CN116109281B - Machine room equipment self-adaptive management system and method based on cloud computing - Google Patents
Machine room equipment self-adaptive management system and method based on cloud computing Download PDFInfo
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Abstract
The invention discloses a cloud computing-based machine room equipment self-adaptive management system and a cloud computing-based machine room equipment self-adaptive management method, and belongs to the technical field of machine room equipment data management. The system comprises an assembly type module, a BIM component management module, a machine room engineering processing module, an auditing port module and a self-adaptive feedback regulation module. The prefabricated equipment room equipment installation system is provided based on cloud computing means, can overcome various defects caused by traditional installation, and improves the installation level in multiple directions such as energy conservation, environmental protection, construction period management, cost control, construction technical quality, safety production and the like. And meanwhile, based on BIM technical management of project display boards in the installation process of prefabricated assembly type machine room equipment, data analysis, warning and intelligent means processing among components are provided.
Description
Technical Field
The invention relates to the technical field of computer room equipment data management, in particular to a computer room equipment self-adaptive management system and method based on cloud computing.
Background
In the current computer lab installation construction, most enterprises still adopt the construction process mode of traditional computer lab, and it takes time and energy to take materials at the job site to carry out manual welding, and raise dust makes ash, and rubbish is many, and the noise is big, and air quality is poor in the computer lab, and safety is difficult to guarantee. Meanwhile, scaffold is still adopted in the construction site, pipelines and welding seams are dense, the quality is difficult to ensure, and the process cost and the progress are difficult to control. Meanwhile, the problems of repeated planning and design, large project cost measuring and calculating gap, high material consumption degree and the like exist.
Along with the continuous development of technology, the installation of prefabricated assembled machine room equipment is gradually known, and as a means for realizing the construction of modern digital buildings, the development difficulty is high, the required technical level is high, and a perfect installation collaborative management system is required to be equipped. Meanwhile, in the whole installation process of prefabricated assembly type machine room equipment, project display boards are required to be constructed in advance according to BIM technology, the project display boards are manufactured according to professional design drawings, manufacturer equipment drawings and parameters, a deepened designer carries out BIM modeling on pipelines, equipment, air pipes, bridges and the like in a station room, modeling data adopts real data, and meanwhile, the actual situation of a site is required to be measured, and deviation between the site size and the drawing size is rechecked; and (5) observing conditions of a site construction channel, a transportation route and the like, determining a hoisting scheme, carrying the channel and the like. In the whole BIM design, detailed component data management needs to be realized through a cloud platform, and at present, no technical management means exists.
Disclosure of Invention
The invention aims to provide a cloud computing-based machine room equipment self-adaptive management system and a cloud computing-based machine room equipment self-adaptive management method, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a machine room equipment self-adaptive management method based on cloud computing comprises the following steps:
s1, constructing a prefabricated equipment installation system of a machine room, creating a position diagram of pre-installed equipment in the machine room, acquiring names of all parts of the pre-installed equipment in the machine room, and generating corresponding BIM components;
s2, creating a machine room engineering structure, wherein the machine room engineering structure comprises node management, data tracking, synchronous components and audit alarm;
s3, under the engineering structure of the machine room, a role login platform with an engineering structure tree management function is created, rights are given to an administrator, an engineering structure tree is created, and management of the engineering structure tree is carried out; the management comprises selecting corresponding BIM components according to the requirements of engineering projects of a machine room, synchronizing the components under an engineering structure tree, and outputting the components to an audit port module;
s4, a sequence early warning unit is arranged in front of the auditing port module, a front analysis model is established by the sequence early warning unit based on historical auditing data, and after the management result of the engineering structure tree passes through the front analysis model, priority analysis is carried out on synchronous components in the engineering structure tree, and the synchronous components are integrated into a component auditing list to be output;
s5, if the examination and approval of the constructed examination and approval list passes, equipment is installed according to the current machine room engineering structure; if the constructed examination list passes the examination, an alarm is fed back to the main page, and after the first-line staff adjusts the position diagram of the pre-installed equipment in the machine room according to the alarm data, the engineering structure of the machine room is re-established and the examination is performed again.
The components are the names of all parts in BIM modeling, and certain naming rules exist, such as C30_300mm of shear wall; building panels 50mm, etc.;
according to the above technical solution, in step S1, the prefabricated equipment room equipment installation system includes:
and (3) creating a pre-installation equipment position diagram in the machine room, obtaining names of all parts of the pre-installation equipment in the machine room, generating corresponding BIM components, utilizing REVIT software, building a machine room equipment engineering BIM model based on the physical size according to the pre-installation equipment position diagram in the machine room on the basis of building information modeling BIM, and synchronizing the BIM model into a machine room engineering structure.
According to the technical scheme, in the steps S2-S3, the node management comprises node names and node types, wherein the node types comprise areas, professions and procedures; the area refers to an installation area of equipment in a machine room corresponding to the current node; the professional finger corresponds to a component of the equipment component of the machine room at the current node; the working procedure refers to a machine room engineering state corresponding to the current node, wherein the state comprises design, production and construction; the design comprises to-be-designed, being designed and being designed to be completed; the production comprises the steps of waiting for production, producing and completing the production; the construction comprises the steps of waiting for construction, constructing and completing the construction;
the data tracking is based on a data cloud platform built by each server in the system, data circulating among the servers are monitored and tracked, a notification function is configured, and when any server fails to timely reply the data, a warning prompt is generated;
the synchronous component marks a corresponding BIM component synchronous with the BIM model of equipment engineering in the machine room, extracts and gathers data of each BIM component, and generates a preliminary audit list;
and (3) checking and measuring the building structure in the machine room by a first-line staff, feeding the measured actual size back to the sequence early warning unit, wherein the checking and warning means to acquire the measured actual size, calculate the difference value between the actual measurement value and the design value, and if the number of the difference items between the actual measurement value and the design value exceeds a set threshold A or the difference value data between the actual measurement value and the design value exceeds a set threshold B, take a preliminary checking list, send the preliminary checking list to the checking port module, and output a warning result according to the checking result of the checking port module, wherein A, B is a system setting constant.
In the technical scheme, the method is generally suitable for rechecking and measuring a building structure after a certain building construction is completed, and because different constructions can lead to fine adjustment of the original construction drawing, BIM component data participating in the construction drawing are required to be continuously checked for many times, so that the deviation value of the whole drawing data is prevented from being gradually increased, and finally a false area is caused in actual construction.
According to the above technical solution, in step S4, the sequence early-warning unit includes:
constructing a pre-analysis model, obtaining a difference value between an actual measured value and a design value, and correspondingly marking the difference value in a data folder of each component;
acquiring association indexes between the components, wherein the association indexes refer to direct connection between any two components, and if the association indexes exist between any two components, the number of the association indexes of each component is increased by 1, and the number of the association indexes of each component is recorded respectively;
normalizing the difference value between the actual measured value and the design value of each component and the number of associated indexes, and calculating the priority value Y=k of each component for the processed data 1 x 1 +k 2 x 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein k is 1 、k 2 Weights respectively representing priority valuesDistributing; x is x 1 、x 2 Normalized values representing the difference between the actual measured value and the design value of each member and the number of associated indexes, respectively;
adjusting the preliminary audit list according to the order of the priority value of each component from large to small, and if the priority values are equal, randomly sequencing to generate a component audit list;
the auditing port carries out auditing treatment on each component according to the component auditing list, and when any component fails to audit, all subsequent components with associated indexes are invoked, and an intelligent analysis model is constructed:
acquiring historical audit data, wherein the historical audit data comprises audit success data and audit failure data, and marking state probability data for each group of audit data, wherein the state probability data refers to the number of the associated index members of each member, which is the number of completed construction, to the number ratio of the total associated index members;
acquiring all subsequent components which are correspondingly called by the components with correlation indexes under the real-time condition and have the correlation indexes, marking the components as a set M, acquiring the states of all the components with the correlation indexes of any component L in the set M, calculating the states as the duty ratio data of the construction completion, marking the states as L 0 ；
Under the condition of successful data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 1 The method comprises the steps of carrying out a first treatment on the surface of the Under the condition of failed audit data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 2 The method comprises the steps of carrying out a first treatment on the surface of the The historical audit data has state probability data less than or equal to L 0 The probability of (2) is denoted as R 3 ；
The prediction probability of the audit failure of the generating component L is P L =（R 1 *R 3 ）/[（R 1 *R 3 ）+R 2 *（1-R 3 ）]；
Setting probability threshold, if P exists L If the probability threshold value is exceeded, the corresponding component L is directly output to an auditing port for preferential auditing;
if the constructed audit list passes the approval, an alarm is fed back to the main page, all audit failure data are recorded into alarm data, and after a first-line staff adjusts a pre-installation equipment position diagram in the machine room according to the alarm data, the machine room engineering structure is re-established, and the machine room engineering structure is audited again.
In the self-adaptive management process of machine room equipment installation, construction drawings are processed by continuously checking the data of BIM components, the checking efficiency is improved by using the association indexes among the components, for example, if a certain component A fails in checking, the corresponding association index component B, C, D is obtained, optionally, a component B is selected, because the association indexes exist between A and B, the checking problem occurs in A, and then the association indexes have larger deviation, so that the intelligent analysis is performed on B, the association index component of the component B is obtained, the states of the association index components are analyzed, nine states are provided, and under the condition that the states are completed, the other association indexes of the component B are proved to have no problem, the checking failure probability of the component B is gradually reduced, and the more the states of the association index components are completed, the lower the checking failure probability of the association index components is.
A computer room equipment self-adaptive management system based on cloud computing comprises: the system comprises an assembly type module, a BIM component management module, a machine room engineering processing module, an audit port module and a self-adaptive feedback regulation module;
the prefabricated assembly type machine room equipment installation system is built by the assembly type module, and a pre-installation equipment position diagram in the machine room is built; the BIM component management module is used for obtaining names of all components of pre-installed equipment in the machine room and generating corresponding BIM components; the machine room engineering processing module is used for creating a machine room engineering structure; under the engineering structure of the machine room, a role logging platform with an engineering structure tree management function is created, rights are given to an administrator, an engineering structure tree is created, and management of the engineering structure tree is carried out; the auditing port module creates a pre-analysis model based on historical auditing data, and after the management result of the engineering structure tree passes through the pre-analysis model, the priority analysis is carried out on synchronous components in the engineering structure tree, and the components are integrated into a component auditing list to be output; the self-adaptive feedback adjustment module is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed examination list passes the examination, an alarm is fed back to the main page, and after the first-line staff adjusts the position diagram of the pre-installed equipment in the machine room according to the alarm data, the engineering structure of the machine room is re-established and the examination is performed again;
the output end of the assembly type module is connected with the input end of the BIM component management module; the output end of the BIM component management module is connected with the input end of the machine room engineering processing module; the output end of the machine room engineering processing module is connected with the input end of the auditing port module; and the output end of the auditing port module is connected with the input end of the self-adaptive feedback regulation module.
According to the technical scheme, the assembly type module comprises a prefabricated assembly type machine room equipment installation unit and a drawing analysis unit;
the prefabricated equipment room equipment installation unit is used for constructing a prefabricated equipment room equipment installation system and constructing project display boards in advance; the drawing analysis unit is used for creating a pre-installation equipment position diagram in the machine room;
and the output end of the prefabricated assembly type machine room equipment installation unit is connected with the input end of the drawing analysis unit.
According to the technical scheme, the BIM component management module comprises a machine room equipment classification unit and a BIM component analysis unit;
the machine room equipment classification unit is used for acquiring names of all parts of pre-installed equipment in the machine room; the BIM component analysis unit generates a corresponding BIM component based on the names of all parts of pre-installed equipment in the machine room;
and the output end of the machine room equipment classification unit is connected with the input end of the BIM component analysis unit.
According to the technical scheme, the machine room engineering processing module comprises a machine room engineering structure creation unit and a management unit;
the machine room engineering structure creation unit is used for creating a machine room engineering structure, and the machine room engineering structure comprises node management, data tracking, a synchronous component and audit alarm; the management unit is used for creating a role login platform of an engineering structure tree management function under the engineering structure of the machine room, giving authority to an administrator, creating an engineering structure tree and managing the engineering structure tree; the management comprises selecting corresponding BIM components according to the requirements of engineering projects of a machine room, synchronizing the components under an engineering structure tree, and outputting the components to an audit port module;
and the output end of the machine room engineering structure creation unit is connected with the input end of the management unit.
According to the technical scheme, the auditing port module comprises a sequence early warning unit and an output unit;
the sequence early warning unit creates a pre-analysis model based on the historical auditing data, and the management result of the engineering structure tree is subjected to priority analysis on synchronous components after passing through the pre-analysis model; the output unit is used for integrating the components for priority analysis and generating a component audit list for output;
the output end of the sequence early warning unit is connected with the input end of the output unit.
According to the technical scheme, the self-adaptive feedback adjustment module comprises an approval processing unit and a self-adaptive feedback unit;
the examination and approval processing unit is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed audit list passes the approval, feeding back an alarm to the main page; the self-adaptive feedback unit is used for acquiring alarm data, and after adjusting a pre-installation equipment position diagram in the machine room according to the alarm data, a first-line staff re-creates a machine room engineering structure and re-checks the machine room engineering structure;
the output end of the approval processing unit is connected with the input end of the self-adaptive feedback unit.
Compared with the prior art, the invention has the following beneficial effects: in the application, the prefabricated equipment room equipment installation system is provided based on cloud computing means, so that various defects caused by traditional installation can be overcome, and the installation level is improved in multiple directions such as energy conservation, environmental protection, construction period management, cost control, construction technical quality, safety production and the like. And meanwhile, based on BIM technical management of project display boards in the installation process of prefabricated assembly type machine room equipment, data analysis, warning and intelligent means processing among components are provided. In response to the great advocacy of the national and local governments on green buildings and the specific industrialized actions thereof, advanced industry technology is provided, the aim of providing an epoch-making essence for society is achieved, the marker post is made for the whole digital building industry, and precious experience can be provided for subsequent building projects.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic flow chart of a cloud computing-based computer room equipment self-adaptive management system and a cloud computing-based computer room equipment self-adaptive management method.
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. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, in a first embodiment: the method comprises the steps of taking the case of an assembly type refrigerating machine room of Shenzhen urban rail transit No. 13 plumber Cheng Luozu station as analysis, wherein part of data involved in the analysis is processed, and the actual situation is not equal;
constructing a prefabricated assembly type machine room equipment installation system to obtain pre-installation equipment in a machine room, wherein the pre-installation equipment comprises two water-cooling screw type water chilling units with the same model, which are arranged in a station B end station hall layer water chilling machine room, run in parallel in daytime and are mutually standby, required cold water is provided for large and small system air conditioning equipment of a station, the cold water supply/return water temperature of the large and small system of the station is 7/14 ℃, the cold water supply/return water temperature of the cooling water is 32/37 ℃, and 2 cold water pumps and 2 cooling water pumps are correspondingly arranged respectively; 2 cooling towers with the cooling water quantity of 2 are arranged on the ground, and each tower is provided with 2 fans which can be respectively started. The cold water machine room is internally provided with a water dividing and collecting device, and water supply and return branch pipes of cold water required by large and small systems at two ends of the station are respectively connected out of the water dividing and collecting device and are separately arranged. A proportional integral dynamic balance electric regulating valve is arranged on the water return pipe at the tail end of each air conditioner; a differential pressure bypass device is arranged between the water separator and the water collector, a primary pump variable flow system is adopted at the evaporator side of the water chilling unit, and variable flow control is also adopted at the cooling water side; creating a pre-installation equipment position diagram in the machine room, acquiring names of all parts of the pre-installation equipment in the machine room, and generating a corresponding BIM component;
building a BIM model of a pipeline of a central refrigeration machine room: building a BIM model of a pipeline of the central refrigeration machine room based on the physical size according to the design drawing of the central refrigeration machine room and the requirements of assembly construction on the basis of building information modeling BIM by utilizing REVIT software;
a first-line staff performs rechecks and measures on the building structure in the machine room, the measured actual size is fed back to the sequence early warning unit, the auditing alarm means acquires the measured actual size, calculates the difference value between the actual measured value and the design value, and if the number of the difference items between the actual measured value and the design value exceeds a set threshold A or the difference value data between the actual measured value and the design value exceeds a set threshold B, invokes a preliminary auditing list and sends the preliminary auditing list to an auditing port module, and outputs an alarm result according to the auditing result of the auditing port module, wherein A, B is a system setting constant;
constructing a pre-analysis model, obtaining a difference value between an actual measured value and a design value, and correspondingly marking the difference value in a data folder of each component;
acquiring association indexes between the components, wherein the association indexes refer to direct connection between any two components, and if the association indexes exist between any two components, the number of the association indexes of each component is increased by 1, and the number of the association indexes of each component is recorded respectively;
normalizing the difference value between the actual measured value and the design value of each component and the number of associated indexes, and calculating the priority value Y=k of each component for the processed data 1 x 1 +k 2 x 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein k is 1 、k 2 Respectively are provided withWeight assignment representing a priority value; x is x 1 、x 2 Normalized values representing the difference between the actual measured value and the design value of each member and the number of associated indexes, respectively;
adjusting the preliminary audit list according to the order of the priority value of each component from large to small, and if the priority values are equal, randomly sequencing to generate a component audit list;
the auditing port carries out auditing treatment on each component according to the component auditing list, and when any component fails to audit, all subsequent components with associated indexes are invoked, and an intelligent analysis model is constructed:
acquiring historical audit data, wherein the historical audit data comprises audit success data and audit failure data, and marking state probability data for each group of audit data, wherein the state probability data refers to the number of the associated index members of each member, which is the number of completed construction, to the number ratio of the total associated index members;
acquiring all subsequent components which are correspondingly called by the components with correlation indexes under the real-time condition and have the correlation indexes, marking the components as a set M, acquiring the states of all the components with the correlation indexes of any component L in the set M, calculating the states as the duty ratio data of the construction completion, marking the states as L 0 ；
Under the condition of successful data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 1 The method comprises the steps of carrying out a first treatment on the surface of the Under the condition of failed audit data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 2 The method comprises the steps of carrying out a first treatment on the surface of the The historical audit data has state probability data less than or equal to L 0 The probability of (2) is denoted as R 3 ；
The prediction probability of the audit failure of the generating component L is P L =（R 1 *R 3 ）/[（R 1 *R 3 ）+R 2 *（1-R 3 ）]；
Setting probability threshold, if P exists L If the probability threshold value is exceeded, the corresponding component L is directly output to an auditing port for preferential auditing; the examination list passes the examination and approval, the examination list feeds back an alarm to the main page, and all the examination failure data are recorded into alarm dataAnd after adjusting the position diagram of the pre-installed equipment in the machine room according to the alarm data, the first-line staff recreates the engineering structure of the machine room and checks again.
In a second embodiment, a cloud computing-based machine room device adaptive management system is provided, where the system includes: the system comprises an assembly type module, a BIM component management module, a machine room engineering processing module, an audit port module and a self-adaptive feedback regulation module;
the prefabricated assembly type machine room equipment installation system is built by the assembly type module, and a pre-installation equipment position diagram in the machine room is built; the BIM component management module is used for obtaining names of all components of pre-installed equipment in the machine room and generating corresponding BIM components; the machine room engineering processing module is used for creating a machine room engineering structure; under the engineering structure of the machine room, a role logging platform with an engineering structure tree management function is created, rights are given to an administrator, an engineering structure tree is created, and management of the engineering structure tree is carried out; the auditing port module creates a pre-analysis model based on historical auditing data, and after the management result of the engineering structure tree passes through the pre-analysis model, the priority analysis is carried out on synchronous components in the engineering structure tree, and the components are integrated into a component auditing list to be output; the self-adaptive feedback adjustment module is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed examination list passes the examination, an alarm is fed back to the main page, and after the first-line staff adjusts the position diagram of the pre-installed equipment in the machine room according to the alarm data, the engineering structure of the machine room is re-established and the examination is performed again;
the output end of the assembly type module is connected with the input end of the BIM component management module; the output end of the BIM component management module is connected with the input end of the machine room engineering processing module; the output end of the machine room engineering processing module is connected with the input end of the auditing port module; and the output end of the auditing port module is connected with the input end of the self-adaptive feedback regulation module.
The assembly type module comprises a prefabricated assembly type machine room equipment installation unit and a drawing analysis unit;
the prefabricated equipment room equipment installation unit is used for constructing a prefabricated equipment room equipment installation system and constructing project display boards in advance; the drawing analysis unit is used for creating a pre-installation equipment position diagram in the machine room;
and the output end of the prefabricated assembly type machine room equipment installation unit is connected with the input end of the drawing analysis unit.
The BIM component management module comprises a machine room equipment classification unit and a BIM component analysis unit;
the machine room equipment classification unit is used for acquiring names of all parts of pre-installed equipment in the machine room; the BIM component analysis unit generates a corresponding BIM component based on the names of all parts of pre-installed equipment in the machine room;
and the output end of the machine room equipment classification unit is connected with the input end of the BIM component analysis unit.
The machine room engineering processing module comprises a machine room engineering structure creation unit and a management unit;
the machine room engineering structure creation unit is used for creating a machine room engineering structure, and the machine room engineering structure comprises node management, data tracking, a synchronous component and audit alarm; the management unit is used for creating a role login platform of an engineering structure tree management function under the engineering structure of the machine room, giving authority to an administrator, creating an engineering structure tree and managing the engineering structure tree; the management comprises selecting corresponding BIM components according to the requirements of engineering projects of a machine room, synchronizing the components under an engineering structure tree, and outputting the components to an audit port module;
and the output end of the machine room engineering structure creation unit is connected with the input end of the management unit.
The auditing port module comprises a sequence early warning unit and an output unit;
the sequence early warning unit creates a pre-analysis model based on the historical auditing data, and the management result of the engineering structure tree is subjected to priority analysis on synchronous components after passing through the pre-analysis model; the output unit is used for integrating the components for priority analysis and generating a component audit list for output;
the output end of the sequence early warning unit is connected with the input end of the output unit.
The self-adaptive feedback regulation module comprises an approval processing unit and a self-adaptive feedback unit;
the examination and approval processing unit is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed audit list passes the approval, feeding back an alarm to the main page; the self-adaptive feedback unit is used for acquiring alarm data, and after adjusting a pre-installation equipment position diagram in the machine room according to the alarm data, a first-line staff re-creates a machine room engineering structure and re-checks the machine room engineering structure;
the output end of the approval processing unit is connected with the input end of the self-adaptive feedback unit.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A machine room equipment self-adaptive management method based on cloud computing is characterized by comprising the following steps of: the method comprises the following steps:
s1, constructing a prefabricated equipment installation system of a machine room, creating a position diagram of pre-installed equipment in the machine room, acquiring names of all parts of the pre-installed equipment in the machine room, and generating corresponding BIM components;
s2, creating a machine room engineering structure, wherein the machine room engineering structure comprises node management, data tracking, synchronous components and audit alarm;
s3, under the engineering structure of the machine room, a role login platform with an engineering structure tree management function is created, rights are given to an administrator, an engineering structure tree is created, and management of the engineering structure tree is carried out; the management comprises selecting corresponding BIM components according to the requirements of engineering projects of a machine room, synchronizing the components under an engineering structure tree, and outputting the components to an audit port module;
s4, a sequence early warning unit is arranged in front of the auditing port module, a front analysis model is established by the sequence early warning unit based on historical auditing data, and after the management result of the engineering structure tree passes through the front analysis model, priority analysis is carried out on synchronous components in the engineering structure tree, and the synchronous components are integrated into a component auditing list to be output;
s5, if the examination and approval of the constructed examination and approval list passes, equipment is installed according to the current machine room engineering structure; if the constructed examination list passes the examination, an alarm is fed back to the main page, and after the first-line staff adjusts the position diagram of the pre-installed equipment in the machine room according to the alarm data, the engineering structure of the machine room is re-established and the examination is performed again;
in step S4, the sequence early warning unit includes:
constructing a pre-analysis model, obtaining a difference value between an actual measured value and a design value, and correspondingly marking the difference value in a data folder of each component;
acquiring association indexes between the components, wherein the association indexes refer to direct connection between any two components, and if the association indexes exist between any two components, the number of the association indexes of each component is increased by 1, and the number of the association indexes of each component is recorded respectively;
the difference value between the actual measurement value and the design value of each component and the number of associated indexes are normalized,calculating a priority value y=k for each component for the processed data 1 x 1 +k 2 x 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein k is 1 、k 2 Weight distribution respectively representing priority values; x is x 1 、x 2 Normalized values representing the difference between the actual measured value and the design value of each member and the number of associated indexes, respectively;
adjusting the preliminary audit list according to the order of the priority value of each component from large to small, and if the priority values are equal, randomly sequencing to generate a component audit list;
the auditing port carries out auditing treatment on each component according to the component auditing list, and when any component fails to audit, all subsequent components with associated indexes are invoked, and an intelligent analysis model is constructed:
acquiring historical audit data, wherein the historical audit data comprises audit success data and audit failure data, and marking state probability data for each group of audit data, wherein the state probability data refers to the number of the associated index members of each member, which is the number of completed construction, to the number ratio of the total associated index members;
acquiring all subsequent components which are correspondingly called by the components with correlation indexes under the real-time condition and have the correlation indexes, marking the components as a set M, acquiring the states of all the components with the correlation indexes of any component L in the set M, calculating the states as the duty ratio data of the construction completion, marking the states as L 0 ；
Under the condition of successful data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 1 The method comprises the steps of carrying out a first treatment on the surface of the Under the condition of failed audit data, the data with state probability is less than or equal to L 0 The probability of (2) is denoted as R 2 The method comprises the steps of carrying out a first treatment on the surface of the The historical audit data has state probability data less than or equal to L 0 The probability of (2) is denoted as R 3 ；
The prediction probability of the audit failure of the generating component L is P L =（R 1 *R 3 ）/[（R 1 *R 3 ）+R 2 *（1-R 3 ）]；
Setting probability threshold, if P exists L Exceeding the probability threshold value, the corresponding member is thenL is directly output to an auditing port for preferential auditing;
if the constructed audit list passes the approval, an alarm is fed back to the main page, all audit failure data are recorded into alarm data, and after a first-line staff adjusts a pre-installation equipment position diagram in the machine room according to the alarm data, the machine room engineering structure is re-established, and the machine room engineering structure is audited again.
2. The cloud computing-based machine room equipment self-adaptive management method as claimed in claim 1, wherein the method comprises the following steps: in step S1, the prefabricated building equipment installation system includes:
and (3) creating a pre-installation equipment position diagram in the machine room, obtaining names of all parts of the pre-installation equipment in the machine room, generating corresponding BIM components, utilizing REVIT software, building a machine room equipment engineering BIM model based on the physical size according to the pre-installation equipment position diagram in the machine room on the basis of building information modeling BIM, and synchronizing the BIM model into a machine room engineering structure.
3. The cloud computing-based machine room equipment self-adaptive management method as claimed in claim 2, wherein the method comprises the following steps: in steps S2-S3, the node management comprises node names and node types, wherein the node types comprise areas, professions and procedures; the area refers to an installation area of equipment in a machine room corresponding to the current node; the professional finger corresponds to a component of the equipment component of the machine room at the current node; the working procedure refers to a machine room engineering state corresponding to the current node, wherein the state comprises design, production and construction; the design comprises to-be-designed, being designed and being designed to be completed; the production comprises the steps of waiting for production, producing and completing the production; the construction comprises the steps of waiting for construction, constructing and completing the construction;
the data tracking is based on a data cloud platform built by each server in the system, data circulating among the servers are monitored and tracked, a notification function is configured, and when any server fails to timely reply the data, a warning prompt is generated;
the synchronous component marks a corresponding BIM component synchronous with the BIM model of equipment engineering in the machine room, extracts and gathers data of each BIM component, and generates a preliminary audit list;
and (3) checking and measuring the building structure in the machine room by a first-line staff, feeding the measured actual size back to the sequence early warning unit, wherein the checking and warning means to acquire the measured actual size, calculate the difference value between the actual measurement value and the design value, and if the number of the difference items between the actual measurement value and the design value exceeds a set threshold A or the difference value data between the actual measurement value and the design value exceeds a set threshold B, take a preliminary checking list, send the preliminary checking list to the checking port module, and output a warning result according to the checking result of the checking port module, wherein A, B is a system setting constant.
4. A management system using the cloud computing-based machine room equipment adaptive management method according to any one of claims 1 to 3, characterized in that: the system comprises: the system comprises an assembly type module, a BIM component management module, a machine room engineering processing module, an audit port module and a self-adaptive feedback regulation module;
the prefabricated assembly type machine room equipment installation system is built by the assembly type module, and a pre-installation equipment position diagram in the machine room is built; the BIM component management module is used for obtaining names of all components of pre-installed equipment in the machine room and generating corresponding BIM components; the machine room engineering processing module is used for creating a machine room engineering structure; under the engineering structure of the machine room, a role logging platform with an engineering structure tree management function is created, rights are given to an administrator, an engineering structure tree is created, and management of the engineering structure tree is carried out; the auditing port module creates a pre-analysis model based on historical auditing data, and after the management result of the engineering structure tree passes through the pre-analysis model, the priority analysis is carried out on synchronous components in the engineering structure tree, and the components are integrated into a component auditing list to be output; the self-adaptive feedback adjustment module is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed examination list passes the examination, an alarm is fed back to the main page, and after the first-line staff adjusts the position diagram of the pre-installed equipment in the machine room according to the alarm data, the engineering structure of the machine room is re-established and the examination is performed again;
the output end of the assembly type module is connected with the input end of the BIM component management module; the output end of the BIM component management module is connected with the input end of the machine room engineering processing module; the output end of the machine room engineering processing module is connected with the input end of the auditing port module; and the output end of the auditing port module is connected with the input end of the self-adaptive feedback regulation module.
5. The management system of the cloud computing-based machine room equipment adaptive management method according to claim 4, wherein: the assembly type module comprises a prefabricated assembly type machine room equipment installation unit and a drawing analysis unit;
the prefabricated equipment room equipment installation unit is used for constructing a prefabricated equipment room equipment installation system and constructing project display boards in advance; the drawing analysis unit is used for creating a pre-installation equipment position diagram in the machine room;
and the output end of the prefabricated assembly type machine room equipment installation unit is connected with the input end of the drawing analysis unit.
6. The management system of the cloud computing-based machine room equipment adaptive management method according to claim 4, wherein: the BIM component management module comprises a machine room equipment classification unit and a BIM component analysis unit;
the machine room equipment classification unit is used for acquiring names of all parts of pre-installed equipment in the machine room; the BIM component analysis unit generates a corresponding BIM component based on the names of all parts of pre-installed equipment in the machine room;
and the output end of the machine room equipment classification unit is connected with the input end of the BIM component analysis unit.
7. The management system of the cloud computing-based machine room equipment adaptive management method according to claim 4, wherein: the machine room engineering processing module comprises a machine room engineering structure creation unit and a management unit;
the machine room engineering structure creation unit is used for creating a machine room engineering structure, and the machine room engineering structure comprises node management, data tracking, a synchronous component and audit alarm; the management unit is used for creating a role login platform of an engineering structure tree management function under the engineering structure of the machine room, giving authority to an administrator, creating an engineering structure tree and managing the engineering structure tree; the management comprises selecting corresponding BIM components according to the requirements of engineering projects of a machine room, synchronizing the components under an engineering structure tree, and outputting the components to an audit port module;
and the output end of the machine room engineering structure creation unit is connected with the input end of the management unit.
8. The management system of the cloud computing-based machine room equipment adaptive management method according to claim 4, wherein: the auditing port module comprises a sequence early warning unit and an output unit;
the sequence early warning unit creates a pre-analysis model based on the historical auditing data, and the management result of the engineering structure tree is subjected to priority analysis on synchronous components after passing through the pre-analysis model; the output unit is used for integrating the components for priority analysis and generating a component audit list for output;
the output end of the sequence early warning unit is connected with the input end of the output unit.
9. The management system of the cloud computing-based machine room equipment adaptive management method according to claim 4, wherein: the self-adaptive feedback regulation module comprises an approval processing unit and a self-adaptive feedback unit;
the examination and approval processing unit is used for installing equipment according to the current machine room engineering structure if the examination and approval of the constructed examination and approval list passes; if the constructed audit list passes the approval, feeding back an alarm to the main page; the self-adaptive feedback unit is used for acquiring alarm data, and after adjusting a pre-installation equipment position diagram in the machine room according to the alarm data, a first-line staff re-creates a machine room engineering structure and re-checks the machine room engineering structure;
the output end of the approval processing unit is connected with the input end of the self-adaptive feedback unit.
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