CN110853182B - User road minimum collection mileage calculation method during association of user and test field - Google Patents
User road minimum collection mileage calculation method during association of user and test field Download PDFInfo
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- CN110853182B CN110853182B CN201911107640.1A CN201911107640A CN110853182B CN 110853182 B CN110853182 B CN 110853182B CN 201911107640 A CN201911107640 A CN 201911107640A CN 110853182 B CN110853182 B CN 110853182B
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/12—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time in graphical form
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
Abstract
The invention relates to the technical field of vehicle durability tests, in particular to a method for calculating the minimum collected mileage of a user road when a user is associated with a test field, and load spectrum collection of the durability of the user road is obtained; determining an analysis object, and acquiring a pseudo damage density; carrying out normality test on a load spectrum subjected to an analysis object by using a nonparametric test method; based on the theory of probability statistics, sampling is carried out from the pseudo-damage density under the target mileage generally obeying normal distribution, and sampling distribution containing a mean value and a variance is obtained; defining the relative deviation of the mean value of the sampled samples from the overall mean value; specifying a confidence level of the collected sample; obtaining a minimum sample amount calculation formula; and finally determining the minimum collected mileage. The method avoids overlarge data collection amount, and improves the accuracy and the representativeness of the vehicle damage information obtained by the durability test.
Description
Technical Field
The invention relates to the technical field of vehicle durability tests, in particular to a method for calculating the minimum collected mileage of a user road when the user is associated with a test field.
Background
When a durability test of a vehicle is performed, the durability problem of the vehicle during a target mileage period is repeated in a short time by a strengthening test of a vehicle test field. But different users use the operating mode and driving behavior, and the strengthening mode on the road surface of the test field is different. In order to realize that the durability of the vehicle is mutually consistent under the conditions of a test field strengthening test and a user working condition, the correlation between the test field and the user working condition is necessary, and the basic principle is as follows: the damage to the user's vehicle during the target range is consistent with the damage from the automotive test yard durability test.
The user working condition association is carried out, the load spectrum of a bearing structure or a part of a user vehicle needs to be collected, the longer the collection mileage of the vehicle under the user working condition is, the more the user working condition refers to a user road in actual driving, the more comprehensive the use condition of a user can be described, but the longer the collection time is, the more resources are consumed. It is necessary to combine probability and statistical theory to calculate the minimum collection mileage of the user working condition load spectrum, and the collected load spectrum can still represent the use condition of the user.
In the prior art, a method for determining the endurance load spectrum acquisition mileage of an automobile user under typical working conditions mainly comprises the following steps: (1) formulating the collected mileage according to experience; (2) and analyzing the probability density distribution condition of the amplitude according to the load spectrum data acquired in a certain period, and determining the acquired mileage after the probability density distribution of the amplitude is stable. Among the above methods, the subjectivity of the method (1) is too strong and there is no theoretical support; the method (2) will consume a lot of resources on the endurance loading spectrum acquisition. Therefore, the method calculates the minimum acquisition mileage of the load spectrum under the typical working condition of the user by a probability statistics method based on the pseudo-damage density distribution characteristic of the load spectrum, and provides theoretical support for the determination of the acquisition mileage of the load spectrum under the working condition of the user.
Disclosure of Invention
The invention aims to provide a method for calculating the minimum collected mileage of a user road when the user is associated with a test field, so that the minimum collected mileage of a load spectrum under typical working conditions of the user is calculated, and theoretical support is provided for determining the collected mileage of the load spectrum under the working conditions of the user.
The method for calculating the least collected mileage of the user road when the user is associated with the test field in the scheme comprises the following steps:
s100, acquiring a durability load spectrum of a user road, and acquiring pseudo damage densities of four shaft head vertical acceleration signals by taking the shaft head vertical acceleration signals as analysis objects;
s200, when the accumulated driving mileage of the vehicle reaches a target mileage, the target mileage is the mileage when the vehicle component has a fault, and whether the logarithmic pseudo-damage of the vehicle structure or the component load spectrum obeys normal distribution or not is verified, namely: ln (D) -N (mu, sigma)2)；
S300, recording d as the false damage density, and d is per literThe cumulative pseudo-damage of the loading spectrum, which can be expressed as D ═ D/l, so that the logarithmic pseudo-damage density also follows a normal distribution, i.e.: ln (d) ═ ln (d) — ln (l) — N (l), σ ═ l2)；
S400, sampling from a sample of the pseudo-damage density population which follows normal distribution, wherein
S are the mean value and the sample standard deviation of the sample respectively, and the mean value and the sample standard deviation obey t distribution according to the quantity of the extracted samples;
s500, defining the relative deviation of the mean value of the sampling samples and the overall mean value as
And taking the relative deviation as a preset parameter for measuring the approximation degree of the sample mean value and the overall mean value, wherein the preset parameter is within the range.
S600, obtaining the coefficient of variation
To reflect the relative relationship between the sample standard deviation and the sample mean;
s700, driving the test vehicle to a user road for load spectrum acquisition, designating the confidence coefficient 1-alpha of the acquired sample, and determining the relative deviation between the sample mean value and the overall mean value to be within the range
Calculating a minimum sample size n;
and S800, after the minimum acquisition sample amount n is determined, calculating the minimum acquisition mileage nxl based on the acceleration signal of each shaft head.
The beneficial effect of this scheme is: the acceleration signals of the plurality of shaft heads in the vertical direction are collected, the minimum sample volume is obtained, the minimum collection mileage of the durability test is calculated, the condition that the collected data volume is overlarge is avoided, and meanwhile, the accuracy and the representativeness of the vehicle damage information obtained by the durability test are improved.
Further, the step S400, when the sample size is 5<n<At 30 hours, there are
Obeying t distribution with the degree of freedom of n-1; and the sample size n>At 30 hours, there are
Obeying a t distribution with n-1 degrees of freedom, i.e.
The beneficial effects are that: and (3) verifying t distribution aiming at different sample sizes, and improving the calculation accuracy of the data mean value and the sample standard deviation.
Further, in step S500, the preset parameters are expressed as:
The beneficial effects are that: the range is determined more accurately, data redundancy caused by overlarge range is prevented, and data missing caused by overlong range is prevented.
Further, there is a right side for the comparison inequality in step S500
tα/2Can be obtained by looking up the distribution table of t, i.e.
The beneficial effects are that: and solving the contrast inequality through t distribution, so that the accuracy of a solving result is improved.
Further, in the step S100, a durability load spectrum is collected by a three-way acceleration sensor, a displacement sensor and a strain sensor.
The beneficial effects are that: the durability load spectrums are acquired through different sensors, mutual interference is avoided, and reliability of the acquired durability load spectrums is guaranteed.
Further, in the step S100, the method further includes acquiring a component durability load spectrum through a six-component sensor at the wheel end to perform minimum acquired mileage calculation.
The beneficial effects are that: durability load spectra are measured from multiple directions, and the integrity of the durability load spectra of the components of the vehicle is improved.
Further, in step S100, the user roads include expressways, national roads, mountain roads, urban roads, and rural villages.
The beneficial effects are that: and acquiring the durability load spectrum aiming at the user roads with different road conditions so as to accurately obtain the representative load spectrum under the target mileage of the user.
Further, in the step S200, when the accumulated driving mileage of the vehicle reaches the target mileage, the logarithmic pseudo damage of the vehicle structure or component load spectrum follows the weibull distribution.
The beneficial effects are that: the logarithmic pseudo-damage of the load spectrum follows Weibull distribution, and the reliability of the load spectrum is improved.
Further, in step S300, the load spectrum sample is l kilometers, and the normality of the sample is checked by a non-parametric test method.
The beneficial effects are that: the method is used for detection in a nonparametric detection cost method, has few assumed conditions and simple operation, can quickly finish calculation to obtain a result, and saves calculation time.
Further, in step S100, acquiring the false damage density of the spindle nose force signal and the displacement signal.
The beneficial effects are that: and the completeness of the durability load spectrum test on each part of the vehicle is improved.
Drawings
FIG. 1 is a flow chart of a first embodiment of a calculation method for a least-collected mileage on a user road when the user is associated with a test field according to the present invention;
FIG. 2 is a load spectrum pseudo-damage density normal probability chart with a sample length of 2km in a first embodiment of the calculation method for the least collected mileage of the user road when the user is associated with the test field according to the present invention;
FIG. 3 is a load spectrum pseudo-damage density normal probability chart with a sample length of 5km in the first embodiment of the calculation method for the least collected mileage of the user road when the user is associated with the test field;
FIG. 4 is a load spectrum pseudo-damage density normal probability chart with a sample length of 8km in a first embodiment of the calculation method for the least collected mileage of the user road when the user is associated with the test field according to the present invention;
fig. 5 is a load spectrum pseudo-damage density normal probability chart with a sample length of 10km in the first embodiment of the calculation method for the least collected mileage of the user road when the user is associated with the test field.
Detailed Description
The following is a more detailed description of the present invention by way of specific embodiments.
This embodiment A
The method for calculating the minimum collected mileage of the user road when the user is associated with the test field, as shown in fig. 1, comprises the following steps:
s100, acquiring a durability load spectrum of a user road, taking the vertical acceleration signals of the shaft heads as an analysis object, acquiring pseudo damage densities of the vertical acceleration signals of the four shaft heads, and acquiring pseudo damage densities of the force signals and the displacement signals of the shaft heads;
s200, when the accumulated driving mileage of the vehicle reaches a target mileage, the target mileage is the mileage when the vehicle component has a fault, and whether the logarithmic pseudo-damage of the vehicle structure or the component load spectrum obeys normal distribution or not is verified, namely: ln (D) -N (mu, sigma)2) When the accumulated driving mileage of the vehicle reaches the target mileage, the logarithmic pseudo damage of the vehicle structure or component load spectrum follows Weibull distribution;
s300, D is the pseudo-damage density, D is the accumulated pseudo-damage per kilometer of the load spectrum, which can be expressed as D ═ D/l, so that the logarithmic pseudo-damage density also follows a normal distribution, i.e.: ln (d) ═ ln (d) — ln (l) — N (l), σ ═ l2) The sample of the load spectrum is l kilometer, and the sample is subjected to normality test by a nonparametric test method;
s400, sampling from a sample of the pseudo-damage density population which follows normal distribution, wherein
S is the mean value and the standard deviation of the sample, the mean value and the standard deviation of the sample are determined according to the number of the extracted sample amount and obey t distribution when the extracted sample amount is 5<n<At 30 hours, there are
Obeying t distribution with the degree of freedom of n-1; and the sample size n>At 30 hours, there are
Obeying a t distribution with n-1 degrees of freedom, i.e.
S500, defining the relative deviation of the mean value of the sampling samples and the overall mean value as
And taking the relative deviation as a preset parameter for measuring the approximation degree of the sample mean value and the overall mean value, wherein the preset parameter is within a range, and the preset parameter is represented as:
S600, obtaining the coefficient of variation
To reflect the relative relationship between the sample standard deviation and the sample mean;
s700, driving the test vehicle to a user road for load spectrum acquisitionDetermining the confidence coefficient 1-alpha of the collected sample, and when the relative deviation of the sample mean value and the overall mean value is within a range, determining the confidence coefficient
Calculating a minimum sample size n;
and S800, after the minimum acquisition sample amount n is determined, calculating the minimum acquisition mileage nxl based on the acceleration signal of each shaft head.
On the basis of the method, the pseudo damage density of an acceleration load spectrum is calculated by taking vertical acceleration signals of four wheel shaft heads acquired under a high-speed working condition as an example under a heavy-load condition, and the pseudo damage density is taken as a sample extracted from the total. For a 100km acquired load spectrum, the lengths are respectively 2km, 5km, 8km and 10km, and 50, 20, 12 and 10 sampling samples are respectively obtained. And accumulating the pseudo damage value of the load spectrum fragment in each sample length, calculating the ratio of the accumulated pseudo damage to the sample length, and acquiring the pseudo damage density of each sample.
The samples are subjected to normality test by a Kolmogorov-Smirnov (K-S) nonparametric test method, the load spectrum pseudo-damage densities of all the sample lengths are obtained and obey normal distribution, the probability density distribution diagram of the normal distribution is shown in figures 2, 3, 4 and 5, and the parameters are shown in Table 1.
TABLE 1 load spectrum false damage Density Normal distribution parameters under different sample lengths
| Sample length | Mean value | Variance (variance) |
| 2km | 2.26×10-2 | 7.60×10-3 |
| 5km | 5.73×10-2 | 1.34×10-1 |
| 8km | 9.14×10-2 | 1.79×10-2 |
| 10km | 1.13×10-2 | 2.25×10-2 |
And (3) the confidence coefficient of the pseudo-damage density sampling sample is designated to be 95%, the deviation between the sample and the overall mean value is not more than 5%, the minimum sample number can be calculated, and the minimum acquisition mileage is obtained by multiplying the sample number by the corresponding sample length. Based on the collected vertical acceleration load spectrum of the four channel shaft heads under the high-speed working condition of 100km, the minimum sample number and the minimum collected mileage are obtained by calculation, and are shown in a table 2.
TABLE 2 minimum sample size and minimum collected mileage under high-speed operating conditions
As can be seen from the results in the table and the attached drawings, once the acceleration signals in the vertical direction of the plurality of spindle heads are acquired, the minimum acquisition mileage of the minimum sample size calculation durability test is acquired, the condition that the acquired data size is too large is avoided, meanwhile, the calculation results of different load spectrums are different, and the accuracy and the representativeness of the vehicle damage information acquired by the durability test are improved.
Example two
The difference from the first embodiment is that in step S100, the durability load spectrum is collected by a three-way acceleration sensor, a displacement sensor and a strain sensor, the three-way acceleration sensor can use an existing acceleration sensor of 8396A type, the displacement sensor can use a sensor of ZLDS100 type, the strain sensor can use a strain flower of T type, the least collected mileage calculation is performed by collecting the durability load spectrum of the component by a six-component sensor at the wheel end, the six-component sensor at the wheel end can use a sensor of LW-2T-300K type, and the user road includes an expressway, a national road, a mountain road, an urban road and a rural village road.
In the second embodiment, the least collected mileage is obtained by calculating the collection of the road surface information of different roads, the types of the user roads can be completely covered, so that the load spectrum representative of the user target mileage can be accurately obtained, and the test accuracy of the test field is improved.
The foregoing is merely an example of the present invention and common general knowledge of known specific structures and features of the embodiments is not described herein in any greater detail. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The method for calculating the minimum collected mileage of the user road when the user is associated with the test field is characterized by comprising the following steps of:
s100, acquiring a durability load spectrum of a user road, and acquiring pseudo damage densities of four shaft head vertical acceleration signals by taking the shaft head vertical acceleration signals as analysis objects;
s200, when the accumulated driving mileage of the vehicle reaches the target mileage, the target mileage is a condition that the vehicle part has a faultAnd (3) verifying whether the logarithmic pseudo-damage of the load spectrum of the vehicle structure or the component follows normal distribution or not by the mileage in fault, namely: ln (D) -N (mu, sigma)2)；
S300, D is the pseudo-damage density, D is the accumulated pseudo-damage per kilometer of the load spectrum, which can be expressed as D ═ D/l, so that the logarithmic pseudo-damage density also follows a normal distribution, i.e.: ln (d) ═ ln (d) — ln (l) — N (l), σ ═ l2)；
S400, sampling from a sample of the pseudo-damage density population which follows normal distribution, wherein
S are the mean value and the sample standard deviation of the sample respectively, and the mean value and the sample standard deviation obey t distribution according to the quantity of the extracted samples;
s500, defining the relative deviation of the mean value of the sampling samples and the overall mean value as
Taking the relative deviation as a preset parameter for measuring the approximation degree of the sample mean value and the overall mean value, wherein the preset parameter is within a range;
s600, obtaining the coefficient of variation
To reflect the relative relationship between the sample standard deviation and the sample mean;
s700, driving the test vehicle to a user road for load spectrum acquisition, designating the confidence coefficient 1-alpha of the acquired sample, and determining the relative deviation between the sample mean value and the overall mean value to be within the range
Calculating a minimum sample size n;
and S800, after the minimum acquisition sample amount n is determined, calculating the minimum acquisition mileage nxl based on the acceleration signal of each shaft head.
2. According to claim 1The method for calculating the minimum collected mileage of the user road when the user is associated with the test field is characterized by comprising the following steps of: in the step S400, when the sample size is 5<n<At 30 hours, there are
Obeying t distribution with the degree of freedom of n-1; and the sample size n>At 30 hours, there are
Obeying a t distribution with n-1 degrees of freedom, i.e.
3. The method of claim 1, wherein the method comprises the following steps: in step S500, the preset parameters are represented within a range as:
4. The method of claim 3, wherein the method comprises the following steps: to the right of the comparison inequality in step S500 is
tα/2Can be obtained by looking up the distribution table of t, i.e.
5. The method of claim 1, wherein the method comprises the following steps: in the step S100, a durability load spectrum is collected by the three-way acceleration sensor, the displacement sensor, and the strain sensor.
6. The method of claim 5, wherein the method comprises the following steps: in the step S100, the method further includes acquiring a component durability load spectrum through a six-component sensor at the wheel end to perform minimum acquired mileage calculation.
7. The method of claim 6, wherein the method comprises the following steps: in step S100, the user roads include expressways, national roads, mountain roads, urban roads, and rural villages.
8. The method of claim 1, wherein the method comprises the following steps: in the step S200, when the accumulated driving mileage of the vehicle reaches the target mileage, the logarithmic pseudo damage of the vehicle structure or component load spectrum follows the weibull distribution.
9. The method of claim 1, wherein the method comprises the following steps: in step S300, the load spectrum sample is l kilometers, and the sample is subjected to normality test by a non-parametric test method.
10. The method of claim 1, wherein the method comprises the following steps: in the step S100, the method further includes acquiring a pseudo damage density of the spindle nose force signal and the displacement signal.
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