Intelligent construction project operation and maintenance management platform and method

Abstract

The invention discloses an intelligent construction engineering operation and maintenance management platform and method, and relates to the technical field of intelligent construction engineering.The intelligent construction engineering operation and maintenance management platform comprises a shopping mall information acquisition module, a shopping mall noise evaluation module, a shopping mall noise processing module, a display terminal and a database. Equipment noise and people stream noise are classified and processed, so that the reasonability of a noise processing mode of a shopping mall is effectively guaranteed, the noise processing quality is improved, the customer satisfaction degree is improved, the proportion of return customers is guaranteed, and the health problems of hearing loss, pressure increase, sleep disorder and the like of employees are avoided; according to the method, the group labels of the abnormal noise sub-regions in the shopping mall are generated, the noise processing urgency of each region in the shopping mall is analyzed, the reasonability of the noise processing sequence of each region in the shopping mall is guaranteed, the balance of the noise in the shopping mall is optimized, and the noise processing efficiency of the shopping mall is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent construction engineering, and in particular to an intelligent construction engineering operation and maintenance management platform and method. Background Art

[0002] With the rapid development of science and technology, intelligent construction has gradually become an important trend in the construction industry. From design, construction to later operation and maintenance management, the integration of intelligent technology has brought revolutionary changes to the traditional construction industry. Especially in the engineering operation and maintenance stage, the importance and necessity of intelligent management are becoming increasingly prominent. It is not only related to the service life and safety performance of the building, but also to the optimization of energy efficiency and economic benefits. In the operation of shopping malls, abnormal noise problems usually occur. If not handled in time, it will affect the normal communication and experience of customers. Therefore, it is extremely necessary to manage the noise of shopping malls.

[0003] Prior art, such as the invention application patent with announcement number: CN113516449B, discloses an information processing method and device for reducing construction noise, the method comprising: obtaining a first construction noise source. Obtaining volume information of the first construction noise source. Obtaining location information of the first construction noise source. Obtaining a predetermined area based on the volume information and location information of the first construction noise source. Obtaining first user information within the predetermined area. Obtaining work and rest information of the first user information. Classifying the volume information of the first construction noise source into levels according to the volume size to obtain a first noise level and a second noise level. Obtaining first construction time information of the first noise level and second construction time information of the second noise level based on the work and rest information of the first user information. This solves the problem of the impact of construction noise on people's work, study and life during construction.

[0004] In combination with the above scheme, it can be found that in the prior art, on the one hand, there is little specific analysis and specific treatment of the causes of noise in shopping malls. The noise inside shopping malls is mainly divided into equipment noise and human noise, and the equipment noise and human noise must be classified and treated in a targeted manner to effectively ensure the rationality of the noise treatment method of the shopping mall. The prior art ignores this level and it is difficult to ensure the rationality of the noise treatment method of the shopping mall, thereby reducing the quality of noise treatment, reducing customer satisfaction, affecting the proportion of repeat customers, and causing employees to have health problems such as hearing loss, increased stress, and sleep disorders. On the other hand, there is also a lack of attention to the urgency of noise treatment in each area of ​​the shopping mall. For example, the urgency of areas with large traffic and narrow passages is high, which makes it difficult to ensure the order of noise treatment in each area of ​​the shopping mall, and it is difficult to optimize the balance of noise in the shopping mall, which reduces the efficiency of noise treatment in the shopping mall. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent construction project operation and maintenance management platform and method, which solves the problems existing in the background technology.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The first aspect of the present invention provides an intelligent construction project operation and maintenance management platform, including: a shopping mall information acquisition module, which is used to divide the interior of the shopping mall into areas, obtain several sub-areas on each floor of the shopping mall, and obtain the internal noise information and external noise information of the shopping mall.

[0007] The shopping mall noise assessment module assesses abnormal noise parameters inside the shopping mall based on the internal noise information of the shopping mall.

[0008] The shopping mall noise processing module evaluates the noise anomaly solutions inside the mall based on the noise anomaly parameters inside the mall, and evaluates the noise anomaly solutions outside the mall based on the external noise information of the mall.

[0009] The display terminal displays the solutions to the noise anomalies inside the mall and the solutions to the noise anomalies outside the mall.

[0010] The second aspect of the present invention provides a method for executing the intelligent construction project operation and maintenance management platform described in any one of the present invention, comprising: S1. dividing the interior of the shopping mall into areas, obtaining a number of sub-areas on each floor of the shopping mall, and obtaining the internal noise information and external noise information of the shopping mall.

[0011] S2. Evaluate abnormal noise parameters inside the mall based on the internal noise information of the mall.

[0012] S3. Evaluate the noise anomaly solution inside the mall based on the noise anomaly parameters inside the mall, and evaluate the noise anomaly solution outside the mall based on the external noise information of the mall.

[0013] S4. Display the solutions to the noise anomaly inside the shopping mall and the solutions to the noise anomaly outside the shopping mall.

[0014] The beneficial effects of the present invention are: (1) The present invention obtains the internal noise information and external noise information of the shopping mall in the shopping mall information acquisition module, laying a foundation for the subsequent shopping mall noise assessment.

[0015] (2) In the shopping mall noise assessment module, the present invention first screens the noise abnormality sub-areas inside the shopping mall based on the internal noise information of the shopping mall and the overall decibel value of the sub-areas inside the shopping mall, thereby providing data support for the subsequent evaluation of the noise abnormality solution inside the shopping mall.

[0016] (3) In the shopping mall noise processing module, the present invention first determines the noise anomaly solution type of each noise anomaly sub-area of ​​the shopping mall based on the noise anomaly sub-area inside the shopping mall and combines the internal noise information of the shopping mall, so as to conduct targeted analysis on whether it is the equipment control method or the method of adding sound-absorbing materials, and classifies the equipment noise and human flow noise, thereby effectively ensuring the rationality of the shopping mall's noise processing method, improving the quality of noise processing, improving customer satisfaction, ensuring the proportion of repeat customers, and avoiding employees from experiencing health problems such as hearing loss, increased stress, and sleep disorders.

[0017] (4) The present invention generates a group label of the noise abnormality sub-area in the shopping mall in the shopping mall noise processing module, analyzes the urgency of the noise processing in each area in the shopping mall, ensures the rationality of the order of noise processing in each area in the shopping mall, optimizes the balance of noise in the shopping mall, and improves the efficiency of noise processing in the shopping mall.

[0018] (5) The present invention also analyzes the noise anomaly solutions outside the mall in the mall noise processing module, which not only reduces the internal noise of the mall, but also effectively blocks the spread of the external noise of the mall. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of the system structure connection of the present invention.

[0021] Figure 2 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the present invention provides an intelligent construction project operation and maintenance management platform, including: a shopping mall information acquisition module, a shopping mall noise assessment module, a shopping mall noise processing module and a display terminal.

[0024] It should be noted that the present invention also includes a database for storing the internal appropriate decibel value of the shopping mall, the decibel abnormality ratio coefficient threshold, the decibel threshold of each device, the decibel threshold of each replacement device corresponding to each device, the adjustment decibel parameter, the noise risk index interval corresponding to each sound-absorbing material, the additional sound absorption area and sound absorption thickness corresponding to the reference noise risk index, the additional sound absorption area corresponding to the unit increased noise risk index, the reduced sound absorption area corresponding to the unit reduced noise risk index, the additional green area corresponding to the unit increased noise risk index, and the reduced green area corresponding to the unit reduced noise risk index.

[0025] It should also be noted that the shopping mall information acquisition module is connected to the shopping mall noise assessment module, the shopping mall noise assessment module is connected to the shopping mall noise processing module, the shopping mall noise processing module is connected to the display terminal, and the database is respectively connected to the shopping mall noise assessment module and the shopping mall noise processing module.

[0026] The shopping mall information acquisition module is used to divide the interior of the shopping mall into areas, obtain a number of sub-areas on each floor of the shopping mall, and obtain the internal noise information and external noise information of the shopping mall.

[0027] In a specific embodiment of the present invention, the internal noise information includes the overall decibel value of each sub-area of ​​each layer in each detection period, the flow of people, the average length of stay per person, and the average decibel value of each associated device.

[0028] It should be noted that the overall decibel value of each sub-area on each floor of the mall in each detection period is obtained through the mall's online noise monitoring system, wherein the mall's online noise monitoring system is used to monitor the decibel value of each sub-area on each floor of the mall in real time, and to monitor the decibel value of the storage equipment in each sub-area on each floor in real time, wherein the storage equipment is the above-mentioned associated equipment.

[0029] It should also be noted that the monitoring system of the shopping mall is used to obtain the flow of people and the average length of stay of each person in each sub-area of ​​each floor of the shopping mall during each detection period.

[0030] The external noise information includes the overall decibel value of each detection area in each detection period.

[0031] It should be noted that the various detection areas of the shopping mall are specifically planned according to the area planning map of the shopping mall, with the landing center point of the shopping mall as the origin, and according to the set radius and detection distance, the shopping mall is evenly divided into several fan-shaped areas, and combined with the outer contour of the shopping mall, the fan-shaped part between the outer contour of the shopping mall and the origin is cut off to obtain the various detection areas of the shopping mall.

[0032] It should also be added that the set radius and detection distance are set specifically according to the management personnel of the shopping mall. For example, in order to improve the accuracy of noise detection outside the shopping mall, the set radius can be set smaller or the detection distance can be set longer, aiming to expand the number of detection areas or extend the length of the detection areas, so that the subsequent analysis of the detection areas is more accurate.

[0033] It should be understood that the overall decibel value of each detection area of ​​the shopping mall during each detection period is obtained through the traffic management platform.

[0034] The present invention obtains the internal noise information and external noise information of the shopping mall in the shopping mall information acquisition module, laying a foundation for the subsequent shopping mall noise evaluation.

[0035] The shopping mall noise assessment module assesses abnormal noise parameters inside the shopping mall based on the internal noise information of the shopping mall.

[0036] In a specific embodiment of the present invention, the specific evaluation method for evaluating the abnormal noise parameters inside the shopping mall is as follows: the overall decibel value of each sub-area on each floor in each detection period is extracted from the internal noise information of the shopping mall, and compared with the appropriate internal decibel value of the shopping mall stored in the database; if the overall decibel value of a sub-area on a floor of the shopping mall in a certain detection period is greater than the appropriate internal decibel value, then the detection period is recorded as a decibel abnormality detection period, and the decibel abnormality detection periods of each sub-area on each floor of the shopping mall are obtained by screening.

[0037] The number of decibel anomaly detection periods and the number of detection periods of each sub-area on each floor of the shopping mall are counted, and the number of decibel anomaly detection periods of each sub-area on each floor of the shopping mall is divided by the number of detection periods to obtain the decibel anomaly ratio coefficient of each sub-area on each floor of the shopping mall.

[0038] The decibel anomaly ratio coefficient of each sub-area on each floor of the shopping mall is compared with the decibel anomaly ratio coefficient threshold stored in the database. If the decibel anomaly ratio coefficient of a sub-area is greater than or equal to the decibel anomaly ratio coefficient threshold, the sub-area is recorded as a noise anomaly sub-area, and the noise anomaly sub-areas inside the shopping mall are screened and used as the noise anomaly parameters inside the shopping mall.

[0039] In the shopping mall noise assessment module, the present invention first screens the noise abnormality sub-areas inside the shopping mall according to the internal noise information of the shopping mall and the overall decibel value of the sub-areas inside the shopping mall, thereby providing data support for the subsequent evaluation of the noise abnormality solution inside the shopping mall.

[0040] The shopping mall noise processing module evaluates the noise anomaly solution inside the shopping mall based on the noise anomaly parameters inside the shopping mall, and evaluates the noise anomaly solution outside the shopping mall based on the external noise information of the shopping mall.

[0041] In a specific embodiment of the present invention, the specific evaluation method for evaluating the noise anomaly solution inside the shopping mall is as follows: based on each noise anomaly sub-area inside the shopping mall, combined with the overall decibel value, pedestrian flow, average dwelling time per person, and average decibel value of each associated equipment in each sub-area on each floor of the shopping mall during each detection period, the pedestrian flow, average dwelling time per person, and average decibel value of each associated equipment in each noise anomaly sub-area inside the shopping mall are obtained, and the noise anomaly solution type of each noise anomaly sub-area inside the shopping mall is determined, wherein the noise anomaly solution type is equipment noise control and adding sound-absorbing materials, and a group label for the noise anomaly sub-area inside the shopping mall is generated.

[0042] If the abnormality resolution type of a certain noise abnormality sub-area inside the shopping mall is equipment noise control, then the noise control equipment and noise control methods of the noise abnormality sub-area inside the shopping mall are evaluated to obtain a processing solution for the noise abnormality sub-area inside the shopping mall.

[0043] If the abnormal solution type for a certain noise abnormality sub-area inside the shopping mall is to add sound-absorbing materials, then the appropriate additional sound-absorbing materials, appropriate additional sound-absorbing area and sound-absorbing thickness of the noise abnormality sub-area inside the shopping mall are evaluated to obtain a solution for the noise abnormality sub-area inside the shopping mall.

[0044] The processing solutions for each noise anomaly sub-area inside the mall are summarized, and based on the group labels of the noise anomaly sub-areas inside the mall, the noise anomaly solution inside the mall is summarized.

[0045] In the shopping mall noise processing module, the present invention first determines the noise anomaly solution type of each noise anomaly sub-area of ​​the shopping mall according to each noise anomaly sub-area inside the shopping mall in combination with the internal noise information of the shopping mall, so as to carry out targeted analysis whether it is a device control method or a method of adding sound-absorbing materials, classify and process the equipment noise and human flow noise, effectively ensure the rationality of the shopping mall's noise processing method, improve the quality of noise processing, improve customer satisfaction, ensure the proportion of repeat customers, and avoid employees from hearing loss, increased stress, sleep disorders and other health problems.

[0046] In a specific embodiment of the present invention, the noise anomaly solution type of each noise anomaly sub-area inside the shopping mall is determined by a specific determination method as follows: the average decibel value of each associated device in each detection period of each noise anomaly sub-area of ​​the shopping mall is compared with the decibel threshold of each device stored in a database; if the average decibel value of all associated devices in each detection period is less than the decibel threshold of the corresponding device in the database, then the average decibel value is compared again with the decibel threshold of each replacement device corresponding to each device stored in the database; if the average decibel value of all associated devices in each detection period is less than the decibel threshold of the corresponding replacement device, then the noise anomaly solution type of the noise anomaly sub-area inside the shopping mall is determined to be the addition of sound-absorbing materials; otherwise, the noise anomaly solution type of the noise anomaly sub-area inside the shopping mall is determined to be equipment noise control.

[0047] In a specific embodiment of the present invention, the noise abnormal sub-area group label inside the shopping mall is generated by: based on the flow of people R in each noise abnormal sub-area inside the shopping mall i , Average length of stay per person M i , and obtain the sales volume T of each noise abnormal sub-area inside the mall from the mall operation background i 、Number of complaints about abnormal noise i , channel area S i After numerical processing, the processing emergency index ε of each noise abnormal sub-area inside the mall is obtained _0i ,in Wherein, i is the number of each noise abnormality sub-region, i=1, 2, ..., n, and n is any integer greater than 2.

[0048] Get the overall decibel value F of each noise abnormal sub-area inside the mall during each detection period im , combined with the appropriate decibel value inside the mall, through the noise risk index model Output the noise risk index ε of each noise abnormal sub-area inside the mall _1i , F′ is the appropriate decibel value inside the mall, m is the number of each detection period, m=1,2,...,l, l is any integer greater than 2, l is the number of detection periods, F i(m-1) is the overall decibel value of the i-th noise abnormality sub-area inside the mall during the m-1-th detection period.

[0049] If (ε _0i ≥ε′ _0 )∧(ε _1i ≥ε′ _1 ), then the noise anomaly sub-region is recorded as a noise anomaly sub-region type I region label, where ∧ is a logical symbol and .

[0050] like The noise anomaly sub-region is recorded as the noise anomaly sub-region second-category region label, where ∨ is the logical symbol or.

[0051] If (ε _0i <ε′ _0 )∧(ε _1i <ε′ _1 ), then the noise anomaly sub-region is recorded as the noise anomaly sub-region three-category region label.

[0052] The summary results include the first-category group label of the noise abnormality sub-area inside the shopping mall, the second-category group label of the noise abnormality sub-area, and the third-category group label of the noise abnormality sub-area.

[0053] It should be noted that, among the noise abnormality sub-area category one group label, the noise abnormality sub-area category two group label, and the noise abnormality sub-area category three group label, the importance of the noise abnormality sub-area category one group label is greater than the noise abnormality sub-area category two group label, and the importance of the noise abnormality sub-area category two group label is greater than the noise abnormality sub-area category three group label. In other words, the noise abnormality sub-area in the noise abnormality sub-area category one group label is more affected by the noise abnormality, while the noise abnormality sub-area in the noise abnormality sub-area category three group label is less affected by the noise abnormality. When the shopping mall is subsequently subjected to internal noise processing, the noise abnormality sub-area in the noise abnormality sub-area category one label can be processed first to reduce the impact of noise on the normal operation of the shopping mall.

[0054] The present invention generates a group label of noise abnormality sub-areas inside a shopping mall in a shopping mall noise processing module, analyzes the urgency of noise processing in each area in the shopping mall, ensures the rationality of the order of noise processing in each area in the shopping mall, optimizes the balance of noise in the shopping mall, and improves the efficiency of noise processing in the shopping mall.

[0055] In a specific embodiment of the present invention, the noise control devices and noise control methods of the noise abnormality sub-area inside the shopping mall are evaluated by a specific evaluation method as follows: the average decibel value of each associated device in the noise abnormality sub-area inside the shopping mall in each detection period is obtained, and the average value is processed to obtain the average decibel value of each associated device in the noise abnormality sub-area inside the shopping mall; if the average decibel value of an associated device is greater than the decibel threshold corresponding to the associated device stored in the database, the associated device is recorded as a noise control device; based on the decibel threshold of each replacement device corresponding to each device stored in the database, the decibel threshold of each replacement device corresponding to the noise control device is obtained, and the decibel threshold of each replacement device is subtracted from the average decibel value of the noise control device to obtain the decibel difference between the noise control device and each replacement device; if the decibel difference between the noise control device and a replacement device is greater than or equal to the adjustment decibel parameter stored in the database, the noise control method of the noise control device is recorded as a replacement method, and the replacement device is recorded as a pointing device of the noise control device; otherwise, the noise control method of the noise control device is recorded as an external interference method, and a silencer is installed.

[0056] In a specific embodiment of the present invention, the specific evaluation method for evaluating the appropriate additional sound absorbing material, the appropriate additional sound absorbing area and the sound absorbing thickness of the noise abnormal sub-area inside the shopping mall is: based on the noise risk index ε of each noise abnormal sub-area inside the shopping mall _1i , obtain the noise risk index range corresponding to each sound-absorbing material, the additional sound absorption area and sound absorption thickness corresponding to the reference noise risk index from the database, and screen the appropriate additional sound absorption materials for each noise abnormal sub-area inside the shopping mall and the additional sound absorption area SI' and sound absorption thickness corresponding to the reference noise risk index εi.

[0057] The appropriate additional sound absorption area model is used to output the appropriate additional sound absorption area for the noise abnormality sub-area inside the shopping mall. Where SI represents the appropriate additional sound absorption area for the noise abnormality sub-area inside the mall, εu is the noise risk index of the noise abnormality sub-area inside the mall, and SI _0 、SI _1 The increased sound absorption area corresponding to the unit increased noise risk index and the reduced sound absorption area corresponding to the unit reduced noise risk index are stored in the database respectively.

[0058] After similar treatment, the appropriate sound absorption thickness of the abnormal noise sub-area inside the shopping mall is output.

[0059] In a specific embodiment of the present invention, the noise anomaly solution outside the shopping mall is evaluated based on the external noise information of the shopping mall. The specific evaluation method is: extract the overall decibel value of each detection area in each detection period from the external noise information of the shopping mall, and divide it by the external decibel threshold stored in the database after averaging, so as to obtain the noise anomaly coefficient μ of each detection area of ​​the shopping mall. p , p is the number of each detection area, p=1,2,...,q, q is any integer greater than 2.

[0060] The suitable green area assessment model Output the suitable green area SV of each detection area of ​​the shopping mall p , where SV′ is the green area corresponding to the reference noise anomaly coefficient μ′, SV _0 SV _1 The increased green area corresponding to the unit increased noise risk index and the reduced green area corresponding to the unit reduced noise risk index stored in the database are respectively.

[0061] Summarize the suitable greening areas of each detection area of ​​the shopping mall and obtain the solution to the noise anomaly outside the shopping mall.

[0062] The present invention also analyzes the abnormal noise solution outside the shopping mall in the shopping mall noise processing module, which not only reduces the internal noise of the shopping mall, but also effectively blocks the spread of the external noise of the shopping mall.

[0063] The display terminal displays the abnormal noise solutions inside the mall and the abnormal noise solutions outside the mall.

[0064] Reference Figure 2 As shown, the second aspect of the present invention provides a method for executing the intelligent construction project operation and maintenance management platform described in any one of the present invention, including: S1. Dividing the interior of the shopping mall into areas to obtain several sub-areas on each floor of the shopping mall, and obtaining the internal noise information and external noise information of the shopping mall.

[0065] S2. Evaluate abnormal noise parameters inside the mall based on the internal noise information of the mall.

[0066] S3. Evaluate the noise anomaly solution inside the mall based on the noise anomaly parameters inside the mall, and evaluate the noise anomaly solution outside the mall based on the external noise information of the mall.

[0067] S4. Display the solutions to the noise anomaly inside the shopping mall and the solutions to the noise anomaly outside the shopping mall.

[0068] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent construction engineering operation and maintenance management platform, characterized in that: include: The mall information acquisition module is used to divide the mall into areas, obtain several sub-areas on each floor of the mall, and obtain the internal noise information and external noise information of the mall; The shopping mall noise assessment module assesses the abnormal noise parameters inside the shopping mall based on the internal noise information of the shopping mall; The shopping mall noise processing module evaluates the noise anomaly solution inside the shopping mall based on the noise anomaly parameters inside the shopping mall, and evaluates the noise anomaly solution outside the shopping mall based on the external noise information of the shopping mall; The display terminal displays the solutions to the noise anomalies inside the mall and the solutions to the noise anomalies outside the mall.

2. According to claim 1, the intelligent construction engineering operation and maintenance management platform is characterized in that: The internal noise information includes the overall decibel value of each sub-area of ​​each floor during each detection period, the flow of people, the average length of stay per person, and the average decibel value of each associated device; The external noise information includes the overall decibel value of each detection area in each detection period.

3. The intelligent construction engineering operation and maintenance management platform according to claim 2 is characterized in that: The specific evaluation method for evaluating the abnormal noise parameters inside the shopping mall is as follows: Extract the overall decibel value of each sub-area on each floor in each detection period from the internal noise information of the shopping mall, and compare it with the internal suitable decibel value of the shopping mall stored in the database, and screen out the decibel abnormal detection period of each sub-area on each floor of the shopping mall; Counting the number of decibel anomaly detection periods and the number of detection periods in each sub-area of ​​each floor of the shopping mall, and dividing the number of decibel anomaly detection periods in each sub-area of ​​each floor of the shopping mall by the number of detection periods, to obtain the decibel anomaly ratio coefficient of each sub-area of ​​each floor of the shopping mall; The decibel anomaly ratio coefficient of each sub-area on each floor of the shopping mall is compared with the decibel anomaly ratio coefficient threshold stored in the database. If the decibel anomaly ratio coefficient of a sub-area is greater than or equal to the decibel anomaly ratio coefficient threshold, the sub-area is recorded as a noise anomaly sub-area, and the noise anomaly sub-areas inside the shopping mall are screened and used as the noise anomaly parameters inside the shopping mall.

4. The intelligent construction engineering operation and maintenance management platform according to claim 3 is characterized in that: The specific evaluation method for evaluating the noise anomaly solution inside the shopping mall is as follows: Based on each noise abnormality sub-area inside the mall, combined with the overall decibel value, pedestrian flow, average length of stay per person, and average decibel value of each associated device in each sub-area on each floor of the mall during each detection period, the pedestrian flow, average length of stay per person, and average decibel value of each associated device in each noise abnormality sub-area inside the mall are obtained, and the noise abnormality solution type of each noise abnormality sub-area inside the mall is determined, where the noise abnormality solution type is equipment noise control and adding sound-absorbing materials, and a group label of the noise abnormality sub-area inside the mall is generated; If the abnormality resolution type of a certain noise abnormality sub-area inside the mall is equipment noise control, then evaluate the noise control equipment and noise control methods of the noise abnormality sub-area inside the mall to obtain a resolution for the noise abnormality sub-area inside the mall; If the abnormal solution type for a certain noise abnormal sub-area inside the mall is to add sound absorbing materials, then the appropriate additional sound absorbing materials, appropriate additional sound absorbing area and sound absorbing thickness of the noise abnormal sub-area inside the mall are evaluated to obtain a solution for the noise abnormal sub-area inside the mall; The processing solutions for each noise anomaly sub-area inside the mall are summarized, and based on the group labels of the noise anomaly sub-areas inside the mall, the noise anomaly solution inside the mall is summarized.

5. The intelligent construction engineering operation and maintenance management platform according to claim 4 is characterized in that: The specific determination method for determining the noise anomaly resolution type for each noise anomaly sub-area within the shopping mall is as follows: The average decibel value of each associated device in each noise abnormality sub-area of ​​the shopping mall in each detection period is compared with the decibel threshold of each device stored in the database. If the average decibel value of all associated devices in each detection period is less than the decibel threshold of the corresponding device in the database, then it is compared again with the decibel threshold of each replacement device corresponding to each device stored in the database. If the average decibel value of all associated devices in each detection period is less than the decibel threshold of the corresponding replacement device, then it is judged that the noise abnormality solution type for this noise abnormality sub-area inside the shopping mall is to add sound-absorbing materials; otherwise, it is judged that the noise abnormality solution type for this noise abnormality sub-area inside the shopping mall is equipment noise control.

6. The intelligent construction engineering operation and maintenance management platform according to claim 4, characterized in that: The specific method for generating the noise abnormality sub-area group labels inside the shopping mall is as follows: The flow rate R of each noise abnormal sub-area inside the mall i , Average length of stay per person M i , and obtain the sales volume T of each noise abnormal sub-area inside the mall from the mall operation background i 、Number of complaints about abnormal noise i , channel area S i After numerical processing, the processing emergency index ε of each noise abnormal sub-area inside the mall is obtained _0i ,in Where i is the number of each noise abnormal sub-region, i=1,2,...,n, n is any integer greater than 2; Get the overall decibel value F of each noise abnormal sub-area inside the mall during each detection period im , combined with the appropriate decibel value inside the mall, through the noise risk index model Output the noise risk index ε of each noise abnormal sub-area inside the mall _1i , F′ is the appropriate decibel value inside the mall, m is the number of each detection period, m=1,2,...,l, l is any integer greater than 2, l is the number of detection periods, F i(m-1) is the overall decibel value of the ith noise abnormality sub-area inside the mall during the m-1th detection period; If (ε _0i ≥ε′ _0 )∧(ε _1i ≥ε′ _1 ), then the noise abnormal sub-region is recorded as a noise abnormal sub-region type I region label, where ^ is a logical symbol and; like Then the noise abnormal sub-region is recorded as the noise abnormal sub-region type II region label, where ∨ is the logical symbol or; If (ε _0i <ε′ _0 )∧(ε _1i <ε′ _1 ), then the noise abnormal sub-region is recorded as the noise abnormal sub-region three-category region label; The summary results include the first-category group label of the noise abnormality sub-area inside the shopping mall, the second-category group label of the noise abnormality sub-area, and the third-category group label of the noise abnormality sub-area.

7. The intelligent construction engineering operation and maintenance management platform according to claim 4 is characterized in that: The specific evaluation method for evaluating the noise control equipment and noise control methods of the noise abnormality sub-area inside the shopping mall is as follows: The average decibel value of each associated device in the noise abnormality sub-area inside the shopping mall in each detection period is obtained, and the average decibel value is processed to obtain the average decibel value of each associated device in the noise abnormality sub-area inside the shopping mall. If the average decibel value of an associated device is greater than the decibel threshold corresponding to the associated device stored in the database, the associated device is recorded as a noise control device. Based on the decibel thresholds of each replacement device corresponding to each device stored in the database, the decibel thresholds of each replacement device corresponding to the noise control device are obtained, and the decibel thresholds of each replacement device are subtracted from the average decibel value of the noise control device to obtain the decibel difference between the noise control device and each replacement device. If the decibel difference between the noise control device and a replacement device is greater than or equal to the adjustment decibel parameter stored in the database, the noise control mode of the noise control device is recorded as the replacement mode, and the replacement device is recorded as the pointing device of the noise control device. Otherwise, the noise control mode of the noise control device is recorded as the external interference mode, and a silencer is installed.

8. The intelligent construction engineering operation and maintenance management platform according to claim 4, characterized in that: The specific evaluation method for evaluating the appropriate additional sound absorbing materials, the appropriate additional sound absorbing area and the sound absorbing thickness of the noise abnormal sub-area inside the shopping mall is: Noise risk index ε based on each noise abnormality sub-area inside the mall _1i , obtain the noise risk index range corresponding to each sound-absorbing material, the additional sound absorption area and sound absorption thickness corresponding to the reference noise risk index from the database, and screen the appropriate additional sound absorption materials for each abnormal noise sub-area inside the shopping mall and the additional sound absorption area SI' and sound absorption thickness corresponding to the reference noise risk index εi; The appropriate additional sound absorption area model is used to output the appropriate additional sound absorption area for the noise abnormality sub-area inside the shopping mall. Where SI represents the appropriate additional sound absorption area for the noise abnormality sub-area inside the mall, εu is the noise risk index of the noise abnormality sub-area inside the mall, and SI _0 、SI _1 The increased sound absorption area corresponding to the unit increased noise risk index and the reduced sound absorption area corresponding to the unit reduced noise risk index stored in the database are respectively; After similar treatment, the appropriate sound absorption thickness of the abnormal noise sub-area inside the shopping mall is output.

9. The intelligent construction engineering operation and maintenance management platform according to claim 2, characterized in that: The solution to the noise anomaly outside the shopping mall is evaluated based on the external noise information of the shopping mall. The specific evaluation method is as follows: The overall decibel value of each detection area in each detection period is extracted from the external noise information of the shopping mall, and the decibel value is averaged and divided by the external decibel threshold stored in the database to obtain the noise anomaly coefficient μ of each detection area of ​​the shopping mall. p , p is the number of each detection area, p = 1, 2, ..., q, q is any integer greater than 2; The suitable green area assessment model Output the suitable green area SV of each detection area of ​​the shopping mall p , where SV′ is the green area corresponding to the reference noise anomaly coefficient μ′, SV _0 SV _1 The green area increase corresponding to the unit noise risk index and the green area reduction corresponding to the unit noise risk index stored in the database are respectively: Summarize the suitable greening areas of each detection area of ​​the shopping mall and obtain the solution to the noise anomaly outside the shopping mall.

10. A method for executing the intelligent construction engineering operation and maintenance management platform according to any one of claims 1 to 9, characterized in that: include: S1. Divide the interior of the mall into regions, obtain several sub-regions on each floor of the mall, and obtain the internal noise information and external noise information of the mall; S2. Evaluate abnormal noise parameters inside the mall based on the internal noise information of the mall; S3. Evaluate the noise anomaly solution inside the mall based on the noise anomaly parameters inside the mall, and evaluate the noise anomaly solution outside the mall based on the external noise information of the mall; S4. Display the solutions to the noise anomaly inside the shopping mall and the solutions to the noise anomaly outside the shopping mall.

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