CN113465642B - Data correction method and system of stay wire displacement encoder based on attitude simulation - Google Patents
Data correction method and system of stay wire displacement encoder based on attitude simulation Download PDFInfo
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Abstract
The invention relates to the technical field of stay wire displacement encoders, in particular to a stay wire displacement encoder data correction method and a system based on attitude simulation, wherein the method comprises the following steps: step 1: acquiring attitude data and environmental data of the stay wire displacement encoder when acquiring data, and acquiring experimental data acquired by the stay wire displacement encoder, wherein the experimental data is used as a pre-correction value. Various errors in the process of acquiring experimental data are obtained by acquiring attitude data and environmental data of the stay wire displacement encoder in the process of acquiring data, and the data are corrected through errors obtained through calculation, so that the accuracy of the data is improved; meanwhile, when the error is calculated, the error is obtained by calculating the key data and the non-key data in different modes after the time sequence mapping is based instead of the traditional data analysis, so that the processing efficiency is improved.
Description
Technical Field
The invention belongs to the technical field of stay wire displacement encoders, and particularly relates to a stay wire displacement encoder data correction method and system based on attitude simulation.
Background
An encoder (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 their operation principles. The incremental encoder converts displacement into periodic electrical signals, and then converts the electrical signals into counting pulses, and the number of the pulses is used for expressing the magnitude of the displacement. Each position of the absolute encoder corresponds to a certain digital code, so that its representation is only dependent on the start and end positions of the measurement, and not on the intermediate course of the measurement.
With the continuous development of economy and the progress of science and technology in China, the stay wire displacement encoder becomes a main high-precision measurement product in the field of industrial control, is structurally and delicately integrated with a photoelectric and mechanical displacement encoder, and fully combines the advantages of the photoelectric encoder and mechanical measurement. The stay wire displacement encoder is particularly suitable for a linear guide rail system, and is also suitable for related dimension measurement and position control of a hydraulic cylinder system, a testing machine, a telescopic system, storage position positioning, a pressure machine, a papermaking machine, a textile machine, a metal plate machine, a packaging machine, a printing machine, a horizontal controller, a construction machine and the like, and control of an electro-hydraulic servo hydraulic universal testing machine. Can completely replace a grating ruler.
However, in the working process of the stay wire displacement encoder, errors are often caused by self factors or environmental factors, so that the accuracy of the data acquired by the stay wire displacement encoder is not satisfactory. Therefore, the data of the stay wire displacement encoder is corrected, and the accuracy of the stay wire displacement encoder can be greatly improved under the condition that the stay wire displacement encoder is not processed.
Patent No. cn201911419761.xa discloses a position data correction method, apparatus, and computer-readable storage medium. The method comprises the following steps: acquiring first position data of a predicted first time; when first positioning data is acquired at a first moment, acquiring a positioning error value according to the first positioning data and the first position data, acquiring a position error value corresponding to a first time period, and correcting the first position data according to the positioning error value and the position error value, wherein the first time period is a time period before the first moment; when a first distance value between the first distance value and a first reference object is acquired at a first moment, a second distance value between the first distance value and the first reference object is determined in the map according to the first position data, and the first position data is corrected according to the first distance value and the second distance value.
Although the first position data can be corrected according to the positioning error value and the position prediction error so as to improve the accuracy of the data, the error value correction method cannot be applied to high-precision equipment such as a stay wire displacement encoder.
Disclosure of Invention
In view of the above, the main objective of the present invention is to provide a method and a system for correcting data of a stay wire displacement encoder based on attitude simulation, in which various errors in the process of acquiring experimental data are obtained by collecting attitude data and environmental data of the stay wire displacement encoder in the process of acquiring data, and the data is corrected by the errors obtained by calculation, so as to improve the accuracy of the data; meanwhile, when the error is calculated, the error is obtained by calculating the key data and the non-key data in different modes after the time sequence mapping is based instead of the traditional data analysis, so that the processing efficiency is improved.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the data correction method of the stay wire displacement encoder based on the attitude simulation comprises the following steps:
step 1: acquiring attitude data and environmental data of the stay wire displacement encoder when the stay wire displacement encoder acquires the data, and acquiring experimental data acquired by the stay wire displacement encoder, wherein the experimental data is used as a pre-correction value;
step 2: generating a significant error by using a preset error generation model based on the acquired attitude data and the acquired environment data;
and step 3: performing data analysis based on the acquired experimental data to acquire experimental errors in the experimental data;
and 4, step 4: correcting the significant error based on the acquired experimental error to generate a corrected error;
and 5: performing time sequence mapping on the significant errors and the experimental data according to a time sequence order to obtain a first mapping result; meanwhile, according to the time sequence, performing time sequence mapping on the corrected error and the experimental data to obtain a second mapping result;
step 6: grouping is carried out in the first mapping result to obtain 5 groups; grouping is carried out in a second mapping result based on the obtained 5 groups to obtain 20 sub-groups; meanwhile, in 20 subgroups, performing key data analysis on the experimental data to obtain a key data part in the experimental data;
and 7: correcting the key data distribution based on the corrected error to obtain first corrected data, and correcting all data except the key data part by using a significant error to obtain second corrected data; and combining the first correction data and the second correction data to obtain a corrected value.
Further, the pose data includes: the external and internal properties of the pull wire displacement encoder; the external attributes include: the included angle between the stay wire displacement encoder and the horizontal direction and the moving speed of the stay wire displacement encoder; the internal attributes include: the pull force of the wire outlet of the stay wire displacement encoder and the maximum reciprocating speed.
Further, the environment data includes: operating voltage, operating temperature and vibration intensity.
Further, the step 2: the method for generating the significant error by using the preset error generation model based on the acquired attitude data and the acquired environment data comprises the following steps: significant error was calculated using the following equation:
wherein, theta is an included angle between the stay wire displacement encoder and the horizontal direction; gamma is the moving speed of the stay wire displacement encoder; epsilon is the working voltage;
is the outlet tension of the stay wire displacement encoder; delta is the maximum round-trip speed of the stay wire displacement encoder; t is the working temperature; the vibration intensity is adopted; p is a significant error.
Further, the method for performing data analysis based on the acquired experimental data in step 3 to acquire experimental errors in the experimental data includes: determining a data simulation model obtained based on experimental data and prediction data simulation of the experimental data; the predicted data of the experimental data are: generating data based on historical experimental data acquired by a stay wire displacement encoder; obtaining simulation data of prediction data of the experimental data and an error model of the experimental data based on the data simulation model; determining a plurality of absolute value error data representing the data change trend according to the data change trend of the error model, and taking analog data corresponding to the absolute value error data as absolute value analog data to obtain an absolute value analog data group; and carrying out normalization processing on the absolute value simulation data set to obtain an experimental error.
Further, the data simulation model is represented by the following formula:
wherein,
carrying out data simulation on the generated data simulation model to obtain simulation data; n is the average value of the experimental data and the predicted data of the experimental data; b is prediction data of experimental data; a is experimental data.
Further, the method for obtaining the error model of the experimental data based on the data simulation model includes: the error model is a conjugate model of the data simulation model, and the error model is obtained by performing conjugate operation on the data simulation model.
Further, the method for performing timing mapping in step 5 includes: according to the time sequence, one-to-one connection is carried out on the significant errors and the experimental data; significant errors in the connection and experimental data are at the same time.
Further, the method for performing the key data analysis in step 6 includes: filling experimental data in the 20 subgroups into a multi-dimensional data matrix in sequence; calculating the absolute value of each data element in the multidimensional data matrix to form a multidimensional experimental data absolute value matrix, wherein each data element with the distance from each calculated data element less than or equal to the dimension number of the multidimensional data matrix is taken as each nearby data element, the position and the gray value of each nearby data element are combined to form a multidimensional local absolute value matrix, and each data element with the distance from each calculated data element greater than the dimension number of the multidimensional data matrix is taken as each peripheral data element, and the position and the gray value of each peripheral data element are combined to form a multidimensional global absolute value matrix; and selecting each data element with the maximum value from the multidimensional experimental data absolute value matrix as an absolute value point, and forming a line segment representing the absolute value of the experimental data to obtain key data of the extracted experimental data.
A data correction system of a stay wire displacement encoder based on attitude simulation.
According to the method and the system for correcting the data of the stay wire displacement encoder based on the attitude simulation, various errors in the process of acquiring experimental data are obtained by acquiring the attitude data and the environmental data of the stay wire displacement encoder in the process of acquiring the data, and the data is corrected through the errors obtained by calculation, so that the accuracy of the data is improved; meanwhile, when the error is calculated, the error is obtained by calculating the key data and the non-key data in different modes after the time sequence mapping is based instead of the traditional data analysis, so that the processing efficiency is improved. The method is mainly realized by the following processes:
1. and correcting based on the attitude data and the environment data: because the stay wire displacement encoder is possibly influenced by self or environmental factors in the data acquisition process, when error correction is carried out, only one-sided factors can not be considered, all factors influencing the data accuracy are combined, and the data accuracy is greatly improved;
2. when the error correction is carried out, the error is obtained by analyzing the data, the experimental error and the obvious error are combined for correction, and meanwhile, the corrected error and the experimental data are corrected after being grouped by carrying out time sequence mapping to finish the experimental data, so that the accuracy of the data is further improved;
3. packet error correction: according to the invention, through key data analysis, non-key data are distinguished, different error correction modes are used for different data, and the data correction efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart of a method for correcting data of a guy wire displacement encoder based on attitude simulation according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an experimental principle of grouping a first mapping result and a second mapping result of the method and system for correcting data of a pull wire displacement encoder based on attitude simulation according to the embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a principle of key data analysis of a method and system for data correction of a guy wire displacement encoder based on attitude simulation according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a deviation relationship between experimental data and an accurate value after correction and before correction of the experimental data in the method and system for correcting data of a pull wire displacement encoder based on attitude simulation according to the embodiment of the present invention.
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, the method for correcting data of a guy wire displacement encoder based on attitude simulation comprises the following steps:
step 1: acquiring attitude data and environmental data of the stay wire displacement encoder when the stay wire displacement encoder acquires the data, and acquiring experimental data acquired by the stay wire displacement encoder, wherein the experimental data is used as a pre-correction value;
step 2: generating a significant error by using a preset error generation model based on the acquired attitude data and the acquired environment data;
and step 3: performing data analysis based on the acquired experimental data to acquire experimental errors in the experimental data;
and 4, step 4: correcting the significant error based on the acquired experimental error to generate a corrected error;
and 5: performing time sequence mapping on the significant errors and the experimental data according to a time sequence order to obtain a first mapping result; meanwhile, according to the time sequence, performing time sequence mapping on the corrected error and the experimental data to obtain a second mapping result;
step 6: grouping is carried out in the first mapping result to obtain 5 groups; grouping is carried out in a second mapping result based on the obtained 5 groups to obtain 20 sub-groups; meanwhile, in 20 subgroups, performing key data analysis on the experimental data to obtain a key data part in the experimental data;
and 7: correcting the key data distribution based on the corrected error to obtain first corrected data, and correcting all data except the key data part by using a significant error to obtain second corrected data; and combining the first correction data and the second correction data to obtain a corrected value.
Referring to fig. 2, in the first mapping result, the present invention performs grouping to obtain 5 groups; based on the obtained 5 packets, in the second mapping result, the grouping is performed, resulting in 20 sub-packets.
Referring to fig. 3, in 20 subgroups, the critical data analysis is performed on the experimental data, resulting in critical data portions in the experimental data.
Referring to fig. 4, the experimental data of the present invention is a pre-correction value before correction, and a post-correction value is obtained after correction. The deviation of the corrected value from the accurate value is significantly lower than the value before correction.
According to the method, various errors in the process of acquiring experimental data are obtained by acquiring the attitude data and the environmental data of the stay wire displacement encoder in the process of acquiring the data, and the data are corrected through the errors obtained through calculation, so that the accuracy of the data is improved; meanwhile, when the error is calculated, the error is obtained by calculating the key data and the non-key data in different modes after the time sequence mapping is based instead of the traditional data analysis, so that the processing efficiency is improved. The method is mainly realized by the following steps:
1. and correcting based on the attitude data and the environment data: because the stay wire displacement encoder is possibly influenced by self or environmental factors in the data acquisition process, when error correction is carried out, only one-sided factors can not be considered, all factors influencing the data accuracy are combined, and the data accuracy is greatly improved;
2. when the error correction is carried out, the error is obtained by analyzing the data, the experimental error and the obvious error are combined for correction, and meanwhile, the corrected error and the experimental data are corrected after being grouped by carrying out time sequence mapping to finish the experimental data, so that the accuracy of the data is further improved;
3. packet error correction: according to the invention, through key data analysis, non-key data are distinguished, different error correction modes are used for different data, and the data correction efficiency is improved.
Example 2
On the basis of the above embodiment, the attitude data includes: the external and internal properties of the pull wire displacement encoder; the external attributes include: the included angle between the stay wire displacement encoder and the horizontal direction and the moving speed of the stay wire displacement encoder are calculated; the internal attributes include: the pull force of the wire outlet of the stay wire displacement encoder and the maximum reciprocating speed.
Specifically, experimental error is the difference between the experimental measurements (including direct and indirect measurements) and the true values (the exact values that exist objectively). The experimental error is never equal to zero. Regardless of the subjective desire of people and how carefully and carefully people control in the measurement process, errors are generated and cannot be eliminated, and the existence of the errors is absolute.
Experimental errors were random. Under the same experimental conditions, the experiment, test or observation is repeated for the same research object for a plurality of times, and the obtained result is not a determined result, namely the experimental result has uncertainty.
Example 3
On the basis of the above embodiment, the environment data includes: operating voltage, operating temperature and vibration intensity.
Specifically, the error can be classified into a systematic error, a random error and a coarse error according to the nature of the experimental error and the cause of the experimental error.
Systematic error
Caused by some fixed and unchanging factors. The measurement is carried out for a plurality of times under the same condition, the magnitude and the positive and negative of the error value are kept constant, or the error changes according to a certain rule along with the change of the condition.
Random error
Caused by certain factors that are not easily controlled. The error value and sign of the measurement are uncertain, the instant magnitude and the instant timing are small, the instant timing is negative, and the fixed magnitude and the deviation are absent. The random error follows a statistical law, the error of which is related to the number of measurements. As the number of measurements increases, the random error of the average may be reduced, but not eliminated.
Gross error
Errors that are clearly inconsistent with reality are mainly due to the carelessness of the experimenter, such as reading errors, recording errors or operation failures. These errors are often very different from normal values and should be removed in the data processing according to the usual criteria.
Example 4
On the basis of the above embodiment, the step 2: the method for generating the significant error by using the preset error generation model based on the acquired attitude data and the acquired environment data comprises the following steps: significant error was calculated using the following equation:
wherein theta is an included angle between the stay wire displacement encoder and the horizontal direction; gamma is the moving speed of the stay wire displacement encoder; epsilon is the working voltage;
is the outlet tension of the stay wire displacement encoder; delta is the maximum round-trip speed of the stay wire displacement encoder; is the working temperature; s is the vibration intensity; p is a significant error.
Specifically, an encoder (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 their operation principles. The incremental encoder converts displacement into periodic electrical signals, and then converts the electrical signals into counting pulses, and the number of the pulses is used for expressing the magnitude of the displacement. Each position of the absolute encoder corresponds to a certain digital code, so that its representation is only dependent on the start and end positions of the measurement, and not on the intermediate course of the measurement.
Example 5
On the basis of the previous embodiment, the method for performing data analysis based on the acquired experimental data in step 3 to acquire experimental errors in the experimental data includes: determining a data simulation model obtained based on experimental data and prediction data simulation of the experimental data; the predicted data of the experimental data are: generating data based on historical experimental data acquired by a stay wire displacement encoder; obtaining simulation data of prediction data of the experimental data and an error model of the experimental data based on the data simulation model; determining a plurality of absolute value error data representing the data change trend according to the data change trend of the error model, and taking simulation data corresponding to the absolute value error data as absolute value simulation data to obtain an absolute value simulation data set; and carrying out normalization processing on the absolute value simulation data set to obtain an experimental error.
Specifically, data simulation is also called data simulation and curve fitting, and is commonly called a pull curve, which is a representation mode that substitutes the existing data into a mathematical expression through a mathematical method. Scientific and engineering problems can be solved by obtaining several discrete data through methods such as sampling, experiment, etc., and from these data, we often want to obtain a continuous function (i.e. curve) or a more dense discrete equation fitting the known data, which is called fitting (fitting).
Example 6
On the basis of the above embodiment, the data simulation model is represented by the following formula:
wherein,
carrying out data simulation on the generated data simulation model to obtain simulation data; n is the average value of the experimental data and the predicted data of the experimental data; b is prediction data of experimental data; a is experimental data.
Example 7
On the basis of the above embodiment, the method for obtaining the error model of the experimental data based on the data simulation model includes: the error model is a conjugate model of the data simulation model, and the error model is obtained by performing conjugate operation on the data simulation model.
Example 8
On the basis of the previous embodiment, the method for performing timing mapping in step 5 includes: according to the time sequence, one-to-one connection is carried out on the significant errors and the experimental data; significant errors in the connection and experimental data are at the same time.
Example 9
On the basis of the above embodiment, the method for performing the key data analysis in step 6 includes: filling experimental data in the 20 subgroups into a multi-dimensional data matrix in sequence; calculating the absolute value of each data element in the multidimensional data matrix to form a multidimensional experimental data absolute value matrix, wherein each data element with the distance from each calculated data element less than or equal to the dimension number of the multidimensional data matrix is taken as each nearby data element, the position and the gray value of each nearby data element are combined to form a multidimensional local absolute value matrix, and each data element with the distance from each calculated data element greater than the dimension number of the multidimensional data matrix is taken as each peripheral data element, and the position and the gray value of each peripheral data element are combined to form a multidimensional global absolute value matrix; and selecting each data element with the maximum value from the multidimensional experimental data absolute value matrix as an absolute value point, and forming a line segment representing the absolute value of the experimental data to obtain key data of the extracted experimental data.
In particular, the function of a pull-cord type displacement sensor is to convert mechanical motion into an electrical signal that can be metered, recorded or transmitted. The ChujiaCKS series displacement sensor is formed by winding a stretchable stainless steel wire around a threaded hub, which is connected to a precision rotary sensor, which can be an incremental encoder, an absolute encoder, a hybrid or conductive plastic rotary potentiometer, a synchronizer or a resolver.
In operation, the pull-cord type displacement sensor is mounted in a fixed position and the pull cord is tied to a moving object. The linear motion of the pull rope is aligned with the motion axis of the moving object. As the motion occurs, the drawstring expands and contracts. An internal spring ensures constant tension in the pull cord. The hub with the thread drives the precise rotary inductor to rotate, and an electric signal proportional to the moving distance of the pull rope is output. The displacement, direction or speed of the moving object can be obtained by measuring the output signal.
Common parameters include measuring stroke, output signal mode, linearity, repeatability, resolution, wire diameter specification, outlet tension, maximum round-trip speed, weight, input resistance, power, operating voltage, operating temperature, vibration, protection level, and the like.
Example 10
A data correction system of a stay wire displacement encoder based on attitude simulation.
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. The data correction method of the stay wire displacement encoder based on the attitude simulation is characterized by comprising the following steps:
step 1: acquiring attitude data and environmental data of the stay wire displacement encoder when the stay wire displacement encoder acquires the data, and acquiring experimental data acquired by the stay wire displacement encoder, wherein the experimental data is used as a pre-correction value;
step 2: generating a significant error by using a preset error generation model based on the acquired attitude data and the acquired environment data;
and step 3: performing data analysis based on the acquired experimental data to acquire experimental errors in the experimental data;
and 4, step 4: correcting the significant error based on the acquired experimental error to generate a corrected error;
and 5: performing time sequence mapping on the significant errors and the experimental data according to a time sequence order to obtain a first mapping result; meanwhile, according to the time sequence, performing time sequence mapping on the corrected error and the experimental data to obtain a second mapping result;
step 6: grouping is carried out in the first mapping result to obtain 5 groups; grouping is performed in the second mapping result based on the obtained 5 groups to obtain 20 sub-groups; meanwhile, in 20 subgroups, performing key data analysis on the experimental data to obtain a key data part in the experimental data;
and 7: correcting the key data distribution based on the corrected error to obtain first corrected data, and correcting all data except the key data part by using a significant error to obtain second corrected data; and combining the first correction data and the second correction data to obtain a corrected value.
2. The method of claim 1, wherein the pose data comprises: the external and internal properties of the pull wire displacement encoder; the external attributes include: the included angle between the stay wire displacement encoder and the horizontal direction and the moving speed of the stay wire displacement encoder; the internal attributes include: the pull force of the wire outlet of the stay wire displacement encoder and the maximum reciprocating speed.
3. The method of claim 2, wherein the environmental data comprises: operating voltage, operating temperature and vibration intensity.
4. The method of claim 3, wherein the step 2: the method for generating the significant error by using the preset error generation model based on the acquired attitude data and the acquired environment data comprises the following steps: using e.g. asThe following formula, the significant error is calculated:
wherein theta is an included angle between the stay wire displacement encoder and the horizontal direction; gamma is the moving speed of the stay wire displacement encoder; epsilon is the working voltage;
is the outlet tension of the stay wire displacement encoder; delta is the maximum round-trip speed of the stay wire displacement encoder; t is the working temperature; s is the vibration intensity; p is a significant error.
5. The method of claim 4, wherein the step 3 of performing data analysis based on the acquired experimental data to acquire experimental errors in the experimental data comprises: determining a data simulation model obtained based on experimental data and prediction data simulation of the experimental data; the predicted data of the experimental data are: generating data based on historical experimental data acquired by a stay wire displacement encoder; obtaining simulation data of prediction data of the experimental data and an error model of the experimental data based on the data simulation model; determining a plurality of absolute value error data representing the data change trend according to the data change trend of the error model, and taking analog data corresponding to the absolute value error data as absolute value analog data to obtain an absolute value analog data group; and carrying out normalization processing on the absolute value simulation data set to obtain an experimental error.
6. The method of claim 5, wherein the data simulation model is represented using the following formula:
wherein,
carrying out data simulation on the generated data simulation model to obtain simulation data; n is the average value of the experimental data and the predicted data of the experimental data; b is the predicted data of the experimental data; a is experimental data.
7. The method of claim 6, wherein the method of obtaining an error model of the experimental data based on the data simulation model comprises: the error model is a conjugate model of the data simulation model, and the error model is obtained by performing conjugate operation on the data simulation model.
8. The method of claim 7, wherein the step 5 of performing timing mapping comprises: according to the time sequence, one-to-one connection is carried out on the significant errors and the experimental data; significant errors in the connection and experimental data are at the same time.
9. The method of claim 8, wherein the step 6 of performing key data analysis comprises: filling experimental data in the 20 subgroups into a multi-dimensional data matrix in sequence; calculating the absolute value of each data element in the multidimensional data matrix to form a multidimensional experimental data absolute value matrix, wherein each data element with the distance from each calculated data element less than or equal to the dimension number of the multidimensional data matrix is taken as each nearby data element, the position and the gray value of each nearby data element are combined to form a multidimensional local absolute value matrix, and each data element with the distance from each calculated data element greater than the dimension number of the multidimensional data matrix is taken as each peripheral data element, and the position and the gray value of each peripheral data element are combined to form a multidimensional global absolute value matrix; and selecting each data element with the maximum value from the multidimensional experimental data absolute value matrix as an absolute value point, and forming a line segment representing the absolute value of the experimental data to obtain key data of the extracted experimental data.
10. Wire-based displacement encoder data correction system for the implementation of the method according to one of claims 1 to 9.
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