A data acquisition system and method based on an industrial internet operating system

Abstract

The application discloses a kind of data acquisition system and method based on industrial internet operating system, belong to data technical field, including equipment data acquisition module, data preprocessing module, equipment state evaluation module, data packing processing module, data level classification module.The application can comprehensively obtain the running state data of each industrial production equipment, and the data is converted into digital, it is convenient for subsequent data processing work;It can compress the running state digital data sequence, reduce the requirement of transmission process to hardware, and increase the equipment type identification, equipment model identification corresponding to each running state digital data sequence, it is convenient for subsequent level classification work of each running state digital data sequence, also it is convenient for subsequent data classification storage work;It can be easily given each running state digital data sequence and increase level identification, it is convenient for subsequent data level and sets different level access authentication mode to data access.

Description

Technical Field

[0001] This invention relates to the field of data acquisition technology, and specifically to a data acquisition system and method based on an industrial internet operating system. Background Technology

[0002] An Industrial Internet Operating System (IIoT) is a commonly used industrial management tool, developed by Rootcloud. Rootcloud is committed to transforming existing IIoT operating systems into universal attributes and empowering new business models and operating systems based on overall IIoT business solutions or operating systems. It rapidly provides reusable templates for digital transformation, penetrating deep into the capillaries of the manufacturing industry and accelerating the upgrading of the industrial base and the modernization of the industrial chain.

[0003] The Industrial Internet Operating System (IIoT) is the "next-generation highway" for industrial digital transformation. It possesses the characteristics of next-generation infrastructure, accumulating general industrial capabilities, common technologies needed for enterprise digital transformation, and innovative applications built upon these common technologies. Specifically, the system connects downwards to a massive number of devices, providing a unified interface for various types of equipment to achieve interconnectivity between different devices; and connects upwards to industrial application software such as industrial apps.

[0004] The Industrial Internet operating system is equivalent to Windows in the PC era and Android in the mobile era. Industrial application software is the application running on the platform, similar to various apps on a mobile phone. Users download and combine the applications they need, thereby continuously reducing the cost and barriers to digital transformation in various industries, especially benefiting SMEs with relatively limited funds and digital experience. Industrial application software is based on the Industrial Internet, carrying industrial knowledge and experience to meet specific needs. These specific needs can include various vertical fields, such as machinery, automotive, and electronics manufacturing; or they can include various stages of industrial processes, such as R&D design, production manufacturing, and operations management.

[0005] Existing data acquisition systems based on industrial internet operating systems have certain shortcomings in use, such as the inability to better evaluate the status of industrial equipment based on collected data and the inconvenience of classifying equipment data. Therefore, a data acquisition system based on an industrial internet operating system is proposed. Summary of the Invention

[0006] The technical problem to be solved by this invention is: how to solve the problem that existing industrial internet operating systems cannot better evaluate the status of industrial equipment by collecting data and are inconvenient to classify the data of equipment, and provides a data acquisition system based on an industrial internet operating system.

[0007] The present invention solves the above-mentioned technical problems through the following technical solutions, the present invention comprising:

[0008] The equipment data acquisition module is used to acquire simulated data sequences of the operating status of each industrial device through sensors, and to perform analog-to-digital conversion on the simulated data sequences of the operating status of each industrial device.

[0009] The data preprocessing module is used to preprocess the digital data sequences of the operating status of various industrial equipment;

[0010] Data packaging and processing is used to package and compress the pre-processed digital data sequence of the operating status of various industrial equipment, and add equipment type and equipment model identifiers.

[0011] The data level classification module is used to obtain the industrial equipment level information corresponding to each operating status digital data sequence according to the preset industrial equipment level-type matching library, and add level identifiers to each operating status digital data sequence.

[0012] The equipment status assessment module is used to record the frequency of abnormal data occurrences in the digital data sequence of operating status, calculate the abnormality degree of the current operating status digital data sequence based on the frequency of abnormal data occurrences, calculate the equipment health value based on the abnormality degree of each operating status digital data sequence of individual equipment within a set time period, and then assess the equipment status based on the equipment health value of each industrial equipment.

[0013] Furthermore, the equipment data acquisition module includes a sensor unit, an analog-to-digital conversion unit, and a data transmission unit. The sensor unit includes multiple sensors, each of which is communicatively connected to various industrial equipment according to data acquisition requirements, and is used to collect simulated data sequences of the operating status of each industrial device. The analog-to-digital conversion unit is used to convert the data type of the simulated data sequences of the operating status of each industrial device from analog data to digital data. The data transmission unit is used to send the digital data to the data preprocessing module in parallel.

[0014] Furthermore, the data preprocessing module includes a data cleaning unit and a data filling unit. The data cleaning unit is used to delete individual data points in the digital data sequence of the operating status of each piece of industrial equipment that exceed the historical average and reach a set threshold. The data filling unit is used to fill in the missing individual data points in the digital data sequence of the operating status of each piece of industrial equipment, and at the same time, fill in the data corresponding to the deleted time points in the digital data sequence of the operating status of each piece of industrial equipment.

[0015] Furthermore, the packaging processing module includes a data packet compression unit, a device type identifier addition unit, and a device model identifier addition unit. The data packet compression unit is used to package and compress the digital data sequences of the operating status of each industrial device in the pre-processed industrial equipment. The device type identifier addition unit is used to add a corresponding device type identifier to the header of each compressed digital data sequence of operating status. The device model identifier addition unit is used to add a corresponding device model identifier to the tail of each compressed digital data sequence of operating status.

[0016] Furthermore, the data level classification module includes a level matching unit and a level identifier addition unit; the level matching unit is used to obtain the level information of each industrial equipment corresponding to each operating state digital data sequence based on the equipment model identifier corresponding to each operating state digital data sequence and in combination with a preset industrial equipment level-type matching library; the level identifier addition unit is used to add a level identifier to the header of each operating state digital data sequence compressed package containing the equipment type identifier and the equipment model identifier based on the level information of each industrial equipment corresponding to each operating state digital data sequence.

[0017] Furthermore, the equipment status assessment module includes an anomaly frequency recording unit and a status assessment unit. The anomaly frequency recording unit is used to record the frequency of anomaly data occurrences in the current operating status digital data sequence, and to record the data during the acquisition time period of the operating status digital data sequence. The status assessment unit is used to calculate the anomaly degree of the current operating status digital data sequence based on the anomaly data, and to calculate the equipment status health value based on the anomaly degree of each operating status digital data sequence of a single device within a set time period, and then assess the equipment status based on the equipment status health value of each industrial device.

[0018] Furthermore, the data filling unit fills in the missing data points by using the average of historical data from each industrial device in that type of industrial equipment.

[0019] Furthermore, the equipment type identifier is a single uppercase letter, the equipment model identifier is a three-digit number, and the industrial equipment level information includes high-level, medium-level, and low-level, where high-level represents core equipment, medium-level represents secondary core equipment, and low-level represents non-core and non-secondary core equipment.

[0020] Furthermore, the formula for calculating the equipment health value is as follows:

[0021] J = (Y1 + ... + Y) n ) / n

[0022] Y = (P 异常 / P 总 )*100%

[0023] Where J represents the device health value of a single device within a set time period, Y1…Y n P represents the anomaly degree of a sequence of n digital data representing the operating status of a single device within a specified time period. 异常 P represents the frequency of abnormal data occurrences in a single sequence of running status digital data. 总 This represents the number of data points in a single sequence of digital data representing the operating status.

[0024] Compared with the prior art, the present invention has the following advantages: it can obtain the level information of each industrial production equipment corresponding to each operating state digital data sequence based on the equipment model identifier corresponding to each operating state digital data sequence and in combination with the preset level-type matching library of each industrial production equipment, thereby conveniently adding level identifiers to each operating state digital data sequence, and facilitating the setting of different levels of access authentication methods for data access based on the data level. Attached Figure Description

[0025] Figure 1 This is the overall architecture diagram of the data acquisition system based on the industrial internet operating system in this embodiment of the invention. Detailed Implementation

[0026] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0027] like Figure 1 As shown, this embodiment provides a technical solution: a data acquisition system based on an industrial internet operating system, including: an equipment data acquisition module, a data preprocessing module, an equipment status assessment module, a data packaging and processing module, and a data level classification module;

[0028] In this embodiment, the equipment data acquisition module includes a sensor unit, an analog-to-digital conversion unit, and a data transmission unit. The sensor unit includes multiple sensors, each connected to various industrial equipment according to data acquisition requirements. These sensors collect simulated data sequences of the operating status of each piece of industrial equipment and transmit these sequences to the analog-to-digital conversion unit for conversion processing. The analog-to-digital conversion unit receives the simulated data sequences of the operating status of each piece of industrial equipment collected by the sensor unit, converts the data type from analog to digital, and then transmits these digital data sequences to the data transmission unit. The data transmission unit receives the digital data sequences of the operating status of each piece of industrial equipment and sends them in parallel to the data preprocessing module for preprocessing. Through this equipment data acquisition module, the operating status data of each piece of industrial equipment can be comprehensively acquired, and the data can be converted from analog to digital, facilitating subsequent data processing.

[0029] In this embodiment, the data preprocessing module includes a data cleaning unit and a data filling unit. The data cleaning unit is used to delete individual data points in the digital data sequence of the operating status of each industrial device in various types of industrial equipment that exceed the historical average and reach a set threshold, and then transmits the digital data sequence of the operating status of each industrial device in various types of industrial equipment after deletion to the data filling unit. The data filling unit is used to fill in the missing individual data points in the digital data sequence of the operating status of each industrial device in various types of industrial equipment, and at the same time, fill in the data corresponding to the deleted time points in the digital data sequence of the operating status of each industrial device in various types of industrial equipment, so that the digital data sequence of the operating status of each industrial device in various types of industrial equipment becomes a complete sequence, that is, each time point has a unique corresponding data point.

[0030] In this embodiment, the data packaging and processing module includes a data packet compression unit, a device type identifier addition unit, and a device model identifier addition unit. The data packet compression unit is used to package and compress the pre-processed digital data sequences of the operating status of various industrial devices to obtain compressed packages of each operating status digital data sequence, and transmit each compressed package of the operating status digital data sequence to the device type identifier addition unit. The device type identifier addition unit is used to add a corresponding device type identifier to the header of each compressed package of the operating status digital data sequence, and transmit each compressed package of the operating status digital data sequence containing the device type identifier to the device model identifier addition unit. The identifier addition unit is used to add a corresponding device model identifier to the end of each running status digital data sequence compressed package, and send each running status digital data sequence compressed package containing the device type identifier and device model identifier to the data level classification module for level classification processing. Through the set data packet compression unit, device type identifier addition unit, and device model identifier addition unit, the running status digital data sequence can be compressed, reducing the hardware requirements of the transmission process, and adding the device type identifier and device model identifier corresponding to each running status digital data sequence, which facilitates the subsequent level classification of each running status digital data sequence and the subsequent data classification and storage work.

[0031] In this embodiment, the data level classification module includes a level matching unit and a level identifier addition unit. The level matching unit is used to obtain the industrial equipment level information corresponding to each operating state digital data sequence based on the equipment model identifier corresponding to each operating state digital data sequence and in conjunction with a preset industrial equipment level-type matching library, and then send the industrial equipment level information corresponding to each operating state digital data sequence to the level identifier addition unit. The level identifier addition unit is used to add a level identifier to the header of each operating state digital data sequence compressed package containing the equipment type identifier and the equipment model identifier based on the industrial equipment level information corresponding to each operating state digital data sequence. Through the set level matching unit, the industrial equipment level information corresponding to each operating state digital data sequence can be obtained based on the equipment model identifier corresponding to each operating state digital data sequence and in conjunction with the preset industrial equipment level-type matching library, thereby conveniently adding level identifiers to each operating state digital data sequence, which facilitates setting different levels of access authentication methods for data access based on the data level.

[0032] In this embodiment, the equipment status assessment module includes an anomaly frequency recording unit and a status assessment unit. The anomaly frequency recording unit records the frequency of abnormal data (data exceeding the historical average and reaching a set threshold, missing data) in the current operating status digital data sequence, and records the data during the collection time period of the operating status digital data sequence. The status assessment unit calculates the anomaly degree of the current operating status digital data sequence based on the abnormal data, calculates the equipment status health value based on the anomaly degree of each operating status digital data sequence of a single device within a set time period, and then assesses the equipment status based on the equipment status health value of each industrial device. Through the anomaly frequency recording unit, the frequency of abnormal data and the collection time period can be conveniently recorded in real time when collecting data from various industrial devices, facilitating subsequent assessment of the operating status of each industrial device and reminding staff to perform timely maintenance, thus significantly reducing the adverse impact on the production line.

[0033] In this embodiment, the data filling unit fills in the missing data points by filling in the average of the historical data of each industrial device in this type of industrial equipment.

[0034] In this embodiment, the equipment type identifier is a single uppercase letter, such as A for production equipment, B for quality inspection equipment, C for packaging equipment, and so on.

[0035] In this implementation, the device model identifier is a three-digit identifier. For example, 001 represents the first device in the corresponding device class, 002 represents the second device in the corresponding device class, 003 represents the third device in the corresponding device class, and so on.

[0036] In this embodiment, the preset industrial equipment level-type matching library contains pre-set one-to-one correspondence of industrial equipment level and industrial equipment type information. The administrator can change the industrial equipment level information corresponding to the industrial equipment type. The industrial equipment level information includes high-level, medium-level, and low-level, where high-level represents core equipment, medium-level represents secondary core equipment, and low-level represents non-core and non-secondary core equipment.

[0037] In this embodiment, the formula for calculating the device health status value is as follows:

[0038] J = (Y1 + ... + Y) n ) / n

[0039] Y = (P 异常 / P 总 )*100%

[0040] Where J represents the device health value of a single device within a set time period, Y1…Y n P represents the anomaly degree of a sequence of n digital data representing the operating status of a single device within a specified time period. 异常 P represents the frequency of abnormal data occurrences in a single sequence of running status digital data. 总 This represents the number of data points in a single operational status digital data sequence. By calculating the health value of a single device within a set time period, the device status of that single device can be effectively assessed within that time period.

[0041] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A data acquisition system based on an industrial internet operating system, characterized in that, include: The equipment data acquisition module is used to acquire simulated data sequences of the operating status of each industrial device through sensors, and to perform analog-to-digital conversion on the simulated data sequences of the operating status of each industrial device. The data preprocessing module is used to preprocess the digital data sequences of the operating status of various industrial equipment; The data packaging and processing module is used to package and compress the pre-processed digital data sequence of the operating status of various industrial equipment, and add equipment type identifier and equipment model identifier. The data packaging and processing module includes a data packet compression unit, a device type identifier addition unit, and a device model identifier addition unit. The data packet compression unit is used to package and compress the operating status digital data sequences of various industrial devices that have undergone preprocessing. The device type identifier addition unit is used to add a corresponding device type identifier to the header of each operating status digital data sequence compressed package. The device model identifier addition unit is used to add a corresponding device model identifier to the tail of each operating status digital data sequence compressed package. The data level classification module is used to obtain the industrial equipment level information corresponding to each operating status digital data sequence according to the preset industrial equipment level-type matching library, and add level identifiers to each operating status digital data sequence. The data level classification module includes a level matching unit and a level identifier addition unit. The level matching unit is used to obtain the level information of each industrial equipment corresponding to each operating state digital data sequence based on the equipment model identifier corresponding to each operating state digital data sequence and in combination with a preset industrial equipment level-type matching library. The level identifier addition unit is used to add a level identifier to the header of each operating state digital data sequence compressed package containing the equipment type identifier and the equipment model identifier based on the level information of each industrial equipment corresponding to each operating state digital data sequence. The equipment status assessment module is used to record the frequency of abnormal data occurrences in the digital data sequence of operating status, calculate the abnormality degree of the current operating status digital data sequence based on the frequency of abnormal data occurrences, calculate the equipment health value based on the abnormality degree of each operating status digital data sequence of individual equipment within a set time period, and then assess the equipment status based on the equipment health value of each industrial equipment.

2. The data acquisition system based on an industrial internet operating system according to claim 1, characterized in that: The equipment data acquisition module includes a sensor unit and an analog-to-digital conversion unit. The sensor unit includes multiple sensors, each of which is connected to various industrial equipment according to data acquisition requirements to collect simulated data sequences of the operating status of each industrial device. The analog-to-digital conversion unit is used to convert the data type of the simulated data sequences of the operating status of each industrial device from analog data to digital data.

3. The data acquisition system based on an industrial internet operating system according to claim 2, characterized in that: The data preprocessing module includes a data cleaning unit and a data filling unit. The data cleaning unit is used to delete individual data points in the digital data sequence of the operating status of each piece of industrial equipment that exceed the historical average and reach a set threshold. The data filling unit is used to fill in the missing individual data points in the digital data sequence of the operating status of each piece of industrial equipment, and at the same time, fill in the data corresponding to the deleted time points in the digital data sequence of the operating status of each piece of industrial equipment.

4. The data acquisition system based on an industrial internet operating system according to claim 1, characterized in that: The equipment status assessment module includes an anomaly frequency recording unit and a status assessment unit. The anomaly frequency recording unit is used to record the frequency of anomaly data occurrences in the current operating status digital data sequence and to record the data during the acquisition time period of the operating status digital data sequence. The status assessment unit is used to calculate the anomaly degree of the current operating status digital data sequence based on the anomaly data, and to calculate the equipment status health value based on the anomaly degree of each operating status digital data sequence of a single device within a set time period. Finally, the equipment status is assessed based on the equipment status health value of each industrial device.

5. A data acquisition system based on an industrial internet operating system according to claim 3, characterized in that: The data filling unit is filled by filling the missing data points with the average of the historical data of each industrial device in this type of industrial equipment.

6. A data acquisition system based on an industrial internet operating system according to claim 5, characterized in that: The equipment type identifier is a single uppercase letter, and the equipment model identifier is a three-digit number. The industrial equipment level information includes high-level, medium-level, and low-level, where high-level represents core equipment, medium-level represents secondary core equipment, and low-level represents non-core and non-secondary core equipment.

7. A data acquisition system based on an industrial internet operating system according to claim 6, characterized in that: The formula for calculating the equipment health status value is as follows: J=(Y1+…+Y n ) / n Y=(P 异常 / P 总 ) 100% Where J represents the device health value of a single device within a set time period, Y1…Y n P represents the anomaly degree of a sequence of n digital data representing the operating status of a single device within a specified time period. 异常 P represents the frequency of abnormal data occurrences in a single sequence of running status digital data. 总 This represents the number of data points in a single sequence of digital data representing the operating status.

8. A data acquisition method based on an industrial internet operating system, characterized in that, The data acquisition system described in any one of claims 1-7 is used to collect data from various industrial devices under the Industrial Internet operating system, comprising the following steps: S1: Acquire simulated data sequences of the operating status of each industrial device through sensors, and perform analog-to-digital conversion on the simulated data sequences of the operating status of each industrial device; S2: Preprocess the digital data sequence of the operating status of each industrial device; S3: Package and compress the pre-processed digital data sequence of the operating status of each industrial device, and add device type identifier and device model identifier; S4: Based on the preset industrial equipment level-type matching library, obtain the industrial equipment level information corresponding to each operating status digital data sequence, and add level identifiers to each operating status digital data sequence; S5: Record the frequency of abnormal data occurrences in the digital data sequence of operating status, calculate the abnormality degree of the current digital data sequence of operating status based on the frequency of abnormal data occurrences, calculate the equipment health value based on the abnormality degree of each digital data sequence of operating status of individual equipment within a set time period, and then evaluate the equipment status based on the equipment health value of each industrial equipment.

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