An intelligent recommendation system for hardware selection of ACU controllers

Abstract

The present invention relates to the technical field of urban underground integrated pipe corridors, and specifically to an intelligent recommendation system for hardware selection of ACU controllers, the system comprising a server, the server comprising: a data acquisition module: used to obtain structural data of underground urban integrated pipe corridors and user demand data; a function analysis module: used to perform functional analysis on structural data and demand data, and arrange and combine function modules of screened models to obtain a function module combination; and also used to evaluate the cost performance and sort the list according to the parameter data of each function module in the function module combination; an intelligent recommendation module: used to recommend the sorted list of function module combinations to the user. The present invention solves the problem that in the current stage of manually completing the hardware design stage of the ACU regional controller, due to the many factors to be considered and the need for repeated adjustments, a lot of time and resources will be consumed, and there are risks caused by human errors.

Description

Technical Field

[0001] The present invention relates to the technical field of urban underground integrated pipe corridors, and in particular to an intelligent recommendation system for hardware selection of an ACU controller. Background Art

[0002] The urban underground integrated pipe gallery is an integral part of urban construction. It includes power supply, water supply, gas supply, heating / cooling, drainage and various information pipelines. It is the foundation and guarantee for the survival and development of the city. It is the nerve and blood vessel that ensures the normal functioning of the city and the people's living and working in peace and contentment. The integrated pipe gallery is an important part of the urban underground pipeline integration. The area controller (ACU) control system can comprehensively analyze the various environmental data in the integrated pipe gallery and check whether the data is abnormal, so as to judge whether to open or close the fan or lighting system to achieve the purpose of ventilation, energy saving and emission reduction. While realizing real-time monitoring of the environmental conditions of the integrated pipe gallery, it can respond to abnormal situations in a timely manner to improve operational efficiency and safety management level.

[0003] At the beginning of the ACU area controller, engineers usually need to complete the hardware design of the ACU area controller based on environmental characteristics and design data, including the selection of electronic components such as cabinets and sensors, as well as the layout of cabinets and electronic components. These tasks are usually completed manually by engineers, but due to the many factors to consider and the need for repeated adjustments, it will consume a lot of time and resources, and there is a risk of human error. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent recommendation system for hardware selection of ACU controllers, so as to solve the problem that in the current manual completion of the ACU area controller hardware design stage, there are many factors to consider and repeated adjustments are required, which consumes a lot of time and resources and has the risk of human errors.

[0005] In order to achieve the above object, a hardware selection intelligent recommendation system for an ACU controller is provided, including a server, wherein the server includes:

[0006] Data acquisition module: used to obtain the structural data of underground urban integrated pipeline corridors and user demand data;

[0007] Functional analysis module: used to perform functional analysis on structural data and demand data, and select the matching functional modules from the preset hardware database according to the functional results of the functional analysis;

[0008] Model screening module: used to screen the models of functional modules according to the structural data of the underground urban integrated pipe gallery and the user's demand data, and arrange and combine the functional modules of the screened models to obtain a functional module combination; it is also used to evaluate the cost performance according to the parameter data of each functional module in the functional module combination, and sort the functional module combination according to the cost performance evaluation result, and output the sorted list of functional module combinations;

[0009] Intelligent recommendation module: used to recommend a combined ranked list of functional modules to users.

[0010] Principles and advantages:

[0011] 1. The data acquisition module and the function analysis module are set up. The data acquisition module can obtain the structural data of the underground urban integrated pipe corridor and the user's demand data. Among them, since the geographical environment of the underground urban integrated pipe corridor is complex, only through the demand data and the function analysis module to screen the matching function modules from the preset hardware database can only meet the user's needs but may not adapt to the environment of the underground urban integrated pipe corridor, resulting in the possibility that the installed hands may not work properly or other problems may occur. Therefore, by combining the structural data and the demand data, and letting the function analysis module screen the matching function modules, on the one hand, the selection of the function modules can be completed automatically without excessive human participation, saving labor costs. On the other hand, a function module that better meets the needs can be selected without repeated adjustments, which consumes a lot of time and resources.

[0012] 2. The setting of the model screening module. The function analysis module is only a preliminary screening of the functions, while the model screening module performs a secondary refinement screening of the models of the functional modules according to the structural data of the underground urban integrated pipe gallery and the user's demand data. After the screening is completed, the functional modules of the screened models are arranged and combined to obtain multiple sets of functional module combinations. On the one hand, it is convenient for the staff to easily complete the selection of the ACU controller according to the functional module combination, and the process is greatly simplified, which improves the work efficiency. On the other hand, the diversification of the functional module combination makes it easier for the staff to choose a more suitable one, avoiding the risk problems caused by human selection and combination errors. In addition, the model screening module will also evaluate the cost-effectiveness of each functional module in the functional module combination according to the parameter data of each functional module in the functional module combination, and sort the functional module combination according to the cost-effectiveness evaluation results, and output the functional module combination sorting list. The functional module combination sorting list can realize the quantitative analysis of each functional module combination, which is more convenient for the staff to make intuitive choices, thereby avoiding repeated adjustments that consume a lot of time and resources.

[0013] 3. The setting of the intelligent recommendation module can recommend a combination and sorting list of functional modules to users, so that users do not need to participate too much, which improves work efficiency and reduces the impact of subjective factors of personnel. They only need to make a choice.

[0014] Furthermore, the data acquisition module is also used to obtain the size data of the ACU cabinet corresponding to the ACU controller and the model data of the corresponding functional modules in each functional module combination. The server also includes the following modules:

[0015] Model matching module: used to match the pre-installed device model of the corresponding functional module in each functional module combination from the preset model database, and also used to match the cabinet model of the corresponding ACU cabinet from the preset model database according to the size data of the ACU cabinet;

[0016] Preliminary verification module: used to calculate the capacity information of the cabinet model of the ACU cabinet, as well as the total volume information of the pre-installed device models of the functional modules in each functional module combination, and perform preliminary analysis and verification based on the capacity information and the total volume information of each functional module combination to see whether the functional module combination is compatible with the ACU cabinet.

[0017] The setting of the model matching module will match the pre-installed device model of the corresponding functional module and the cabinet model of the ACU cabinet. The preliminary verification module will calculate the capacity information of the cabinet model of the ACU cabinet, as well as the total volume information of the pre-installed device models of the functional modules in each functional module combination. By numerically comparing the capacity information with the total volume information of each functional module combination, it is possible to simply and conveniently determine whether the functional module combination has sufficient space in the ACU cabinet to accommodate the access of new functional modules in the future, thereby making it easier to prepare space for the access of new functional modules in the future and avoiding the need for a large amount of manpower and time costs for renovation in the future due to insufficient internal space in the ACU cabinet.

[0018] Furthermore, the server also includes the following modules:

[0019] List optimization module: used to obtain the preliminary verification results of the preliminary verification module, and optimize the functional module combination sorting list according to the verification results.

[0020] The list optimization module can optimize the sorting list of functional module combinations, eliminate invalid functional module combinations, and reduce interference options for selection, thereby facilitating the selection of functional module combinations that better meet the needs.

[0021] Furthermore, the server also includes the following modules:

[0022] Space planning module: used to carry out installation planning according to the model and quantity of each functional module in the optimized functional module combination sorting list and the size data of the ACU cabinet, and to assemble the cabinet model and the pre-installed device model of each functional module according to the installation plan.

[0023] The setting of the space planning module firstly makes installation planning according to the model and quantity of each functional module in the optimized functional module combination sorting list and the size data of the ACU cabinet, so as to make convenient and effective use of the space inside the ACU cabinet. Then, according to the installation plan, the cabinet model and the pre-installed device models of each functional module are assembled. The model assembly can be conveniently used as the basis for installation during actual installation, thereby improving the efficiency of installation and avoiding repeated adjustments that consume a lot of time and resources. At the same time, because it is simulated by the model, it can be continuously tried and wrong, thereby reducing the risk of human error.

[0024] Furthermore, the server also includes the following modules:

[0025] Secondary verification module: used to perform secondary analysis and verification after the space planning module completes the model assembly, to determine whether there is sufficient space in the ACU cabinet to meet the needs of future new functional modules. If so, the size of the sufficient space is recorded and marked in the optimized functional module combination sorting list.

[0026] The setting of the secondary verification module will perform secondary analysis and verification to determine whether there is sufficient space in the ACU cabinet to accommodate the access of new functional modules in the future, thereby facilitating the preparation of space for the access of new functional modules in the future and avoiding the need for a large amount of manpower and time costs for renovation in the future due to insufficient internal space in the ACU cabinet.

[0027] Furthermore, the data acquisition module is also used to obtain the structural data of the underground urban integrated pipe gallery; the server also includes the following modules:

[0028] Alternative plan module: used to determine whether the size of the recorded surplus space meets the set space threshold. If not, an alternative plan is set according to the structural data of the underground urban integrated pipeline corridor. The alternative plan includes the ACU main cabinet and the ACU sub-cabinet, as well as the planned setting locations of the ACU main cabinet and the ACU sub-cabinet.

[0029] The setting of the alternative solution module can provide alternative solutions when the size of the remaining space does not meet the set space threshold, so as to prepare space for the future access of new functional modules and avoid the need for large amounts of manpower and time costs for renovation due to insufficient internal space in the ACU cabinet in the future.

[0030] Furthermore, the ACU main cabinet and the ACU sub-cabinet communicate via DeviceNet fieldbus or EtherNet / IP industrial Ethernet.

[0031] Communicating via DeviceNet fieldbus or EtherNet / IP industrial Ethernet can ensure communication effectiveness and save the cost of the underground urban integrated pipeline corridor monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 The present invention is a logic block diagram of an intelligent recommendation system for hardware selection of an ACU controller according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following is further described in detail through specific implementation methods:

[0034] Example

[0035] An intelligent recommendation system for hardware selection of ACU controllers is basically as follows: Figure 1 As shown: It includes a server and a user end. The user end is used by the staff who design and install the ACU controller. The user end is a smart phone equipped with an APP to communicate with the server remotely. It can send required data to the server and receive information sent by the server. The server includes:

[0036] Data acquisition module: used to obtain the structural data of the underground urban integrated pipeline corridor and the user's demand data; also used to obtain the size data of the ACU cabinet corresponding to the ACU controller and the model data of the corresponding functional modules in each functional module combination; also used to obtain the structural data of the underground urban integrated pipeline corridor.

[0037] Functional analysis module: used to perform functional analysis on structural data and demand data, and select the matching functional modules from the preset hardware database according to the functional results of the functional analysis;

[0038] Model screening module: used to screen the models of functional modules according to the structural data of the underground urban integrated pipe gallery and the user's demand data, and arrange and combine the functional modules of the selected models to obtain a functional module combination; it is also used to evaluate the cost performance according to the parameter data of each functional module in the functional module combination, and sort the functional module combination according to the cost performance evaluation results, and output the sorted list of functional module combinations; the function analysis module is only a preliminary screening of the functions that meet the requirements, while the model screening module performs a secondary refinement screening of the models of functional modules according to the structural data of the underground urban integrated pipe gallery and the user's demand data. After the screening is completed, the functional modules of the selected models are arranged and combined to obtain multiple sets of functional module combinations. On the one hand, it is convenient for the staff to easily complete the selection of the ACU controller according to the functional module combination, and the process is greatly simplified, which improves work efficiency. On the other hand, the diversification of functional module combinations makes it easier for the staff to choose a more suitable one, avoiding the risk problems caused by human selection and combination errors. In addition, the model screening module will also evaluate the cost performance of each functional module in the functional module combination according to the parameter data of each functional module, and sort the functional module combination according to the cost performance evaluation results, and output the functional module combination sorting list. The functional module combination sorting list can realize the quantitative analysis of each functional module combination, making it easier for staff to make intuitive choices, thereby avoiding repeated adjustments that consume a lot of time and resources.

[0039] Model matching module: used to match the pre-installed device model of the corresponding functional module in each functional module combination from the preset model database, and also used to match the cabinet model of the corresponding ACU cabinet from the preset model database according to the size data of the ACU cabinet;

[0040] Preliminary verification module: used to calculate the capacity information of the cabinet model of the ACU cabinet, as well as the volume sum information of the pre-installed device models of the functional modules in each functional module combination, and to perform preliminary analysis and verification based on the capacity information and the volume sum information of each functional module combination to see whether the functional module combination is compatible with the ACU cabinet. The preliminary verification of the preliminary verification module can easily and conveniently determine whether the functional module combination has sufficient space in the ACU cabinet to accommodate the access of new functional modules in the future, thereby facilitating space preparation for the access of new functional modules in the future and avoiding the need for a large amount of manpower and time costs for renovation in the future due to insufficient internal space in the ACU cabinet.

[0041] List optimization module: used to obtain the preliminary verification results of the preliminary verification module, and optimize the functional module combination sorting list according to the verification results. The list optimization module can optimize the functional module combination sorting list, exclude invalid functional module combinations, and reduce interference options for selection, so as to facilitate the selection of functional module combinations that better meet the needs.

[0042] Space planning module: It is used to carry out installation planning according to the model and quantity of each functional module in the optimized functional module combination sorting list and the size data of the ACU cabinet, and to assemble the cabinet model and the pre-installed device model of each functional module according to the installation plan. Through installation planning, the space inside the ACU cabinet can be conveniently and effectively utilized. Then, according to the installation plan, the cabinet model and the pre-installed device model of each functional module are assembled into models. The model assembly can be conveniently used as the basis for installation during actual installation, thereby improving the efficiency of installation and avoiding repeated adjustments that consume a lot of time and resources. At the same time, because it is simulated by the model, it can be continuously tried and errored, thereby reducing the risk of human error.

[0043] Secondary verification module: used to perform secondary analysis and verification after the space planning module completes model assembly, to determine whether there is sufficient space in the ACU cabinet to meet the needs of future new functional modules. If so, the size of the sufficient space is recorded and marked in the optimized functional module combination sorting list. Through secondary analysis and verification, it is determined whether there is sufficient space in the ACU cabinet to meet the needs of future new functional modules, so as to facilitate space preparation for the future access of new functional modules and avoid the need for a large amount of manpower and time costs for transformation due to insufficient internal space in the ACU cabinet in the future.

[0044] Alternative plan module: used to determine whether the size of the recorded surplus space meets the set space threshold. If not, an alternative plan is set according to the structural data of the underground urban integrated pipeline corridor. The alternative plan includes the ACU main cabinet and the ACU sub-cabinet, and the planned location of the ACU main cabinet and the ACU sub-cabinet. The ACU main cabinet and the ACU sub-cabinet communicate via the DeviceNet fieldbus or the EtherNet / IP industrial Ethernet. When the size of the surplus space does not meet the set space threshold, an alternative plan can be provided to facilitate space preparation for the future access to new functional modules, avoiding the need for a large amount of manpower and time costs for transformation in the future due to insufficient internal space in the ACU cabinet.

[0045] Intelligent recommendation module: used to recommend a combined ranked list of functional modules to users.

[0046] Embodiment 2

[0047] The difference between the second embodiment and the first embodiment is that the server further includes the following modules:

[0048] Space margin analysis module: used to analyze the first overall space ratio of the assembly model in the ACU cabinet, and analyze the second overall space ratio according to the surplus installation space and reserved installation space of the ACU cabinet, set a fixed weight ratio for the first overall space ratio and the second overall space ratio, and analyze the overall space utilization efficiency of the ACU cabinet.

[0049] Data storage module: used to store the overall space utilization efficiency of each ACU cabinet, and correspondingly store the assembly model, spare installation space and reserved installation space of each ACU cabinet.

[0050] Space layout optimization module: used to obtain each device model in the assembly model and the device model corresponding to the function expansion demand predicted in the function prediction module when the overall space utilization efficiency of the ACU cabinet is lower than the set space utilization efficiency threshold, and match and search from the data storage module for an ACU cabinet that completely contains all device models of the current ACU cabinet and whose overall space utilization efficiency reaches the space utilization efficiency threshold according to each device model in the assembly model and the device model corresponding to the function expansion demand, and generate a layout optimization plan according to the layout of the ACU cabinet.

[0051] Selection optimization module: It is used to obtain the function data, size data and model data of each device model in the assembly model when the overall space utilization efficiency of the ACU cabinet is lower than the set space utilization efficiency threshold, and obtain the function data, size data and model data of the device model corresponding to the function expansion demand predicted in the function prediction module, and match and search for a device model with complete function data and smaller size from the data storage module according to the function data, size data and model data of the device model, and re-generate a layout optimization plan through the space planning module according to the device model.

[0052] Application difficulty analysis module: used to analyze the combination difficulty of actual application according to the layout optimization scheme and the assembly model of the current ACU cabinet, the remaining installation space and the reserved installation space. The combination difficulty includes the equipment optimization cost, and sorts the layout optimization schemes according to the combination difficulty. By analyzing and sorting the application difficulty of the layout optimization scheme, it is convenient to select a layout optimization scheme with low cost and low combination difficulty.

[0053] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is described too much here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. An intelligent recommendation system for hardware selection of ACU controller, characterized by: A server is included, wherein the server includes: Data acquisition module: used to obtain the structural data of the underground urban integrated pipe gallery and the user's demand data; also used to obtain the size data of the ACU cabinet corresponding to the ACU controller and the model data of the corresponding functional modules in each functional module combination; Functional analysis module: used to perform functional analysis on structural data and demand data, and select the matching functional modules from the preset hardware database according to the functional results of the functional analysis; Model screening module: used to screen the models of functional modules according to the structural data of the underground urban integrated pipe gallery and the user's demand data, and arrange and combine the functional modules of the screened models to obtain a functional module combination; it is also used to evaluate the cost performance according to the parameter data of each functional module in the functional module combination, and sort the functional module combination according to the cost performance evaluation result, and output the sorted list of functional module combinations; Intelligent recommendation module: used to recommend the combined sorted list of functional modules to users; Model matching module: used to match the pre-installed device model of the corresponding functional module in each functional module combination from the preset model database, and also used to match the cabinet model of the corresponding ACU cabinet from the preset model database according to the size data of the ACU cabinet; Preliminary verification module: used to calculate the capacity information of the cabinet model of the ACU cabinet, and calculate the volume sum information of the pre-installed device models of the functional modules in each functional module combination, and perform preliminary analysis and verification based on the capacity information and the volume sum information of each functional module combination to determine whether the functional module combination is compatible with the ACU cabinet; Space margin analysis module: used to analyze the overall space utilization efficiency of the ACU cabinet; Data storage module: used to store the overall space utilization efficiency of each ACU cabinet, as well as the assembly model, spare installation space and reserved installation space of each ACU cabinet; Function prediction module: used to predict the device model corresponding to the function expansion requirements; Space layout optimization module: used for obtaining each device model in the assembly model and the device model corresponding to the function expansion requirement predicted in the function prediction module when the overall space utilization efficiency of the ACU cabinet is lower than the set space utilization efficiency threshold, and matching and searching from the data storage module for an ACU cabinet that completely contains all device models of the current ACU cabinet and whose overall space utilization efficiency reaches the space utilization efficiency threshold according to each device model in the assembly model and the device model corresponding to the function expansion requirement, and generating a layout optimization plan according to the layout of the ACU cabinet; Selection optimization module: used to obtain the function data, size data and model data of each device model in the assembly model when the overall space utilization efficiency of the ACU cabinet is lower than the set space utilization efficiency threshold, and obtain the function data, size data and model data of the device model corresponding to the function expansion demand predicted in the function prediction module, and match and search for a device model with complete function data and smaller size from the data storage module according to the function data, size data and model data of the device model, and regenerate a layout optimization plan through the space planning module according to the device model; Application difficulty analysis module: used to analyze the combination difficulty of actual application according to the layout optimization scheme and the assembly model of the current ACU cabinet, the remaining installation space and the reserved installation space, the combination difficulty includes the equipment optimization cost, and sort multiple layout optimization schemes according to the combination difficulty.

2. The hardware selection intelligent recommendation system for ACU controller according to claim 1, characterized in that: The server also includes the following modules: List optimization module: used to obtain the preliminary verification results of the preliminary verification module, and optimize the functional module combination sorting list according to the verification results.

3. The hardware selection intelligent recommendation system for ACU controller according to claim 2, characterized in that: The server also includes the following modules: Space planning module: used to carry out installation planning according to the model and quantity of each functional module in the optimized functional module combination sorting list and the size data of the ACU cabinet, and to assemble the cabinet model and the pre-installed device model of each functional module according to the installation plan.

4. The hardware selection intelligent recommendation system for ACU controller according to claim 3, characterized in that: The server also includes the following modules: Secondary verification module: used to perform secondary analysis and verification after the space planning module completes the model assembly, to determine whether there is sufficient space in the ACU cabinet to meet the needs of future new functional modules. If so, the size of the sufficient space is recorded and marked in the optimized functional module combination sorting list.

5. The hardware selection intelligent recommendation system for ACU controller according to claim 4, characterized in that: The data acquisition module is also used to obtain the structural data of the underground urban integrated pipe gallery; the server also includes the following modules: Alternative plan module: used to determine whether the size of the recorded surplus space meets the set space threshold. If not, an alternative plan is set according to the structural data of the underground urban integrated pipeline corridor. The alternative plan includes the ACU main cabinet and the ACU sub-cabinet, as well as the planned setting locations of the ACU main cabinet and the ACU sub-cabinet.

6. The hardware selection intelligent recommendation system for ACU controller according to claim 5, characterized in that: The ACU main cabinet and the ACU sub-cabinet communicate via DeviceNet fieldbus or EtherNet / IP industrial Ethernet.

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