WO2024040738A1

WO2024040738A1 - Smart park management method and management platform

Info

Publication number: WO2024040738A1
Application number: PCT/CN2022/127633
Authority: WO
Inventors: 刘铄
Original assignee: 刘铄
Priority date: 2022-08-23
Filing date: 2022-10-26
Publication date: 2024-02-29
Also published as: CN115393142A

Abstract

The present invention relates to a smart park management method and management platform. The method comprises: constructing an all-real three-dimensional digital graphical model; acquiring data to be monitored in a preset range of a park; monitoring and analyzing the data to be monitored by means of a preset PHM system, comparing the data to be monitored with historical operation experience data, and before a deviation occurs in the data to be monitored, determining that an abnormality will occur in the data to be monitored and performing early warning; and displaying key operation data, an abnormal position, early warning information and an intervention means. In the present invention, by providing the PHM system, the operation state of a monitoring subject in the preset range of the park can be monitored, operation trend state analysis is performed in accordance with the historical operation experience data, and when the operation result trend state is a key condition in which a fault will occur, an early warning function is enabled in advance, so that an operator can perform preventive intervention in an a timely manner, thereby continuously guaranteeing operation of various management services of the park, preventing various services of the park from stopping operating, and guaranteeing continuous normal operation of the park.

Description

Smart park management methods and management platform

Technical field

The invention belongs to the technical field of management methods, and specifically relates to a smart park management method and a management platform.

Background technique

In related technologies, most smart parks adopt a preset management method: through certain types of Internet of Things collection and sensing means. When certain types of business facts in the park have become abnormal, the collection and sensing of the facts will trigger an alarm and arrange for adverse results. The technical route for follow-up personnel and equipment is solved to carry out the daily operation and management of the entire park.

However, the above-mentioned management methods within the preset scope of smart parks cannot use scientifically deployed monitoring, collection and analysis methods, combined with various historical park operation and management experience data in the past, to target the current collection of real-time multi-type data before specific adverse consequences occur. , analyze the operating trend status, and issue early warnings to park operation managers and users when the trend status of the operation results tends to the critical situation of imminent failure. Nor can preventive intervention be carried out in a timely manner after early warning through means such as personnel and equipment, to troubleshooting points where adverse situations are about to occur, so as to ensure the continuous operation of various management services in the park, avoid the shutdown of various services in the park, and ensure the continued normal operation of the park. smart park method functions.

Contents of the invention

In view of this, the purpose of the present invention is to overcome the shortcomings of the existing technology and provide a smart park management method to solve the problem in the existing technology that the smart park cannot ensure the continuous operation of various management services in the park.

In order to achieve the above objectives, the present invention adopts the following technical solution: a smart park management method, including: constructing a fully realistic three-dimensional digital graphic model for various scenes within the preset range of the park that needs to be managed on a visual interface;

Obtain the data to be measured within the preset range of the park;

Monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested with historical operating experience data, determine whether the data to be tested is about to deviate, and determine whether the data to be tested will deviate before the deviation occurs. If the data to be tested is about to become abnormal, an early warning will be issued;

Key operating data, abnormal locations, early warning information and intervention methods are displayed in the graphical model through a visual interface.

Further, the monitoring and analysis of the data to be measured through the preset PHM system includes:

Obtain the historical operation experience data of various scenarios within the preset range of the park, and import the historical operation experience data into the PHM system as basic data classification;

Compare the data to be measured with the base data.

Further, the basic data also includes preset early warning key values; and comparing the data to be measured with the basic data includes:

If the data to be tested is compared with the historical operating experience data and it is determined that the data to be tested is abnormal, then the data to be tested is compared with the early warning key value; and/or

At the same time, the data to be tested is compared with historical operating experience data, and the data to be tested is compared with the early warning key value.

Further, the standard range of the data is determined based on historical operating experience data, and it is judged whether the data to be tested is about to deviate. Before the data to be tested deviates, if it is determined that the data to be tested is about to be abnormal, an early warning is performed. ,include:

For different scenarios and different applications, compare historical operating experience data and early warning key values at the same time; specifically include:

When the change trend status of the data to be measured in a preset time period in the future exceeds the standard range, it is determined that the data to be measured will be abnormal, and an early warning is issued; or

When the change trend state of the data to be measured in the preset time period in the future reaches the early warning key value, it is determined that the data to be measured will be abnormal, and an early warning is issued; or

When the change trend status of the data to be measured in the preset time period in the future exceeds the standard range, the data to be measured is compared with the early warning key value. When the data to be measured is in the preset time period in the future, When the changing trend state reaches the pre-warning key value and it is determined that the data to be measured is abnormal, an early warning will be issued;

Before a deviation occurs in the data to be measured, an early warning is provided based on the scenario corresponding to the abnormality, and the key operation data and intervention steps that need to be displayed and set according to the early warning information are displayed through a visual interface.

Furthermore, it also includes:

Store the monitored object information and intervention process data of each intervention into the database of the PHM system to update the database to determine the operational reliability of the monitored object within the preset time;

The storage is to select a corresponding storage method according to the scenario, and the storage method includes real-time storage, staged storage, post-completion storage and external data entry storage.

Further, the acquisition of data to be measured within the preset range of the park includes:

Obtain data in the database through system software probes and/or collect operating data of the monitored object through sensors installed on the monitored object;

The operating data of the monitored object is determined as the data to be measured.

Furthermore, in the visual management front-end platform, firstly perform full-real three-dimensional digital graphical modeling of various park scenes that need to be managed, and then use the relevant intervention business data output by the PHM system to correspond to the intervention business one by one. The data forms a data link with each corresponding collection device and the collected business data; and this link is combined with data and graphics to display intuitive visual effects on a modern visual management front-end platform.

Further, the visual interface includes a variety of data display methods, and the various data display methods include:

Data display, including collected data to be tested, normal business monitoring data, abnormal business monitoring data, and intervention business data;

Chart display, based on the different attributes of the monitored objects, uses data charts, column charts, bar charts, pie charts, line charts, trend status charts, area charts, quadrant charts, surface charts, tree charts, radar charts, Histogram, box plot, waterfall chart, funnel chart, combination chart or dynamic chart for display;

Color display, using multiple colors to differentiate data color display of various data elements;

Media display is used to provide intervention steps for monitoring data and key early warning data. Graphic alarms, sound alarms and vibration alarms are multi-dimensional notifications based on various display media.

Further, the collection equipment includes: sensor group, QR code reader and writer, RFID reader and writer, camera, GPS, M2M terminal and system software probe.

The embodiment of this application provides a smart park management platform, including:

The building module is used to build a fully realistic three-dimensional digital graphic model of various scenes within the preset range of the park that needs to be managed on the visual interface;

The acquisition module is used to obtain the data to be measured within the preset range of the park;

The analysis module is used to monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested and historical operating experience data, and determine whether the data to be tested is about to deviate. Before deviation occurs, if it is determined that the data to be measured will be abnormal, an early warning will be issued;

A display module is used to display key operation data, abnormal locations, early warning information and intervention means in the graphical model through a visual interface.

By adopting the above technical solutions, the beneficial effects that can be achieved by the present invention include:

By combining visual management with the PHM system, this application can use monitoring collection and analysis methods, combined with various historical park operation and management experience data, to analyze the current real-time multi-type data collected, and analyze the operation trend status, and use the operation results as The trend status can provide early warning to park operation managers and users before critical situations that are about to occur. It also has the function of carrying out preventive intervention at fault points where adverse situations are about to occur through personnel, equipment and other means in a timely manner after early warning. And through preventive intervention, the various management services in the park can continue to operate, avoid the shutdown of various services in the park, and ensure the continued normal operation of the park.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic diagram of the steps of a smart park management method of the present invention;

Figure 2 is a schematic structural diagram of a smart park management platform system of the present invention;

Figure 3 is a schematic structural diagram of the PHM system provided by the present invention;

Figure 4 is a schematic structural diagram of a smart park management platform provided by the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. Obviously, the described embodiments are only some of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other implementations obtained by those of ordinary skill in the art without any creative work fall within the scope of protection of the present invention.

A specific smart park management method and management platform provided in the embodiment of this application will be introduced below with reference to the accompanying drawings.

As shown in Figure 1, the smart park management method provided in the embodiment of this application includes:

S101, construct a fully realistic three-dimensional digital graphic model for various scenes within the preset range of the park that needs to be managed on the visual interface;

Specifically, within the modern visual management front-end platform, this application first conducts full-real three-dimensional digital graphical modeling of various scenes in the park that need to be managed based on the objective principle of physical consistency. Then, according to the principle of one-to-one correspondence, the relevant intervention business data output by the PHM system is linked to each corresponding collection device and its collected business data in a one-to-one correspondence. It can be understood that the collection device provided in this application can be a system software probe or an Internet of Things device, such as a sensor component, etc., and this link can be used in modern visual management in a combined data-based and graphical manner. In terms of front-end methods, specific and intuitive visual effects are displayed. It should be noted that the fully true three-dimensional digital graphic model provided by this application can be set as an absolute model with geographical location coordinate information and riveted to the physical environment according to the actual needs of the user, or it can also be set without geographical location coordinate information. A relatively realistic three-dimensional model. That is to say, the fully real three-dimensional digital graphic model provided by this application can be set accordingly according to actual needs, and this application will not elaborate on it here.

This visualization effect is displayed because the back-end display data elements are the data collected by the monitored objects in real time, and the relevant intervention business data output by the PHM system. Therefore, this data display method after the integration of the two technologies can not only display the physical entities visible to the naked eye (such as the opening and closing of valves/the on and off of indicator lights/the position of objects, etc.), but can also be collected through collection equipment. The data shows the operating process elements that cannot be directly judged by the naked eye (for example: the temperature in the wire/the fluid speed in the pipeline/the number of floating objects in the air/the flow progress of the ERP/OA office process/the data flow transmitted by the platform operation capacity, etc.).

S102, obtain the data to be measured within the preset range of the park;

In some embodiments, obtaining the data to be measured within a preset range of the park includes:

Further, the collection equipment includes: sensor group, QR code reader and writer, RFID reader and writer, camera, GPS, M2M terminal and system software probe, etc.

Data transmission can use wireless communication equipment including: sensor terminals, sensor group gateways, RFID communication modules, Bluetooth modules, industrial field buses, wireless routers and infrared modules. It may also include communication equipment, which is not limited in this application. The collection equipment provided by this application can monitor in real time: the monitored objects are monitored through various application scenarios integrated in the smart park method. The smart park method can collect multi-element park different scene data at the first time, and target different scenarios in different scenarios. The scene data of the monitored object is used to carry out corresponding subsequent processing applications. Among them, historical operating experience data is not limited to: air quality, weather conditions, atmospheric particulate matter, smoke, temperature and humidity, noise, CO ₂ concentration, indoor light intensity, environmental pollution, water pollution and other natural environment element data, and can also include other natural environment element data. Monitoring objects, such as household equipment or various operating equipment, can also be computer software, such as ERP, OA or databases. It can be understood that the "historical operating experience data" of any operating process is all data in its entirety. It includes: normal data, abnormal data, abnormal data, invalid data, fault data, maintenance history data (maintenance plan, process, tools, personnel, money, etc.), update status data and other related data.

Among them, the application scenarios and industries can be: park operation of water, electricity, gas and other facilities, industry special equipment operation and management monitoring, real-time sensing of production and manufacturing units, chemical gas pipelines, office building elevators, ERP/OA office process flow, etc. The processes in each scenario are Are not the same.

S103. Monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested and historical operating experience data, and determine whether the data to be tested is about to deviate. Before the data to be tested deviates, , if it is determined that the data to be tested is going to be abnormal, an early warning will be issued;

Specifically, fault prediction and health management (PHM, Prognostic and Health Management) are widely used in various fields. It is a brand-new solution for managing the running processes and health status of various events by comprehensively utilizing the latest research results of modern information technology and artificial intelligence technology.

The PHM system has the ability to manage the possibility of system failure within a period of time and take appropriate intervention measures. It generally has the capabilities of fault detection and isolation, fault diagnosis, fault prediction, health management and component life tracking.

In some embodiments, as shown in Figure 2, the monitoring and analysis of the data to be measured through a preset PHM system includes:

Compare the data to be tested with the basic data;

As a specific embodiment, the historical operating experience data includes but is not limited to operation manuals, intervention manuals, spare parts lists, tool lists, daily intervention records, routine shutdown intervention records, fault intervention records, spare parts replacement records, and production Manufacturer intervention records;

In some embodiments, the basic data also includes preset early warning key values; and comparing the data to be tested with the basic data includes:

At the same time, the data to be tested is compared with historical operating experience data, and the data to be tested is compared with the early warning key value;

As an example, the early warning key values include water flow velocity, water quality, impeller rotation speed, impeller polarization, current value, voltage value, motor temperature value, ambient temperature value, ventilation value, air quality value, suspended particulate matter value, smoke Sense alarm value, fire extinguishing pipeline value, vibration value, current value, current voltage stabilization value, impedance value, battery temperature value and leakage monitoring value, etc.

In some embodiments, the standard range of data is determined based on historical operating experience data, and the determination of whether the data to be measured is about to deviate, and before the data to be measured is deviated, it is determined that the data to be measured is about to be abnormal, then Provide early warning, including:

For different scenarios and different applications, compare historical operating experience data and early warning key values at the same time;

When the change trend state of the data to be measured in the future preset time period exceeds the standard range, it is determined that the data to be measured will be abnormal, and an early warning is issued;

When the change trend state of the data to be measured in the future preset time period reaches the early warning key value, it is determined that the data to be measured will be abnormal, and an early warning is performed;

When the change trend status of the data to be measured in the preset time period in the future exceeds the standard range, the data to be measured is compared with the early warning key value. When the data to be measured is in the preset time period in the future, When the change trend state reaches the pre-warning key value and it is determined that the data to be measured is abnormal, an early warning will be issued.

Before deviations occur in the data to be measured, an early warning is provided based on the scenario corresponding to the anomaly, and the key operating data and intervention steps that need to be displayed and set according to the early warning information are displayed through a visual interface;

The intervention steps include intervention outline, MEL minimum equipment list, CDL commonly used associated data and other related technologies. details as follows:

This application collects operating data of various parks in real time through collection equipment, and combines the background PHM to perform calculation judgment, intervention execution and calculation update. Specifically, data collection is through collection equipment, which can be system software probes or sensor networks. Detect parameters, monitor alarm signals and real-time status parameters to perform real-time status monitoring, and then perform feature extraction, information fusion, trend analysis and threshold estimation on the real-time status data through historical operating experience data to perform fault prediction and remaining life prediction, combined with Run data inspection reports to conduct intervention diagnosis and make intervention decisions. Intervention decisions include intervention outline, MEL (minimum equipment list), CDL (commonly used linked data) and other related technologies. Through intervention decisions, intervention plans are set to obtain intervention case management. This enables reliability management.

This application implements preventive intervention business logic through the above method (park business logic is set differently for different industries and business attributes), and uses key business data of various types of business intervention that the park has continuously run in the past to make judgments on various preventive intervention businesses in the park. The judgment results of this operation (normal data, abnormal data, etc.) are output to the visual management module at the front end of the smart park system in a visual data loading method to display the visual comprehensive data calculation results. PHM can provide effective "fault prediction and health management" functions for transactions and business content that need to produce specific results through the "operation" link.

S104. Display key operation data, abnormal locations, early warning information and intervention means in the graphical model through a visual interface.

Specifically, this application updates and upgrades the traditional visual management of physical substances to a higher level of visualization that is not limited to the visual management of physical substances (visualization of elements invisible to the naked eye) or the visual management that may appear in the future. For example, the invisible temperature in the wires, the liquid flow rate in the pipeline, and the actual pressure in the container can be collected through a variety of IoT sensing methods, and can be visualized through comprehensive calculations by the PHM system and combined with modern visualization technology.

Specifically, in this application, all monitored objects within the scope of the visual management park can be managed uniformly to standardize and standardize the site. It realizes the visualization of management by using methods such as positioning, drawing lines, and hanging signboards on tools and items, etc., so that personnel with different functions in the park can promptly discover problems, anomalies, and waste that occur on-site, so that existing problems can be solved or prevented in a timely manner. question. In addition, various on-site production management information is also visually managed, such as dashboard management of the allowable range of instruments, management processes, implementation of planned indicators, etc., so that employees can correctly and quickly grasp normal and abnormal situations and their implementation, and carry out preventive measures in advance. Or corresponding measures can be taken promptly and quickly. Visual management is becoming an important management model for modern enterprises.

Among them, the color lines include the basic color standards of the park/enterprise, commonly used line specifications, and key processes; the space place names include building numbers, room naming, and regional nameplates; the bottom passages include traffic lines, ground guides, and door management; the equipment and electrical appliances include fluid passages, logistics Directions, instruments and valves; object materials include the original location of the object, storage cabinets, and quantitative markings; tools and equipment include various tools, gloves, ropes, and transportation vehicles; safety warnings include fire protection facilities, safety guardrails, and dangerous goods; peripheral environments include garages, municipal Facilities and roadside; office departments include office desk items, drawers and cabinets, and documents; management boards include policy instructions, bulletin boards, and red cards. This application clearly informs staff what they should do through visual management, so as to detect abnormal situations early and make the inspection effective; prevent human errors or omissions, and always maintain normal conditions; through vision, make problem points easier to expose, prevent and eliminate in advance Various hidden dangers and waste. Among them, the principles of visual management are visualization: thorough marking, identification, and color management; transparency: revealing the hidden areas that need to be seen, as well as intelligence; boundaryization: marking management boundaries, marking normal and normal The quantitative limits of the anomaly make it clear at a glance.

As shown in Figure 3, the smart park management system provided in the embodiment of the present application includes a perception layer, a connection layer, a data layer, a platform layer, an application layer and a user layer that are connected in sequence. The data layer is provided with a PHM algorithm; The perception layer obtains real-time monitoring data monitored within the preset range of the park through various sensor networks and facilities, and transmits data to the data layer through the connection layer to form a collection of real-time collected data. The real-time collected data and the operation intervention data generated by the calculation of the corresponding real-time collected data are constantly updated and accumulated in the data layer, forming historical operation experience data. It can be understood that the PHM algorithm is a function within the operation management instructions in the data layer. Data The IoT sensing layer is the data aggregation center for all sensing layer facilities to collect data; the connection layer is used to send real-time monitoring data to the data layer; the data layer classifies and divides the collected data according to the received data and passes the corresponding storage storage method; the platform layer performs visual management on the comparison results of real-time monitoring data and key values and corresponding intervention methods, and expands the functions of the smart park management platform; the application layer applies the smart park management platform to multiple A variety of business application scenarios; the user layer supports users with various types of business application needs and park management needs. For each type of user, according to the different application business types in the smart park platform, different application access rights are granted to complete their respective tasks. Daily business of the park.

This application obtains real-time monitoring data within the preset range of the park through system software probes or Internet of Things equipment, and then analyzes the real-time monitoring data through the PHM algorithm to perform fault prediction; the connection layer uses wired, wireless, 4G/5G , NB-IoT, LoRa, Bluetooth, BDS and other communication network connection methods can establish safe, reliable, and continuously available network information transmission channels. This channel aggregates various types of IoT sensing status and business data collected by the perception layer to the data layer through a scientific and efficient network transmission channel; the data layer targets campus business, enterprise business, geographical information, IoT sensing, and operation. The data that will be generated in the daily operation of various smart parks, such as management instructions, are organized into targeted and classified thematic data warehouses. It is convenient for the upper platform layer, application layer and end-user layer to quickly access and use various business data according to their different business divisions and authority functions; the platform layer integrates the Internet of Things, BIM/CIM, OA/ERP, In addition to the necessary functional support modules within the preset scope of the smart park such as BI/reporting, disaster recovery/operation and maintenance, in order to support the continuous derivative expansion of the smart park platform business in the future, an integrated application interface for unified standard docking/functional expansion is integrated. . For the smart park platform, continue to expand functions in the future use process and make sufficient preparations for application support; the application layer applies the smart park management platform to a variety of business application scenarios; the user layer is the overall platform support management unit , construction units, operating units, settled enterprises, corporate employees, external visitors, commissioned users and many other types of users with different business application needs and park management needs. Each type of user is given different application access rights according to the type of application business in the smart park platform to complete their respective daily work in the park.

The working principle of the smart park management method is as follows: This application first loads and combines the visual interface with the PHM system, that is, based on the objective principle of physical consistency, a full three-dimensional digital graphical modeling of various scenes in the park that needs to be managed is carried out . Then, according to the principle of one-to-one correspondence, the relevant intervention business processes output by the PHM system form a data link with each corresponding collection device and its collected business data in a one-to-one correspondence, and this The link combines data and graphics to display specific and intuitive visual effects on the modern visual management front-end platform. Then it obtains real-time monitoring data within the preset range of the park, that is, the data to be tested, and then the PHM system analyzes the data to be tested to determine whether there is a deviation in the data to be tested; if there is a deviation, there may have been a problem with the collection object corresponding to the data to be tested. However, the monitored object can still operate, such as aging. At this time, the PHM system can determine the abnormality of the monitored object based on the abnormality of the data to be measured, thereby informing the intervention personnel to intervene and pre-process to avoid the abnormality or abnormality of the collected object. The park was unable to maintain normal operations after the situation had deviated and was dealt with only after it occurred.

This application combines visual management with PHM, leaping from traditional material visual visualization to twin scene visualization in the information age.

In some embodiments, it also includes:

The storage is to select a corresponding storage method according to the scenario, and the storage method includes real-time storage, staged storage, post-completion storage, external data entry storage, and other methods.

As a specific embodiment, the intervention process data includes operator qualification certificates, specific point measurement values, fault judgment results, operating tools and intervention and replacement component information.

It can be understood that the PHM system in this application can be updated to facilitate the staff to understand the real-time monitoring data of the collection objects.

In some embodiments, loading the PHM system to the visual interface includes:

In the visual management front-end platform, firstly conduct a full three-dimensional digital graphical modeling of various scenes in the park that need to be managed, and then use the relevant intervention business data output by the PHM system to correspond to each intervention business data in one-to-one correspondence. A corresponding collection object forms a data link; and this link is combined with data and graphics to display intuitive visualization effects on a modern visual management front-end platform.

In some embodiments, the modern visual management front-end platform, based on the above mechanism, realizes the function of jointly displaying "physically visible entity conditions" and "operational process elements that cannot be directly judged by the naked eye", and also supports multiple types, multi-dimensions and multi-methods. Data presentation methods and effects. These include but are not limited to:

Data related: Basic three-dimensional solid model data of management objects produced according to park management requirements.

The collection object collects, sets and compares with the PHM system, does not need to trigger relevant intervention business processes, is connected to the basic three-dimensional entity model and displayed, and is the normal business monitoring data.

The business abnormal monitoring data collected by the collection object, compared with the PHM system settings, need to trigger relevant intervention business processes, hooked up to the basic three-dimensional entity model and displayed.

Different related intervention businesses require relevant technical information displayed in the modern visual management front-end method (operation manual/maintenance manual/spare parts list/tool list/daily maintenance record/routine shutdown maintenance record/fault maintenance record/spare parts Replacement records/fault diagnosis reports/manufacturer maintenance records/intervention outline/MEL minimum equipment list/CDL commonly used associated data/other related technologies, etc.)

Chart-related: Data element display methods. Due to the different attributes of the objects that need to be managed (physical equipment/logical processes, etc.), there can be a variety of chart and graphical display methods. including but not limited to:

Data chart, column chart, bar chart, pie chart, line chart, trend state chart, area chart, quadrant chart, surface chart, tree chart, radar chart, histogram, box chart, waterfall chart, funnel chart , combination charts and dynamic charts, etc.

Color related: In order to be more intuitive and more prominent in the park management process, it is necessary to reflect the real-time need to reflect the relevant intervention business and the specific physical location of the business point, so that users can most efficiently understand the key content of method operation and intervene in relevant points in a timely manner. business. Therefore, the front-end data element display will use different colors to display differentiated data colors for various data elements. For example: normal values are green, critical data are bright yellow, early warning key data are red, etc.

Media related: In order to improve the timeliness and responsiveness of related intervention services. The modern visual management front-end method not only supports traditional large-screen display, but also supports computer monitors, mobile terminals, tablets, industrial control computers and other methods for separate display on the application side. And since related intervention services will seriously affect the overall sustainable and efficient operation of the smart park, while providing visual display, it also provides multi-dimensional notifications and perceptions based on various devices such as sound alarms and vibration alarms for monitoring data and key early warning data. Function.

The final results displayed can facilitate various managers within the preset scope of the smart park to discover in advance various operating trends in the park's operation that may lead to adverse results, and conduct early operational warnings and interventions. This ensures that the ultimate goal of continuous operation of the park can be achieved through intervention means.

As a specific embodiment, this application adopts the turbine unit monitoring scenario business description:

1) Import the daily operation and maintenance data of the early turbine unit into the PHM system by category (operating manual/maintenance manual/spare parts list/tool list/daily maintenance record/routine shutdown maintenance record/fault maintenance record/spare parts replacement record/ Manufacturer's maintenance records, etc.). As the basic data of early equipment, it is used to compare with the real-time collected data of IoT acquisition equipment. Based on the comparison numerical results, it is judged whether the corresponding equipment needs to perform intervention operations, and the original data basis for executing the corresponding intervention operations is implemented.

2) In the PHM system, according to the key requirements for the operation and maintenance of the turbine unit, set the corresponding operating data detection index early warning key values (water flow speed/water quality/impeller rotation number/impeller polarization/current value/voltage value/motor temperature wait). This data is set as the criterion for triggering "whether intervention operation is required".

3) In the PHM system, based on the key requirements for the operation and maintenance of the turbine unit, set the output of early warning information that the PHM system should perform when the collected data reaches the previously set key value of early warning, and the output of intervention related to the corresponding early warning information. Specific technical implementation steps (intervention outline/MEL minimum equipment list/CDL commonly used linked data/other related technologies).

4) Install sensors (water pipes/impellers/wires/motors, etc.) for collecting operating data at relevant locations of the turbine unit. Used to collect relevant real-time accurate values when the turbine unit is running (water flow velocity/water quality/impeller rotation number/impeller polarization/current value/voltage value/motor temperature, etc.). It is used to compare data with the preset intervention parameter conditions in the PHM system to determine whether to trigger the intervention service.

5) When the background setting data and the Internet of Things collection data are compared through real-time monitoring data to trigger the intervention business, the PHM system will use the basic data inserted in the early stage to determine the specific trigger data for this comparison based on Run the data inspection report and output the intervention diagnostic report.

6) At this time, PHM outputs specific technical implementation steps for intervention related to the corresponding early warning information based on the preset early warning information (intervention outline/MEL minimum equipment list/CDL commonly used associated data/other related technologies). It is used for operators to complete this intervention business in a standardized manner according to the instructions and guidance of the system.

7) After each intervention business is completed, the corresponding specific monitored object information that was intervened will be recorded in the reliability management data of the PHM system. This data is used as the data basis for judging the operational reliability of the corresponding monitored object within a certain period of time.

8) After each intervention business is completed, the specific intervention process data (operator qualification certificates/specific point measurement values/fault judgment results/operating tools/maintenance and replacement component information, etc.) need to be entered into the PHM system. Corresponding intervention cases. This data serves as the key element data that drives the PHM system to generate subsequent long-term intervention plans for the device. The PHM system standardizes data retention for each intervention business process, so that through continuous data accumulation, a large-volume intervention data reference basic database can be formed for the system to continuously use this data accumulation source and collection equipment data for real-time monitoring. Compare data to determine whether to trigger intervention services.

As another embodiment, this application uses centralized energy storage power distribution monitoring to describe the business:

1) Import the daily operation and maintenance data of early energy storage distribution units into the PHM system by category (operating manual/maintenance manual/spare parts list/tool list/daily maintenance record/routine shutdown maintenance record/fault maintenance record/spare parts Replacement records/manufacturers/intervention records, etc.). As the basic data of early equipment, it is used to compare with the real-time collected data of IoT acquisition equipment. Based on the comparison numerical results, it is judged whether the corresponding equipment needs to perform intervention operations, and the original data basis for executing the corresponding intervention operations is implemented.

2) In the PHM system, according to the key requirements for the operation and maintenance of energy storage power distribution units, set corresponding operating data detection index early warning key values (ambient temperature value/ventilation value/air quality value/suspended particulate matter value/smoke alarm Device value/Fire protection "dry powder/inert gas" fire extinguishing pipeline value/Vibration value/Current value/Current voltage stabilization value/Current "trickle/surge" value/Voltage value/Impedance value/Battery temperature value/Motor temperature value/ leakage monitoring values, etc.). This data is set as the criterion for triggering "whether intervention operation is required".

3) In the PHM system, based on the key requirements for the operation and maintenance of the energy storage power distribution unit, set the output warning information that the PHM system should execute when the collected data reaches the previously set key value for warning, as well as the output of the corresponding warning information. Specific technical implementation steps of the intervention (intervention outline/MEL minimum equipment list/CDL commonly used linked data/other related technologies).

4) Install sensors for collecting operating data at relevant locations of the energy storage power distribution unit (house space/distributor/meter/gate box/wires/battery/motor/battery cabinet/smoke sensor/firefighting "dry powder/inert gas" fire extinguishing pipes, etc.). Used to collect relevant real-time accurate values when the energy storage power distribution unit is running (ambient temperature value/ventilation value/air quality value/suspended particulate matter value/smoke alarm value/firefighting "dry powder/inert gas" fire extinguishing pipeline value/vibration Value/current value/current regulation value/current "trickle/surge" value/voltage value/impedance value/battery temperature value/motor temperature value/leakage monitoring value, etc.). It is used to compare data with the preset intervention parameter conditions in the PHM system to determine whether to trigger the intervention service.

8) After each intervention business is completed, the specific intervention process data (operator qualification certificates/specific point measurement values/fault judgment results/operating tools/intervention and replacement component information, etc.) need to be entered into the PHM system. Corresponding maintenance cases. This data serves as the key element data that drives the PHM system to generate subsequent long-term intervention plans for the device. The PHM system standardizes data retention for each intervention business process, so that through continuous data accumulation, a large-volume intervention data reference basic database can be formed for the system to continuously use this data accumulation source and collection equipment data for real-time monitoring. Compare data to determine whether to trigger intervention services.

In this application, the PHM system serves as the computing and processing end of the IoT data collection data at the backend of the platform, the core functional end of the main operation judgment mechanism for intervention mechanism judgment, early warning and intervention diagnosis report/intervention outline/MEL minimum equipment list/CDL commonly used associated data/ The output end of other related technologies and other relevant early warning results and technical data. With PHM's unique "fault prediction and health management" system mechanism, various business data collected by the collection object are judged based on the imported data, reports are output, and technical standard information and intervention data for specific intervention purposes are output. Experience and specific technical operation methods recommended by the system.

When the PHM system outputs relevant intervention business processes to the outside, the modern visual management front-end platform, as the front-end functional module that ultimately carries and is presented to method users in an intuitive way, cooperates with the relevant intervention business processes output by the PHM system to perform intuitive graphical and Various presentation methods combined with data.

It can be understood that the above two specific embodiments are only examples. In this application, PHM can manage all processes that "need to produce results through operation". Its management scope is not limited to equipment and facilities, but also includes similar administrative office processes, etc. Businesses can all be managed by PHM. PHM can be applied to equipment, business, administrative procedures or ERP/OA office systems, etc. This application will not give examples one by one here.

Based on the above technical description, through the combination of PHM technology and modern visual management technology, different business logics are set according to different business parks, and key points that may cause problems in the operation of various parks can be predicted, and Implementation of technical methods for early warning and control. The scientific and standardized combination of PHM technology and modern visual management technology within the overall approach of the smart park can greatly improve the level of park/enterprise management and ensure the continued operation of the overall park.

As shown in Figure 4, this embodiment of the present application provides a smart park management platform, including:

The building module 401 is used to construct a fully realistic three-dimensional digital graphic model of various scenes within the preset range of the park that needs to be managed on the visual interface;

The acquisition module 402 is used to acquire the data to be measured within the preset range of the park;

The analysis module 403 is used to monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested and historical operating experience data, and determine whether the data to be tested is about to deviate. Before the data deviates, if it is determined that the data to be measured will be abnormal, an early warning will be issued;

The display module 404 is used to display key operation data, abnormal locations, early warning information and intervention means in the graphical model through a visual interface.

The smart park management platform provided by this application can be applied to a variety of business application scenarios including but not limited to security, traffic, facilities, energy, production, logistics, environment, public services, etc., and can be customized as needed for continued use in the future. Expand corresponding business functions for smart campus methods. For various types of domestic parks, the overall structure of this smart park can support special services in industrial parks, government parks, commercial and office parks, logistics parks, science and technology parks, cultural and tourism parks and other park types according to industry attributes, and can be used in smart During the use of the park method, more characteristic types of park applications are provided, as well as function customization extensions.

It can be understood that the above-mentioned system embodiments correspond to the above-mentioned method embodiments, and the corresponding specific contents can be referred to each other, and will not be described again here.

Those skilled in the art will understand that embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, magnetic disk storage and optical storage, etc.) embodying computer-usable program code therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture that includes the instruction method, the instructions A method implements the functionality specified in a process or processes in a flow diagram and/or in a block or blocks in a block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention. should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

A smart park management method, which is characterized by including:

Construct a fully realistic three-dimensional digital graphic model of various scenes within the preset range of the park that needs to be managed on the visual interface;

Obtain the data to be measured within the preset range of the park;

Monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested with historical operating experience data, determine whether the data to be tested is about to deviate, and determine whether the data to be tested will deviate before the deviation occurs. If the data to be tested is about to become abnormal, an early warning will be issued;

Key operating data, abnormal locations, early warning information and intervention methods are displayed in the graphical model through a visual interface.
The smart park management method according to claim 1, wherein the monitoring and analysis of the data to be measured through a preset PHM system includes:

Obtain the historical operation experience data of various scenarios within the preset range of the park, and import the historical operation experience data into the PHM system as basic data classification;

Compare the data to be measured with the base data.
The smart park management method according to claim 2, wherein the basic data also includes a preset early warning key value; and comparing the data to be measured with the basic data includes:

If the data to be tested is compared with the historical operating experience data and it is determined that the data to be tested is abnormal, then the data to be tested is compared with the early warning key value; and/or

At the same time, the data to be tested is compared with historical operating experience data, and the data to be tested is compared with the early warning key value.
The smart park management method according to claim 3, characterized in that the standard range of data is determined based on historical operating experience data, and the judgment of whether the data to be tested is about to deviate, before the data to be tested deviates, If it is determined that the data to be tested is going to be abnormal, an early warning will be issued, including:

For different scenarios and different applications, compare historical operating experience data and early warning key values at the same time; specifically include:

When the change trend status of the data to be measured in a preset time period in the future exceeds the standard range, it is determined that the data to be measured will be abnormal, and an early warning is issued; or

When the change trend state of the data to be measured in the preset time period in the future reaches the early warning key value, it is determined that the data to be measured will be abnormal, and an early warning is issued; or

When the change trend status of the data to be measured in the preset time period in the future exceeds the standard range, the data to be measured is compared with the early warning key value. When the data to be measured is in the preset time period in the future, When the changing trend state reaches the pre-warning key value and it is determined that the data to be measured is abnormal, an early warning will be issued;

Before a deviation occurs in the data to be measured, an early warning is provided based on the scenario corresponding to the abnormality, and the key operation data and intervention steps that need to be displayed and set according to the early warning information are displayed through a visual interface.
The smart park management method according to claim 4, further comprising:

Store the monitored object information and intervention process data of each operation into the database of the PHM system to update the database to determine the operational reliability of the monitored object within the preset time;

The storage is to select a corresponding storage method according to the scenario, and the storage method includes real-time storage, staged storage, post-completion storage and external data entry storage.
The smart park management method according to claim 1, wherein said obtaining the data to be measured within the preset range of the park includes:

Obtain data in the database through system software probes and/or collect operating data of the monitored object through sensors installed on the monitored object;

The operating data of the monitored object is determined as the data to be measured.
The smart park management method according to claim 1, characterized in that:

In the visual management front-end platform, firstly conduct a full three-dimensional digital graphical modeling of various scenes in the park that need to be managed, and then use the relevant intervention business data output by the PHM system to correspond to each intervention business data in one-to-one correspondence. A corresponding collection device and its collected business data form a data link; and this link is combined with data and graphics to display intuitive visual effects on a modern visual management front-end platform.
The smart park management method according to claim 1, wherein the visual interface includes multiple data display methods, and the multiple data display methods include:

Data display, including collected data to be tested, normal business monitoring data, abnormal business monitoring data, and intervention business data;

Chart display, based on the different attributes of the monitored objects, uses data charts, column charts, bar charts, pie charts, line charts, trend status charts, area charts, quadrant charts, surface charts, tree charts, radar charts, Histogram, box plot, waterfall chart, funnel chart, combination chart or dynamic chart for display;

Color display, using multiple colors to differentiate data color display of various data elements;

Media display is used to provide multi-dimensional notifications of monitoring data, early warning key data, and intervention steps based on graphic alarms, sound alarms, and vibration alarms based on various display media.
The smart park management method according to claim 7, characterized in that:

Collection equipment includes: sensor group, QR code reader and writer, RFID reader and writer, camera, GPS, M2M terminal and system software probe.
A smart park management platform, which is characterized by including:

The building module is used to build a fully realistic three-dimensional digital graphic model of various scenes within the preset range of the park that needs to be managed on the visual interface;

The acquisition module is used to obtain the data to be measured within the preset range of the park;

The analysis module is used to monitor and analyze the data to be tested through the preset PHM system, compare the data to be tested and historical operating experience data, and determine whether the data to be tested is about to deviate. Before deviation occurs, if it is determined that the data to be measured will be abnormal, an early warning will be issued;

A display module is used to display key operation data, abnormal locations, early warning information and intervention means in the graphical model through a visual interface.