CN117555295A - Engineering mechanical equipment accessory management system - Google Patents
Engineering mechanical equipment accessory management system Download PDFInfo
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- CN117555295A CN117555295A CN202311369581.1A CN202311369581A CN117555295A CN 117555295 A CN117555295 A CN 117555295A CN 202311369581 A CN202311369581 A CN 202311369581A CN 117555295 A CN117555295 A CN 117555295A
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- 238000005259 measurement Methods 0.000 claims abstract description 49
- 238000012545 processing Methods 0.000 claims abstract description 28
- 230000010354 integration Effects 0.000 claims abstract description 24
- 238000012216 screening Methods 0.000 claims description 36
- 238000000034 method Methods 0.000 claims description 29
- 230000002159 abnormal effect Effects 0.000 claims description 28
- 238000011084 recovery Methods 0.000 claims description 24
- 238000000605 extraction Methods 0.000 claims description 22
- 239000011159 matrix material Substances 0.000 claims description 10
- 238000003908 quality control method Methods 0.000 claims description 10
- 238000005070 sampling Methods 0.000 claims description 10
- 238000012790 confirmation Methods 0.000 claims description 9
- 230000004927 fusion Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 5
- 238000002592 echocardiography Methods 0.000 claims description 5
- 230000035772 mutation Effects 0.000 claims description 5
- 239000002689 soil Substances 0.000 claims description 4
- 239000000463 material Substances 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims description 2
- 230000005856 abnormality Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010924 continuous production Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31282—Data acquisition, BDE MDE
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- Automation & Control Theory (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
Abstract
The invention discloses an accessory management system of engineering machinery equipment, which relates to the field of accessory management and comprises a data processing unit, an information acquisition unit and a multi-source information integration unit; according to the engineering mechanical equipment accessory management system, equipment accessory measurement data are acquired through the information acquisition unit, data adjustment is carried out on the data acquired through the information acquisition unit through the data processing unit, so that the data are convenient to use, the processed multi-source data are integrated through the multi-source information integration unit, the three-dimensional model is generated through the three-dimensional generation unit by the data integrated through the multi-source information integration unit, the three-dimensional model generated through the three-dimensional generation unit and the data processed through the data processing unit are displayed through the display unit, meanwhile, the update state of the overlapping characteristics is determined through the multi-source information integration unit, and therefore the choice of the overlapping characteristics is determined, useful measurement data can be selected according to the extracted characteristics, and the situation that proper data cannot be selected due to more data is avoided.
Description
Technical Field
The invention relates to an accessory management technology, in particular to an accessory management system of engineering machinery equipment.
Background
When the yield of the current continuous production line is very high, only the information of each batch is recorded, and most of single products are only recorded in quantity, so that the omnibearing product information recording is realized, the system is huge, the efficiency is low, the cost is high, the quality control and the follow-up traceability of each part are difficult, and the information recording and the relevant state recording of each part are incomplete, so that the quality control and improvement are quite difficult.
At present, most of accessory management systems of engineering machinery equipment adopt manual recording when data recording is carried out, so that data errors exist when the data recording is carried out, errors exist when the accessory management is carried out, and the accuracy of the accessory management is reduced
Disclosure of Invention
The invention aims to provide an accessory management system of engineering machinery equipment, which aims to solve the defects in the prior art.
In order to achieve the above object, the present invention provides the following technical solutions: the engineering mechanical equipment accessory management system comprises a data processing unit, an information acquisition unit, a multi-source information integration unit, a three-dimensional generation unit and a display unit:
the information acquisition unit is used for acquiring equipment accessory measurement data;
the data processing unit is used for carrying out data adjustment on the data acquired by the information acquisition unit so that the data is convenient to use;
the multi-source information integration unit is used for integrating the data processed by the data processing unit, so that multiple data can be conveniently used in combination;
the three-dimensional generation unit is used for generating a three-dimensional model from the data integrated by the multi-source information integration unit;
the display unit is used for displaying the data processed by the data processing unit and the three-dimensional model generated by the three-dimensional generating unit.
Further, the information acquisition unit includes:
the laser measuring module is used for measuring the internal environment data of the equipment accessory;
the flatness detection module is used for shooting equipment accessory wall flatness data;
and the radar measurement module is used for measuring foundation data below the soil.
Further, the data processing unit adjusts the data collected by the data collection unit including, but not limited to, abnormal data recovery, discarding, filling, replacement, and deduplication.
Further, the specific method for the data processing unit to perform data adjustment is as follows:
s1, data screening, wherein the data screening further comprises:
preliminary screening;
threshold value screening;
quality control screening, wherein if the measured parameter data of a certain sampling interval has mutation, the abnormal condition of the group of measured parameters can be considered;
s2, data recovery, wherein the data recovery method further comprises the following steps:
a time-series-based data recovery method, and a time-series data prediction method should be essentially suitable for recovery of measured data;
the data recovery method based on the space-time correlation is to establish a correlation model of any measured data and other measured data in space-time, and then recover abnormal data through the other measured data.
Further, the multi-source information integrating unit includes:
the feature screening module is used for screening features in the measurement data;
the same feature extraction module is used for extracting the same features screened by the feature screening module;
the abnormal feature extraction module is used for extracting the abnormal features screened by the feature screening module;
the overlapped feature extraction module is used for extracting the overlapped features screened by the feature screening module;
and the feature fusion unit is used for carrying out feature fusion on the corresponding features extracted by the same feature extraction module, the abnormal feature extraction module and the overlapped feature extraction module.
Further, the specific method for extracting the overlapping features by the multi-source information integration unit comprises the following steps:
a1, calculating all measurement data j (j epsilon Z) in each target T (t=1, 2,.. t (k) Associated probability beta) with target t jt ；
A2, constructing a confirmation matrix, and judging whether the measurement is public measurement belonging to a plurality of targets according to the confirmation matrix, wherein the expression of the confirmation matrix is;
a3, calculating the probability of the affiliation between the public echo and each target, and calculating the probability of the public echo and each target T (T epsilon T) assuming a target set T and a public echo j M ) Euclidean distance d between jt Because the greater the measured distance from a target, the less the probability that the measurement belongs to that target, the probability of the affiliation between the common echo and each target is inversely related to the distance, and the echoes should all be assigned to their associated targets;
a4, correcting the association probability of the public echo obtained in the first step by utilizing the affiliation probability between the echo formula and each target, thereby obtaining new association probability beta 'between the public echo and each related target' jt ，；
A5, normalizing the interconnection probabilities of all measurements in the association gate where each target is located to obtain beta' jt ；
A6, utilizing the association probability beta' jt The state is updated by weighting all the metrology data within each target.
Further, the specific method for three-dimensional modeling by the three-dimensional generating unit comprises the following steps:
b1, creating an axis network, elevation and a reference plane;
b2, creating a main body structure, wherein the main body structure creating further comprises:
performing foundation creation with reference to the foundation size;
creating a column structure, namely naming columns with different sections of the structural column according to drawing numbers;
a housing creation including input device accessory material, and various housing parameters;
establishing a beam, wherein after the size of the longitudinal section of the beam is determined, modeling and drawing are carried out along an axis;
board creation, wherein the board creation is created by extracting boundaries from walls;
and (5) creating a surface.
Compared with the prior art, the engineering mechanical equipment accessory management system provided by the invention has the advantages that equipment accessory measurement data are acquired through the information acquisition unit, the data acquired through the information acquisition unit is subjected to data adjustment through the data processing unit, so that the data are convenient to use, the processed multi-source data are integrated through the multi-source information integration unit, the three-dimensional model is generated through the three-dimensional generation unit by the data integrated through the multi-source information integration unit, the data processed through the data processing unit and the three-dimensional model generated through the three-dimensional generation unit are displayed through the display unit, meanwhile, the update state of the overlapping features is determined through the multi-source information integration unit by extracting the overlapping features, and therefore the choice of the overlapping features is determined, so that useful measurement data can be selected according to the extracted features, and the situation that proper data cannot be selected due to more data is avoided.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
Fig. 1 is a schematic diagram of an overall flow structure according to an embodiment of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings.
Referring to fig. 1, an accessory management system of engineering machinery equipment includes a data processing unit, an information acquisition unit, a multi-source information integration unit, a three-dimensional generation unit and a display unit:
the information acquisition unit is used for acquiring equipment accessory measurement data;
the data processing unit is used for carrying out data adjustment on the data acquired by the information acquisition unit so that the data is convenient to use;
the multi-source information integration unit is used for integrating the data processed by the data processing unit, so that multiple data can be conveniently used in a combined mode;
the three-dimensional generation unit is used for generating a three-dimensional model from the data integrated by the multi-source information integration unit;
and the display unit is used for displaying the data processed by the data processing unit and the three-dimensional model generated by the three-dimensional generating unit.
The device comprises an information acquisition unit, a data processing unit, a multi-source information integration unit, a three-dimensional generation unit, a display unit, a data processing unit, a three-dimensional generation unit and a display unit.
The information acquisition unit includes:
the laser measuring module is used for measuring the internal environment data of the equipment accessory;
the flatness detection module is used for shooting equipment accessory wall flatness data;
and the radar measurement module is used for measuring foundation data below the soil.
The device accessory internal environment data are measured through the laser measuring module, the device accessory wall flatness data are shot through the flatness detecting module, the foundation data below the soil are measured through the radar measuring module, and the device accessory can be set.
The data processing unit adjusts the data acquired by the data acquisition unit, including but not limited to abnormal data recovery, discarding, filling, replacing and deduplication, so that usable data can be selected for use.
The specific method for the data processing unit to adjust the data comprises the following steps:
s1, data screening, wherein the data screening further comprises:
preliminary screening;
threshold screening, which is to set certain data critical values and screen the measurement data exceeding the critical values, so as to ensure that the measurement data is within a reasonable range. The key of the threshold screening is to determine a proper critical threshold value which is closely related to different places, external environments and data sampling intervals, and the expression is that
x max ＝x 0 +3f(T)，
Wherein x is max To measure the critical threshold of the data, x 0 For the basic limit of the measured data, T is the sampling interval of the data, and f () is the fitting function of the root mean square error of the measured data stream parameters and the sampling interval T.
And (3) quality control screening, wherein the measured data has a certain continuity in time, i.e. the measured data in a certain period of time does not have mutation. If the measured data of a certain sampling interval has mutation, the group of measured data can be considered to have abnormal conditions, and the abnormal value screening is carried out by combining the correlation among the measured data and the sampling multisource quality control method. The index formula for constructing the multi-source quality control is as follows
Wherein the formula is as follows: i is an index of multi-source data quality control, mq n 、mν n 、mo n Mean values of n sampling interval x-axis measurement data q, y-axis measurement data v and z-axis measurement data o, sq respectively n 、sν n 、so n The standard deviation of the x-axis measurement data q, the y-axis measurement data v and the z-axis measurement data o are respectively, and the index I is an ellipsoid of multi-source quality control established according to the 3 sigma principle. If a set of measurement data q, v and o is such that I is greater than 1, indicating that the point of the three-dimensional data vector of the measurement point falls outside the quality control ellipsoid in three-dimensional space, the set of data is abnormal and should be taken as cullingThe data is normal, except.
The reason for data screening is that measurement data acquired by a detector is affected by external factors, and thus, there are abnormal cases such as deletion, mutation, and error, and thus, the measurement data cannot be directly used as data.
S2, data recovery, wherein the data recovery method further comprises the following steps:
the time series-based data recovery method is essentially suitable for recovering the measured data, but takes the real-time property, the randomness and the mass property of the measured data into consideration, and needs strong on-line processing capacity, so the specific calculation mode is as follows
Wherein the method comprises the steps ofThe value is the recovery value of abnormal data in the formula, x is the detection value of the first several sampling intervals, beta is a weight coefficient, and Σbeta=1; k is the sampling interval width adopted by smooth recovery, the method is mainly suitable for recovery of isolated abnormal data, and for a plurality of continuous abnormal data, the error of the method can be greatly increased. Therefore, when the continuous abnormal data is too much, the method is not applicable;
the data recovery method based on the space-time correlation is to establish a data recovery formula by establishing a correlation model of any detector data and other detector data in space-time, recovering abnormal data by the other detector data and considering binary regression and median robustness according to a data regression model
Wherein the method comprises the steps ofValues are recovered for the j-position data for the pairs of detectors m and n associated with the j-position. Gamma ray 1 、γ 2 And gamma 3 For regression equation coefficients, x i (m) and x i (n) is the actual detection value of m and n positions,/->And for the predicted value of the missing detector j, a plurality of regression equations are obtained by establishing a correlation model among a plurality of detector data, the median value of the recovery values of the plurality of regression equation data is used as final recovery data, and the model with the median robust characteristic is adopted, so that the influence of the abnormality and the loss of part of detector data on the final recovery result can be avoided, and the anti-interference capability of the method is improved.
The multi-source information integration unit includes:
the feature screening module is used for screening features in the measurement data;
the same feature extraction module is used for extracting the same features screened by the feature screening module;
the abnormal feature extraction module is used for extracting the abnormal features screened by the feature screening module;
the overlapped feature extraction module is used for extracting the overlapped features screened by the feature screening module;
and the feature fusion unit is used for carrying out feature fusion on the corresponding features extracted by the same feature extraction module, the abnormal feature extraction module and the overlapped feature extraction module.
The method comprises the steps of setting the same feature selected by a feature screening module through the same feature extraction module, extracting the abnormal feature selected by the feature screening module through the abnormal feature extraction module, extracting the overlapped feature selected by the feature screening module through the overlapped feature extraction module, fusing the same feature through a feature fusion unit, eliminating the abnormal feature, extracting the overlapped feature, and determining the updating state of the overlapped feature, thereby determining the choice of the overlapped feature, and selecting useful measurement data according to the extracted feature, thereby avoiding the situation that the proper data cannot be selected due to more data.
The specific method for extracting the overlapping characteristics by the multi-source information integration unit comprises the following steps:
a1, calculating all measurement data j (j epsilon Z) in each target T (t=1, 2,.. t (k) Associated probability beta) with target t jt ；
A2, constructing a confirmation matrix, and judging whether the measurement is public measurement belonging to a plurality of targets according to the confirmation matrix, wherein the expression of the confirmation matrix is as follows:
if in the above formula:
then it is explained that the measurement j is a common echo, the element equal to 1 in each row of the validation matrix is judged, and the target label t is recorded 1 ，t 2 .. the measurement j is the t of each of the mouthpieces 1 ，t 2 ... Public measurements, all measurements are judged to obtain all public echoes, and targets corresponding to these echoes, respectively;
a3, calculating the probability of the affiliation between the public echo and each target, and calculating the probability of the public echo and each target T (T epsilon T) assuming a target set T and a public echo j M ) Euclidean distance d between jt Because the greater the measured distance from a target, the less the probability that the measurement belongs to that target, the probability of the affiliation between the common echo and each target is inversely related to the distance, and the echoes should all be assigned to their associated targets;
a4, utilizing echo formula to make them be between every targetThe association probability of the public echo obtained in the first step is corrected to obtain new association probability beta 'between the public echo and each related target' jt
A5, normalizing the interconnection probabilities of all measurements in the association gate where each target is located to obtain beta' jt ：
A6, utilizing the association probability beta' jt The update state of all the measurement data in each target is carried out through the weighting process, the update state of the overlapped features is determined through the extraction of the overlapped features, and therefore the choice of the overlapped features is determined, and therefore useful measurement data can be selected according to the extracted features, and the situation that proper data cannot be selected due to more data is avoided.
The specific method for the three-dimensional generating unit to perform three-dimensional modeling comprises the following steps:
b1, creating an axis network, elevation and a reference plane;
b2, creating a main body structure, wherein the main body structure creating further comprises:
performing foundation creation with reference to the foundation size;
creating a column structure, namely naming columns with different sections of the structural column according to drawing numbers;
a housing creation including input device accessory material, and various housing parameters;
establishing a beam, wherein after the size of the longitudinal section of the beam is determined, modeling and drawing are carried out along an axis;
board creation, wherein the board creation is created by extracting boundaries from walls;
and (5) creating a surface.
Working principle: when the method is used, the equipment accessory measurement data are acquired through the information acquisition unit, the data acquired through the information acquisition unit are subjected to data adjustment through the data processing unit, so that the data are convenient to use, the processed multi-source data are integrated through the multi-source information integration unit, the three-dimensional model is generated through the three-dimensional generation unit, the three-dimensional model generated through the three-dimensional generation unit and the data processed through the data processing unit are displayed through the display unit, meanwhile, the update state of the overlapping characteristics is determined through the multi-source information integration unit, the selection and the rejection of the overlapping characteristics are determined, useful measurement data can be selected according to the extracted characteristics, and the situation that proper data cannot be selected due to more data is avoided.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the invention, which is defined by the appended claims.
Claims (7)
1. The engineering mechanical equipment accessory management system is characterized by comprising a data processing unit, an information acquisition unit, a multi-source information integration unit, a three-dimensional generation unit and a display unit:
the information acquisition unit is used for acquiring equipment accessory measurement data;
the data processing unit is used for carrying out data adjustment on the data acquired by the information acquisition unit so that the data is convenient to use;
the multi-source information integration unit is used for integrating the data processed by the data processing unit, so that multiple data can be conveniently used in combination;
the three-dimensional generation unit is used for generating a three-dimensional model from the data integrated by the multi-source information integration unit;
the display unit is used for displaying the data processed by the data processing unit and the three-dimensional model generated by the three-dimensional generating unit.
2. The accessory management system of an engineering machine of claim 1, wherein the information acquisition unit comprises:
the laser measuring module is used for measuring the internal environment data of the equipment accessory;
the flatness detection module is used for shooting equipment accessory wall flatness data;
and the radar measurement module is used for measuring foundation data below the soil.
3. The accessory management system of claim 1, wherein the data processing unit adjusts the data collected by the data collection unit including, but not limited to, abnormal data recovery, discarding, filling, replacement, deduplication.
4. A system for managing attachments to an engineering machine according to claim 3, wherein the specific method for the data processing unit to perform data adjustment is:
s1, data screening, wherein the data screening further comprises:
preliminary screening;
threshold value screening;
quality control screening, wherein if the measured parameter data of a certain sampling interval has mutation, the abnormal condition of the group of measured parameters can be considered;
s2, data recovery, wherein the data recovery method further comprises the following steps:
a time-series-based data recovery method, and a time-series data prediction method should be essentially suitable for recovery of measured data;
the data recovery method based on the space-time correlation is to establish a correlation model of any measured data and other measured data in space-time, and then recover abnormal data through the other measured data.
5. The accessory management system of claim 2, wherein the multi-source information integration unit includes:
the feature screening module is used for screening features in the measurement data;
the same feature extraction module is used for extracting the same features screened by the feature screening module;
the abnormal feature extraction module is used for extracting the abnormal features screened by the feature screening module;
the overlapped feature extraction module is used for extracting the overlapped features screened by the feature screening module;
and the feature fusion unit is used for carrying out feature fusion on the corresponding features extracted by the same feature extraction module, the abnormal feature extraction module and the overlapped feature extraction module.
6. The accessory management system of claim 5, wherein the specific method for extracting overlapping features by the multi-source information integration unit is as follows:
a1, calculating all measurement data j (j epsilon Z) in each target T (t=1, 2,.. t (k) Associated probability beta) with target t jt ；
A2, constructing a confirmation matrix, and judging whether the measurement is public measurement belonging to a plurality of targets according to the confirmation matrix, wherein the expression of the confirmation matrix is as follows:
a3, calculating the probability of the affiliation between the public echo and each target, and calculating the probability of the public echo and each target T (T epsilon T) assuming a target set T and a public echo j M ) Euclidean distance d between jt Because the greater the measured distance from a target, the less the probability that the measurement belongs to that target, the probability of the affiliation between the common echo and each target is inversely related to distance, and the echoes should all be assigned to their associated targets, the affiliation probability is
A4, correcting the association probability of the public echo obtained in the first step by utilizing the affiliation probability between the echo formula and each target, thereby obtaining new association probability beta 'between the public echo and each related target' jt ，
A5, normalizing the interconnection probabilities of all measurements in the association gate where each target is located to obtain beta' jt ，
A6, utilizing the association probability beta' jt The state is updated by weighting all the metrology data within each target.
7. The accessory management system of engineering machinery equipment according to claim 1, wherein the specific method for three-dimensional modeling by the three-dimensional generating unit is as follows:
b1, creating an axis network, elevation and a reference plane;
b2, creating a main body structure, wherein the main body structure creating further comprises:
performing foundation creation with reference to the foundation size;
creating a column structure, namely naming columns with different sections of the structural column according to drawing numbers;
a housing creation including input device accessory material, and various housing parameters;
establishing a beam, wherein after the size of the longitudinal section of the beam is determined, modeling and drawing are carried out along an axis;
board creation, wherein the board creation is created by extracting boundaries from walls;
and (5) creating a surface.
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