CN113465643A - Error analysis method and system of stay wire displacement encoder - Google Patents
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Abstract
The invention relates to the technical field of stay wire encoders, in particular to an error analysis method and system of a stay wire displacement encoder, wherein the method comprises the following steps: step 1: acquiring attribute data, environmental data and measurement data of a stay wire displacement encoder; the attribute data is defined as the parameter data of the stay wire encoder; step 2: generating a measurement curve according to the measurement data, generating an attribute curve according to the attribute data, and generating an environment curve according to the environment data. The method has the advantages that the attribute data, the measurement data and the environment data of the stay wire encoder are firstly converted into the spherical mirror surface coordinate system to carry out curve error analysis, the three data are mapped and then clustered to carry out error analysis, the accuracy of the error analysis is improved, meanwhile, the error calculation is carried out by combining the curve error analysis, the obtained error is more accurate, the result of the measurement data obtained by final correction is more accurate, and the error magnitude of the measurement data is reduced.
Description
Technical Field
The invention belongs to the technical field of stay wire encoders, and particularly relates to an error analysis method and system of a stay wire displacement encoder.
Background
An encoder is a device that compiles, converts, and formats signals (e.g., bitstreams) or data into a form of signals that can be communicated, transmitted, and stored; encoders convert angular or linear displacements, called codewheels, into electrical signals, called coderulers. The encoder can be divided into a contact type and a non-contact type according to a reading mode; encoders can be classified into an incremental type and an absolute type according to the working principle; the incremental encoder comprises an incremental stay wire encoder and the like; the incremental type stay wire encoder consists of an incremental encoder and a stay wire box; when the incremental encoder shaft rotates, corresponding pulse output is provided, and the identification of the rotating direction and the increase and decrease of the pulse number are realized by a rear direction-judging circuit and a counter; the counting starting point can be set arbitrarily, and infinite accumulation and measurement of multiple circles can be realized; the pulse number is fixed, and when the resolution is required to be improved, the original pulse number can be multiplied by two paths of signals A and B with the phase difference of 90 degrees.
With the continuous development of economy and the progress of science and technology in China, the stay wire displacement sensor becomes the most main high-precision measurement product in the field of industrial control, is structurally and delicately integrated with a photoelectric and mechanical displacement sensor, fully combines the advantages of the photoelectric sensor and mechanical measurement, is particularly suitable for a linear guide rail system, is also suitable for a hydraulic cylinder system, a testing machine, a telescopic system, storage position positioning, a pressure machine, a paper making machine, a textile machine, a metal plate machine, a packaging machine, a printing machine, a horizontal controller, construction machinery and other related dimension measurement and position control, and can completely replace a grating ruler for use.
Patent No. CNB008064598A discloses a capacitive motion encoder for detecting the position of a moving object relative to a fixed object, comprising: at least one fixed element connected to the fixed object, and a moving element connected to the moving object and in proximity to the fixed object. A field emitter generates an electrostatic field that is modulated by a change in capacitance between the fixed and moving elements in response to relative movement of the elements. The conductive shield is electrically isolated from the moving and stationary objects and encloses the moving and stationary elements to protect them from external electrical interference. Processing circuitry detects the modulated electrostatic fields and determines a measure of the position of the moving object in response thereto.
Although the accuracy of the encoder is improved through circuit processing, the encoder is only a capacitive encoder, errors of the encoder cannot be fundamentally solved, and meanwhile influences of the encoder caused by different errors cannot be eliminated.
Disclosure of Invention
In view of the above, the present invention provides an error analysis method and system for a pull-wire displacement encoder, in which attribute data, measurement data, and environment data of the pull-wire encoder are first converted into a spherical mirror coordinate system to perform curve error analysis, and then the three data are mapped and then clustered to perform error analysis, so as to improve the accuracy of error analysis, and meanwhile, the error calculation is performed in combination with the curve error analysis, so that the obtained error is more accurate, the result of the measurement data obtained through final correction is more accurate, and the magnitude of error of the measurement data is reduced.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
an error analysis method of a pull wire displacement encoder, the method performing the steps of:
step 1: acquiring attribute data, environmental data and measurement data of a stay wire displacement encoder; the attribute data is defined as the parameter data of the stay wire encoder;
step 2: generating a measurement curve according to the measurement data, generating an attribute curve according to the attribute data and generating an environment curve according to the environment data;
and step 3: performing multiple data mapping on the attribute data and the measured data according to a set mapping model; the process of data mapping comprises: carrying out curve mapping on the measurement data at intervals of theta degrees according to a set curve mapping model each time to obtain multiple groups of mapped measurement data, and respectively using the multiple groups of mapped measurement data
Is shown, and thetanN θ; performing linear mapping on the attribute data at intervals of k according to a set linear mapping model to obtain multiple groups of mapped attribute data, and respectively using
Is shown, and k isn＝nk；
And 4, step 4: carrying out coordinate transformation on the measurement curve, and transforming the coordinates of the measurement points in the measurement curve from a measurement coordinate system to a spherical mirror surface coordinate system; calculating the error between the attribute curve and the measurement curve after coordinate transformation, and simultaneously adding an environment curve for correction; acquiring curve error analysis data; generating an error curve according to the curve error analysis data; outputting curve error analysis data and an error curve;
and 5: clustering the data of the multiple groups of mapped measurement data and attribute data by using a set clustering model to obtain a plurality of measurement data clusters and a plurality of attribute data clusters;
step 6: carrying out data cluster coincidence operation on the measured data cluster and the attribute data cluster to obtain data cluster coincidence distribution, finding data which are in the data cluster coincidence distribution and are far away from the center of each cluster and exceed a set threshold range, and taking the data as error analysis data;
and 7: and based on the output curve error analysis data, the error curve and the error analysis data, finding out the error of the stay wire displacement encoder, and based on the error, carrying out error correction on each measurement data of the stay wire displacement encoder.
Further, the curve mapping model in step 3 is expressed by using the following formula:
wherein, F (P)i) Representing a mapping function, F (P)i)＝siniθ*Pi；PiPresentation measurement(ii) volume data;
representing multiple sets of mapped measurement data.
Further, the linear mapping model in step 3 is expressed by using the following formula:
wherein the content of the first and second substances,
b is an adjustment parameter, and the value range is as follows: 2.5 to 4.5;
in order to be a function of the mapping,
a is an adjustment coefficient, and the value range is as follows: 1 to 3.
Further, the step 4 further includes the following steps after the step of obtaining the error analysis data: carrying out smooth denoising processing on the obtained error analysis data;
further, the step 4 further includes the following steps after the step of obtaining the error analysis data: fitting the error analysis data by using a least square method; and minimizing an error between the attribute data and the measurement data to obtain an optical parameter of the spherical mirror.
Further, the clustering model in step 5 is expressed by using the following formula:
wherein D isijRepresenting the data cluster obtained by clustering; a istjRepresenting elements in a clustering matrix A;
Further, the method for finding the error of the stay wire displacement encoder based on the output curve error analysis data, the error curve and the error analysis data in the step 7 includes: the error of the stay wire displacement encoder is obtained by using the following formula: the error of the stay wire displacement encoder is 0.1 × curve error analysis data +0.3 error curve +0.6 error analysis data.
Further, the method for performing error correction on each measurement data of the pull wire displacement encoder based on the error in step 7 comprises: the corrected result is obtained using the following formula: the corrected result is the measurement data error.
Further, the method for adding the environmental curve to correct in the step 4 includes: transforming the coordinates in the environment curve from the environment coordinate system to a spherical mirror coordinate system; and then, overlapping the measurement curves transformed into the spherical mirror coordinate system.
An error analysis system of a stay wire displacement encoder.
According to the error analysis method and system of the stay wire displacement encoder, the attribute data, the measurement data and the environment data of the stay wire encoder are firstly converted into the spherical mirror coordinate system to carry out curve error analysis, and then the three data are mapped and clustered to carry out error analysis, so that the accuracy of error analysis is improved, meanwhile, error calculation is carried out by combining curve error analysis, the obtained error is more accurate, the result of the measurement data obtained by final correction is more accurate, and the error magnitude of the measurement data is reduced. The method is mainly realized by the following steps:
1. binding analysis of various data: when the error of the stay wire encoder is analyzed, the measurement data is not analyzed, but the attribute data and the environment data of the stay wire encoder are combined for analysis, because multiple factors are often present which influence the accuracy of the measurement data, and the environment and the attribute of the environment are the two most important factors, the error analysis is carried out by combining the multiple data, not only can the error be obtained, but also the accuracy of the result can be fundamentally improved, and the measurement error of the stay wire encoder can be greatly reduced after error correction is carried out on all the results;
2. data mapping: when the invention is used for data mapping, the data is not simply analyzed and corrected, but the error analysis is carried out after the measured data and the attribute data are mapped, so that the invention has two advantages: firstly, mapping is carried out through various parameters, and after multiple groups of mapping data are obtained, hidden characteristics and rules of the data can be better found, and errors among the data can be found more easily; secondly, after data mapping, equivalently performing a divergent operation on the data, the obtained data have larger intervals, so that small errors can be found, and the accuracy of error analysis is improved;
3: combination of various error analysis methods: the method finds the error of the stay wire displacement encoder based on the output curve error analysis data, the error curve and the error analysis data, and carries out error correction on each measurement data of the stay wire displacement encoder based on the error, so that the scientificity of error analysis and the accuracy of error analysis are higher compared with single error correction and error analysis; because the weights of the errors caused by different factors are different, different weights are adopted for processing different errors, and the accuracy rate of the obtained result is higher;
4: data clustering treatment: according to the invention, multiple groups of mapped measurement data and attribute data are clustered by using the set clustering model to obtain a plurality of measurement data clusters and a plurality of attribute data clusters, after the plurality of data clusters are formed, data far away from the cluster center can be found, the data are error data, and the standard for judging the error data can be judged based on the set distance value, so that the error obtaining efficiency is higher.
Drawings
FIG. 1 is a schematic flow chart of a method for analyzing an error of a pull wire displacement encoder according to an embodiment of the present invention;
fig. 2 is a schematic diagram of data distribution after data mapping in the error analysis method and system for a stay wire displacement encoder according to the embodiment of the present invention;
FIG. 3 is a schematic diagram of a distribution of data clusters obtained by clustering data of the method and system for analyzing an error of a stay wire displacement encoder according to an embodiment of the present invention;
fig. 4 is a graph illustrating the variation of the magnitude of error with the number of experiments in the method and system for analyzing the error of the stay wire displacement encoder according to the embodiment of the present invention, and a comparison experiment effect diagram in the prior art.
Detailed Description
The method of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments of the invention.
Example 1
As shown in fig. 1, 2 and 4, an error analysis method of a stay wire displacement encoder performs the following steps:
step 1: acquiring attribute data, environmental data and measurement data of a stay wire displacement encoder; the attribute data is defined as the parameter data of the stay wire encoder;
step 2: generating a measurement curve according to the measurement data, generating an attribute curve according to the attribute data and generating an environment curve according to the environment data;
and step 3: performing multiple data mapping on the attribute data and the measured data according to a set mapping model; the process of data mapping comprises: carrying out curve mapping on the measurement data at intervals of theta degrees according to a set curve mapping model each time to obtain multiple groups of mapped measurement data, and respectively using the multiple groups of mapped measurement data
Is shown, and thetanN θ; performing linear mapping on the attribute data at intervals of k according to a set linear mapping model to obtain multiple groups of mapped attribute data, and respectively using
Is shown, and k isn＝nk；
And 4, step 4: carrying out coordinate transformation on the measurement curve, and transforming the coordinates of the measurement points in the measurement curve from a measurement coordinate system to a spherical mirror surface coordinate system; calculating the error between the attribute curve and the measurement curve after coordinate transformation, and simultaneously adding an environment curve for correction; acquiring curve error analysis data; generating an error curve according to the curve error analysis data; outputting curve error analysis data and an error curve;
and 5: clustering the data of the multiple groups of mapped measurement data and attribute data by using a set clustering model to obtain a plurality of measurement data clusters and a plurality of attribute data clusters;
step 6: carrying out data cluster coincidence operation on the measured data cluster and the attribute data cluster to obtain data cluster coincidence distribution, finding data which are in the data cluster coincidence distribution and are far away from the center of each cluster and exceed a set threshold range, and taking the data as error analysis data;
and 7: and based on the output curve error analysis data, the error curve and the error analysis data, finding out the error of the stay wire displacement encoder, and based on the error, carrying out error correction on each measurement data of the stay wire displacement encoder.
Adopt above-mentioned technical scheme: according to the method, the attribute data, the measurement data and the environment data of the stay wire encoder are firstly converted into the spherical mirror surface coordinate system to perform curve error analysis, and then the three data are mapped and clustered to perform error analysis, so that the accuracy of the error analysis is improved, meanwhile, the error calculation is performed by combining the curve error analysis, the obtained error is more accurate, the result of the measurement data obtained by final correction is more accurate, and the error magnitude of the measurement data is reduced. The method is mainly realized by the following steps:
1. binding analysis of various data: when the error of the stay wire encoder is analyzed, the measurement data is not analyzed, but the attribute data and the environment data of the stay wire encoder are combined for analysis, because multiple factors are often present which influence the accuracy of the measurement data, and the environment and the attribute of the environment are the two most important factors, the error analysis is carried out by combining the multiple data, not only can the error be obtained, but also the accuracy of the result can be fundamentally improved, and the measurement error of the stay wire encoder can be greatly reduced after error correction is carried out on all the results;
2. data mapping: when the invention is used for data mapping, the data is not simply analyzed and corrected, but the error analysis is carried out after the measured data and the attribute data are mapped, so that the invention has two advantages: firstly, mapping is carried out through various parameters, and after multiple groups of mapping data are obtained, hidden characteristics and rules of the data can be better found, and errors among the data can be found more easily; secondly, after data mapping, equivalently performing a divergent operation on the data, the obtained data have larger intervals, so that small errors can be found, and the accuracy of error analysis is improved;
3: combination of various error analysis methods: the method finds the error of the stay wire displacement encoder based on the output curve error analysis data, the error curve and the error analysis data, and carries out error correction on each measurement data of the stay wire displacement encoder based on the error, so that the scientificity of error analysis and the accuracy of error analysis are higher compared with single error correction and error analysis; because the weights of the errors caused by different factors are different, different weights are adopted for processing different errors, and the accuracy rate of the obtained result is higher;
4: data clustering treatment: according to the invention, multiple groups of mapped measurement data and attribute data are clustered by using the set clustering model to obtain a plurality of measurement data clusters and a plurality of attribute data clusters, after the plurality of data clusters are formed, data far away from the cluster center can be found, the data are error data, and the standard for judging the error data can be judged based on the set distance value, so that the error obtaining efficiency is higher.
Example 2
On the basis of the above embodiment, the curve mapping model in step 3 is used as followsThe formula expresses:
wherein, F (P)i) Representing a mapping function, F (P)i)＝siniθ*Pi；PiRepresenting the measurement data;
representing multiple sets of mapped measurement data.
In particular, data mapping is the process of creating two different data models and defining links between the models. The data model may include metadata, i.e., data atomic units that have semantically precise meaning, that use an atomic unit system to measure attributes of electricity containing information. Data mapping is most easily used in software engineering to describe the best way to access or represent some form of information. It acts as an abstract model to determine the areas of interest for relationships between certain information. This is the basic first step in establishing domain-specific data integration.
Example 3
On the basis of the previous embodiment, the linear mapping model in step 3 is represented by the following formula:
wherein the content of the first and second substances,
b is an adjustment parameter, and the value range is as follows: 2.5 to 4.5;
in order to be a function of the mapping,
a is an adjustment coefficient, and the value range is as follows: 1 to 3.
Example 4
On the basis of the above embodiment, the step 4 further includes, after the step of acquiring error analysis data, the steps of: and carrying out smooth denoising processing on the obtained error analysis data.
Specifically, the cause of the noisy data may be hardware malfunction, programming error, voice or optical character recognition program (OCR) recognition error, and the like. For example: the mobile phone signals come from electromagnetic waves transmitted by the base station, and some places are stronger and some places are weaker. An engineer of an operator can be responsible for counting the signal strength of different areas to plan a network, and the method for collecting the signals by the engineer is to fix a signal receiving terminal on a vehicle, then drive the vehicle to rotate around a base station, so that the signal terminal can automatically collect the signal strength of the different areas to generate data. However, if the vehicle encounters an emergency or sudden braking in the acquisition process, the signal acquisition may be affected to some extent, and noise data is generated.
Example 5
On the basis of the above embodiment, the step 4 further includes, after the step of acquiring error analysis data, the steps of: fitting the error analysis data by using a least square method; and minimizing an error between the attribute data and the measurement data to obtain an optical parameter of the spherical mirror.
Specifically, a spherical coordinate system is another way to represent a certain point in three-dimensional space. It also requires three values, two of which are angles and the third is distance. Imagine a ray (line segment) from the origin, whose two angles can determine the direction of the ray.
Example 6
As shown in fig. 3, on the basis of the previous embodiment, the clustering model in step 5 is represented by the following formula:
wherein D isijRepresenting the data cluster obtained by clustering; a istjRepresenting elements in a clustering matrix A;
In particular, the process of dividing a collection of physical or abstract objects into classes composed of similar objects is called clustering. The cluster generated by clustering is a collection of a set of data objects that are similar to objects in the same cluster and distinct from objects in other clusters. "the groups of things and the groups of people" have a great number of classification problems in natural science and social science. Clustering analysis, also known as cluster analysis, is a statistical analysis method for studying (sample or index) classification problems. The clustering analysis originates from taxonomy, but clustering is not equal to classification. Clustering differs from classification in that the class into which the clustering is required to be divided is unknown. The clustering analysis content is very rich, and a system clustering method, an ordered sample clustering method, a dynamic clustering method, a fuzzy clustering method, a graph theory clustering method, a clustering forecasting method and the like are adopted.
Example 7
On the basis of the above embodiment, the method for finding the error of the pull-wire displacement encoder in step 7 based on the output curve error analysis data, the error curve and the error analysis data includes: the error of the stay wire displacement encoder is obtained by using the following formula: the error of the stay wire displacement encoder is 0.1 × curve error analysis data +0.3 error curve +0.6 error analysis data.
Specifically, the error analysis is to analyze the cause and effect of the deviation of the desired target and the stage of the system in which the deviation occurs when the error completes the system function, thereby minimizing the error.
The purpose of studying the error is not to eliminate it, as this is not possible; nor is it made so small that it cannot be made any smaller, which is not necessarily necessary because it costs a lot of manpower and material resources; but under certain conditions an optimal measurement result is obtained that is closer to the true value. The physical chemistry takes the measurement of physical quantity as basic content, and reasonably processes the measured data to obtain some important rules, thereby researching the relationship between the physical and chemical properties of the system and the chemical reaction.
However, in actual measurement of physical quantities, whether directly measured quantities or indirectly measured quantities (quantities calculated from directly measured quantities by formulas), there is a difference between a measured value and a true value (or experimental average value) due to limitations of measuring instruments, methods, and influences of external conditions, which is called a measurement error.
The purpose of studying the error is: obtaining an optimal measurement result closer to the true value under certain conditions; determining the uncertainty of the result; according to the pre-required result, reasonable experimental instruments, experimental conditions and methods are selected to reduce the cost and shorten the experimental time. Therefore, in addition to careful experimentation, we need the ability to correctly express the results of the experiment, which are equally important. Experiments that report only the results without also indicating the uncertainty of the results are worthless and we therefore want to have a correct concept of error.
Example 8
On the basis of the above embodiment, the method for performing error correction on each measurement data of the wire displacement encoder in step 7 based on the error includes: the corrected result is obtained using the following formula: the corrected result is the measurement data error.
Example 9
On the basis of the above embodiment, the method for adding the environmental curve to correct in step 4 includes: transforming the coordinates in the environment curve from the environment coordinate system to a spherical mirror coordinate system; and then, overlapping the measurement curves transformed into the spherical mirror coordinate system.
Example 10
An error analysis system of a stay wire displacement encoder.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.
It should be noted that, the system provided in the foregoing embodiment is only illustrated by dividing the functional units, and in practical applications, the functions may be distributed by different functional units according to needs, that is, the units or steps in the embodiments of the present invention are further decomposed or combined, for example, the units in the foregoing embodiment may be combined into one unit, or may be further decomposed into multiple sub-units, so as to complete all or the functions of the units described above. The names of the units and steps involved in the embodiments of the present invention are only for distinguishing the units or steps, and are not to be construed as unduly limiting the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Those of skill in the art would appreciate that the various illustrative elements, method steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that programs corresponding to the elements, method steps may be located in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether these functions are performed in electronic hardware or software depends on the particular application and property constraints of the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or unit/apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or unit/apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent modifications or substitutions of the related art marks may be made by those skilled in the art without departing from the principle of the present invention, and the technical solutions after such modifications or substitutions will fall within the protective scope of the present invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (10)
1. An error analysis method of a stay wire displacement encoder, characterized in that the method performs the steps of:
step 1: acquiring attribute data, environmental data and measurement data of a stay wire displacement encoder; the attribute data is defined as the parameter data of the stay wire encoder;
step 2: generating a measurement curve according to the measurement data, generating an attribute curve according to the attribute data and generating an environment curve according to the environment data;
and step 3: performing multiple data mapping on the attribute data and the measured data according to a set mapping model; the process of data mapping comprises: carrying out curve mapping on the measurement data at intervals of theta degrees according to a set curve mapping model each time to obtain multiple groups of mapped measurement data, and respectively using the multiple groups of mapped measurement data
Is shown, and thetanN θ; the attribute data are respectively linearly mapped at intervals of k according to a set linear mapping model each time,obtaining multiple groups of mapped attribute data for respective use
Is shown, and k isn＝nk；
And 4, step 4: carrying out coordinate transformation on the measurement curve, and transforming the coordinates of the measurement points in the measurement curve from a measurement coordinate system to a spherical mirror surface coordinate system; calculating the error between the attribute curve and the measurement curve after coordinate transformation, and simultaneously adding an environment curve for correction; acquiring curve error analysis data; generating an error curve according to the curve error analysis data; outputting curve error analysis data and an error curve;
and 5: clustering the data of the multiple groups of mapped measurement data and attribute data by using a set clustering model to obtain a plurality of measurement data clusters and a plurality of attribute data clusters;
step 6: carrying out data cluster coincidence operation on the measured data cluster and the attribute data cluster to obtain data cluster coincidence distribution, finding data which are in the data cluster coincidence distribution and are far away from the center of each cluster and exceed a set threshold range, and taking the data as error analysis data;
and 7: and based on the output curve error analysis data, the error curve and the error analysis data, finding out the error of the stay wire displacement encoder, and based on the error, carrying out error correction on each measurement data of the stay wire displacement encoder.
2. The method of claim 1, wherein the curve mapping model in step 3 is represented by the following formula:
wherein, F (P)i) Representing a mapping function, F (P)i)＝siniθ*Pi；PiRepresenting the measurement data;
representing multiple sets of mapped measurement data.
3. The method of claim 2, wherein the linear mapping model in step 3 is represented using the following formula:
wherein the content of the first and second substances,
b is an adjustment parameter, and the value range is as follows: 2.5 to 4.5;
in order to be a function of the mapping,
a is an adjustment coefficient, and the value range is as follows: 1 to 3.
4. The method of claim 3, wherein the step 4 further comprises, after the step of obtaining error analysis data, the steps of: and carrying out smooth denoising processing on the obtained error analysis data.
5. The method of claim 4, wherein the step 4 further comprises, after the step of obtaining error analysis data, the steps of: fitting the error analysis data by using a least square method; and minimizing an error between the attribute data and the measurement data to obtain an optical parameter of the spherical mirror.
6. The method of claim 5, wherein the clustering model in step 5 is expressed using the following formula:
wherein D isijRepresenting the data cluster obtained by clustering; a istjRepresenting elements in a clustering matrix A;
p(atj) Representing an element a in a clustering matrix AtjThe probability of occurrence; m is the upper limit of clustering, and m is satisfied<n。
7. The method of claim 6, wherein the step 7 of finding the error of the pull-wire displacement encoder based on the outputted curve error analysis data, the error curve and the error analysis data comprises: the error of the stay wire displacement encoder is obtained by using the following formula: the error of the stay wire displacement encoder is 0.1 × curve error analysis data +0.3 error curve +0.6 error analysis data.
8. The method of claim 7, wherein the step 7 of error correcting each measurement data of the wire displacement encoder based on the error comprises: the corrected result is obtained using the following formula: the corrected result is the measurement data error.
9. The method of claim 8, wherein the step 4 of adding an environment curve for correction comprises: transforming the coordinates in the environment curve from the environment coordinate system to a spherical mirror coordinate system; and then, overlapping the measurement curves transformed into the spherical mirror coordinate system.
10. Error analysis system for a pull wire displacement encoder for carrying out the method of claims 1 to 9.
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