A performance degradation data processing method for machine tool step acceleration test

Abstract

The present invention discloses a performance degradation data processing method for a step acceleration test of a machine tool, comprising the following steps: one, performing a step stress acceleration performance degradation test on a test machine tool, and collecting acceleration performance degradation test data of each step stress; two, converting the step stress degradation data into constant stress degradation data; three, establishing various performance degradation models of the machine tool under constant stress and estimating their parameter values; four, establishing various acceleration models of the machine tool and estimating their parameter values, and extrapolating the failure time of various performance degradations of the machine tool under working stress; five, performing consistency test on the failure mechanism of the machine tool under accelerated stress and working stress; and six, establishing a multi-performance dependent competitive degradation model of the machine tool and calculating the multi-performance retention of the machine tool. The present invention has the characteristics of high efficiency and simple data processing.

Description

Technical Field

[0001] The present 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 domestically produced machine tools has lagged significantly behind that of advanced foreign machine tools. This is due to the late start of domestic machine tool development. The various performance characteristics of CNC machine tools, such as precision and rigidity, continue to degrade over the course of service, interfering with each other and evolving in complex and unclear patterns. Furthermore, existing methods mostly focus on analyzing performance degradation—that is, predicting lifespan—while neglecting to analyze the factors influencing performance retention. This has led to slow improvements in domestic performance retention.

[0003] At present, domestic machine tools are still mainly based on traditional on-site tracking test methods, which obtain data through long-term tracking tests. However, due to the slow performance degradation of some equipment, traditional analysis methods require processing 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 existing methods are based on multi-sample data for analysis, which requires more samples and longer test time. In the limited test time, less performance degradation data is obtained. At the same time, most existing performance degradation tests are based on the ideal state of a single influencing factor, often ignoring the impact of the interaction of multiple stress factors on machine tool performance. They cannot accurately grasp and describe the characteristics of product degradation, resulting in an inability to accurately analyze the performance retention of machine tools under multi-dimensional performance accelerated degradation. In addition, most 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-dimensional performance retention of machine tools. Summary of the Invention

[0004] The object of the present invention is to provide a method for processing performance degradation data for a step acceleration test of a machine tool, so as 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 solution: a method for processing performance degradation data for a step acceleration test of a machine tool, comprising the following steps:

[0006] Step 1: Perform a step stress accelerated performance degradation test on the test machine tool and collect the accelerated performance degradation test data of each step stress. The specific steps include:

[0007] 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;

[0008] Collect the test data of the test machine tool at each step stress acceleration performance degradation test;

[0009] Step 2: Convert the step stress degradation data to constant stress degradation data. The specific steps include:

[0010] Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time in the step stress acceleration performance degradation data, and describe the degradation process d(t) of the machine tool step acceleration test as:

[0011]

[0012] Where s1, s2, ...s k represents a total of k step acceleration stress levels, 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 Equivalent starting time of the lower degradation test;

[0013] 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 based on the degradation trajectory of each performance of the machine tool:

[0014] y ilj =g(t ilj ,θ)+ε lj

[0015] Where y ilj It represents the degradation increment measurement value of the jth step acceleration stress level of the machine tool, the lth performance, and the i-th 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;

[0016] Identify the degradation trajectory function graph of each machine tool performance, anchor the moment when the degradation amount is equal, and obtain the formula:

[0017] d(w k |s k )=d(w k-1 +τ k-1 -τ k-2 |s k-1 )

[0018] Among them, at stress level s k Next test w k The degradation amount produced by the time is equal to the degradation test carried out to the stress level s k-1 The amount of degradation accumulated at the cutoff time;

[0019] Step 3: Establish the performance degradation model of the machine tool under constant stress and estimate its parameter values;

[0020] Step 4: Establish various acceleration models of the machine tool and estimate their parameter values, and extrapolate the failure time of various performance degradation of the machine tool working stress;

[0021] Step 5: Consistency test of machine tool failure mechanism under accelerated stress and working stress;

[0022] According to the above technical solution, the method step of converting the step stress degradation data to the constant stress degradation data further includes:

[0023] 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:

[0024]

[0025] 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:

[0026]

[0027] According to the above accelerated test degradation process, anchoring the moment when the degradation amount is equal, the formula is obtained:

[0028]

[0029] Further calculations yield the formula:

[0030]

[0031] Where w1=0, τ0=0, we can further obtain:

[0032]

[0033] Where, t 11 ,t 21 ,L,t i1 represents the 1st, 2nd, L, i-th performance test time at stress level s1, and recursively represents w3, w4, w5, ..., w k .

[0034] 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:

[0035] The performance degradation model is determined according to the degradation trajectory function of each performance of the machine tool. The machine tool performance degradation model is established according to the determined performance degradation model as follows:

[0036]

[0037] according to Transform the degradation model:

[0038]

[0039] Furthermore, a likelihood function of the machine tool performance degradation model is established:

[0040]

[0041] The likelihood function is derived and solved to obtain the parameter estimates a of each performance degradation model for each accelerated stress. lj ,b lj .

[0042] According to the above technical solution, the method of establishing various acceleration models of machine tools and estimating their parameter values, and extrapolating the degradation failure time of various performance of machine tool working stress includes:

[0043] 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:

[0044]

[0045] Where, Indicates permutation and combination, a lj (α0,α1,L,α u ) is the obtained accelerated stress level s j , parameters of the lth performance degradation model, x1,x2,L,x Krepresents K stress forms in the accelerated stress level;

[0046] When the performance of the machine tool degrades by the same amount under 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:

[0047]

[0048] Ap,q=t d,p / t d,q

[0049] Furthermore, the calculation formula of the acceleration factor is obtained according to the above two formulas:

[0050]

[0051] Where, Ap,q represents the acceleration stress level s p ,s q The acceleration factor when .

[0052] According to the above technical solution, the method of establishing various acceleration models of the machine tool and estimating their parameter values, and extrapolating the failure time of various performance degradation of the machine tool working stress also includes:

[0053] 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 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:

[0054]

[0055] 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:

[0056]

[0057] Furthermore, the time when the performance degradation of the tool reaches the failure threshold under the working stress and J accelerated stress levels is recursively calculated: l0 ,ζ l1 ,ζ l2 …,ζ lJ ;

[0058] 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:

[0059]

[0060] 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 at each stress level.

[0061] According to the above technical solution, the method steps for consistency testing of machine tool failure mechanisms under accelerated stress and working stress include:

[0062] Set the test threshold θ and establish the test function:

[0063]

[0064] Set the parameter values b0, b1, b2, L, b k The test function is injected to obtain an 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.

[0065] According to the above technical solution, the method steps of establishing a machine tool multi-performance dependent competitive degradation model and calculating the multi-performance retention of the machine tool include:

[0066] Establish a multivariate machine tool multi-performance dependent competitive degradation model:

[0067]

[0068] Where, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i ),μ2(t i ),μ l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, Σ(t i ) is the degenerate level covariance matrix, and the element of the degenerate level defense matrix in the nth row and mth column is:

[0069]

[0070] Where Cov(x n (t i ),x m (t i )) and Var(x n (t i )) are covariance function and variance function respectively;

[0071] 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:

[0072]

[0073] The working stress level of the machine tool is set as s0, and the retention degree of the multivariate performance of the machine tool is calculated based on the working stress level s0 of the machine tool. The performance that affects the failure of the machine tool is traced back and determined as the performance to be improved.

[0074] 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;

[0075] 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;

[0076] The data conversion module is used to convert the step stress degradation data into constant stress degradation data;

[0077] The model training module is used to establish various performance degradation models of the machine tool under constant stress and estimate their parameter values;

[0078] 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;

[0079] The model detection module is used to check the consistency of machine tool failure mechanism under accelerated stress and working stress;

[0080] The performance retention calculation module is used to establish a multi-performance interdependent competition degradation model of a machine tool and calculate the multi-performance retention of the machine tool.

[0081] Compared with the prior art, the present invention has the following beneficial effects:

[0082] 1) The present invention proposes a feasible method for processing performance degradation data of step acceleration test for 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.

[0083] 2) The present invention can evaluate the degradation history and failure time of various performances 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.

[0084] 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, and provide data support for improving the performance retention degree of machine tools. That is, the present invention can limit multiple 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, and then realize the upgrade of machine tools to improve the performance retention degree of machine tools. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] 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:

[0086] Figure 1 It is a flow chart of the method steps of the present invention.

[0087] Figure 2 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0088] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0089] See also Figure 1 The present invention provides a technical solution: a method for processing performance degradation data for a step acceleration test of a machine tool, comprising the following steps:

[0090] Step 1: Perform a step stress accelerated performance degradation test on the test machine tool and collect the accelerated performance degradation test data of each step stress. The specific steps include:

[0091] 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;

[0092] Collect the test data of the test machine tool at each step stress acceleration performance degradation test;

[0093] Step 2: Convert the step stress degradation data to constant stress degradation data. The specific steps include:

[0094] Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time in the step stress acceleration performance degradation data, and describe the degradation process d(t) of the machine tool step acceleration test as:

[0095]

[0096] Where s1, s2, …s k represents a total of k step acceleration stress levels, 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 Equivalent starting time of the lower degradation test;

[0097] 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 based on the degradation trajectory of each performance of the machine tool:

[0098] y ilj =g(t ilj ,θ)+ε lj

[0099] Where y ilj It represents the degradation increment measurement value of the jth step acceleration stress level of the machine tool, the lth performance, and the i-th 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;

[0100] Identify the degradation trajectory function graph of each machine tool performance, anchor the moment when the degradation amount is equal, and obtain the formula:

[0101] d(w k |s k )=d(w k-1 +τ k-1 -τ k-2 |s k-1 )

[0102] Among them, at stress level s k Next test w k The degradation amount produced by the time is equal to the degradation test carried out to the stress level s k-1 The amount of degradation accumulated at the cutoff time;

[0103] Step 3: Establish the performance degradation model of the machine tool under constant stress and estimate its parameter values;

[0104] Step 4: Establish various acceleration models of the machine tool and estimate their parameter values, and extrapolate the failure time of various performance degradation of the machine tool working stress;

[0105] Step 5: Consistency test of machine tool failure mechanism under accelerated stress and working stress;

[0106] 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.

[0107] Step one further comprises the following steps:

[0108] Step S11: Perform an accelerated test of k step stress levels on a three-axis vertical machining center (machine tool). Each stress level contains four stress forms: vibration, temperature, speed, and static and dynamic forces. After the machine tool step stress accelerated degradation test, a total of l performance degradation data are tested, including positioning accuracy, repeatability, X-axis Y-direction straightness, X-axis Z-direction straightness, Y-axis X-direction straightness, Y-axis Z-direction straightness, Z-axis X-direction straightness, Z-axis Y-direction straightness, and static stiffness of each X / Y / Z axis. Different step accelerated stress levels s1, s2, s3, ...s are set. k , and s1 <s2<s3,...<s k ;

[0109] Step S12: Collecting test data of the test machine tool at each step stress acceleration performance degradation test.

[0110] Step 2 further includes the following steps:

[0111] Step 2 also includes the following steps:

[0112] Step S21: transform the acceleration performance degradation test data under different step acceleration stress levels to obtain constant acceleration stress levels s1, s2, Ls 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:

[0113]

[0114] Step S22: According to the machine tool step acceleration test degradation process d(t), the machine tool step acceleration test degradation process is further obtained:

[0115]

[0116] According to the above accelerated test degradation process, anchoring the moment when the degradation amount is equal, the formula is obtained:

[0117]

[0118] Further calculations yield the formula:

[0119]

[0120] Among them, w1=0, τ0=0, further we get:

[0121]

[0122] Where, t 11 ,t 21 ,L,t i1 represents the 1st, 2nd, L, i-th performance test time at stress level s1, and recursively represents w3, w4, w5, ..., w k ;

[0123] Step three further includes the following steps:

[0124] The performance degradation model is determined according to the degradation trajectory function of each performance of the machine tool. The machine tool performance degradation model is established according to the determined performance degradation model as follows:

[0125]

[0126] according to Transform the degradation model:

[0127]

[0128] Furthermore, a likelihood function of the machine tool performance degradation model is established:

[0129]

[0130] The likelihood function is derived and solved to obtain the parameter estimates a of each performance degradation model for each accelerated stress. lj ,b lj .

[0131] Step 4 further includes the following steps:

[0132] Step S41: A multi-stress acceleration model consisting of a single stress, a double stress coupling term, a triple stress coupling term, ..., and a K stress coupling term is established according to the machine tool performance degradation model:

[0133]

[0134] Where, Indicates permutation and combination, a lj (α0,α1,L,α u ) is the obtained accelerated stress level s j , parameters of the lth performance degradation model, x1,x2,L,x K represents K stress forms in the accelerated stress level;

[0135] Step S42: When the performance of the machine tool degrades by the same amount d under 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:

[0136]

[0137] Ap,q=t d,p / t d,q

[0138] Furthermore, the calculation formula of the acceleration factor is obtained according to the above two formulas:

[0139]

[0140] Where, Ap,q represents the acceleration stress level s p ,s q The acceleration factor when

[0141] Step 4 also includes the following steps:

[0142] 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 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:

[0143]

[0144] Set the machine tool to work at a stress level where the performance degradation reaches the failure threshold D l The time is ζl0 , the calculation formula is:

[0145]

[0146] Furthermore, the time when the performance degradation of the tool reaches the failure threshold under the working stress and J accelerated stress levels is recursively calculated: l0 ,ζ l1 ,ζ l2 …,ζ lJ ;

[0147] 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:

[0148]

[0149] 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 at each stress level.

[0150] Step five further includes the following steps:

[0151] Set the test threshold θ and establish the test function:

[0152]

[0153] Set the parameter values b0, b1, b2, L, b k Inject 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, L, b k Obeying the normal distribution, 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, and b remains invariant, that is, b can be expressed as the degradation rate constant.

[0154] Step six further includes the following steps:

[0155] Step S61: Establish a multivariate machine tool multi-performance dependent competitive degradation model:

[0156]

[0157] Where, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i),μ2(t i ),μ l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, Σ(t i ) is the degradation level covariance matrix, and the element of the degradation level defense matrix in the nth row and mth column is:

[0158]

[0159] Where Cov(x n (t i ),x m (t i )) and Var(x n (t i )) are covariance function and variance function respectively;

[0160] 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:

[0161]

[0162] Step S62: Set the machine tool working stress level as s0, calculate the retention degree of the machine tool's multi-performance according to the machine tool working stress level s0, trace back to obtain the performance that affects the failure of the machine tool, and determine it as the performance to be improved.

[0163] A performance degradation data processing method for a step-by-step acceleration test of a machine tool is provided, which runs on a performance degradation data processing system for a step-by-step acceleration test of a machine tool, and 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;

[0164] 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;

[0165] The data conversion module is used to convert the step stress degradation data into constant stress degradation data;

[0166] The model training module is used to establish various performance degradation models of machine tools under constant stress and estimate their parameter values;

[0167] 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;

[0168] The model checking module is used to check the consistency of machine tool failure mechanism under accelerated stress and working stress;

[0169] The performance retention calculation module is used to establish a multi-performance interdependent competition degradation model of machine tools and calculate the multi-performance retention of machine tools.

[0170] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0171] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are 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 will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for processing performance degradation data for a machine tool step acceleration test, characterized by: The method comprises the following steps: Perform a step stress accelerated performance degradation test on the test machine tool and collect the accelerated performance degradation test data of each step stress. The specific steps 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; Collect the test data of the test machine tool at each step stress acceleration performance degradation test; Convert step stress degradation data to constant stress degradation data. The specific steps include: Identify the degradation amount, step acceleration stress level, test cutoff time and equivalent start time 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, 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 Equivalent starting time of the lower degradation test; 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 based on the degradation trajectory of each performance of the machine tool: y ilj =g(t ilj ,i)+e lj Where y ilj It represents the degradation increment measurement value of the jth step acceleration stress level of the machine tool, the lth performance, and the i-th 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 ε lj : N(*) is a normal distribution, s lj represents the standard deviation of measurement error; Identify the degradation trajectory function graph of each machine tool performance, 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 degradation amount produced by the time is equal to the degradation test carried out to the stress level s k-1 The amount of degradation accumulated at the cutoff time; Establish various performance degradation models of machine tools under constant stress and estimate their 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 to calculate the retention of multiple performances of machine tools.

2. The method for processing performance degradation data for a machine tool step acceleration test according to claim 1, characterized in that: The method step of converting the step stress degradation data to constant stress degradation data further 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: Where w1=0, τ0=0, we can further obtain: Where, t 11 ,t 21 ,L,t i1 Indicates the stress level s j The 1st, 2nd, L,ith performance test time is recursively represented by w3, w4, w5, ..., w k .

3. The method for processing performance degradation data for a machine tool step acceleration test according to claim 2, 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. The machine tool performance degradation model is established according to the determined performance degradation model as follows: According to ε lj : 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 estimates a of each performance degradation model for each accelerated stress. lj ,b lj .

4. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 3, 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: Where, Indicates permutation and combination, a lj (α0,α1,L,α u ) is the obtained accelerated stress level s j , parameters of the lth performance degradation model, x1,x2,L,x K represents K stress forms in the accelerated stress level; When the performance of the machine tool degrades by the same amount under 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 .

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 of establishing various acceleration models of the machine tool and estimating their parameter values, and extrapolating the failure time of various performance degradation of the 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 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 reaches the failure threshold under the working stress and J accelerated stress levels is recursively calculated: 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 at each stress level.

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 steps for testing the consistency of the machine tool failure mechanism under the accelerated stress and the working stress include: Set the test threshold θ and establish the test function: Set the parameter values b0, b1, b2, L, b k The test function is injected to obtain an 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.

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 steps for establishing a machine tool multi-performance interdependent competition degradation model and calculating the multi-performance retention of the machine tool include: Establish a multivariate machine tool multi-performance dependent competitive degradation model: Where, f(X(t i )) is X(t i ), μ(t i )=(μ1(t i ),μ2(t i ),μ l (t i )), μ l (t i ) is the lth variable at t i The degradation level mean function at the moment, Σ(t i ) is the degenerate horizontal covariance matrix, and the element of the degenerate horizontal covariance matrix in the nth row and mth column is: Where 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 as s0, and the retention degree of the multivariate performance of the machine tool is calculated based on the working stress level s0 of the machine tool. The performance that affects the failure of the machine tool is traced back and determined as the performance to be improved.

8. The method for processing performance degradation data for a step acceleration test of a machine tool according to claim 7, which is run on a performance degradation data processing system for a step 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 the machine tool 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 to check the consistency of machine tool failure mechanism under accelerated stress and working stress; The performance retention calculation module is used to establish a multi-performance interdependent competition degradation model of a machine tool and calculate the multi-performance retention of the machine tool.

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