072] Establish a multivariate machine tool multi-performance dependent competitive degradation model:

[0073]

[0074] In the formula, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i ),μ2(t i ),…m l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, S(t i ) is the degradation level covariance matrix, and the element of the degradation level defense matrix in the nth row and the mth column is:

[0075]

[0076] In the formula, Cov(x n (t i )),x m (t i )) and Var(x n (t i )) are covariance function and variance function respectively;

[0077] According to the degradation level of any variable exceeding the actual degradation threshold D l When the machine tool fails, the maintenance function of the multivariate performance of the machine tool is established:

[0078]

[0079] The working stress level of the machine tool is set to s0, and the retention degree of the multivariate performance of the machine tool is calculated according to the working stress level s0 of the machine tool. The performance that affects the failure of the machine tool is traced back to obtain the performance to be improved.

[0080] According to the above technical solution, the system includes an experimental design module, a data conversion module, a model training module, a model detection module, an expiration time calculation module and a performance retention calculation module;

[0081] The test design module is used to perform a step stress accelerated performance degradation test on the test machine tool and collect accelerated performance degradation test data of each step stress;

[0082] The data conversion module is used to convert the step stress degradation data into constant stress degradation data;

[0083] The model training module is used to establish various performance degradation models of machine tools under constant stress and estimate their parameter values;

[0084] The failure time calculation module is used to establish various acceleration models of the machine tool and estimate their parameter values, and to extrapolate the failure time of various performance degradation of the machine tool working stress;

[0085] The model detection module is used for consistency inspection of machine tool failure mechanism under acceleration stress and working stress;

[0086] The performance retention degree calculation module is used to establish a machine tool multi-performance interdependent competition degradation model and calculate the multi-performance retention degree of the machine tool.

[0087] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0088] 1) The present invention proposes a feasible method for processing performance degradation data for step acceleration test of machine tools, which realizes the feasibility of performing step acceleration test on single sample products such as machine tools, which is impossible to process performance degradation data.

[0089] 2) The present invention can evaluate the degradation history and failure time of each performance of the machine tool, calculate the maintenance degree of the multi-performance dependence competition of the machine tool, that is, the performance maintenance degree of the machine tool, and determine the performance status of the machine tool.

[0090] 3) The present invention can realize accurate analysis of the retention degree of multiple performance dependencies of machine tools, and then determine the factors affecting the performance retention degree of machine tools, thereby providing data support for improving the performance retention degree of machine tools. That is, the present invention can limit various conditions such as different stress levels, single stress, uncoupled multiple stresses, and coupled multiple stresses, and then accurately determine the factors affecting the performance retention degree of machine tools, thereby realizing the upgrade of machine tools to improve the performance retention degree of machine tools. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0092] Figure 1 It is a flow chart of the method steps of the present invention.

[0093] Figure 2 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0094] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0095] See also Figure 1 The present invention provides a technical solution: a performance degradation data processing method for a machine tool step acceleration test, comprising the following steps:

[0096] Step 1: Perform a step stress accelerated performance degradation test on the test machine tool and collect accelerated performance degradation test data of each step stress;

[0097] Step 2: Convert the step stress degradation data to constant stress degradation data;

[0098] Step 3: Establish the performance degradation model of the machine tool under constant stress and estimate its parameter values;

[0099] Step 4: Establish various acceleration models of machine tools and estimate their parameter values, and extrapolate the failure time of various performance degradation of machine tool working stress;

[0100] Step 5: Consistency test of machine tool failure mechanism under accelerated stress and working stress;

[0101] Step 6: Establish a model of interdependent competitive degradation of multiple performances of machine tools and calculate the degree of retention of multiple performances of machine tools.

[0102] Step one further comprises the following steps:

[0103] Step S11: Perform k step stress level acceleration tests on a three-axis vertical machining center (machine tool), and each stress level contains four stress forms: vibration, temperature, speed, and static and dynamic forces. After the step stress acceleration degradation test of the machine tool, a total of l performance degradation data including positioning accuracy, repeatability, straightness in the Y direction of the X axis, straightness in the Z direction of the X axis, straightness in the X direction of the Y axis, straightness in the Z direction of the Y axis, straightness in the X direction of the Z axis, straightness in the Y direction of the Z axis, and static stiffness of each axis of the X / Y / Z axis are tested and obtained, among which different step acceleration stress levels s1, s2, s3, ...s k , and s1 <s2<s3,...<s k ;

[0104] Step S12: Collecting test data of the test machine tool under each step stress acceleration performance degradation test.

[0105] Step 2 further includes the following steps:

[0106] Step S21: Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time of the test in the step stress acceleration performance degradation data, and describe the machine tool step acceleration test degradation process d(t) as:

[0107]

[0108] Where s1, s2, …s k represents a total of k step acceleration stress levels (s1 <s2<…<s k ),τ1,τ2,…,τ k represents the test deadline when the step acceleration stress level increases, d(t) is the performance degradation of the machine tool at time t, and w k is the stress level s k The equivalent starting time of the lower degradation test;

[0109] Step S22: Establish a coordinate system, mark the performance degradation coordinates at each time t in the coordinate system, connect the performance degradation coordinates at each time t to construct the degradation trajectory of each performance of the machine tool, and construct the degradation trajectory function of each performance of the machine tool according to the degradation trajectory of each performance of the machine tool:

[0110] y ilj =g(t ilj ,θ)+ε lj

[0111] In the formula, y ilj represents the jth step acceleration stress level of the machine tool, the lth performance, and the degradation increment measurement value of the ith measurement time, g(t ilj ,θ) represents the theoretical value of degradation increment at the jth step acceleration stress level, the lth performance, and the ith measurement time, and g(t ilj ,θ) is the power function of time t at each step acceleration stress level, θ is the function g(t ilj ,θ), the unknown parameters, ε lj is the measurement error, and N(*) is a normal distribution, s lj represents the standard deviation of measurement error;

[0112] Step S23: Identify the degradation trajectory function images of various machine tool performances, anchor the moment when the degradation amount is equal, and obtain the formula:

[0113] d(w k |s k )=d(w k-1 +τ k-1 -τ k-2 |s k-1 )

[0114] Among them, at stress level s k Next test w k The amount of degradation produced by the time is equal to the degradation test carried out to the stress level s k-1 The accumulated degradation at the cutoff time.

[0115] Step 2 also includes the following steps:

[0116] Step S24: transform the acceleration performance degradation test data under different step acceleration stress levels to obtain constant acceleration stress levels s1, s2, ...s j , and the corresponding performance degradation rate a, and then fit. Without loss of generality, the power law model is used to establish the machine tool performance degradation trajectory function:

[0117]

[0118] Step S25: According to the machine tool step acceleration test degradation process d(t), the machine tool step acceleration test degradation process is further obtained:

[0119]

[0120] According to the above accelerated test degradation process, anchoring the moment when the degradation amount is equal, the formula is obtained:

[0121]

[0122] Further calculations yield the formula:

[0123]

[0124] Among them, w1=0, τ0=0, further we get:

[0125]

[0126] In the formula, t 11 ,t 21 ,…,t i1 represents the 1st, 2nd, ..., i-th performance test time at stress level s1, and recursively represents w3, w4, w5, ..., w k ;

[0127] Furthermore, the step-accelerated stress level s k Degradation time to constant stress s j The formula for equivalent degradation time converted from degradation time is:

[0128]

[0129] In the formula, h ij is the converted constant acceleration stress s jThe equivalent degradation test time of each performance at , and the complete performance degradation data of the machine tool under k constant acceleration stress levels after conversion are calculated in sequence.

[0130] Step three further includes the following steps:

[0131] The performance degradation model is determined according to the degradation trajectory function of each performance of the machine tool, and the machine tool performance degradation model is established according to the determined performance degradation model:

[0132]

[0133] according to Transform the degradation model:

[0134]

[0135] Furthermore, a likelihood function of the machine tool performance degradation model is established:

[0136]

[0137] The likelihood function is derived and solved to obtain the parameter estimation value a of each performance degradation model of each accelerated stress. lj ,b lj .

[0138] Step 4 further includes the following steps:

[0139] Step S41: A multi-stress acceleration model consisting of a single stress, a double stress coupling term, a triple stress coupling term, ..., a K stress coupling term is established according to the machine tool performance degradation model:

[0140]

[0141] In the formula, Represents permutations and combinations, a lj (α0,α1,…,α u ) is the obtained accelerated stress level s j , the parameters of the lth performance degradation model, x1,x2,…,x K represents K stress forms in the accelerated stress level;

[0142] Step S42: When the performance of the machine tool is degraded by the same amount d at different stress levels l When the degradation time ratio is defined as the acceleration factor between stress levels, at the accelerated stress level s p ,s q The calculation formula of the acceleration factor is:

[0143]

[0144] Furthermore, the calculation formula of the acceleration factor is obtained according to the above two formulas:

[0145]

[0146] Where, Ap,q represents the acceleration stress level s p ,s q The acceleration factor when

[0147] Step 4 also includes the following steps,

[0148] Set the failure threshold of machine tool performance degradation to D l , the machine tool working stress level is recorded as s0, and the corresponding performance degradation model parameters are a l0 ,b l0 , the machine tool is at the accelerated stress level s j The performance degradation model at time s is extrapolated to the working stress s0, and the time when the performance degradation reaches the failure threshold is ζ lj , the calculation formula is:

[0149]

[0150] Set the machine tool to work at a stress level where the performance degradation reaches the failure threshold D l The time is ζ l0 , the calculation formula is:

[0151]

[0152] Furthermore, the time when the performance degradation of the tool machine under the working stress and J accelerated stress levels reaches the failure threshold is recursively calculated in sequence: ζ l0 ,ζ l1 ,ζ l2 …,ζ lJ .

[0153] Furthermore, a coordinate system is established to set all ζ lj The values ​​of are marked in the coordinate system, identifying ζ lj The distribution characteristics of lj The normal distribution characteristics of establish the maximum likelihood function:

[0154]

[0155] Solve the maximum likelihood function to obtain all unknown parameters of the machine tool acceleration model, and calculate the time ζ when the performance degradation reaches the failure threshold. lj The calculation formula is used to calculate the performance degradation failure time of the machine tool under various stress levels.

[0156] Step five further includes the following steps:

[0157] Set the test threshold θ and establish the test function:

[0158]

[0159] Set the parameter values ​​b0, b1, b2, …, b k Inject into the test function and obtain the output test value AD. When the test value AD is greater than θ, it indicates that the parameter values ​​b0, b1, b2, ..., b k It obeys the normal distribution, and the failure mechanism of the marked machine tool under the accelerated stress of the performance degradation model is consistent with the failure mechanism under the working stress. b meets the invariance, that is, b can be expressed as the degradation rate constant.

[0160] Step six further includes the following steps:

[0161] Step S61: Establish a multivariate machine tool multi-performance dependent competitive degradation model:

[0162]

[0163] In the formula, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i ),μ2(t i ),…m l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, S(t i ) is the degradation level covariance matrix, and the element of the degradation level defense matrix in the nth row and the mth column is:

[0164]

[0165] In the formula, Cov(x n (t i )),x m (t i )) and Var(x n (t i )) are covariance function and variance function respectively;

[0166] According to the degradation level of any variable exceeding the actual degradation threshold D l When the machine tool fails, the maintenance function of the multivariate performance of the machine tool is established:

[0167]

[0168] Step S62: setting the machine tool working stress level to s0, calculating the retention degree of the machine tool's multivariate performance according to the machine tool working stress level s0, tracing back to obtain the performance that affects the machine tool failure, and determining it as the performance to be improved.

[0169] A performance degradation data processing method for a machine tool step acceleration test, which runs on a performance degradation data processing system for a machine tool step acceleration test, includes a test design module, a data conversion module, a model training module, a model detection module, a failure time calculation module and a performance retention calculation module;

[0170] The test design module is used to perform step stress accelerated performance degradation tests on the test machine tool and collect accelerated performance degradation test data of each step stress;

[0171] The data conversion module is used to convert the step stress degradation data into constant stress degradation data;

[0172] The model training module is used to establish various performance degradation models of machine tools under constant stress and estimate their parameter values;

[0173] The failure time calculation module is used to establish various acceleration models of machine tools and estimate their parameter values, and to extrapolate the failure time of various performance degradation of machine tool working stress;

[0174] The model detection module is used to check the consistency of machine tool failure mechanism under accelerated stress and working stress;

[0175] The performance retention calculation module is used to establish a multi-performance interdependent competition degradation model for machine tools and calculate the multi-performance retention of machine tools.

[0176] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0177] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A performance degradation data processing method for a machine tool step acceleration test, characterized in that: The method comprises the following steps: Conducting a step stress accelerated performance degradation test on the test machine tool, and collecting accelerated performance degradation test data of each step stress; Convert step stress degradation data to constant stress degradation data; Establish the performance degradation model of the machine tool under constant stress and estimate its parameter values; Establish various acceleration models of machine tools and estimate their parameter values, and extrapolate the failure time of various performance degradation of machine tool working stress; Consistency test of machine tool failure mechanism under accelerated stress and working stress; A model of interdependent competitive degradation of multiple performances of machine tools is established, and the retention degree of multiple performances of machine tools is calculated.

2. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 1, characterized in that: The method steps of performing a step stress accelerated performance degradation test on a machine tool and collecting accelerated performance degradation test data of each step stress include: The step stress acceleration performance degradation test is carried out on the test machine tool, and different step acceleration stress levels s1, s2, s3, ...s are set. k , where s1 <s2<s3,...<s k , k represents the number of step acceleration stress levels; The test data of performance degradation of the test machine tool at each step stress acceleration are collected.

3. The performance degradation data processing method for a machine tool step acceleration test according to claim 2, characterized in that: The method steps for converting step stress degradation data to constant stress degradation data include: Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time of the test in the step stress acceleration performance degradation data, and describe the degradation process d(t) of the machine tool step acceleration test as: Where s1, s2, …s k represents a total of k step acceleration stress levels (s1 <s2<…<s k ),τ1,τ2,…,τ k represents the test deadline when the step acceleration stress level increases, d(t) is the performance degradation of the machine tool at time t, and w k is the stress level s k The equivalent starting time of the lower degradation test; A coordinate system is established, and the coordinates of the performance degradation at each time t are marked in the coordinate system. The coordinates of the performance degradation at each time t are connected to construct the degradation trajectory of each performance of the machine tool. According to the degradation trajectory of each performance of the machine tool, a degradation trajectory function of each performance of the machine tool is constructed: y ilj =g(t ilj ,i)+e lj In the formula, y ilj represents the jth step acceleration stress level of the machine tool, the lth performance, and the degradation increment measurement value of the ith measurement time, g(t ilj ,θ) represents the theoretical value of degradation increment at the jth step acceleration stress level, the lth performance, and the ith measurement time, and g(t ilj ,θ) is the power function of time t at each step acceleration stress level, θ is the function g(t ilj ,θ) unknown parameters, ε lj is the measurement error, and N(*) is a normal distribution, s lj represents the standard deviation of measurement error; Identify the degradation trajectory function images of various machine tool performances, anchor the moment when the degradation amount is equal, and obtain the formula: d(w k |s k )=d(w k-1 +t k-1 -t k-2 |s k-1 ) Among them, at stress level s k Next test w k The amount of degradation produced by the time is equal to the degradation test carried out to the stress level s k-1 The accumulated degradation at the cutoff time.

4. The performance degradation data processing method for a machine tool step acceleration test according to claim 3 is characterized in that: The method step of converting the step stress degradation data to the constant stress degradation data also includes: The accelerated performance degradation test data under different progressive acceleration stress levels are transformed to obtain constant acceleration stress levels s1, s2, s3, ...s j , and the corresponding performance degradation rate a, and then fit. Without loss of generality, the power law model is used to establish the machine tool performance degradation trajectory function: According to the degradation process d(t) of the machine tool step acceleration test, the degradation process of the machine tool step acceleration test is further obtained: According to the above accelerated test degradation process, anchoring the moment when the degradation amount is equal, the formula is obtained: Further calculations yield the formula: Among them, w1=0, τ0=0, further we get: Where, t 11 ,t 21 ,…,t i1 Indicates the stress level s j The 1st, 2nd, ..., i-th performance test time is represented by w3, w4, w5, ..., w k ; Furthermore, the step-accelerated stress level s k Degradation time to constant stress S j The formula for equivalent degradation time converted from degradation time is: In the formula, h ij is the converted constant acceleration stress s j The equivalent degradation test time of each performance at , and the complete performance degradation data of the machine tool under k constant acceleration stress levels after conversion are calculated in sequence.

5. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 4, characterized in that: The method steps of establishing various performance degradation models of machine tools under constant stress and estimating their parameter values ​​include: The performance degradation model is determined according to the degradation trajectory function of each performance of the machine tool, and the machine tool performance degradation model is established according to the determined performance degradation model: according to Transform the degradation model: Furthermore, a likelihood function of the machine tool performance degradation model is established: The likelihood function is derived and solved to obtain the parameter estimation value a of each performance degradation model of each accelerated stress. lj ,b lj .

6. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 5, characterized in that: The method of establishing various acceleration models of machine tools and estimating their parameter values, and extrapolating the failure time of various performance degradation of machine tool working stresses includes: According to the machine tool performance degradation model, a multi-stress acceleration model consisting of single stress, double stress coupling terms, triple stress coupling terms, ..., K stress coupling terms is established: In the formula, Represents permutations and combinations, a lj (α0,α1,…,α u ) is the obtained accelerated stress level s j , the parameters of the lth performance degradation model, x1,x2,…,x K represents K stress forms in the accelerated stress level; When the performance of the machine tool degrades by the same amount at different stress levels, l When the degradation time ratio is defined as the acceleration factor between stress levels, at the accelerated stress level s p ,s q The calculation formula of the acceleration factor is: Ap,q=t d,p / t d,q Furthermore, the calculation formula of the acceleration factor is obtained according to the above two formulas: Where, Ap,q represents the acceleration stress level s p ,s q The acceleration factor when .

7. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 6, characterized in that: The method of establishing various acceleration models of machine tools and estimating their parameter values, and extrapolating the failure time of various performance degradation of machine tool working stress also includes: Set the failure threshold of machine tool performance degradation to D l , the machine tool working stress level is recorded as s0, and the corresponding performance degradation model parameters are a l0 ,b l0 , the machine tool is at the accelerated stress level s j The performance degradation model at time s is extrapolated to the working stress s0, and the time when the performance degradation reaches the failure threshold is ζ lj , the calculation formula is: Set the machine tool to work at a stress level where the performance degradation reaches the failure threshold D l The time is ζ l0 , the calculation formula is: Furthermore, the time when the performance degradation of the tool machine under the working stress and J accelerated stress levels reaches the failure threshold is recursively calculated in sequence: ζ l0 ,ζ l1 ,ζ l2 …,ζ lJ . Furthermore, a coordinate system is established to set all ζ lj The values ​​of are marked in the coordinate system, identifying ζ lj The distribution characteristics of lj The normal distribution characteristics of establish the maximum likelihood function: Solve the maximum likelihood function to obtain all unknown parameters of the machine tool acceleration model, and calculate the time ζ when the performance degradation reaches the failure threshold. lj The calculation formula is used to calculate the performance degradation failure time of the machine tool under various stress levels.

8. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 7, characterized in that: The method steps for consistency inspection of machine tool failure mechanism under accelerated stress and working stress include: Set the test threshold θ and establish the test function: Set the parameter values ​​b0, b1, b2, …, b k The test function is injected to obtain the output test value AD. When the test value AD is greater than θ, it is marked that the failure mechanism of the machine tool under the accelerated stress of the performance degradation model is consistent with the failure mechanism under the working stress.

9. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 8, characterized in that: The method steps of establishing a machine tool multi-performance interdependent competition degradation model and calculating the multi-performance retention degree of the machine tool include: Establish a multivariate machine tool multi-performance dependent competitive degradation model: In the formula, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i ),μ2(t i ),…m l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, S(t i ) is the degradation level covariance matrix, and the element of the degradation level defense matrix in the nth row and the mth column is: In the formula, Cov(x n (t i )),x m (t i )) and Var(x n (t i )) are covariance function and variance function respectively; According to the degradation level of any variable exceeding the actual degradation threshold D l When the machine tool fails, the maintenance function of the multivariate performance of the machine tool is established: The working stress level of the machine tool is set to s0, and the retention degree of the multivariate performance of the machine tool is calculated according to the working stress level s0 of the machine tool. The performance that affects the failure of the machine tool is traced back to obtain the performance to be improved.

10. The method for processing performance degradation data for a stepping acceleration test of a machine tool according to claim 9, which is run on a performance degradation data processing system for a stepping acceleration test of a machine tool, is characterized in that: The system includes an experimental design module, a data conversion module, a model training module, a model detection module, an expiration time calculation module and a performance retention calculation module; The test design module is used to perform a step stress accelerated performance degradation test on the test machine tool and collect accelerated performance degradation test data of each step stress; The data conversion module is used to convert the step stress degradation data into constant stress degradation data; The model training module is used to establish various performance degradation models of machine tools under constant stress and estimate their parameter values; The failure time calculation module is used to establish various acceleration models of the machine tool and estimate their parameter values, and to extrapolate the failure time of various performance degradation of the machine tool working stress; The model detection module is used for consistency inspection of machine tool failure mechanism under acceleration stress and working stress; The performance retention degree calculation module is used to establish a machine tool multi-performance interdependent competition degradation model and calculate the multi-performance retention degree of the machine tool.

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