Park equipment data acquisition method, system, equipment and medium

Abstract

The invention provides a park equipment data acquisition method and system, equipment and a medium, and the method comprises the steps: obtaining the operation data and equipment basic information of park equipment at an acquisition point, carrying out the collection and arrangement of the operation data after preprocessing, and extracting key operation data; based on the key operation data and the equipment basic information, carrying out real-time monitoring on the operation state of the park equipment and calculating a statistical index; analyzing rules and trends of the statistical indexes by adopting a data analysis algorithm; according to a monitoring result and an analysis result, generating a report and a visual icon, predicting potential faults of park equipment, optimizing an equipment maintenance plan, and generating an equipment management report, so as to solve the problem that enterprise production equipment in the prior art does not have equipment data acquisition and transmission capabilities and cannot meet the requirements of field fine management and timeliness management.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a method, system, equipment and medium for collecting data of park equipment. Background Art

[0002] The equipment data acquisition system is a comprehensive software that integrates and manages elements such as sensors, equipment, networks and applications through cloud computing, big data analysis and other technical means. The equipment data acquisition system can realize the interconnection between equipment, data collection and processing, as well as monitoring and analysis of the operating status of equipment. The system integrates multiple functions such as equipment overview, basic data management, equipment template management, and equipment management. The equipment data acquisition system is the key and core to realize industrial Internet services. By connecting equipment and collecting data generated by equipment through the system, analyzing and processing, it can provide support for various applications, realize intelligent management and operation and maintenance of factory equipment, improve production efficiency and product quality, and reduce production costs.

[0003] However, the existing production equipment of enterprises generally does not have the ability to collect and transmit equipment data. They have not yet carried out online monitoring of equipment status and operation monitoring based on equipment networking. They rely on manual transmission of production plans and documents. The flow of production processes, progress tracking, and abnormal feedback are still mainly manual, which cannot meet the needs of on-site refined management and timely management. At the same time, enterprises lack the integration and mining of data from all links and dynamic monitoring, lack input-output analysis, product quality analysis, and visual monitoring of production processes, making it difficult for enterprise managers to grasp the production and operation situation in a timely manner.

[0004] Therefore, it is urgently necessary to propose a park equipment data collection method, system, medium and equipment to solve the problem that the enterprise production equipment in the existing technology does not have the equipment data collection and transmission capabilities and cannot meet the needs of on-site refined management and timely management. Summary of the invention

[0005] In order to overcome the problems existing in the related technology, the present disclosure provides a park equipment data collection method, system, equipment and medium to solve the technical problem in the related technology that the enterprise production equipment does not have the equipment data collection and transmission capabilities and cannot meet the needs of on-site refined management and timely management.

[0006] One or more embodiments of this specification provide a method for collecting data from a campus device, including the following steps:

[0007] Obtain the operation data and basic information of the park equipment at the collection point, summarize and organize the operation data after pre-processing, and extract key operation data;

[0008] Based on the key operating data and basic equipment information, real-time monitoring of the operating status of the park equipment and calculation of statistical indicators are performed;

[0009] Analyzing the patterns and trends of the statistical indicators using data analysis algorithms;

[0010] Generate reports and visualization icons based on monitoring and analysis results, predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

[0011] Preferably, the method further comprises the following steps:

[0012] Create a general device template, define basic device information of the general device, and configure and manage the newly added devices through the general device template to form campus devices;

[0013] Establish an electronic file for each park equipment, and regularly update the electronic file based on the operating data of the park equipment, wherein the electronic file includes basic equipment information, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports.

[0014] Preferably, the method further comprises the following steps:

[0015] Establish the association between collection points and park equipment through the management of collection points;

[0016] By setting the configuration information of the collection point, the data collection task of the data collection terminal is controlled.

[0017] Preferably, the acquisition of the operation data and basic information of the park equipment at the collection point, the aggregation and arrangement of the operation data after pre-processing, and the extraction of key data indicators also include the following steps:

[0018] The pre-processed operation data is stored in a real-time database according to different dimensions for organization and indexing;

[0019] The key operation data is stored in a relational database using a database table structure, and an association relationship between tables is established through a database mechanism;

[0020] The real-time database and the relational database interact with each other through a data synchronization service.

[0021] One or more embodiments of this specification provide a park equipment data collection system, including a data acquisition module, an equipment monitoring module, a data analysis module, and an application module;

[0022] The data acquisition module is used to acquire the operation data and basic information of the park equipment at the collection point, summarize and organize the operation data after pre-processing, and extract key operation data;

[0023] The equipment monitoring module is used to monitor the operating status of the park equipment in real time and calculate statistical indicators based on the key operating data and basic equipment information;

[0024] The data analysis module is used to analyze the rules and trends of the statistical indicators using a data analysis algorithm;

[0025] The application module is used to generate reports and visualization icons based on monitoring results and analysis results, predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

[0026] Preferably, it also includes a configuration module and a file creation module;

[0027] The configuration module is used to create a general device template, define basic device information of the general device, and configure and manage the newly added device through the general device template to form a campus device;

[0028] The filing module is used to create an electronic file for each park equipment and regularly update the electronic file based on the operating data of the park equipment. The electronic file includes basic equipment information, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports.

[0029] Preferably, it also includes a collection point management module, which is used to establish an association relationship between the collection points and the park equipment through the management of the collection points, and control the data collection tasks of the data collection terminals by setting the configuration information of the collection points.

[0030] Preferably, the data acquisition module includes a first storage unit, a second storage unit and an interaction unit;

[0031] The first storage unit is used to store the pre-processed operation data in a real-time database according to different dimensions for organization and indexing;

[0032] The second storage unit is used to store the key operation data in a relational database using a database table structure, and to establish an association relationship between tables through a database mechanism;

[0033] The interaction unit is used for data interaction between the real-time database and the relational database through a data synchronization service.

[0034] One or more embodiments of the present specification provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned campus equipment data collection method when executing the computer program.

[0035] One or more embodiments of the present specification provide a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned campus equipment data collection method are implemented.

[0036] The present invention provides a method, system, equipment and medium for collecting park equipment data, which have the advantages of obtaining the operating data and basic equipment information of the park equipment at the collection point, aggregating and organizing the operating data after preprocessing, and extracting key operating data, which can ensure the accuracy and comprehensiveness of the data source, effectively screen out the most valuable data subset, and reduce the interference of data redundancy and invalid information; based on the key operating data and basic equipment information, the operating status of the park equipment is monitored in real time and statistical indicators are calculated, which can instantly capture various working condition changes of the equipment, and can also accurately calculate statistical indicators; data analysis algorithms are used to analyze the laws and trends of the statistical indicators, providing a forward-looking perspective for park equipment management; based on the monitoring results and analysis results, reports and visualization icons are generated, which can improve the efficiency and accuracy of information communication, predict potential failures of park equipment, optimize equipment maintenance plans, and generate equipment management reports. The generated equipment management reports integrate all-round information on equipment operation, including monitoring data, analysis results, failure predictions, and maintenance plan execution, etc., providing a rich and detailed basis for enterprises to formulate long-term equipment management strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0038] Figure 1 A schematic diagram of a process flow of a park equipment data collection method provided for one or more embodiments of this specification;

[0039] Figure 2 A schematic diagram of the structure of a park equipment data acquisition system provided for one or more embodiments of this specification;

[0040] Figure 3A schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the protection scope of the present invention.

[0042] The present invention is described in detail below in conjunction with specific implementation methods and the accompanying drawings.

[0043] Method Embodiment

[0044] According to an embodiment of the present invention, a method for collecting data of a park device is provided, such as Figure 1 FIG. 1 is a flow chart of a method for collecting data of a campus device provided in this embodiment. The method for collecting data of a campus device according to an embodiment of the present invention includes the following steps:

[0045] S110, obtaining the operation data and basic information of the park equipment at the collection point, summarizing and arranging the operation data after pre-processing, and extracting key operation data.

[0046] The operation data can be collected through the device interface. For example, the data collection gateway uploads the production quantity, speed, pressure, number of downtimes and time and other operation process data through the serial port / Ethernet port of the PLC (Programmable Logic Controller) control module / touch screen. If the enterprise equipment has the serial port / network port of the PLC control module / touch screen to collect data, it only needs to adapt the serial port / network port and the gateway to collect data, which has the lowest transformation cost and fast implementation; but if it does not have it, it needs to be transformed. For non-PLC controllers and PLC controllers, for devices without communication interfaces or no remaining communication interfaces, the manufacturer needs to provide the communication interface (adding communication modules), communication protocols, communication parameters, data parameter tables and description documents; for devices with communication interfaces: the manufacturer needs to provide the communication protocol, communication parameters, data parameter tables and description documents. For touch screens unique to the manufacturer: the manufacturer needs to provide the touch screen program, communication parameters, data parameter tables and description documents.

[0047] Electronic scales can also be used for data collection. Electronic scale data collection refers to the use of electronic scales to monitor and record the weight of materials in the production process in real time. The MES (Manufacturing Execution System) system interfaces with the electronic scale equipment and collects and transmits data through communication protocols. This method is used in conjunction with the MES system. Considering that fastener companies generally use processing weight as the basis for the output of production processes from order placement to work orders, the logic of associating orders, work orders, equipment, and personnel can be used to weigh the production equipment of each process in real time using an electronic scale with communication functions after processing is completed, and transmit the weight to the equipment collection system, so that work orders,

[0048] The production process corresponds to the output progress of each device and operator, and it is also convenient for the replacement of spare parts and molds (replacement is required when the usage reaches a certain amount). This method covers the entire production process or key processes, combined with the MES system work order, meets the process control requirements for people, machines, materials, etc., does not change the equipment and processes, and the enterprise has a certain motivation.

[0049] Sensors can also be used for data collection. For situations where the equipment business data cannot be obtained through the above methods, sensors can be installed on key process equipment to monitor the equipment operation status (with or without production action) and production quantity, and data can be uploaded via Ethernet or other communication methods. According to different equipment types and monitoring requirements, carefully select suitable sensors. For example, on large-scale mechanical equipment, highly sensitive vibration sensors are installed on key bearing parts to capture tiny vibration changes and indicate potential mechanical failures; for precision electronic equipment, high-precision temperature and humidity sensors are deployed to ensure the stability of the equipment operating environment. At the same time, for smart devices with built-in communication functions, such as new CNC machine tools and smart meters, directly use their built-in Ethernet, RS485 or wireless communication modules to access the system according to specific communication protocols (such as Modbus, OPC UA, etc.) to achieve efficient data collection. The data collection frequency of sensors and smart devices is flexibly set according to the importance of the data and the operating characteristics of the equipment. For example, the core parameters of key equipment (such as pressure, temperature, etc.) can be set to be collected every 5 seconds, while some auxiliary data (such as equipment appearance status monitoring data) can be collected every 30 seconds to balance the data volume and data value.

[0050] Build a hybrid network architecture with industrial Ethernet as the backbone and wireless LAN (such as Wi-Fi 6 or 5G private network) as a supplement. Inside the workshop, industrial Ethernet connects various data acquisition terminals, servers and other network devices through switches to form a stable and reliable wired network link to meet the high-speed transmission requirements of large amounts of data. For some mobile devices (such as inspection robots) or areas where wiring is difficult, deploy high-performance wireless LANs to ensure that these devices can access the network and transmit data in real time.

[0051] Within the enterprise park, optical fiber networks are used to aggregate the networks of various workshops to the enterprise data center to build a complete park network topology. Firewalls, intrusion detection systems and other network security equipment are deployed at network boundaries and key nodes to strictly restrict external illegal access, while real-time monitoring and filtering of internal network traffic to prevent network attacks and data leaks.

[0052] Low-power, high-reliability IoT transmission protocols, such as MQTT or CoAP, are used between sensors and data collection terminals. These protocols are designed for resource-constrained IoT devices and can achieve efficient data transmission under limited bandwidth and low power conditions. Sensors publish the collected data in the form of messages to specific topics (MQTT) or resources (CoAP), and data collection terminals, as subscribers or clients, receive and process these data.

[0053] Between the data acquisition terminal and the server, for the equipment status data and control instructions with high real-time requirements, a custom binary protocol based on TCP / IP is used to ensure the speed and accuracy of data transmission. For a large amount of historical data and non-real-time data (such as equipment operation logs, statistical reports, etc.), the HTTP protocol can be used for transmission, and with its mature Web technology framework, it is convenient to upload, download and manage data.

[0054] The collected operation data is transmitted to the data acquisition terminal through the corresponding communication interface (such as the analog or digital output interface of the sensor, the network interface of the intelligent device). The data acquisition terminal performs preliminary processing on the data, including data format conversion (such as converting the original analog signal of the sensor into a digital signal), data verification (checking the integrity and accuracy of the data) and data caching (temporarily storing the processed data in the local cache area).

[0055] The data acquisition terminal sends the cached data to the real-time database of the data storage layer through the network transmission layer according to the set data transmission strategy. During the transmission process, the selected transmission protocol (such as MQTT or custom binary protocol) is followed to ensure that the data can reach the destination safely and quickly.

[0056] S120. Based on key operating data and basic equipment information, the operating status of the park equipment is monitored in real time and statistical indicators are calculated. Specifically, advanced data analysis algorithms (such as anomaly detection algorithms in machine learning) are used to analyze the equipment operating data in real time to determine whether the equipment is in an abnormal operating state. Calculate various statistical indicators related to equipment management according to business needs. For example, calculate equipment utilization (the ratio of the actual operating time of the equipment to the planned operating time), equipment failure rate (the ratio of the number of faulty equipment to the total number of equipment), equipment mean time between failures (MTBF, calculated by the total equipment operating time and the number of failures), maintenance cost rate (the ratio of the total equipment maintenance cost to the total value of equipment assets), etc. These indicators can objectively reflect key performance of the equipment, such as operating efficiency, reliability and maintenance cost.

[0057] S130. Use data analysis algorithms to analyze patterns and trends of statistical indicators.

[0058] Use advanced data analysis techniques (such as data mining algorithms, fault tree analysis, machine learning models, etc.) to conduct in-depth analysis of equipment data. For example, use cluster analysis algorithms to classify equipment failure data and find out the characteristics and patterns of different types of failures; use regression analysis models to establish the relationship between equipment operating parameters and product quality, and provide a basis for optimizing equipment operating parameters. Through these analyses and mining, potential problems and optimization opportunities in equipment management can be discovered, and corresponding maintenance recommendations can be provided. For example, by analyzing the changing trend of equipment vibration data, it can be determined whether the equipment has potential failures such as bearing wear, providing valuable support for corporate decision-making.

[0059] S140. Generate reports and visualization icons based on monitoring and analysis results, predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

[0060] Generate various forms of reports and visualization charts based on the results of statistical analysis. The report content includes statistical data summary, data analysis conclusions, improvement suggestions, etc., and is provided to managers and decision makers in the form of documents (such as PDF, Excel). At the same time, through visualization tools (such as Echarts, Tableau, etc.), the statistical analysis results are displayed on the system interface in the form of intuitive charts (such as bar charts, line charts, pie charts, scatter charts, etc.), which makes it easier for users to quickly understand the meaning of the data and discover data trends, thereby improving decision-making efficiency.

[0061] When the equipment operation data exceeds the preset normal range, the system automatically issues a warning message (such as a pop-up window prompt, SMS notification, email notification, etc.) and provides detailed fault diagnosis information (such as possible fault causes, fault location, etc.) to help maintenance personnel quickly locate and solve the problem.

[0062] The method provided in this embodiment obtains the operating data and basic equipment information of the park equipment at the collection point, summarizes and organizes the operating data after pre-processing, and extracts key operating data, which can ensure the accuracy and comprehensiveness of the data source, effectively screen out the most valuable data subset, and reduce the interference of data redundancy and invalid information; based on the key operating data and basic equipment information, the operating status of the park equipment is monitored in real time and statistical indicators are calculated, which can instantly capture various working condition changes of the equipment and accurately calculate statistical indicators; data analysis algorithms are used to analyze the laws and trends of statistical indicators to provide a forward-looking perspective for park equipment management; reports and visualization icons are generated based on monitoring results and analysis results, which can improve the efficiency and accuracy of information communication, predict potential failures of park equipment, optimize equipment maintenance plans, and generate equipment management reports. The generated equipment management reports integrate all-round information on equipment operation, including monitoring data, analysis results, failure predictions, and maintenance plan execution, etc., providing a rich and detailed basis for enterprises to formulate long-term equipment management strategies.

[0063] In one embodiment, the following steps are also included:

[0064] For different types and models of equipment, create a general equipment template, define the basic equipment information of the general equipment, configure and manage the new equipment through the general equipment template to form the park equipment, basic equipment information, technical parameters, sensor configuration, data collection rules, maintenance plan and other standard information. Managers can create, edit and delete equipment templates according to actual needs. When adding new equipment, directly apply the corresponding equipment template to quickly complete the initialization of basic equipment information and configuration, improve equipment management efficiency, and when the equipment template is modified, the system can automatically update the equipment information created based on the template to ensure the consistency and accuracy of equipment management and adapt to changes in enterprise equipment types and adjustments to management requirements.

[0065] Establish an electronic file for each park equipment, and regularly update the electronic file based on the operation data of the park equipment. The electronic file includes basic equipment information, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports. When a new device is connected to the system, enter the detailed information of the device (such as device name, model, manufacturer, purchase date, installation location, etc.) into the relational database through the device management interface, and configure the corresponding sensors and data acquisition parameters for it. During the operation of the equipment, update the maintenance records, fault records and other information of the equipment in real time. This information comes from the operation feedback of the equipment maintenance personnel and the fault alarms automatically detected by the system.

[0066] The method provided in this embodiment significantly improves management efficiency and equipment operating benefits by achieving standardization, informatization and intelligence of park equipment management. The universal equipment template ensures fast and standardized configuration. The electronic archive completely records the equipment's entire life cycle information and updates it in real time, facilitating accurate decision-making, predictive maintenance and optimal resource allocation, reducing operation and maintenance costs and failure risks, and promoting continuous optimization of equipment management strategies to enhance overall competitiveness and sustainable development capabilities.

[0067] In one embodiment, the following steps are also included:

[0068] Through the management of collection points, select the device to which the collection point belongs. After selection, the "Device Number" column is automatically filled with the corresponding device number. This number is used as the unique identifier of the device to accurately locate the device-related collection point data during data storage and query, and to establish the association between the collection point and the park equipment. This association plays a key role in the data collection, storage and analysis process, ensuring that the collection point data can be correctly attributed to the data set of the corresponding device.

[0069] By setting the configuration information of the collection point, including "collection point name", "device name", "device number", "data type", "collection frequency", "data conversion formula", "status", "operation", etc., the data collection task of the data collection terminal is controlled. Specifically, it includes the following contents:

[0070] 1. Data type determination

[0071] The "Data Type" column provides a drop-down menu containing common data types predefined by the system, such as temperature, pressure, flow, current, voltage, displacement, speed, etc. The administrator selects the corresponding data type based on the physical quantity actually monitored at the collection point. After selection, the system further limits the setting range of subsequent related parameters or provides default values ​​based on the selected data type. For example, if the "Pressure" data type is selected, when setting the data conversion formula, the system automatically recommends some conversion formula templates for common pressure sensors for the administrator to refer to and modify. And when storing data, the system stores it according to the database field type corresponding to the selected data type to ensure the accuracy and consistency of data storage.

[0072] 2. Collection frequency setting

[0073] The administrator enters the data collection time interval of the collection point in the text box in the "Collection Frequency" column. The input format requires a positive integer plus a time unit. The time unit can be seconds, minutes, hours, etc., such as "5 seconds", "10 minutes", "1 hour", etc. The system checks the legality of the input collection frequency, including whether the format is correct and whether the value is within a reasonable range (for example, it cannot be less than 1 second or greater than 1 day, etc.). If the check fails, the corresponding error message pops up and requires the administrator to re-enter. The setting of the collection frequency directly affects the real-time nature and data volume of data collection. The administrator needs to consider and determine it based on multiple factors such as device operating characteristics, data importance, and system resources. For example, for the core parameters of some key devices, it may be necessary to set a higher collection frequency to monitor device status changes in real time; for some auxiliary or slowly changing parameters, the collection frequency can be appropriately reduced to reduce data storage and processing pressure.

[0074] 3. Data conversion formula configuration

[0075] In the "Data Conversion Formula" column, the administrator enters the corresponding formula according to the output characteristics of the sensor and the conversion relationship between the actual monitored physical quantity. The system provides a friendly interface for formula editing, supporting common mathematical operators (addition, subtraction, multiplication, division, power, etc.), functions (such as trigonometric functions, logarithmic functions, etc.), and brackets. For some common sensor types, the system automatically fills in the default conversion formula in the formula editing box after selecting the data type, and the administrator can modify it according to the actual situation. For example, for a pressure sensor, its output signal is a voltage value (V), and the range is 0-10V corresponding to the pressure range of 0-10MPa. Its conversion formula may be "pressure value = (collected voltage value * 10) / 10". During the data collection process, the acquisition terminal converts the collected raw voltage data into the actual pressure value according to this formula and then stores it in the database to ensure the accuracy and comprehensibility of the data. In order to help the administrator verify the correctness of the formula, the system provides a formula verification function. The administrator can enter some test data and click the verification button. The system calculates the result according to the formula and compares it with the expected result. If there is any inconsistency, the administrator is prompted to check whether the formula is correct.

[0076] 4. Collection point status management

[0077] The "Status" column displays the current working status of the collection point, including "Enabled", "Disabled", "Faulty", etc. The system automatically updates the status information based on the actual situation of data collection at the collection point. For example, when the collection point works normally and continuously collects data at the set collection frequency, the status is displayed as "Enabled"; when the administrator manually pauses data collection at a certain collection point, the status switches to "Disabled"; when the data collection terminal does not receive the signal from the collection point within a certain period of time or the collected data is abnormal (such as data outside the reasonable range, data format error, etc.) and cannot be restored to normal after multiple retries, the status is updated to "Faulty". The administrator can directly view the current status of the collection point in the status column, and for the collection point in the "Faulty" state, the system provides troubleshooting prompt information, such as checking whether the sensor connection is loose, checking whether the power supply is normal, etc., to help administrators quickly locate and solve problems.

[0078] 5. Operation function

[0079] In the "Operation" column, there are function buttons for editing, deleting and viewing detailed information for each collection point. Click the "Edit" button to enter the editing mode of the collection point configuration. The administrator can modify the configuration parameters of the collection point (except the device number. If the device needs to be modified, the collection point must be deleted first and then re-created and associated with the new device). After the modification is completed, click the Save button, and the system will save the updated configuration information to the database. Click the "Delete" button, and the system will pop up a confirmation dialog box to ask the administrator whether to delete the collection point. If the administrator confirms the deletion, the system will delete the configuration information of the collection point and the related historical data from the database (you can choose whether to back up the historical data), and at the same time, remove the association with the device. Click the "View Details" button, and a new window will pop up to display the detailed configuration information of the collection point, historical data collection records (including collection time, collection data value, comparison before and after data conversion, etc.) and related log information of the data collection terminal (such as collection request sending time, receiving response time, whether there is a data transmission error, etc.), so that the administrator can fully understand the working status of the collection point and conduct data analysis and troubleshooting.

[0080] The method provided in this embodiment can accurately collect data and integrate them efficiently, build a stable bridge to connect collection points and park equipment, realize targeted data acquisition, accurately configure collection points to drive data collection terminals to operate accurately, effectively guarantee data quality and timeliness, and help to accurately control equipment status in real time, warn of faults in advance, optimize maintenance resource allocation, reduce costs, and provide high-value basis for park equipment management decisions, thereby promoting the coordinated improvement of management efficiency and operational benefits.

[0081] In one embodiment, the operation data and basic information of the park equipment at the collection point are obtained, the operation data is summarized and sorted after pre-processing, and key data indicators are extracted, which also includes the following steps:

[0082] The pre-processed operation data is stored in a real-time database according to different dimensions such as device number and timestamp for organization and indexing. For example, the temperature, pressure, vibration and other parameter data of each device are stored in sequence according to the collection time, so that the operation status changes of the equipment within a specific time period can be quickly retrieved and analyzed later.

[0083] Choose a real-time database system specifically designed for industrial real-time data processing, such as Influx DB or TimescaleDB. These databases have efficient data writing and query performance and can quickly process massive amounts of real-time data. Install and configure the database on the data center server, and reasonably plan the database storage space and hardware resources (such as memory, CPU, etc.) based on factors such as the number of devices, data collection frequency, and data retention period.

[0084] The key operation data is stored in the relational database using the database table structure, and the relationship between tables is established through the database mechanism. The relational database (such as MySQL, Oracle, etc.) is used to store the basic information of the equipment, configuration parameters, maintenance records, user information and other structured data. Design a reasonable database table structure, establish the core data tables such as the equipment table (storing basic information of the equipment), sensor table (recording the relationship and parameters between the sensor and the equipment), maintenance record table (saving detailed information on equipment maintenance), user table (managing the account, authority, etc. of the system user), and establish the relationship between the tables through database mechanisms such as foreign key constraints to ensure the consistency and integrity of the data.

[0085] The real-time database and the relational database interact with each other through the data synchronization service. For example, the equipment operation data in the real-time database is regularly summarized and sorted, and key data indicators are extracted and stored in the relational database for long-term data archiving and complex data analysis queries.

[0086] The method provided in this embodiment can realize efficient data storage and flexible use. The real-time database stores pre-processed data according to different dimensions to ensure fast data writing and query to meet real-time monitoring needs. The relational database stores key data in a structured manner and establishes associations to facilitate complex analysis and data integrity maintenance. The data synchronization service promotes interaction between the two, ensures data consistency and liquidity, improves data management efficiency, provides strong support for accurate equipment operation evaluation, fault diagnosis, strategy optimization, etc., and enhances the scientificity and timeliness of park equipment management decisions.

[0087] System Example

[0088] According to an embodiment of the present invention, a park equipment data collection system is provided, such as Figure 2 As shown, it is a structural diagram of the park equipment data acquisition system provided in this embodiment. The park equipment data acquisition system according to the embodiment of the present invention includes a data acquisition module 21, an equipment monitoring module 22, a data analysis module 23 and an application module 24.

[0089] The data acquisition module 21 is used to obtain the operation data and basic information of the park equipment at the collection point, summarize and organize the operation data after pre-processing, and extract key operation data.

[0090] The equipment monitoring module 22 is used to monitor the operating status of the park equipment in real time and calculate statistical indicators based on key operating data and basic equipment information.

[0091] The data analysis module 23 is used to analyze the rules and trends of statistical indicators using data analysis algorithms.

[0092] The application module 24 is used to generate reports and visualization icons based on the monitoring results and analysis results, and predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

[0093] In the system provided in this embodiment, the data acquisition module 21 acquires the operating data and basic equipment information of the park equipment at the collection point, summarizes and organizes the operating data after preprocessing, and extracts key operating data, which can ensure the accuracy and comprehensiveness of the data source, effectively screen out the most valuable data subset, and reduce the interference of data redundancy and invalid information; the equipment monitoring module 22 monitors the operating status of the park equipment in real time and calculates statistical indicators based on the key operating data and basic equipment information, and can instantly capture various working condition changes of the equipment, and can also accurately calculate statistical indicators; the data analysis module 23 uses data analysis algorithms to analyze the laws and trends of statistical indicators, and provides a forward-looking perspective for park equipment management; the application module 24 generates reports and visualization icons based on the monitoring results and analysis results, which can improve the efficiency and accuracy of information communication, predict potential failures of park equipment, optimize equipment maintenance plans, and generate equipment management reports. The generated equipment management reports integrate all-round information on equipment operation, including monitoring data, analysis results, failure predictions, and maintenance plan execution, etc., providing a rich and detailed basis for enterprises to formulate long-term equipment management strategies.

[0094] In one embodiment, a configuration module 25 and a file creation module 26 are also included.

[0095] The configuration module 25 is used to create a general device template, define basic device information of the general device, and configure and manage the newly added devices through the general device template to form campus devices.

[0096] The filing module 26 is used to create an electronic file for each park equipment and regularly update the electronic file based on the operation data of the park equipment. The electronic file includes basic information of the equipment, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports.

[0097] The system provided in this embodiment significantly improves management efficiency and equipment operating benefits by realizing standardization, informatization and intelligence of park equipment management. The universal equipment template ensures fast and standardized configuration. The electronic archive completely records the equipment's entire life cycle information and updates it in real time, facilitating accurate decision-making, predictive maintenance and optimal resource allocation, reducing operation and maintenance costs and failure risks, and promoting continuous optimization of equipment management strategies to enhance overall competitiveness and sustainable development capabilities.

[0098] In one embodiment, it also includes a collection point management module 27, which is used to establish an association relationship between the collection point and the park equipment by managing the collection point, and control the data collection task of the data collection terminal by setting the configuration information of the collection point.

[0099] The system provided in this embodiment can accurately collect data and integrate them efficiently, build a stable bridge to connect collection points and park equipment, realize targeted data acquisition, accurately configure collection points to drive data collection terminals to operate accurately, effectively guarantee data quality and timeliness, and help to accurately control equipment status in real time, warn of faults in advance, optimize maintenance resource allocation, reduce costs, and provide high-value basis for park equipment management decisions, thereby promoting the coordinated improvement of management efficiency and operational benefits.

[0100] In one embodiment, the data acquisition module 21 includes a first storage unit 211 , a second storage unit 212 and an interaction unit 213 .

[0101] The first storage unit 211 is used to store the pre-processed operation data in a real-time database according to different dimensions for organization and indexing.

[0102] The second storage unit 212 is used to store the key operation data in a relational database using a database table structure, and to establish associations between tables through a database mechanism.

[0103] The interaction unit 213 is used for data interaction between the real-time database and the relational database through the data synchronization service.

[0104] The system provided in this embodiment can realize efficient data storage and flexible use. The real-time database stores pre-processed data according to different dimensions to ensure fast data writing and query to meet real-time monitoring needs. The relational database stores key data in a structured manner and establishes associations to facilitate complex analysis and data integrity maintenance. The data synchronization service promotes interaction between the two, ensures data consistency and liquidity, improves data management efficiency, provides strong support for accurate equipment operation evaluation, fault diagnosis, strategy optimization, etc., and enhances the scientificity and timeliness of park equipment management decisions.

[0105] The embodiment of the present invention is a system embodiment corresponding to the above-mentioned method embodiment. The specific operations of the processing steps of each module can be understood by referring to the description of the method embodiment, which will not be repeated here.

[0106] like Figure 3 As shown, the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for collecting data of campus equipment in the above-mentioned embodiment is implemented; or when the computer program is executed by a processor, the method for collecting data of campus equipment in the above-mentioned embodiment is implemented.

[0107] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0108] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for collecting data from a park device, characterized in that: The following steps are involved: Obtain the operation data and basic information of the park equipment at the collection point, summarize and organize the operation data after pre-processing, and extract key operation data; Based on the key operation data and the basic information of the equipment, real-time monitoring of the operation status of the park equipment and calculation of statistical indicators are performed; Analyzing the patterns and trends of the statistical indicators using data analysis algorithms; Generate reports and visualization icons based on monitoring and analysis results, predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

2. The method for collecting data of park equipment according to claim 1, characterized in that: The following steps are also included: Create a general device template, define basic device information of the general device, and configure and manage the newly added devices through the general device template to form campus devices; Establish an electronic file for each park equipment, and regularly update the electronic file based on the operating data of the park equipment, wherein the electronic file includes basic equipment information, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports.

3. The method for collecting data of park equipment according to claim 1, characterized in that: The following steps are also included: Establish the association between collection points and park equipment through the management of collection points; By setting the configuration information of the collection point, the data collection task of the data collection terminal is controlled.

4. The method for collecting data of park equipment according to claim 1, characterized in that: After the preprocessing, the operation data is summarized and sorted, and key data indicators are extracted, and the following steps are also included: The pre-processed operation data is stored in a real-time database according to different dimensions for organization and indexing; The key operation data is stored in a relational database using a database table structure, and an association relationship between tables is established through a database mechanism; The real-time database and the relational database interact with each other through a data synchronization service.

5. A park equipment data acquisition system, characterized in that: It includes data acquisition module, equipment monitoring module, data analysis module and application module; The data acquisition module is used to acquire the operation data and basic information of the park equipment at the collection point, summarize and organize the operation data after pre-processing, and extract key operation data; The equipment monitoring module is used to monitor the operating status of the park equipment in real time and calculate statistical indicators based on the key operating data and basic equipment information; The data analysis module is used to analyze the rules and trends of the statistical indicators using a data analysis algorithm; The application module is used to generate reports and visualization icons based on monitoring results and analysis results, predict potential failures of campus equipment, optimize equipment maintenance plans, and generate equipment management reports.

6. The park equipment data acquisition system according to claim 5, characterized in that: It also includes configuration module and archiving module; The configuration module is used to create a general device template, define basic device information of the general device, and configure and manage the newly added device through the general device template to form a campus device; The filing module is used to create an electronic file for each park equipment and regularly update the electronic file based on the operating data of the park equipment. The electronic file includes basic equipment information, equipment technical parameters, equipment installation and commissioning records, equipment maintenance records, equipment repair records, equipment operation history data and equipment management reports.

7. The park equipment data acquisition system according to claim 5, characterized in that: It also includes a collection point management module, which is used to establish an association relationship between the collection point and the park equipment through the management of the collection point, and to control the data collection task of the data collection terminal by setting the configuration information of the collection point.

8. The park equipment data acquisition system according to claim 5, characterized in that: The data acquisition module includes a first storage unit, a second storage unit and an interaction unit; The first storage unit is used to store the pre-processed operation data in a real-time database according to different dimensions for organization and indexing; The second storage unit is used to store the key operation data in a relational database using a database table structure, and to establish an association relationship between tables through a database mechanism; The interaction unit is used for data interaction between the real-time database and the relational database through a data synchronization service.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the campus equipment data collection method as described in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the campus equipment data collection method as described in any one of claims 1 to 4 are implemented.

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