Building intelligent electrical control system

Abstract

The invention discloses an intelligent electrical control system for a building. The intelligent electrical control system comprises a visual monitoring module, a self-diagnosis module, a safety guarantee module, a learning optimization module and an open platform module, compared with a traditional building electrical control system, the building electrical control system is provided with the anomaly detection unit and the health evaluation unit, automatic fault diagnosis can be carried out through a data analysis technology, related processing suggestions are provided, the maintenance cost of a building is reduced, and the reliability of the system is improved; the strict identity authentication unit and the network security unit are arranged, so that the operation security of the building electrical equipment is ensured, and external attack threats are effectively prevented; the learning optimization module supports adaptive scheduling and can perform automatic adjustment according to the actual situation and workload of the building, so that the calculation efficiency and the response speed of the building electrical equipment are improved; therefore, the technical problem that an existing building intelligent electrical control system still has defects in the aspects of self-diagnosis, safety and self-adaptive scheduling optimization is solved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent electrical control, in particular to an intelligent electrical control system for a building. Background Art

[0002] In the development process of today's society, building intelligence has emerged as a very important trend and development direction. It has an important positive effect on improving the comprehensive efficiency of buildings, optimizing the user experience, and achieving energy conservation and emission reduction. As the key support for this intelligent trend, the building intelligent electrical control system is an intelligent electrical equipment control system built on the basis of Internet of Things technology. It aims to realize the accurate monitoring, efficient control and automatic management of various electrical equipment in the building in all directions, thereby ensuring the stable and reliable operation of the entire building electrical system.

[0003] Some building intelligent electrical control systems still have obvious imperfections in their self-diagnosis functions. Although the system theoretically has certain fault detection and diagnosis capabilities, in the actual operation process, when faced with many common problems, it is often unable to independently complete the diagnosis and repair process, but requires manual intervention to solve. For example, when electrical equipment has some relatively common fault conditions such as slight abnormal fluctuations in circuit parameters and intermittent failure of some sensors, the system may only be able to send out a fault prompt signal, but cannot further accurately determine the root cause of the fault, let alone automatically take effective repair measures. It must rely on professional maintenance personnel to rush to the site and use their experience and professional tools to conduct troubleshooting and repairs.

[0004] Existing intelligent electrical control systems for buildings have significant shortcomings in adaptive scheduling and optimization algorithms. Specifically, during operation, the system lacks effective mechanisms and algorithmic logic that can automatically and accurately adjust according to the actual operating conditions of the building (such as differences in power load in different time periods, changes in equipment usage in different areas, etc.) and actual workload.

[0005] Due to the lack of such adaptive scheduling and optimization capabilities, it is difficult for electrical equipment to achieve the optimal operating status configuration when facing complex and changeable building usage scenarios. For example, during the daytime on weekdays, the office area is densely populated and a large number of electrical equipment are activated. At this time, the electrical system should automatically allocate resources to give priority to the efficient operation of related electrical equipment in the office area, and reasonably adjust the operating parameters of equipment in other non-critical areas to meet the overall power demand and achieve energy-saving optimization; at night or on holidays, when there are few people, the system should automatically reduce the operating power of some equipment or put it into standby mode to reduce unnecessary energy consumption. But the reality is that existing systems are often unable to make such adaptive adjustments, which leads to low computing efficiency of electrical equipment and inability to quickly respond to changes in power demand, affecting the operating performance and energy efficiency of the entire building electrical system. Summary of the invention

[0006] The purpose of the present invention is to provide a building intelligent electrical control system to solve the technical difficulty raised in the above background technology that "the existing building intelligent electrical control systems still have defects in self-diagnosis, safety, and adaptive scheduling optimization".

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A building intelligent electrical control system comprises a visual monitoring module, a self-diagnosis module, a security module, a learning optimization module and an open platform module. The visual monitoring module enables an administrator to intuitively understand the system operation status and operate and control the system through real-time monitoring and visual display; the self-diagnosis module introduces artificial intelligence algorithms to build online fault detection and self-diagnosis, and promptly issues alarms and provides solutions when abnormal situations occur, thereby improving operation and maintenance efficiency and reducing maintenance costs; the security module integrates security measures to ensure the security of the system, and prevents malicious attacks and unauthorized access by using encrypted communication methods and supporting multiple verification and identity authentication technologies; the learning optimization module utilizes machine learning algorithms to optimize the scheduling and management of the system, and automatically predicts and adjusts through analysis of historical data and user behavior, thereby improving the stability and response speed of the system; the open platform module provides an open API interface and standardized data format to facilitate the integration of other building systems, and provides related supporting technical support and services to improve the practicality and compatibility of the entire system.

[0009] The visual monitoring module includes a real-time monitoring unit, which uses real-time monitoring technology to present the operating status of each electrical equipment in the building on the monitor and send alarm information in time so that the administrator can respond quickly and deal with related problems.

[0010] The visual monitoring module also includes a data visualization unit, which presents the data in the system to the administrator in the form of charts and reports, and updates them in real time, so that the administrator can quickly understand the current operating status of the building intelligent electrical control system.

[0011] The self-diagnosis module includes an anomaly detection unit, which performs automatic diagnosis of system faults based on data analysis and anomaly detection technology, and provides solutions for handling related anomalies to improve operation and maintenance efficiency.

[0012] The self-diagnosis module also includes a health assessment unit, which evaluates various system parameters based on the overall health status of the system, actively discovers potential problems and proposes improvement plans, thereby improving the reliability and stability of the system.

[0013] The security module includes a network security unit, which ensures the security of the intranet and effectively prevents external attacks by adopting VPN, firewall, and encrypted communication technologies.

[0014] The security module also includes an identity authentication unit, which supports multiple identity authentication technologies, including password and fingerprint recognition methods, to ensure that only authorized personnel can access the system and perform related operations.

[0015] The learning optimization module includes a data mining unit, which extracts valuable information by mining and analyzing system historical data to provide decision support and reference basis for operation management personnel.

[0016] The learning optimization module also includes an adaptive scheduling unit, which uses an intelligent scheduling method and an optimization algorithm to automatically adjust system parameters according to actual building conditions, thereby improving the computing efficiency and response speed of the system.

[0017] The open platform module includes a data standardization unit and an interface development unit. The data standardization unit standardizes the data formats generated by various sensors and devices to facilitate interaction and collaboration during integration with other systems; the interface development unit provides developers with open API interface documents and supporting development tools to facilitate secondary development, making the system more flexible and diversified.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] (1) More intelligent self-diagnosis and maintenance capabilities: Compared with traditional building electrical control systems, this system is equipped with an anomaly detection unit and a health assessment unit, which can automatically diagnose faults through data analysis technology and provide relevant processing suggestions, greatly reducing the maintenance cost of the building and improving the reliability of the system.

[0020] (2) Higher security: By setting up strict identity authentication units and network security units, the safety of building electrical equipment operation is ensured and external attack threats are effectively prevented.

[0021] (3) Stronger adaptability: The learning optimization module supports adaptive scheduling and can automatically adjust according to the actual situation and workload of the building, thereby improving the computing efficiency and response speed of the building electrical equipment.

[0022] (4) More efficient data processing capabilities: Advanced data mining and analysis technologies are used to quickly process the building’s electrical equipment data, thereby improving data processing capabilities and decision-making quality.

[0023] (5) More flexible interface design: The open platform module standardizes the electrical data format generated by various sensors and devices, making it easier for other systems and devices to integrate and work together, thereby improving the overall operating efficiency of the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of the system structure of a building intelligent electrical control system of the present invention;

[0025] Figure 2 This is a detailed diagram of the system structure of a building intelligent electrical control system of the present invention.

[0026] 1-Visual monitoring module; 2-Self-diagnosis module; 3-Safety assurance module; 4-Learning optimization module; 5-Open platform module; 6-Real-time monitoring unit; 7-Data visualization unit; 8-Anomaly detection unit; 9-Health assessment unit; 10-Network security unit; 11-Identity authentication unit; 12-Data mining unit; 13-Adaptive scheduling unit; 14-Data standardization unit; 15-Interface development unit. DETAILED DESCRIPTION

[0027] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices consistent with some aspects of the present disclosure as detailed in the appended claims.

[0028] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. 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.

[0029] Embodiment 1

[0030] like Figure 1 to Figure 2 As shown, a building intelligent electrical control system includes a visual monitoring module 1, a self-diagnosis module 2, a safety assurance module 3, a learning optimization module 4 and an open platform module 5.

[0031] The visual monitoring module 1 enables the administrator to intuitively understand the system operation status and operate and control the system through real-time monitoring and visual display. The visual monitoring module 1 includes a real-time monitoring unit 6 and a data visualization unit 7; the real-time monitoring unit 6 uses real-time monitoring technology to present the operation status of each electrical equipment in the building on the monitor, and sends alarm information in time, so that the administrator can respond quickly and deal with related problems; the data visualization unit 7 presents the data in the system to the administrator in the form of charts and reports, and updates it in real time, so that the administrator can quickly understand the current operation status of the building intelligent electrical control system.

[0032] The self-diagnosis module 2 introduces artificial intelligence algorithms to build online fault detection and self-diagnosis, and promptly issues alarms and provides solutions when abnormal situations occur, thereby improving operation and maintenance efficiency and reducing maintenance costs. The self-diagnosis module 2 includes an abnormality detection unit 8 and a health assessment unit 9; the abnormality detection unit 8 automatically diagnoses system faults based on data analysis and abnormality detection technology, and at the same time provides solutions for related abnormalities to improve operation and maintenance efficiency; the health assessment unit 9 evaluates various system parameters based on the overall health status of the system, actively discovers potential problems and proposes improvement plans, thereby improving the reliability and stability of the system.

[0033] The security module 3 integrates security measures to ensure the security of the system, and prevents malicious attacks and unauthorized access by using encrypted communication methods and supporting multiple verification and identity authentication technologies. The security module 3 includes a network security unit 10 and an identity authentication unit 11; the network security unit 10 ensures the security of the intranet and effectively prevents external attacks by adopting VPN, firewall, and encrypted communication technologies; the identity authentication unit 11 supports multiple identity authentication technologies, including password and fingerprint recognition methods, to ensure that only authorized personnel can access the system and perform related operations.

[0034] The learning optimization module 4 uses machine learning algorithms to optimize the scheduling and management of the system, and automatically predicts and adjusts by analyzing historical data and user behavior, thereby improving the stability and response speed of the system. The learning optimization module 4 includes a data mining unit 12 and an adaptive scheduling unit 13; the data mining unit 12 extracts valuable information by mining and analyzing the system's historical data, and provides decision support and reference basis for operation management personnel; the adaptive scheduling unit 13 uses intelligent scheduling methods and optimization algorithms to automatically adjust system parameters according to the actual situation of the building, thereby improving the computing efficiency and response speed of the system.

[0035] The open platform module 5 provides an open API interface and a standardized data format to facilitate the integration of building automation systems, access control systems, and security systems, and provides relevant supporting technical support and services to improve the practicality and compatibility of the entire system. The open platform module 5 includes a data standardization unit 14 and an interface development unit 15; the data standardization unit 14 standardizes the data formats generated by various sensors and devices to facilitate interaction and collaboration during integration of other systems; the interface development unit 15 provides developers with open API interface documents and supporting development tools to facilitate secondary development, making the system more flexible and diversified.

[0036] Compared with the traditional building electrical control system, the present invention is equipped with an anomaly detection unit 8 and a health assessment unit 9, which can automatically diagnose faults through data analysis technology and provide relevant processing opinions, greatly reducing the maintenance cost of the building and improving the reliability of the system; by setting a strict identity authentication unit 11 and a network security unit 10, the safety of the operation of the building electrical equipment is ensured, and external attack threats are effectively prevented; and the learning optimization module 4 supports adaptive scheduling, which can be automatically adjusted according to the actual situation and workload of the building, thereby improving the computing efficiency and response speed of the building electrical equipment; furthermore, advanced data mining and analysis technology is adopted to quickly process the electrical equipment data of the building, thereby improving the data processing capability and decision-making quality; finally, the open platform module 5 standardizes the electrical data format generated by various sensors and equipment, so that other systems and equipment can be more conveniently integrated and work together, improving the overall operation efficiency of the building; therefore, the technical difficulties of the existing building intelligent electrical control system in self-diagnosis, safety, and adaptive scheduling optimization are well solved.

[0037] Embodiment 2

[0038] like Figure 1 to Figure 2 As shown, when a commercial building needs to use the building intelligent electrical control system proposed by the present invention, the difference from the first embodiment is that:

[0039] A building intelligent electrical control system comprises a visual monitoring module 1, a self-diagnosis module 2, a safety assurance module 3, a learning optimization module 4 and an open platform module 5.

[0040] The visual monitoring module 1 enables the administrator to intuitively understand the system operation status and operate and control the system through real-time monitoring and visual display. The visual monitoring module 1 includes a real-time monitoring unit 6 and a data visualization unit 7; the real-time monitoring unit 6 uses modern charts and reports to present the operation status, safety and energy consumption data of the electrical equipment in the commercial building to the administrator, and updates them at any time; the data visualization unit 7 uses real-time monitoring technology for electrical equipment operation to display the operation status of each device on the monitor, and sends alarm information in time to ensure the normal operation of the electrical equipment. It also supports health assessments for specific equipment and provides improvement suggestions.

[0041] The self-diagnosis module 2 introduces artificial intelligence algorithms to build online fault detection and self-diagnosis, and promptly issues alarms and provides solutions when abnormal situations occur, thereby improving operation and maintenance efficiency and reducing maintenance costs. The self-diagnosis module 2 includes an abnormality detection unit 8 and a health assessment unit 9; the abnormality detection unit 8 uses advanced data analysis and abnormality detection technology to automatically diagnose faults of electrical equipment in the business building, and provides corresponding abnormality handling solutions, thereby reducing the maintenance cost of the business building and improving the reliability of its electrical equipment; the health assessment unit 9 systematically evaluates various parameters based on the overall health status of the business building's electrical system, actively discovers potential problems and puts forward improvement suggestions, and provides decision support and reference basis for the subsequent operation of the business building's electrical system.

[0042] The security module 3 integrates security measures to ensure the security of the system, and prevents malicious attacks and unauthorized access by using encrypted communication methods and supporting multiple verification and identity authentication technologies. The security module 3 includes a network security unit 10 and an identity authentication unit 11; the network security unit 10 uses VPN, firewall and encrypted communication technology to ensure the internal network security of the electrical equipment in the commercial building and effectively prevent external attacks; the identity authentication unit 11 supports multiple identity authentication technologies, including passwords and fingerprints, to ensure that only authorized personnel can access the system and perform related operations.

[0043] The learning optimization module 4 utilizes machine learning algorithms to optimize the scheduling and management of the system, and automatically predicts and adjusts by analyzing historical data and user behavior, thereby improving the stability and response speed of the system. The learning optimization module 4 includes a data mining unit 12 and an adaptive scheduling unit 13; the data mining unit 12 analyzes the historical data of the electrical system of the commercial building to extract meaningful information to provide decision support and reference basis for the managers of the commercial building; the adaptive scheduling unit 13 uses intelligent scheduling methods and optimization algorithms to automatically adjust system parameters according to the actual situation of the electrical system of the commercial building, thereby improving the computing efficiency and response speed of the system. These optimizations will greatly improve the operating efficiency and reliability of the electrical system of the commercial building.

[0044] The open platform module 5 provides an open API interface and a standardized data format to facilitate the integration of other building systems, and provides relevant supporting technical support and services to improve the practicality and compatibility of the entire system. The open platform module 5 includes a data standardization unit 14 and an interface development unit 15; the data standardization unit 14 standardizes the electrical data formats generated by various sensors and devices to facilitate interaction and collaboration when integrated with other systems; the interface development unit 15 provides an open API interface document and related development tools, so that developers can perform secondary development, thereby providing more complex functions for the electrical control system of the commercial building and improving the operational efficiency of the electrical equipment of the commercial building.

[0045] Compared with the traditional building electrical control system, the present invention is equipped with an anomaly detection unit 8 and a health assessment unit 9, which can automatically diagnose faults through data analysis technology and provide relevant processing opinions, greatly reducing the maintenance cost of the building and improving the reliability of the system; by setting a strict identity authentication unit 11 and a network security unit 10, the safety of the operation of the building electrical equipment is ensured, and external attack threats are effectively prevented; and the learning optimization module 4 supports adaptive scheduling, which can be automatically adjusted according to the actual situation and workload of the building, thereby improving the computing efficiency and response speed of the building electrical equipment; furthermore, advanced data mining and analysis technology is adopted to quickly process the electrical equipment data of the building, thereby improving the data processing capability and decision-making quality; finally, the open platform module 5 standardizes the electrical data format generated by various sensors and equipment, so that other systems and equipment can be more conveniently integrated and work together, improving the overall operation efficiency of the building; therefore, the technical difficulties of the existing building intelligent electrical control system in self-diagnosis, safety, and adaptive scheduling optimization are well solved.

Claims

1. A building intelligent electrical control system, characterized in that: The system comprises a visual monitoring module (1), a self-diagnosis module (2), a security module (3), a learning optimization module (4) and an open platform module (5). The visual monitoring module (1) enables the administrator to intuitively understand the system operation status and operate and control the system through real-time monitoring and visual display; the self-diagnosis module (2) introduces artificial intelligence algorithms to build online fault detection and self-diagnosis, and promptly issues alarms and provides solutions when abnormal situations occur, thereby improving operation and maintenance efficiency and reducing maintenance costs; the security module (3) integrates security measures to ensure the security of the system, and prevents malicious attacks and unauthorized access by using encrypted communication methods and supporting multiple authentication technologies; the learning optimization module (4) uses machine learning algorithms to optimize the scheduling and management of the system, and automatically predicts and adjusts by analyzing historical data and user behavior, thereby improving the stability and response speed of the system; the open platform module (5) provides an open API interface and a standardized data format to facilitate the integration of other building systems, and provides related supporting technical support and services to improve the practicality and compatibility of the entire system.

2. A building intelligent electrical control system according to claim 1, characterized in that: The visual monitoring module (1) comprises a real-time monitoring unit (6). The real-time monitoring unit (6) uses real-time monitoring technology to present the operating status of each electrical device in the building on the monitor and sends alarm information in a timely manner, so that the administrator can respond quickly and deal with related problems.

3. A building intelligent electrical control system according to claim 2, characterized in that: The visual monitoring module (1) also includes a data visualization unit (7), which presents the data in the system to the administrator in the form of charts and reports, and updates them in real time, so that the administrator can quickly understand the current operating status of the building intelligent electrical control system.

4. The intelligent building electrical control system according to claim 1, characterized in that: The self-diagnosis module (2) comprises an abnormality detection unit (8), which performs automatic diagnosis of system faults based on data analysis and abnormality detection technology, and provides solutions for handling related abnormalities, thereby improving operation and maintenance efficiency.

5. A building intelligent electrical control system according to claim 4, characterized in that: The self-diagnosis module (2) also includes a health assessment unit (9), which evaluates various system parameters based on the overall health status of the system, actively discovers potential problems and proposes improvement plans, thereby improving the reliability and stability of the system.

6. The intelligent building electrical control system according to claim 1, characterized in that: The security guarantee module (3) comprises a network security unit (10), and the network security unit (10) ensures the security of the internal network and effectively prevents external attacks by adopting technical means such as VPN, firewall and encrypted communication.

7. A building intelligent electrical control system according to claim 6, characterized in that: The security module (3) further comprises an identity authentication unit (11), wherein the identity authentication unit (11) supports multiple identity authentication technologies, including password and fingerprint recognition methods, to ensure that only authorized personnel can access the system and perform related operations.

8. The intelligent building electrical control system according to claim 1, characterized in that: The learning optimization module (4) comprises a data mining unit (12), and the data mining unit (12) extracts valuable information by mining and analyzing system historical data, thereby providing decision support and reference basis for operation management personnel.

9. A building intelligent electrical control system according to claim 8, characterized in that: The learning optimization module (4) also includes an adaptive scheduling unit (13), which uses an intelligent scheduling method and an optimization algorithm to automatically adjust system parameters according to actual building conditions, thereby improving the calculation efficiency and response speed of the system.

10. The intelligent building electrical control system according to claim 1, characterized in that: The open platform module (5) comprises a data standardization unit (14) and an interface development unit (15); the data standardization unit (14) standardizes the data formats generated by various sensors and devices to facilitate interaction and collaboration when other systems are integrated; the interface development unit (15) provides developers with open API interface documents and supporting development tools to facilitate secondary development, making the system more flexible and diversified.

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