CN113760913B - Elasticity-extensible equipment cost acquisition method - Google Patents
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Abstract
The invention discloses an elastic extensible equipment cost acquisition method, which is oriented to equipment component objects and standardized cost decomposition structures of different levels, constructs an equipment cost acquisition overall frame and sets a cost acquisition template; establishing a multi-level equipment system structure data system, and automatically establishing a summary calculation relation between data layers; setting a data acquisition item set on different levels of the expense decomposition structure, and defining an attribute set of the data acquisition item; according to metadata and data standards, setting data formats, content norms and verification rules of data acquisition items, performing data conversion processing on nonstandard data, and detecting, extracting and marking illegal or abnormal data. The method can effectively solve the problems of structural management, evaluation and analysis of the multi-level multidimensional expense data of the equipment, reduce the difficulty of the economic demonstration personnel in collecting and reorganizing the expense data of the equipment, and improve the evaluation and analysis efficiency of the economic data of the equipment.
Description
Technical Field
The invention relates to a data acquisition method, in particular to an elastically extensible equipment cost acquisition method.
Background
Under the new technological transformation trend of intelligent equipment manufacturing, the digital cost management of the traditional equipment manufacturing process becomes a vital link of current industrial upgrading and future industrial 4.0 development process. In the traditional process of equipment manufacturing production, the economic design of equipment is weak, an efficient technical means is lacked, the support economy analysis and design are matched with the digital production process, and the processes of investment management, cost control, cost management and the like of large-scale equipment can be promoted to follow the industrial development.
A set of generalized and elastically expandable equipment cost data acquisition method is established, and the data resources under long-term span can be integrated in a concentrated manner, so that the basic requirement of data resource development is met. Meanwhile, the method is suitable for compatibility and inclusion of data contents with different levels and different granularities, and effectively solves the problems of difficult manual operation, low efficiency, single means and the like of the expense data acquisition service in a complex data environment.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the equipment cost acquisition method which is reasonable in design and expandable in elasticity. According to the method, a generalized data acquisition method for different types of equipment is constructed based on a cost decomposition structure of typical equipment types according to acquisition management requirements of mass equipment cost data, and flexible and extensible equipment cost data generalized acquisition process management and high-efficiency support are realized.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
an elastic expandable equipment cost acquisition method is characterized by comprising the following steps:
firstly, referring to standardized expense decomposition structures of equipment component objects of different layers in an equipment composition structure based on equipment characteristics, constructing an equipment expense acquisition overall framework, and setting expense acquisition templates of all layers of subsystems or components;
secondly, building an equipment composition structure to form a multi-level equipment system structure data system, and automatically building a summarizing calculation relation between data layers by the system;
thirdly, setting a data acquisition item set on different levels of the expense decomposition structure, and defining an attribute set of the data acquisition item;
fourth, according to metadata and data standards, setting data format, content paradigm and verification rule of data acquisition items, performing data conversion processing on nonstandard data, and detecting, extracting and marking illegal or abnormal data.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the first step, the standardized expense decomposition structure is quoted based on equipment characteristics for equipment component objects of different levels in the equipment composition structure, an equipment expense acquisition overall frame is constructed, and expense acquisition templates of subsystems or components of each level are set, wherein the steps are as follows:
(1) Matching standardized expense decomposition structure
Based on the composition structure and performance index of the equipment, the system or the equipment, extracting the characteristic information of the equipment, matching with the standardized cost decomposition structure of the equipment, and processing rules comprise the following contents:
a) Extracting component structure information of equipment, a system or equipment;
b) Extracting performance index information of equipment, a system or equipment;
c) The system composition information and the performance index information are brought into a unified feature space, and equipment features are extracted;
d) And carrying out relevance search on the characteristic information of the equipment, the system or the equipment and the standardized expense decomposition structure database content to find a matching result.
And finally, reading the matched equipment standardized expense decomposition structure into a user display interface.
(2) Set fee collection template
According to the hierarchical structure formed by the equipment systems, setting a cost acquisition template of each hierarchical subsystem or component, and constructing an equipment cost acquisition frame, wherein the processing rules mainly comprise the following contents:
a) Traversing and setting a cost acquisition template of each subsystem and equipment step by step according to an equipment composition structure;
b) Selecting a proper expense subject set for the attributes of different systems;
c) And establishing a nested expense acquisition structure according to the hierarchical integration relation of equipment, systems and equipment to form a tree-shaped data acquisition framework.
And storing the tree data acquisition framework formed after the processing in a cost acquisition database, and uniformly managing the data versions.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the second step, the equipment composition structure is established to form a multi-level equipment system structure data system, and the system automatically establishes the summarized calculation relation between the data layers:
(1) Establishing multi-level equipment composition structure
On the basis of the equipment standardized expense decomposition structure, according to the structural characteristics of equipment of different types, the equipment composition structure is longitudinally thinned and transversely expanded to form multi-level equipment composition structure data, and the steps are as follows:
a) Based on the common equipment composition structure provided by the standardized expense decomposition structure, expanding the personalized system units of the supplementary equipment, and establishing tree structure information of the primary system;
b) Based on the primary system, the secondary system composition structure provided by the expense decomposition structure is combined to longitudinally refine the secondary system structure information;
c) The three-level equipment level structure information is further refined.
(2) Establishing a multi-level data summarization relationship
According to the structural data of the multi-level equipment, the data are collected step by step upwards to form a data summarizing calculation rule, and the steps are as follows:
a) Traversing subset data of the three-level system to form a collection calculation rule of unit cost of the three-level system;
b) Traversing all three-level subsystem data of the secondary system to form a collection calculation rule of the unit cost of the secondary system;
c) Traversing all secondary subsystem data of the primary system to form a collection calculation rule of primary system unit cost;
d) And binding the cost collection calculation formulas of the system or equipment units of each level into the attribute data sets of the corresponding data units of the cost collection templates.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the third step, the data acquisition item set is set on different levels of the expense decomposition structure, the attribute set of the data acquisition item is defined, and the processing steps are as follows:
(1) Setting a collection of data acquisition items
Based on the fee subject set selected by each device in the fee collection framework, configuring data collection items item by item, and supporting expansion of the data collection items, wherein the processing rule mainly comprises the following contents:
a) Setting the data acquisition item content of the expense items item by item according to the selected expense item collection of different systems in the equipment expense decomposition structure;
b) Loading default data acquisition item configuration information in a template according to different expense subject types;
c) Support extended supplementation of data collection items outside of the template.
(2) Defining a set of attributes for a data collection item
For the data acquisition items which are defined, defining attribute information of the data acquisition items, and meeting the control requirement on the data quality of the acquisition process, wherein the processing rule mainly comprises the following contents:
a) Loading a default data acquisition item attribute set in a template from metadata definition;
b) Support expansion supplement or pruning of data acquisition item attributes outside the template;
c) And carrying out formula editing or modification on the cost calculation process of the data acquisition item set.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the fourth step, the data format, the content paradigm and the verification rule of the data acquisition item are set according to metadata and data standards, the data conversion processing is carried out on nonstandard data, and the detection, the extraction and the marking are carried out on illegal or abnormal data, wherein the processing procedures are as follows:
(1) Data rule for setting data acquisition item
For the data acquisition items which are defined, defining data rule information of the data acquisition items, and meeting the control requirement on the data quality of the acquisition process, wherein the processing rule mainly comprises the following contents:
a) Loading a default data rule set of data acquisition items in a template from metadata definition;
b) Supporting the expansion supplement of the data acquisition item rules outside the template;
c) The definition of the rule set of data collection items includes data type, length limitation, content format, verification method, mandatory properties, etc.
(2) Data acquisition process based on data acquisition framework
For the defined data acquisition framework, the data content can be filled item by item or imported in batches, and the processing rules mainly comprise the following contents:
a) When filling data item by item, checking the validity and compliance of the data in real time;
b) For data content which does not accord with the specification, carrying out classification prompt according to the type of the problem;
c) When the batch data is imported, based on a hierarchical structure formed by the system, hierarchical relation matching is carried out on the batch data, batch verification is carried out on the data content, and batch display is carried out on the problem data in a classified mode.
(3) Non-standardized data conversion
Based on the definition of data standard, the non-standardized data is subjected to data perfection or conversion, and can be timely switched between two strategies of human intervention and system autonomy, and the processing rules mainly comprise the following contents:
a) Loading metadata definitions and data standards of the data acquisition items from the metadata definitions;
b) Traversing all data items to find non-standard data;
c) For the definite data conversion rule in the data standard, the system automatically completes the data format conversion;
for undefined semantic data conversion, the conversion is performed under the condition of human intervention.
Compared with the prior art, the invention has the remarkable advantages that:
(1) The method is characterized in that a fee collection template is formed rapidly based on equipment characteristic analysis and matching means;
(2) The innovation provides that a data level summarization calculation rule and a data cross-item association calculation rule are established, so that a complex data auditing calculation rule is formed, and the requirement of automatic cost calculation is met;
(3) Innovative data acquisition quality constraint and automatic conversion processing of non-compliance data are driven based on data attribute definition and data rule definition, so that the execution efficiency and quality of a data acquisition process are greatly improved, and the manual operation difficulty is greatly reduced.
Drawings
FIG. 1 is a flow chart of an elastically extensible equipment cost acquisition method according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Referring to fig. 1, a flexible and scalable equipment cost collection method comprises the steps of:
firstly, referring to standardized expense decomposition structures of equipment component objects of different layers in an equipment composition structure based on equipment characteristics, constructing an equipment expense acquisition overall framework, setting expense acquisition templates of each layer subsystem or component, and performing the following detailed processing steps:
(1) Matching a standardized expense decomposition structure: based on the composition structure and performance index of the equipment, the system or the equipment, the equipment characteristic information is extracted and matched with the standardized cost decomposition structure of the equipment. Firstly, extracting component structure information of equipment, a system or equipment, and extracting performance index information of the equipment, the system or the equipment; the system composition information and the performance index information are brought into a unified feature space, and equipment features are extracted; and carrying out relevance search on the characteristic information of the equipment, the system or the equipment and the standardized expense decomposition structure database content to find a matching result. And finally, reading the matched equipment standardized expense decomposition structure into a user display interface.
(2) Setting a fee collection template: and setting a cost acquisition template of each hierarchical subsystem or component according to the hierarchical structure formed by the equipment systems, and constructing an equipment cost acquisition frame. Firstly, the cost acquisition templates of all subsystems and equipment are traversed step by step according to the equipment composition structure, for the attributes of different systems, a proper cost subject set is selected, and a nested cost acquisition structure is established according to the hierarchical integration relationship of the equipment, the system and the equipment. And storing the tree data acquisition framework formed after the processing in a cost acquisition database, and uniformly managing the data versions.
Secondly, building an equipment composition structure to form a multi-level equipment system structure data system, and automatically building a summary calculation relation between data layers by the system, wherein the detailed steps are as follows:
(1) Establishing a multi-level equipment composition structure: on the basis of the equipment standardized expense decomposition structure, according to the structural characteristics of equipment of different types, the equipment composition structure is longitudinally thinned and transversely expanded to form multi-level equipment composition structure data. Firstly, expanding individual system units of supplementary equipment based on a common equipment composition structure provided by a standardized expense decomposition structure, and establishing tree structure information of a first-level hierarchical system; based on the primary system, the secondary system composition structure provided by the expense decomposition structure is combined to longitudinally refine the secondary system structure information; the tertiary device level structure information is then further refined.
(2) Establishing a multi-level data summarization relation: and according to the structural data of the multi-level equipment, gradually and upwards collecting to form a data summarizing calculation rule. Firstly, traversing subset data of a three-level system to form a collection calculation rule of unit cost of the three-level system; traversing all three-level subsystem data of the secondary system to form a collection calculation rule of the unit cost of the secondary system; traversing all the secondary subsystem data of the primary system to form a collection calculation rule of the primary system unit cost. And binding the cost collection calculation formulas of the system or equipment units of each level into the attribute data sets of the corresponding data units of the cost collection templates.
Third, on different levels of the cost decomposition structure, a data collection item set is set, and an attribute set of the data collection item is defined, wherein the detailed steps are as follows:
(1) Setting a data acquisition item set: based on the fee subject set selected by each device in the fee collection framework, the data collection items are configured item by item, and expansion of the data collection items is supported. Setting the data acquisition item content of the expense items item by item according to the selected expense item collection of different systems in the equipment expense decomposition structure; loading default data acquisition item configuration information in a template according to different expense subject types; while supporting extended supplementation of data acquisition items outside the template.
(2) Defining a set of attributes of the data collection item: and defining attribute information of the data acquisition items aiming at the data acquisition items which are defined, and meeting the control requirement on the data quality of the acquisition process. Loading a default data acquisition item attribute set in a template from metadata definition; support expansion supplement or pruning of data acquisition item attributes outside the template; and carrying out formula editing or modification on the cost calculation process of the data acquisition item set.
Fourth, according to metadata and data standard, data format, content paradigm and check rule of data collection item are set, data conversion processing is carried out on nonstandard data, illegal or abnormal data are detected, extracted and marked, and the detailed steps are as follows:
(1) Setting a data rule of the data acquisition item: and defining data rule information of the data acquisition items aiming at the data acquisition items which are defined, and meeting the control requirement on the data quality of the acquisition process. Loading a default data rule set of data acquisition items in a template from metadata definition; supporting the expansion supplement of the data acquisition item rules outside the template; the definition of the rule set of data collection items includes data type, length limitation, content format, verification method, mandatory properties, etc.
(2) Data acquisition process based on data acquisition framework: for the defined data acquisition framework, the data content can be filled item by item or imported in batches. When filling data item by item, checking the validity and compliance of the data in real time; for data content which does not accord with the specification, carrying out classification prompt according to the type of the problem; when the batch data is imported, based on a hierarchical structure formed by the system, hierarchical relation matching is carried out on the batch data, batch verification is carried out on the data content, and batch display is carried out on the problem data in a classified mode.
(3) Non-normalized data conversion: based on the data standard definition, the non-standardized data is subjected to data perfection or conversion, and the non-standardized data can be timely switched between two strategies of human intervention and system autonomy. Loading metadata definitions and data standards of the data acquisition items from the metadata definitions; traversing all data items to find non-standard data; for the definite data conversion rule in the data standard, the system automatically completes the data format conversion; for undefined semantic data conversion, the conversion is performed under the condition of human intervention.
According to the method, a generalized data acquisition method for different types of equipment is constructed based on a cost decomposition structure of typical equipment types according to acquisition and management requirements of mass equipment cost data. The method comprises the steps of constructing an equipment cost acquisition overall frame facing equipment component objects and standardized cost decomposition structures of different levels, setting a cost acquisition template, establishing a multi-level equipment system structure data system, automatically establishing a summarization calculation relation between data layers, setting data acquisition items and attribute sets, setting data rules according to metadata and data standards, detecting, extracting and marking the data, and automatically collecting summarized cost data to form a multi-level cost summary report. The elastic expandable equipment cost acquisition method can be widely applied to economic analysis and cost management of various types of equipment, effectively solves the problems of structural management and evaluation analysis of multi-level multi-dimensional cost data of the equipment, greatly reduces the difficulty of economic demonstration personnel in acquiring and reorganizing the equipment cost data, and greatly improves the evaluation analysis efficiency of the equipment economic data.
After the method is realized, data analysts can flexibly operate and develop equipment expense data acquisition operation, meet the personalized and elastically expanded equipment expense data acquisition requirements under different service scenes, adapt to the compatibility and inclusion of data contents with different levels and different granularity, and effectively solve the problems of difficult manual operation, low efficiency, single means and the like of the expense data acquisition service under a complex data environment. The data resource preparation and data conversion integration work is automatically processed by a system background, and the whole data processing process is visualized, traceable and controllable, so that the overall requirements of the intelligent manufacturing field of equipment on comprehensive and standardized economic data are met. The elastic expandable equipment cost acquisition method can be applied to application software such as quotation compilation, economic analysis, cost evaluation, cost management and control, investment evaluation and the like in the equipment manufacturing industry through proper modification and expansion.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (3)
1. An elastically extensible equipment cost acquisition method is characterized by comprising the following steps:
firstly, referring to standardized expense decomposition structures of equipment component objects of different layers in an equipment composition structure based on equipment characteristics, constructing an equipment expense acquisition overall framework, and setting expense acquisition templates of all layers of subsystems or components; the method comprises the following steps:
(1) Matching standardized expense decomposition structure
Based on the composition structure and performance index of the equipment, the system or the equipment, extracting the characteristic information of the equipment, matching with the standardized cost decomposition structure of the equipment, and processing rules comprise the following contents:
extracting component structure information of equipment, a system or equipment;
extracting performance index information of equipment, a system or equipment;
the component structure information and the performance index information are brought into a unified feature space, and equipment features are extracted;
carrying out relevance search on equipment characteristics and the content of the equipment standardized expense decomposition structure database, and searching for a matching result;
finally, reading the matched equipment standardized expense decomposition structure into a user display interface;
(2) Set fee collection template
According to the hierarchical structure formed by the equipment systems, setting a cost acquisition template of each hierarchical subsystem or component, and constructing an equipment cost overall acquisition framework, wherein the processing rules comprise the following contents:
traversing and setting a cost acquisition template of each subsystem or component step by step according to an equipment composition structure;
selecting corresponding cost subject sets for attributes of different systems;
according to the hierarchical integration relationship of equipment, systems and equipment, a nested expense acquisition structure is established to form a tree-shaped data acquisition frame;
storing the tree data acquisition frame formed after processing in a fee acquisition database, and uniformly managing the data versions;
secondly, building an equipment composition structure to form a multi-level equipment system structure data system, and automatically building a summarizing calculation relation between data layers by the system;
(1) Establishing multi-level equipment composition structure
On the basis of the equipment standardized expense decomposition structure, according to the structural characteristics of equipment of different types, the equipment composition structure is longitudinally thinned and transversely expanded to form multi-level equipment composition structure data, and the steps are as follows:
based on the common equipment composition structure provided by the standardized expense decomposition structure, expanding the personalized system units of the supplementary equipment, and establishing tree structure information of the primary system;
based on the primary system, the secondary system composition structure provided by combining the standardized expense decomposition structure is longitudinally thinned;
further refining the three-level equipment level structure information;
(2) Establishing a multi-level data summarization relationship
According to the structural data of the multi-level equipment, the data are collected step by step upwards to form a data summarizing calculation rule, and the steps are as follows:
traversing subsystem data of the three-level system to form a collection calculation rule of unit cost of the three-level system;
traversing all three-level subsystem data of the secondary system to form a collection calculation rule of the unit cost of the secondary system;
traversing all secondary subsystem data of the primary system to form a collection calculation rule of primary system unit cost;
binding the cost collection calculation rules of the system or the equipment units of each level into the attribute data sets of the corresponding data units of the cost collection templates;
thirdly, setting a data acquisition item set on different levels of the expense decomposition structure, and defining an attribute set of the data acquisition item;
fourth, according to metadata and data standards, setting data format, content paradigm and verification rule of data acquisition items, performing data conversion processing on nonstandard data, and detecting, extracting and marking illegal or abnormal data.
2. The flexible and extensible equipment fee collection method according to claim 1, wherein in the third step, at different levels of the fee decomposition structure, a set of data collection items is set, and a set of attributes of the data collection items is defined, and the processing steps are as follows:
(1) Setting a collection of data acquisition items
Based on the fee subject set selected by each device in the fee collection overall framework, configuring data collection items item by item, and supporting expansion of the data collection items, wherein the processing rules comprise the following contents:
setting the data acquisition item content of the expense items item by item according to the selected expense item collection of different systems in the equipment expense decomposition structure;
loading default data acquisition item configuration information in a fee acquisition template according to different fee subject types;
supporting expansion supplement of data acquisition items outside the expense acquisition template;
(2) Defining a set of attributes for a data collection item
For the data acquisition items which are defined, defining attribute information of the data acquisition items, and meeting the control requirement on the data quality of the acquisition process, wherein the processing rule comprises the following contents:
loading a default data acquisition item attribute set in a fee acquisition template from metadata definition;
support expanded supplement or deletion of data acquisition item attributes outside of the fee acquisition template;
and carrying out formula editing or modification on the cost calculation process of the data acquisition item set.
3. The flexible and extensible equipment cost collecting method according to claim 1, wherein in the fourth step, according to metadata and data standards, data format, content paradigm and verification rules of data collection items are set, data conversion processing is performed on nonstandard data, illegal or abnormal data is detected, extracted and marked, and the processing process is as follows:
(1) Data rule for setting data acquisition item
For the data acquisition items which are defined, defining data rule information of the data acquisition items, and meeting the control requirement on the data quality of the acquisition process, wherein the processing rule comprises the following contents:
loading a data rule set of a default data acquisition item in a fee acquisition template from metadata definition;
supporting the expansion and supplement of the rules of the data acquisition items outside the expense acquisition template;
the definition of the rule set of the data acquisition item comprises data types, length limitation, content formats, verification methods and mandatory properties;
(2) Data acquisition process based on data acquisition framework
For the defined data acquisition framework, filling data contents item by item or importing data contents in batches, wherein the processing rules comprise the following contents:
when filling data item by item, checking the validity and compliance of the data in real time;
for data content which does not accord with the specification, carrying out classification prompt according to the type of the problem;
when the batch data is imported, based on a hierarchical structure formed by the system, hierarchical relation matching is carried out on the batch data, batch verification is carried out on the data content, and problem data is classified and displayed in batches;
(3) Non-standardized data conversion
Based on the data standard definition, carrying out data perfection or conversion on non-standardized data, and timely switching in two strategies of human intervention and system autonomy, wherein the processing rules comprise the following contents:
loading metadata definitions and data standards of the data acquisition items from the metadata definitions;
traversing all data items to find non-standard data;
for the definite data conversion rule in the data standard, the system automatically completes the data format conversion;
for undefined semantic data conversion, the conversion is performed under the condition of human intervention.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012094017A1 (en) * | 2011-01-07 | 2012-07-12 | Co-Exprise, Inc. | Total cost management system, method, and apparatus |
| CN111815424A (en) * | 2020-07-09 | 2020-10-23 | 北京中百信信息技术股份有限公司 | Information system engineering supervision project cost accounting management system |
| CN111950922A (en) * | 2020-08-20 | 2020-11-17 | 江苏杰瑞信息科技有限公司 | Equipment economic data evaluation method based on multi-source data interaction analysis |
| CN112950164A (en) * | 2020-07-09 | 2021-06-11 | 北京中百信信息技术股份有限公司 | Information system engineering supervision working hour recording information system based on standardized rules |
-
2021
- 2021-09-03 CN CN202111034136.0A patent/CN113760913B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012094017A1 (en) * | 2011-01-07 | 2012-07-12 | Co-Exprise, Inc. | Total cost management system, method, and apparatus |
| CN111815424A (en) * | 2020-07-09 | 2020-10-23 | 北京中百信信息技术股份有限公司 | Information system engineering supervision project cost accounting management system |
| CN112950164A (en) * | 2020-07-09 | 2021-06-11 | 北京中百信信息技术股份有限公司 | Information system engineering supervision working hour recording information system based on standardized rules |
| CN111950922A (en) * | 2020-08-20 | 2020-11-17 | 江苏杰瑞信息科技有限公司 | Equipment economic data evaluation method based on multi-source data interaction analysis |
Non-Patent Citations (2)
| Title |
|---|
| Shibiao Chen，L. Ken Keys.《Computers & Industrial Engineering》.2009,第56卷(第4期), 第1276-1288页. * |
| 武器装备全寿命费用分析及管理措施研究;任少龙, 曲东才, 何友, 钟秋海;火力与指挥控制(第03期);全文 * |
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