Multi-type data acquisition method, system, terminal and storage medium

Abstract

The application relates to a multi-type data acquisition method, system, terminal and storage medium, wherein the multi-type data acquisition method is suitable for a wired industrial sensor and comprises the following steps: receiving a data acquisition model, completing parameter setting of a corresponding sensor module, generating a parameter setting completion identifier corresponding to the current sensor module and uploading the parameter setting completion identifier to a backend platform; receiving a block data packet and a time sequence data packet and forwarding the block data packet and the time sequence data packet to the backend platform, wherein the block data packet is original data in a single data acquisition process, and the time sequence data packet contains one or more time sequence data obtained by processing the original data and corresponding sampling time stamps. The application can realize efficient integration of various industrial sensors, can adjust data and signal types required to be acquired at will, can realize acquisition of various types of analog signals by one data acquisition terminal, and can control the number of data acquisition terminals while fully utilizing transmission interface resources.

Description

Technical Field

[0001] This application relates to the fields of industrial internet and industrial intelligence applications, and in particular to a method, system, terminal and storage medium for acquiring multiple types of data from wired industrial sensors. Background Technology

[0002] Industrial data acquisition is one of the most practical and frequent needs in industrial manufacturing. Various industrial sensors are typically used in different stages of industrial manufacturing to collect various types of industrial data, such as vibration, temperature, current, pressure, and flow rate. Due to the complexity of industrial production environments and the cost of equipment deployment, most mainstream and widely used industrial sensors are currently wired. These industrial sensors output analog signals such as voltage, current, and IEP, which are connected to a data acquisition terminal via aviation connectors or other interfaces. Upon receiving the analog signals, the data acquisition terminal converts them into digital signals using an ADC, and then uploads the digital signals to backend equipment or an industrial internet cloud platform.

[0003] In practical applications, different industrial sensors collect different types of data and generate different types of analog signals, requiring different transmission interfaces and ADC conversion circuits. Therefore, typically, one data acquisition terminal can only be compatible with one type of industrial sensor. If the monitored equipment or production environment has multiple types of industrial sensors, multiple different data acquisition terminals need to be configured, which obviously increases equipment deployment costs and wastes resources.

[0004] To address the aforementioned issues, some new types of data acquisition terminals have emerged. These terminals can support the connection of different industrial sensors in fixed combinations, such as current + voltage, voltage + IEPE, etc. However, due to differences in transmission interfaces and ADC conversion circuits, and the incompatibility of interfaces, these terminals often fix different types and numbers of transmission interfaces according to the specific target monitoring equipment and industrial sensor type requirements, aiming to collect multiple types of industrial data from a single terminal. While this setup is feasible for specific target monitoring equipment, changes in the application scenario can lead to problems such as mismatched transmission interfaces with application requirements, insufficient number of transmission interfaces affecting data acquisition, or redundant transmission interfaces resulting in wasted resources. Furthermore, to support multiple data types at the hardware level, the internal acquisition and ADC conversion circuits of these terminals become exceptionally complex, occupying a large PCB area, thus increasing the overall size of the terminal and preventing miniaturization, impacting its subsequent installation and use.

[0005] In view of the various shortcomings of the existing technologies, how to propose a brand-new multi-type data acquisition scheme for wired industrial sensors, so as to realize the acquisition of multiple different types of analog signals by a single data acquisition terminal, with data and signal types that can be freely defined, and to make full use of transmission interface resources while controlling the number of data acquisition terminals, has become an urgent problem for those skilled in the art. Summary of the Invention

[0006] To better meet the diverse data acquisition needs in the Industrial Internet, this application provides a multi-type data acquisition method, system, terminal, and storage medium. The solution of this application can efficiently integrate various industrial sensors, arbitrarily adjust the types of data and signals to be acquired, and enable a single data acquisition terminal to acquire multiple different types of analog signals, while controlling the number of data acquisition terminals and fully utilizing transmission interface resources.

[0007] Firstly, this application provides a multi-type data acquisition method, which adopts the technical solution described below.

[0008] A multi-type data acquisition method, adapted for wired industrial sensors, includes the following steps:

[0009] The system receives data acquisition models from each sensor module one by one, sets the parameters of the corresponding sensor module according to the data acquisition models, generates a parameter setting completion identifier corresponding to the current sensor module after the parameter setting is completed, and uploads the parameter setting completion identifier to the backend platform.

[0010] The system receives block data packets and time-series data packets one by one from each of the sensor modules that have the parameter setting completion identifier. The block data packets are the raw data obtained by the sensor module after converting the physical quantity data from the industrial sensor received during a single data acquisition process through ADC conversion. The time-series data packets contain one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. The received block data packets and time-series data packets are then forwarded to the backend platform.

[0011] By adopting the above technical solution, the sensor module connected to the industrial sensor is connected to the back-end platform, realizing the simultaneous adaptation of multiple sensor modules and various types of industrial sensors. This allows for the arbitrary combination of different sensor types according to usage needs, significantly improving the flexibility and compatibility of multi-type data acquisition.

[0012] Preferably, each sensor module corresponds to a unique data acquisition model, which includes sensor type, acquired physical quantity, current software and hardware version information, current acquisition parameters, upload parameters, and a list of data types.

[0013] By adopting the above technical solution, the specific content of the data acquisition model in the solution has been refined and defined, providing a clear execution target for subsequent parameter settings and adjustments.

[0014] Preferably, the step of setting the parameters of the corresponding sensor module based on the data acquisition model includes the following steps:

[0015] The system searches locally for setting parameter information corresponding to the current data acquisition model. If the setting parameter information exists, it sends the found setting parameter information to the corresponding sensor module, which then updates the data acquisition model based on the setting parameter information and completes the parameter setting for the sensor module. If the setting parameter information does not exist, the current data acquisition model is saved locally. The next time data is interacted with the backend platform, the system searches for the corresponding setting parameter information in the setting parameter database of the backend platform based on the locally stored data acquisition model. If the search is successful, the setting parameter information is downloaded locally.

[0016] By adopting the above technical solution, the parameter setting process of the sensor module has been refined and defined, realizing the automated and real-time adjustment of data acquisition parameters during the data acquisition process. This not only further ensures the flexibility and compatibility of the data acquisition process, but also significantly improves the convenience and efficiency of the parameter setting process.

[0017] Preferably, the multi-type data acquisition method further includes the following steps:

[0018] The system receives parameter adjustment instructions from the backend platform, generates parameter adjustment information based on these instructions, and compares the parameter adjustment information with locally stored setting parameters. If locally stored setting parameters match the current parameter adjustment information, a non-execution message is generated and uploaded to the backend platform. If locally stored setting parameters do not match the current parameter adjustment information, the parameter adjustment information is saved locally. The system then determines the corresponding sensor module based on the parameter adjustment information, sends the parameter adjustment information to the corresponding sensor module, and the sensor module updates the data acquisition model settings based on the parameter adjustment information, completing the parameter adjustment of the sensor module. Finally, an execution message is generated and uploaded to the backend platform.

[0019] By adopting the above technical solution, the parameter adjustment process of the sensor module has been refined and defined, realizing manual and targeted adjustment of data acquisition parameters during the data acquisition process. This allows operators to adjust the data acquisition parameters more quickly according to actual application needs, ensuring the efficiency and practicality of multi-type data acquisition.

[0020] Secondly, this application also provides another method for acquiring multiple types of data, using the technical solution described below.

[0021] A multi-type data acquisition method, adapted to wired industrial sensors, is characterized by comprising the following steps:

[0022] After the connected industrial sensor is started, the data acquisition model is uploaded to the core module. When the setting parameter information is received from the core module, the data acquisition model is updated and the parameter settings are completed according to the setting parameter information.

[0023] Based on the data acquisition model, physical quantity data from the industrial sensor is received. The physical quantity data is converted by ADC to obtain raw data. The raw data is encapsulated according to the format required by the core module to obtain block data packets. The raw data is processed by calculation. One or more calculation results are encapsulated together with the sampling timestamp to obtain time-series data packets. The block data packets and the time-series data packets are uploaded to the core module and forwarded to the backend platform by the core module.

[0024] By adopting the above technical solution, the industrial sensors are connected to the core module, realizing the adaptation of the core module to different types of industrial sensors. At the same time, the specific processing and encapsulation process of data during data acquisition is clarified, providing technical support for the solution to meet the requirements of multi-type data acquisition.

[0025] Preferably, the multi-type data acquisition method further includes the following steps:

[0026] The system receives parameter adjustment information from the core module and updates the settings of the data acquisition model based on the parameter adjustment information, thus completing the parameter adjustment.

[0027] Thirdly, this application provides a multi-type data acquisition system, which adopts the technical solution described below.

[0028] A multi-type data acquisition system, adapted to wired industrial sensors, includes the following units:

[0029] The core startup unit is configured to receive data acquisition models from each sensor module one by one, complete the parameter setting of the corresponding sensor module according to the data acquisition model, generate a parameter setting completion identifier corresponding to the current sensor module after the parameter setting is completed, and upload the parameter setting completion identifier to the backend platform.

[0030] The core acquisition unit is configured to receive block data packets and time-series data packets one by one from each of the sensor modules that have the parameter setting completion identifier. The block data packets are the raw data obtained by the sensor module after converting the physical quantity data from the industrial sensor received by the sensor module during a single data acquisition process through ADC conversion. The time-series data packets contain one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. The unit forwards the received block data packets and time-series data packets to the back-end platform.

[0031] The core setting unit is configured to receive parameter adjustment instructions from the backend platform, generate parameter adjustment information based on the instructions, compare the parameter adjustment information with locally stored setting parameter information one by one, and if locally stored setting parameter information is found to match the current parameter adjustment information, generate a non-execution message and upload it to the backend platform; if locally stored setting parameter information is not found to match the current parameter adjustment information, save the parameter adjustment information locally, determine the corresponding sensor module based on the parameter adjustment information, forward the parameter adjustment information to the corresponding sensor module, and have the sensor module update the data acquisition model settings based on the parameter adjustment information, complete the parameter adjustment of the sensor module, generate an executed message and upload it to the backend platform.

[0032] By adopting the above technical solution, the aforementioned multi-type data acquisition method is implemented at the hardware level, enabling a single data acquisition terminal to acquire multiple different types of data and signals. Not only can the number of data acquisition terminals be effectively controlled, but the transmission interface resources on the data acquisition terminal can also be fully utilized, avoiding the waste of hardware resources.

[0033] Fourthly, this application also provides another multi-type data acquisition system, which adopts the technical solution described below.

[0034] A multi-type data acquisition system, adapted to wired industrial sensors, includes the following units:

[0035] The sensor startup unit is configured to upload the data acquisition model to the core module after the connected industrial sensor has started up, and when it receives setting parameter information from the core module, it updates the settings of the data acquisition model and completes the parameter settings according to the setting parameter information.

[0036] The sensor acquisition unit is configured to receive physical quantity data from the industrial sensor according to the data acquisition model, perform ADC conversion on the physical quantity data to obtain raw data, encapsulate the raw data according to the format required by the core module to obtain a block data packet, perform calculation processing on the raw data, encapsulate one or more calculation processing results together with the sampling timestamp to obtain a time-series data packet, and upload the block data packet and the time-series data packet to the core module and forward them to the backend platform by the core module.

[0037] The sensor setting unit is configured to receive parameter adjustment information from the core module, and update the data acquisition model and complete the parameter adjustment based on the parameter adjustment information.

[0038] By adopting the above technical solution, another multi-type data acquisition method is implemented at the hardware level. It can be seen that separating the ADC conversion and computation process from the core module allows the core module to connect to new industrial sensors for data acquisition and functional expansion without requiring any conversion. This is something existing data acquisition terminals or systems cannot achieve. Furthermore, the above solution simplifies the internal circuitry and structure of the core module, reducing its hardware size and making miniaturization of the data acquisition terminal possible.

[0039] Fifthly, this application provides a smart terminal, which adopts the following technical solution:

[0040] A smart terminal includes a memory and a processor. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement any of the multi-type data acquisition methods described above.

[0041] Sixthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0042] A computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement any of the multi-type data acquisition methods described above.

[0043] In summary, this application includes at least one of the following beneficial technical effects:

[0044] 1. In the solution of this application, the signal connection between the industrial sensor and the back-end platform is realized by the cooperation of the sensor module and the core module. The core module does not need to consider the type of industrial sensor, so various types of industrial sensors can be combined as needed, which enriches the application scenarios and enables a single data acquisition terminal to complete the acquisition of multiple different types of data and signals, thus minimizing the waste of hardware resources.

[0045] 2. In the solution of this application, the ADC conversion and calculation process is separated from the core module and transferred to the sensor module. This allows the core module to connect to new industrial sensors for data acquisition and functional expansion without any conversion, which is significantly different from existing data acquisition terminals or systems. Furthermore, the above arrangement simplifies the internal circuitry and structure of the core module, making miniaturization of the data acquisition terminal possible. Attached Figure Description

[0046] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained by referring to these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating a multi-type data acquisition method according to an embodiment of this application;

[0048] Figure 2 This is a flowchart illustrating another multi-type data acquisition method according to an embodiment of this application;

[0049] Figure 3 This is a schematic diagram of the architecture of a multi-type data acquisition system according to an embodiment of this application;

[0050] Figure 4 This is a schematic diagram of the architecture of another multi-type data acquisition system according to an embodiment of this application;

[0051] Figure 5 This is a schematic diagram illustrating a specific application scenario of an embodiment of this application;

[0052] Figure 6 This application's embodiments are based on Figure 5 The interaction process diagram of the application scenario. Detailed Implementation

[0053] This application provides a method, system, terminal, and storage medium for acquiring multiple types of data to better meet the diverse data acquisition needs in the Industrial Internet. To make the objectives, technical solutions, and advantages of this application clearer, the implementation methods of this application will be further described below.

[0054] The following describes in detail an embodiment of a front-end microservice page management method of this application with reference to the accompanying drawings.

[0055] This application first introduces a multi-type data acquisition method adapted to wired industrial sensors. The main body executing the method is the core module, such as... Figure 1 As shown, the method includes the following steps:

[0056] S11. Receive data acquisition models from each sensor module one by one, complete the parameter settings for the corresponding sensor module according to the data acquisition models, generate a parameter setting completion identifier corresponding to the current sensor module after the parameter settings are completed, and upload the parameter setting completion identifier to the backend platform.

[0057] It should be noted that in all embodiments of this solution, each sensor module corresponds to a unique data acquisition model.

[0058] The data acquisition model includes various types of data, including at least the following items: sensor type, such as vibration acceleration, temperature, pressure, etc.; acquired physical quantities, such as vibration acceleration, temperature, pressure, displacement, flow rate, rotational speed, current, etc.; current software and hardware version information; current acquisition parameters, such as sampling rate, acquisition duration, acquisition interval, etc.; and a list of uploaded parameters and data types, such as peak vibration acceleration, raw vibration acceleration data, root mean square value of vibration velocity, average pressure, peak pressure, etc.

[0059] Furthermore, the step of setting the parameters of the corresponding sensor module based on the data acquisition model in the above steps specifically includes the following operation process:

[0060] S111. Search locally for setting parameter information corresponding to the current data acquisition model, and perform the corresponding operation based on the search result.

[0061] If the setting parameter information is found, it will be sent to the corresponding sensor module, and the sensor module will update the data acquisition model according to the setting parameter information to complete the parameter setting of the sensor module.

[0062] If the data acquisition model does not exist, the current data acquisition model is saved locally. The next time data is interacted with the backend platform, the corresponding setting parameter information is searched for in the setting parameter database of the backend platform based on the locally stored data acquisition model. After successful search, the setting parameter information is downloaded locally. When the same data acquisition model is received again, the parameters of the corresponding sensor module are set.

[0063] S12. Receive block data packets and time-series data packets one by one from each of the sensor modules that have the parameter setting completion identifier, and forward the received block data packets and time-series data packets to the backend platform.

[0064] It should be noted that in all embodiments of this solution, each sensor module will collect and process the block data packet and the time-series data packet according to the sampling interval within the data acquisition model before uploading the data.

[0065] The block data packet is the raw data obtained by the sensor module from the physical quantity data of the industrial sensor received during a single data acquisition process after ADC conversion. For example, for a vibration acceleration sensor, the block data packet uploaded at one time contains the raw vibration data. The time-series data packet contains one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. For example, for a vibration acceleration sensor, the time-series data packet uploaded at one time may contain characteristic parameters such as vibration acceleration peak value, vibration acceleration root mean square value, vibration velocity root mean square value and sampling timestamp.

[0066] To achieve automated and real-time adjustment of data acquisition parameters during the implementation of the above method, the aforementioned multi-type data acquisition method further includes the following steps:

[0067] S13. Receive parameter adjustment instructions from the backend platform for one or more specified industrial sensors; generate parameter adjustment information based on the parameter adjustment instructions; compare the parameter adjustment information with locally stored setting parameter information one by one; and perform corresponding operations based on the comparison results.

[0068] If the local storage contains setting parameter information that is consistent with the current parameter adjustment information, then an execution failure message is generated and uploaded to the backend platform;

[0069] If no setting parameter information consistent with the current parameter adjustment information is stored locally, the parameter adjustment information is saved locally. The corresponding sensor module is determined based on the parameter adjustment information, and the parameter adjustment information is sent to the corresponding sensor module. The sensor module updates the settings of the data acquisition model based on the parameter adjustment information and completes the parameter adjustment of the sensor module, so that the next data acquisition process can be performed according to the adjusted parameters. Then, an execution record is generated and uploaded to the backend platform.

[0070] Next, another multi-type data acquisition method in this application embodiment is introduced, adapted to wired industrial sensors. The main body executing the method is the sensor module, such as... Figure 2 As shown, the method includes the following steps:

[0071] S21. Upload the data acquisition model to the core module. When the setting parameter information is received from the core module, update the settings of the data acquisition model according to the setting parameter information and complete the parameter setting.

[0072] It should be noted that the data acquisition model is uploaded to the core module after the industrial sensor connected to the sensor module has started up. Each time the industrial sensor starts up, the connected sensor module automatically uploads its corresponding data acquisition model to indicate its supported data acquisition capabilities and necessary parameter information to the core module and the industrial internet cloud platform.

[0073] S22. Based on the data acquisition model, receive physical quantity data from the industrial sensor, perform ADC conversion on the physical quantity data to obtain raw data, encapsulate the raw data according to the format required by the core module to obtain block data packets, perform calculation processing on the raw data, encapsulate one or more calculation processing results together with the sampling timestamp to obtain time-series data packets, upload the block data packets and the time-series data packets to the core module and forward them to the backend platform by the core module.

[0074] Similarly, in order to automate and enable real-time adjustment of data acquisition parameters during the implementation of the above method, the aforementioned multi-type data acquisition method also includes the following steps:

[0075] S23. Receive parameter adjustment information from the core module, update the settings of the data acquisition model according to the parameter adjustment information, and complete the parameter adjustment.

[0076] Based on the two multi-type data acquisition methods described above, this application also discloses two multi-type data acquisition systems. The embodiments of the two multi-type data acquisition systems of this application are described in further detail below.

[0077] A multi-type data acquisition system, corresponding to the aforementioned multi-type data acquisition method, is adapted to wired industrial sensors. The system includes a core module, which can be set up as a functional module inside a traditional data acquisition terminal, or it can be used as a data acquisition terminal while ensuring basic data processing and data interaction capabilities.

[0078] like Figure 3 As shown, the core module includes the following units:

[0079] The core startup unit is configured to receive data acquisition models from each sensor module one by one, complete the parameter setting of the corresponding sensor module according to the data acquisition model, generate a parameter setting completion identifier corresponding to the current sensor module after the parameter setting is completed, and upload the parameter setting completion identifier to the backend platform.

[0080] The core acquisition unit is configured to receive block data packets and time-series data packets one by one from each of the sensor modules that have the parameter setting completion identifier. The block data packets are the raw data obtained by the sensor module after converting the physical quantity data from the industrial sensor received by the sensor module during a single data acquisition process through ADC conversion. The time-series data packets contain one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. The unit forwards the received block data packets and time-series data packets to the back-end platform.

[0081] The core setting unit is configured to receive parameter adjustment instructions from the backend platform, generate parameter adjustment information based on the instructions, compare the parameter adjustment information with locally stored setting parameter information one by one, and if locally stored setting parameter information is found to match the current parameter adjustment information, generate a non-execution message and upload it to the backend platform; if locally stored setting parameter information is not found to match the current parameter adjustment information, save the parameter adjustment information locally, determine the corresponding sensor module based on the parameter adjustment information, forward the parameter adjustment information to the corresponding sensor module, and have the sensor module update the data acquisition model settings based on the parameter adjustment information, complete the parameter adjustment of the sensor module, generate an executed message and upload it to the backend platform.

[0082] Another type of multi-type data acquisition system, corresponding to the aforementioned other type of multi-type data acquisition method, is adapted to wired industrial sensors. The system includes multiple sensor modules, each of which is connected to one of the aforementioned industrial sensors.

[0083] like Figure 4 As shown, the sensor module includes the following units:

[0084] The sensor startup unit is configured to upload the data acquisition model to the core module after the connected industrial sensor has started up, and when it receives setting parameter information from the core module, it updates the settings of the data acquisition model and completes the parameter settings according to the setting parameter information.

[0085] The sensor acquisition unit is configured to receive physical quantity data from the industrial sensor according to the data acquisition model, perform ADC conversion on the physical quantity data to obtain raw data, encapsulate the raw data according to the format required by the core module to obtain a block data packet, perform calculation processing on the raw data, encapsulate one or more calculation processing results together with the sampling timestamp to obtain a time-series data packet, and upload the block data packet and the time-series data packet to the core module and forward them to the backend platform by the core module.

[0086] The sensor setting unit is configured to receive parameter adjustment information from the core module, and update the data acquisition model and complete the parameter adjustment based on the parameter adjustment information.

[0087] As can be seen from the above description of the two multi-type data acquisition methods and the two multi-type data acquisition systems, the overall logic of multi-type data acquisition in this application has the characteristics of integrity and interactivity. The differences between different multi-type data acquisition methods and different multi-type data acquisition systems are essentially brought about by the different action execution entities of the schemes.

[0088] To better illustrate the above technical solutions, a specific and comprehensive application scenario is presented here, such as... Figure 5 As shown, in this application scenario, in addition to the aforementioned functional units, the core module is also explicitly equipped with a downlink interface and an uplink interface.

[0089] The downlink interface includes a USB interface, which is primarily used to connect to the sensor module. Each core module has multiple USB interfaces (e.g., 8, 16, 24, 32, etc.), allowing simultaneous connection to multiple industrial sensors with different signal types. The signal types and number of these industrial sensors can be arbitrarily combined. To further enrich application scenarios, the downlink interface also includes an RS485 interface, through which one or more digital sensor signals, such as third-party sensor signals or PLC signals, can be connected.

[0090] The uplink interface includes an Ethernet interface, a WiFi interface, and a 4G / 5G interface. The uplink interface is mainly responsible for realizing data interaction between the core module and the backend platform, which can be a local area network system or an industrial internet cloud platform.

[0091] In this application scenario, in addition to the aforementioned functional units, the sensor module also explicitly includes a USB interface, whose main function is to connect to the core module. Since the interfaces and compatible ADC circuits of industrial sensors with different signal types are different, different sensor modules are required for connection to industrial sensors with different signal types. However, all sensor modules have identical interfaces to the core module, allowing for arbitrary combinations of sensor modules to be connected to the core module. The sensor modules and industrial sensors are connected via aviation connectors.

[0092] It should be noted that, in addition to the USB interface, the core module and the sensor module can also be connected by other means. The USB interface solution is chosen here because, under current conditions, the data transmission bandwidth of this interface is sufficient to meet all current industrial data acquisition needs.

[0093] The following combination Figure 6 The document provides a detailed description of the various data acquisition processes in the aforementioned application scenarios. These processes can be broadly categorized into the equipment preparation stage, the data acquisition stage, and the parameter setting stage.

[0094] The process during the equipment preparation phase is as follows:

[0095] 1.1 Determine the required core module and various sensor modules according to the type of industrial sensor in the monitoring equipment or application scenario. The number of sensor modules is consistent with the number of industrial sensors and corresponds one-to-one. The number of core modules is only related to the number of industrial sensors. Complete the setting and signal connection of the sensor modules and the core modules.

[0096] 1.2 After the sensor module detects that the industrial sensor has been activated, it uploads the corresponding data acquisition model to the core module;

[0097] 1.3 The core module searches locally for setting parameter information corresponding to the current data acquisition model. If it exists, it sends the found setting parameter information to the corresponding sensor module. If it does not exist, it saves the current data acquisition model locally.

[0098] 1.4 Upon receiving the setting parameter information, the sensor module updates the data acquisition model based on the setting parameter information, thus completing the parameter setting of the sensor module;

[0099] 1.5 The core module generates a corresponding parameter setting completion identifier for each sensor module after the parameter settings are completed, and uploads the parameter setting completion identifier to the backend platform.

[0100] The data acquisition phase follows this process:

[0101] 2.1 The sensor module receives physical quantity data from the industrial sensor according to the data acquisition model, performs ADC conversion on the physical quantity data to obtain raw data, encapsulates the raw data according to the format required by the core module to obtain a block data packet, performs calculation processing on the raw data, and encapsulates one or more calculation processing results together with the sampling timestamp to obtain a time-series data packet.

[0102] 2.2 The sensor module uploads the block data packet and the time-series data packet to the core module as needed;

[0103] 2.3 The core module forwards the block data packets and the time-series data packets to the backend platform.

[0104] The process during the parameter setting phase is as follows:

[0105] 3.1 The backend platform generates parameter adjustment instructions for one or more specified industrial sensors as needed, and sends the parameter adjustment instructions to the core module;

[0106] 3.2 The core module compares the parameter adjustment information with the setting parameter information stored locally one by one. If the setting parameter information that matches the current parameter adjustment information is stored locally, a non-execution message is generated and uploaded to the backend platform. If the setting parameter information that matches the current parameter adjustment information is not stored locally, the parameter adjustment information is saved locally, and the corresponding sensor module is determined before the parameter adjustment information is sent down.

[0107] 3.3 The sensor module updates the data acquisition model based on the parameter adjustment information and completes the parameter adjustment of the sensor module;

[0108] 3.4 After the parameters are adjusted, the core module generates an execution record and uploads it to the backend platform.

[0109] Based on the same inventive concept described above, this application also discloses a smart terminal, including a memory and a processor. The memory stores at least one instruction, at least one program, code set, or instruction set. The at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement any of the multi-type data acquisition methods described above.

[0110] It should be understood that "multiple" as used in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0111] Based on the same inventive concept described above, this application also discloses a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement any of the multi-type data acquisition methods described above.

[0112] Those skilled in the art should understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code.

[0113] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A multi-type data acquisition method, adapted to wired industrial sensors, comprising at least one of a core processing stage and a sensor processing stage, wherein, The method execution entity in the core processing stage is a core module, and the method execution entity in the sensor processing stage is a sensor module. One core module is matched with multiple sensor modules. The characteristic is that: The core processing stage includes the following steps. The system receives data acquisition models from each sensor module one by one, sets the parameters for the corresponding sensor module based on the data acquisition models, generates a parameter setting completion identifier corresponding to the current sensor module, and uploads the parameter setting completion identifier to the backend platform. The system receives block data packets and time-series data packets one by one from each of the sensor modules that have the parameter setting completion identifier. The block data packets are the raw data obtained by the sensor module after converting the physical quantity data from the industrial sensor received during a single data acquisition process through ADC conversion. The time-series data packets contain one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. The received block data packets and time-series data packets are then forwarded to the backend platform. The sensor processing stage includes the following steps. After the connected industrial sensor completes its startup, it uploads the data acquisition model to the core module. When it receives setting parameter information from the core module, it updates the settings of the data acquisition model based on the setting parameter information and completes the parameter setting. Based on the data acquisition model, physical quantity data from the industrial sensor is received. The physical quantity data is converted by ADC to obtain raw data. The raw data is encapsulated according to the format required by the core module to obtain block data packets. The raw data is processed by calculation. One or more calculation results are encapsulated together with the sampling timestamp to obtain time-series data packets. The block data packets and the time-series data packets are uploaded to the core module and forwarded to the backend platform by the core module.

2. The multi-type data acquisition method according to claim 1, characterized in that: Each sensor module corresponds to a unique data acquisition model, which includes sensor type, acquired physical quantity, current software and hardware version information, current acquisition parameters, upload parameters, and a list of data types.

3. The multi-type data acquisition method according to claim 1, characterized in that, The step of setting the parameters of the corresponding sensor modules based on the data acquisition model includes the following steps: Check locally whether there is setting parameter information corresponding to the current data acquisition model. If the setting parameter information exists, it will be sent to the corresponding sensor module, which will then update the data acquisition model based on the setting parameter information to complete the parameter setting of the sensor module. If the data acquisition model does not exist, the current data acquisition model will be saved locally. The next time data is interacted with the backend platform, the corresponding setting parameter information will be searched for in the setting parameter database of the backend platform based on the locally stored data acquisition model. If the search is successful, the setting parameter information will be downloaded locally.

4. The multi-type data acquisition method according to claim 1, characterized in that, The core processing stage also includes the following steps: The system receives parameter adjustment instructions from the backend platform, generates parameter adjustment information based on the instructions, and compares the parameter adjustment information with the locally stored setting parameters one by one. If the local storage contains setting parameter information that matches the current parameter adjustment information, then a non-execution message is generated and uploaded to the backend platform. If no setting parameter information consistent with the current parameter adjustment information is stored locally, the parameter adjustment information is saved locally, the corresponding sensor module is determined based on the parameter adjustment information, the parameter adjustment information is sent to the corresponding sensor module, the sensor module updates the data acquisition model based on the parameter adjustment information, completes the parameter adjustment of the sensor module, generates an executed information record, and uploads it to the backend platform.

5. The multi-type data acquisition method according to claim 1, characterized in that, The sensor processing stage also includes the following steps: The system receives parameter adjustment information from the core module and updates the settings of the data acquisition model based on the parameter adjustment information, thus completing the parameter adjustment.

6. A multi-type data acquisition system, adapted to wired industrial sensors, the system comprising a core module and sensor modules, wherein one core module is matched with multiple sensor modules, characterized in that: The core module includes the following units. The core startup unit is configured to receive data acquisition models from each sensor module one by one, complete the parameter settings for the corresponding sensor module based on the data acquisition models, generate a parameter setting completion identifier corresponding to the current sensor module after parameter setting is completed, and upload the parameter setting completion identifier to the backend platform. The core acquisition unit is configured to receive, one by one, block data packets and time-series data packets from each of the sensor modules that carries the parameter setting completion identifier. The block data packets are the raw data obtained by the sensor module after converting the physical quantity data from the industrial sensor received during a single data acquisition process via ADC. The time-series data packets contain one or more time-series data obtained by calculating and processing the raw data and the corresponding sampling timestamp. The unit forwards the received block data packets and time-series data packets to the backend platform. The core setting unit is configured to receive parameter adjustment instructions from the backend platform, generate parameter adjustment information based on the instructions, compare the parameter adjustment information with locally stored setting parameter information one by one, and if locally stored setting parameter information is found to match the current parameter adjustment information, generate a non-execution message and upload it to the backend platform; if locally stored setting parameter information is not found to match the current parameter adjustment information, save the parameter adjustment information locally, determine the corresponding sensor module based on the parameter adjustment information, forward the parameter adjustment information to the corresponding sensor module, and have the sensor module update the data acquisition model settings based on the parameter adjustment information, complete the parameter adjustment of the sensor module, generate an execution message and upload it to the backend platform. The sensor module includes the following units. The sensor startup unit is configured to upload the data acquisition model to the core module after the connected industrial sensor has started up. When it receives setting parameter information from the core module, it updates the settings of the data acquisition model according to the setting parameter information and completes the parameter setting. The sensor acquisition unit is configured to receive physical quantity data from the industrial sensor according to the data acquisition model, perform ADC conversion on the physical quantity data to obtain raw data, encapsulate the raw data according to the format required by the core module to obtain block data packets, perform calculation processing on the raw data, encapsulate one or more calculation processing results together with the sampling timestamp to obtain time-series data packets, and upload the block data packets and the time-series data packets to the core module, which then forwards them to the backend platform. The sensor setting unit is configured to receive parameter adjustment information from the core module, and update the data acquisition model and complete the parameter adjustment based on the parameter adjustment information.

7. A smart terminal, characterized in that, The system includes a memory and a processor, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the multi-type data acquisition method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The readable storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the multi-type data acquisition method as described in any one of claims 1 to 5.

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