CN111857092A - Real-time error detection system and method for household parametric model - Google Patents
Real-time error detection system and method for household parametric model Download PDFInfo
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Abstract
The invention discloses a real-time error detection system and a real-time error detection method for a home parameterized model. The invention provides a set of real-time error detection method for parametric modeling based on the structure and the modeling method of the parametric model, which not only can detect and check errors and non-normative parts in the modeling process of the parametric model in real time, but also has the characteristics of accurately positioning error reasons and error positions, dynamically adjusting error levels, continuously iterating, facilitating expansion and the like, greatly improves the modeling efficiency and user experience, and also improves the cognition of users on modeling specifications; through the definition of the checker, error detection can be iterated continuously and detection content is enriched; the dynamic adjustment of the application error level can deal with different application scenes at any time.
Description
Technical Field
The invention relates to the field of information technology, in particular to a real-time error detection system and a real-time error detection method for a home parametric model.
Background
With the rapid development of informatization construction, the informatization and various industries are more closely integrated, and the information system plays more and more obvious roles in various business fields. The error detection system is an important means for ensuring the continuous safe and stable operation of the information system, can prevent the information system from being affected in the bud and avoids serious loss. At present, error detection technologies such as text detection, voice detection, security detection and the like are widely applied to informatization construction of industries such as medical treatment, finance and the like.
Parametric modeling is a computer aided design method which is gradually dominant in the end of the 80 s of the 20 th century, and is an important process of parametric design. In practice parametric modeling is part of the parametric design, which is usually prepared for further parametric design, model production. A parameterized model of the real-world object is constructed through a parameterized modeling tool, and the parameterized model is not only consistent with the three-dimensional appearance of the real-world object, but also provided with a complete information base consistent with the actual object.
A parameterized model is composed of the following modules: parameter system, component system. The creation of any one parameter supports multiple parameter types and value types; the parameter type can be a shaping type, a floating point type, a character string, a Boolean type, a multi-Boolean type, a material, an outline, a style and the like, and the value type can be an interval, an increment, a fixed value, a formula, a compound formula and the like. The parameters can be directly created on the model in the modeling process or can be created in a global parameter list. The already created parameters can then be set as parameter templates. Then these parameters can be taken from the global parameter list or from the template parameter list for direct use in modeling. Another special source of parameters we call reporting parameters: the parameters of the child component are recorded on the parent model.
Sources of the subcomponents: 1. directly added from the basic elements, wherein the basic elements comprise basic parameterized models and auxiliary structures. Wherein the basic parameterized model comprises: the form plates, lofts, grids, spline curves, etc. may be parametric models of various bases that are pre-added to the system with specific parameters. The auxiliary structures include some structures for auxiliary design and production, such as contour restrictions, straight line absorption lines, right angle absorption lines, hollows, door openings, interference areas, pipe connections, and the like. 2. Already built parameterized models can be used. The sub-component may set a reference name, such as: c, so that other children and parent models can get the W parameter of the C part through @ C.W. Thereby achieving the purpose of transferring parameters between the components and transferring the parameters from bottom to top.
Constructing a parameterized model: adding parameters and adding sub-components and controlling the dependent relationship between the parameters and the parameter dependent relationship between the components through expressions.
Based on the above description of the parameterized model, the parameters of the parameterized model are expressions, and tree structures are arranged between model components. All possible modifications in the modeling process may result in model errors or model non-compliance, failure to calculate the geometry of the model or non-compliance with expectations, etc. There are but not limited to the following errors in the modeling process: parameter value error, parameter minimum value error, parameter maximum value minimum value range error, parameter selectable value error, parameter recommended value error, parameter reference name repeat, reference name grammar error, reference name occupied by system, parameter circular reference, custom variable unable to reference intermediate variable, intermediate variable circular reference, attribute error, value unable to be negative, value unable to be null, value too small, value too large, value range error, intermediate variable error, reference name grammar not meeting the specification, part circular reference, part reference name repeat, part self-reference, commodity deleted, commodity information error, part number overrun, array number overrun, reference unknown parameter.
Error detection is also needed in the engineering home parametric modeling system, and modeling errors and modeling modes which are not in accordance with the specifications are prompted in real time, so that the modeling efficiency and the user experience are improved.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a real-time error detection system and a real-time error detection method for a home parametric model.
The purpose of the invention is achieved by the following technical scheme: the real-time error detection system of the home parameterized model mainly comprises a constructor module, a verification driver module, a verifier registration center, a verification context and an exception handler, wherein the constructor module is realized by using reflection and a tree structure, supports any type of object and converts the object into the verification tree structure; the check driver uses depth traversal on the check tree, acquires a checker of a certain node from the registration center and checks the node; the checker registration center registers various checkers; the checker is divided into an object checker and a dependent checker, each checker comprises a supported check object type and a check method, the check of the object and the dependent check are split, and each checker has specific check capability; the exception handler provides a method for throwing the exception for the checker, and sorts the check result.
The object checker comprises a grammar checker, a trinocular operation checker, an entry checker, an intermediate variable checker, an attribute checker, a report variable checker, an environment variable checker, a component checker, a basic model checker, a combined checker, a space checker and various value type checkers.
The dependency checker comprises an entry dependency checker, an intermediate variable dependency checker, a report variable dependency checker, an attribute dependency checker and a component dependency checker.
The real-time error detection method of the home parameterized model mainly comprises the following steps:
1) inputting a real-time constructed parameterized model;
2) constructing data required by verification, namely verifying context;
3) constructing a check tree structure according to the parameterized model tree structure;
4) deeply traversing each node of the check tree, searching a checker supporting the check of the node for each check node, and executing the checker;
5) executing each checker, checking the object to be checked according to the checking context, the grammar logic, the modeling rule and the like, and calling an exception handler to process when the object to be checked is not in accordance with expectation;
6) and the exception handler processes the checking result, acquires the detailed information of the error code from the error configuration library according to the error code, sorts the information and returns the information.
The check context includes all parameter names, all intermediate variable names, commodity, all supported function names, and component reference names.
Each check node for constructing the check tree class structure comprises a checked object, an object type, a parent node, a child node and a current path.
The detailed information of the error code comprises an error description, an error level and an error path.
The invention has the beneficial effects that: the invention provides a set of real-time error detection method for parametric modeling based on the structure and the modeling method of the parametric model, which not only can detect and check errors and non-normative parts in the modeling process of the parametric model in real time, but also has the characteristics of accurately positioning error reasons and error positions, dynamically adjusting error levels, continuously iterating, facilitating expansion and the like, greatly improves the modeling efficiency and user experience, and also improves the cognition of users on modeling specifications; through the definition of the checker, error detection can be iterated continuously and detection content is enriched; the dynamic adjustment of the application error level can deal with different application scenes at any time.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
FIG. 2 is a schematic view of the detection process of the present invention.
FIG. 3 is a schematic diagram of a value type checking process according to the present invention.
Detailed Description
The invention will be described in detail below with reference to the following drawings:
as shown in the attached drawings, the real-time error detection system of the home parameterized model divides an error detection module into: a constructor module, a check driver module, a checker registry, a check context, and an exception handler.
A constructor module: the module supports any type of object and converts the object into a check tree structure by using reflection and tree structure implementation.
Verifying the driver: and (4) performing deep traversal on the check tree, acquiring a checker of a certain node from the registration center and checking the node.
The verifier registry: various verifiers are registered.
The checker: and the method is divided into an object checker and a dependent checker. Each verifier contains supported verification object types and verification methods. The checksum dependent check of the object is split. Each verifier has a specific verification capability. The object checker comprises but is not limited to a grammar checker, a trinocular operation checker, an entry checker, an intermediate variable checker, an attribute checker, a report variable checker, an environment variable checker, a component checker, a basic model checker, a combined checker, a space checker and various value type checkers; dependent checkers include, but are not limited to: an entry dependency checker, an intermediate variable dependency checker, a report variable dependency checker, an attribute dependency checker, and a component dependency checker.
An exception handler: and providing a method for throwing the exception for the checker, and sorting the check result.
The invention also discloses a real-time error detection method of the household parametric model, which mainly comprises the following steps:
1) inputting a real-time constructed parameterized model;
2) constructing data required by verification, namely a verification context, including all parameter names, all intermediate variable names, commodities, all supported function names, part reference names and the like;
3) constructing a check tree class structure according to the parameterized model tree structure, wherein each check node comprises a checked object, an object type, a father node, a child node, a current path and the like;
4) deeply traversing each node of the check tree, searching a checker supporting the check of the node for each check node, and executing the checker;
5) executing each checker, checking the object to be checked according to the checking context, the grammar logic, the modeling rule and the like, and calling an exception handler to process when the object to be checked is not in accordance with expectation;
6) and the exception handler processes the checking result, acquires detailed information of the error code from the error configuration library according to the error code, wherein the detailed information comprises error description, error level, error path and the like, arranges the information and returns the information.
The application example of the invention is as follows:
1) inputting a parameterized model M:
m contains the custom variable a ═ 50, B ═ a + 50; the intermediate variable C ═ B × 2;
subcomponent Component1, Component2, where the attribute H of Component1 is # C + pp;
report variable R ═ compositent1. h;
2) and (3) constructing a context required by verification:
self-defining variables { B, A }; an intermediate variable { C }; part name { Component1, Component2 };
all supported operators and functions { +, -,/, max, average, min, sqrt, etc };
3) constructing a check tree using reflection according to the parameterized model tree structure;
4) and deeply traversing the first-level custom variable nodes of the check tree, and judging that the nodes are the arrays of the custom variables. The method comprises the steps of obtaining a dependency relationship of a custom variable dependency checker to the custom variable, establishing a dependency graph B- > A, adjusting the sequence of the custom variable to be { A, B }, wherein cyclic reference is avoided;
5) deeply traversing each custom variable in the array of custom variables, and acquiring a custom variable checker:
when the analysis result is 50, the verification is passed, and writing 50 in the verification context;
b ═ a +50, take out a ═ 50 from the check context and replace, resolve B ═ 100, check pass, and write B ═ 100 into the check context;
6) Traversing to an intermediate variable, checking the dependency relationship, checking C, resolving C into 200, and writing C into a check context, wherein C is 200;
7) traversing Component1, resolving to its attribute H, H can't resolve, using exception handler to throw interrupt exception, ERROR coding as VALUE _ PARSA _ ERROR, path as [ Components [0], Parameters [1] ];
8) and taking out the abnormal configuration, wherein the error information is 'attribute error' and the error level is 'error', and adding an error path [ Components [0], Parameters [1] ] to return.
It should be understood that equivalent substitutions and changes to the technical solution and the inventive concept of the present invention should be made by those skilled in the art to the protection scope of the appended claims.
Claims (7)
1. A real-time error detection system of a home parameterized model is characterized in that: the system mainly comprises a constructor module, a verification driver module, a verifier registration center, a verification context and an exception handler, wherein the constructor module is realized by using reflection and a tree structure, supports any type of object and converts the object into a verification tree structure; the check driver uses depth traversal on the check tree, acquires a checker of a certain node from the registration center and checks the node; the checker registration center registers various checkers; the checker is divided into an object checker and a dependent checker, each checker comprises a supported check object type and a check method, the check of the object and the dependent check are split, and each checker has specific check capability; the exception handler provides a method for throwing the exception for the checker, and sorts the check result.
2. The real-time error detection system of the home parametric model according to claim 1, wherein: the object checker comprises a grammar checker, a trinocular operation checker, an entry checker, an intermediate variable checker, an attribute checker, a report variable checker, an environment variable checker, a component checker, a basic model checker, a combined checker, a space checker and various value type checkers.
3. The real-time error detection system of the home parametric model according to claim 1, wherein: the dependency checker comprises an entry dependency checker, an intermediate variable dependency checker, a report variable dependency checker, an attribute dependency checker and a component dependency checker.
4. A real-time error detection method of a home parameterized model is characterized by comprising the following steps: the method mainly comprises the following steps:
1) inputting a real-time constructed parameterized model;
2) constructing data required by verification, namely verifying context;
3) constructing a check tree structure according to the parameterized model tree structure;
4) deeply traversing each node of the check tree, searching a checker supporting the check of the node for each check node, and executing the checker;
5) Executing each checker, checking the object to be checked according to the checking context, the grammar logic and the modeling rule, and calling an exception handler to process when the object to be checked is not in accordance with expectation;
6) and the exception handler processes the checking result, acquires the detailed information of the error code from the error configuration library according to the error code, sorts the information and returns the information.
5. The real-time error detection method of the home parametric model according to claim 4, wherein: the check context includes all parameter names, all intermediate variable names, commodity, all supported function names, and component reference names.
6. The real-time error detection method of the home parametric model according to claim 4, wherein: each check node for constructing the check tree class structure comprises a checked object, an object type, a parent node, a child node and a current path.
7. The real-time error detection method of the home parametric model according to claim 4, wherein: the detailed information of the error code comprises an error description, an error level and an error path.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113742805A (en) * | 2021-08-24 | 2021-12-03 | 杭州群核信息技术有限公司 | Interaction method, interaction device, computer readable storage medium and processor |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5363320A (en) * | 1990-12-14 | 1994-11-08 | Tektronix, Inc. | Automatic compilation of model equations into a gradient based analog simulator |
| JP2006059108A (en) * | 2004-08-19 | 2006-03-02 | Mitsubishi Electric Corp | Support system for development test of information system |
| JP2007041677A (en) * | 2005-08-01 | 2007-02-15 | Nec Corp | Policy type management device and method, and program |
| CN101438249A (en) * | 2006-05-07 | 2009-05-20 | 应用材料股份有限公司 | Ranged fault signatures for fault diagnosis |
| US20100125758A1 (en) * | 2008-11-17 | 2010-05-20 | Microsoft Corporation | Distributed system checker |
| CN102656592A (en) * | 2010-02-16 | 2012-09-05 | 松下电器产业株式会社 | Information processing device, information processing system, software routine execution method, and remote attestation method |
| CN103077093A (en) * | 2013-01-14 | 2013-05-01 | 山东电力集团公司 | Substation configuration description (SCD) calibration method based on model objectification semantics |
| KR20150052725A (en) * | 2013-11-06 | 2015-05-14 | 주식회사 엘지씨엔에스 | Method of verifying modeling code, apparatus performing the same and storage media storing the same |
| US20150256556A1 (en) * | 2013-03-05 | 2015-09-10 | Bot Or Not, Llc | Method and system for web integrity validator |
| CN108155717A (en) * | 2017-03-16 | 2018-06-12 | 国网福建省电力有限公司厦门供电公司 | The anti-error methods of calibration of distribution main website FA based on operation of power networks data |
| CN108170404A (en) * | 2017-12-25 | 2018-06-15 | 南京航空航天大学 | A kind of Web service combination verification method based on parameterized model |
| CN108345739A (en) * | 2018-02-08 | 2018-07-31 | 国家电网公司 | Recognize the method that CIME and SVG model file information realizations protection definite value on-line testing function obtains model |
| US20190204814A1 (en) * | 2016-05-24 | 2019-07-04 | Siemens Aktiengesellschaft | System and Method for Visualizing and Validating Process Events |
| JP2019117556A (en) * | 2017-12-27 | 2019-07-18 | キヤノン株式会社 | Information processing apparatus, information processing method and program |
| WO2019153544A1 (en) * | 2018-02-12 | 2019-08-15 | 平安科技（深圳）有限公司 | Annotation backend check method and apparatus, computer device and storage medium. |
| CN110275505A (en) * | 2018-03-14 | 2019-09-24 | 欧姆龙株式会社 | Abnormality detection system supports device and model generating method |
| CN110489853A (en) * | 2019-08-15 | 2019-11-22 | 杭州群核信息技术有限公司 | A kind of modeling method of household parameterized model |
| CN111260071A (en) * | 2018-11-30 | 2020-06-09 | 上海寒武纪信息科技有限公司 | Method, device and storage medium for analyzing universal machine learning model file |
| CN111273635A (en) * | 2020-01-19 | 2020-06-12 | 浙江大学 | Unknown anomaly detection method for industrial control equipment |
-
2020
- 2020-06-22 CN CN202010572427.4A patent/CN111857092B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5363320A (en) * | 1990-12-14 | 1994-11-08 | Tektronix, Inc. | Automatic compilation of model equations into a gradient based analog simulator |
| JP2006059108A (en) * | 2004-08-19 | 2006-03-02 | Mitsubishi Electric Corp | Support system for development test of information system |
| JP2007041677A (en) * | 2005-08-01 | 2007-02-15 | Nec Corp | Policy type management device and method, and program |
| CN101438249A (en) * | 2006-05-07 | 2009-05-20 | 应用材料股份有限公司 | Ranged fault signatures for fault diagnosis |
| US20100125758A1 (en) * | 2008-11-17 | 2010-05-20 | Microsoft Corporation | Distributed system checker |
| CN102656592A (en) * | 2010-02-16 | 2012-09-05 | 松下电器产业株式会社 | Information processing device, information processing system, software routine execution method, and remote attestation method |
| CN103077093A (en) * | 2013-01-14 | 2013-05-01 | 山东电力集团公司 | Substation configuration description (SCD) calibration method based on model objectification semantics |
| US20150256556A1 (en) * | 2013-03-05 | 2015-09-10 | Bot Or Not, Llc | Method and system for web integrity validator |
| KR20150052725A (en) * | 2013-11-06 | 2015-05-14 | 주식회사 엘지씨엔에스 | Method of verifying modeling code, apparatus performing the same and storage media storing the same |
| US20190204814A1 (en) * | 2016-05-24 | 2019-07-04 | Siemens Aktiengesellschaft | System and Method for Visualizing and Validating Process Events |
| CN108155717A (en) * | 2017-03-16 | 2018-06-12 | 国网福建省电力有限公司厦门供电公司 | The anti-error methods of calibration of distribution main website FA based on operation of power networks data |
| CN108170404A (en) * | 2017-12-25 | 2018-06-15 | 南京航空航天大学 | A kind of Web service combination verification method based on parameterized model |
| JP2019117556A (en) * | 2017-12-27 | 2019-07-18 | キヤノン株式会社 | Information processing apparatus, information processing method and program |
| CN108345739A (en) * | 2018-02-08 | 2018-07-31 | 国家电网公司 | Recognize the method that CIME and SVG model file information realizations protection definite value on-line testing function obtains model |
| WO2019153544A1 (en) * | 2018-02-12 | 2019-08-15 | 平安科技（深圳）有限公司 | Annotation backend check method and apparatus, computer device and storage medium. |
| CN110275505A (en) * | 2018-03-14 | 2019-09-24 | 欧姆龙株式会社 | Abnormality detection system supports device and model generating method |
| CN111260071A (en) * | 2018-11-30 | 2020-06-09 | 上海寒武纪信息科技有限公司 | Method, device and storage medium for analyzing universal machine learning model file |
| CN110489853A (en) * | 2019-08-15 | 2019-11-22 | 杭州群核信息技术有限公司 | A kind of modeling method of household parameterized model |
| CN111273635A (en) * | 2020-01-19 | 2020-06-12 | 浙江大学 | Unknown anomaly detection method for industrial control equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113742805A (en) * | 2021-08-24 | 2021-12-03 | 杭州群核信息技术有限公司 | Interaction method, interaction device, computer readable storage medium and processor |
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