High-end equipment fault intelligent diagnosis system and method based on side cloud cooperation

Abstract

The invention provides a high-end equipment fault intelligent diagnosis system based on side cloud cooperation, and the system comprises a cloud control module, one end of the cloud control module is provided with a cloud update maintenance module, one end of the cloud update maintenance module is provided with a cloud storage module, and one end of the cloud storage module is provided with a cloud detection module; the information acquisition module is arranged at one end of the cloud control module, and an information verification module is arranged at one end of the information acquisition module; and the scene adjustment module is arranged at one end of the information verification module, and an APP implantation module is arranged at one end of the scene adjustment module. According to the invention, the problem that the existing technical architecture is difficult to adapt to complex and changeable environment requirements of a user side and operation and maintenance scenes with many points and wide range still exists in the existing distributed photovoltaic access is solved.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic intelligent diagnosis, and in particular to a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration. Background Art

[0002] Photovoltaic, or photovoltaic power generation system, is a power generation system that uses the photovoltaic effect of semiconductor materials to convert solar radiation into electrical energy. The energy of the photovoltaic power generation system comes from inexhaustible solar energy, and is a clean, safe and renewable energy source. The photovoltaic power generation process does not pollute the environment or damage the ecology. The photovoltaic power generation system is divided into independent photovoltaic systems and grid-connected photovoltaic systems, which are composed of solar cell arrays, battery packs, charge and discharge controllers, inverters, AC distribution cabinets, solar tracking control systems and other equipment.

[0003] Distributed photovoltaic power generation is a photovoltaic power generation facility characterized by the self-use of electricity on the user side, the access to the grid of excess electricity, and balanced regulation of the distribution system after the photovoltaic power generation. The photovoltaic APP framework can be quickly implanted in a single ideal environment. However, due to the different installation environments on the user side, the photovoltaic APP framework will be slow or unable to be implanted in different environments.

[0004] Therefore, it is necessary to provide a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration to solve the above technical problems. Summary of the invention

[0005] The present invention provides a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration, which solves the problem that the existing technical architecture of distributed photovoltaic access is still difficult to adapt to the complex and changeable environmental requirements on the user side and the multi-point and wide-ranging operation and maintenance scenarios.

[0006] In order to solve the above technical problems, the present invention provides a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration, including:

[0007] A cloud control module, one end of the cloud control module is provided with a cloud update and maintenance module, one end of the cloud update and maintenance module is provided with a cloud storage module, and one end of the cloud storage module is provided with a cloud detection module;

[0008] An information collection module is provided at one end of the cloud control module, and an information verification module is provided at one end of the information collection module;

[0009] A scene adjustment module is provided at one end of the information verification module, and an APP implantation module is provided at one end of the scene adjustment module.

[0010] Preferably, the cloud control module and the cloud update and maintenance module are bidirectionally connected, and the output end of the cloud control module is connected to the input end of the information collection module.

[0011] Preferably, the cloud update and maintenance module is bidirectionally connected to the cloud storage module, and the cloud storage module is bidirectionally connected to the cloud detection module.

[0012] Preferably, the output end of the information acquisition module is connected to the input end of the information verification module, and the output end of the information verification module is connected to the input end of the scene adjustment module.

[0013] Preferably, the scene adjustment module includes an automatic adjustment module and a manual adjustment module, and a judgment module is provided at one end of the automatic adjustment module.

[0014] Preferably, the output end of the scene adjustment module is connected to the input end of the automatic adjustment module, and the output end of the automatic adjustment module is connected to the input end of the judgment module.

[0015] Preferably, the output end of the scene adjustment module is connected to the input end of the APP implantation module, and a recording module is provided at one end of the APP implantation module.

[0016] Preferably, a storage module is provided at one end of the recording module, and the output end of the APP implantation module is connected to the input end of the recording module.

[0017] Preferably, the output end of the recording module is connected to the input end of the storage module, and the output end of the storage module is connected to the input end of the cloud control module.

[0018] An operating method of a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration, including a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration according to the claims, and a method for using the high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration required by the high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration when in use, including the following steps:

[0019] S1: Verify the collected information through the information verification module;

[0020] S2: The scene adjustment module adjusts to a suitable scene according to the information verified by the information verification module;

[0021] S3: After implanting the module through the APP, input the system to be implanted into the main station;

[0022] S4: Detecting the internal system of the cloud storage module through the cloud detection module;

[0023] S5: Updating or maintaining the system in the cloud storage module through the cloud update and maintenance module.

[0024] Compared with related technologies, the high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration provided by the present invention has the following beneficial effects:

[0025] The present invention provides a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration. Through the cloud control module, an information collection module, an information verification module, a scene adjustment module, and an APP implantation module, signals of distributed photovoltaic access points are collected and then information verification is performed. After adjusting to a suitable scene through the scene adjustment module, the APP is implanted, so that the photovoltaic APP can be quickly implanted to cope with various scenarios. At the same time, the cloud detection module cooperates with the cloud storage module and the cloud update and maintenance module to update and maintain the system in the cloud storage module. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the structure of a preferred embodiment of a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration provided by the present invention;

[0027] Figure 2 for Figure 1 The structural diagram of the APP implantation module shown;

[0028] Figure 3 for Figure 1 The structural diagram of the information verification module is shown. DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with the accompanying drawings and implementation modes.

[0030] The present invention provides an intelligent fault diagnosis system for high-end equipment based on edge-cloud collaboration, comprising:

[0031] A cloud control module, one end of the cloud control module is provided with a cloud update and maintenance module, one end of the cloud update and maintenance module is provided with a cloud storage module, and one end of the cloud storage module is provided with a cloud detection module;

[0032] An information collection module is provided at one end of the cloud control module, and an information verification module is provided at one end of the information collection module;

[0033] A scene adjustment module is provided at one end of the information verification module, and an APP implantation module is provided at one end of the scene adjustment module.

[0034] Through the cloud control module in conjunction with the cloud update and maintenance module, cloud storage module and cloud detection module, the cloud-end protocol verification update, distribution mechanism and support are realized. Through the local feature protocol and the self-description and self-adaptation technology of the equipment, a photovoltaic control APP is developed to realize the master-substation full-transparent protocol implantation, update, maintenance and other related functions, supporting the full-range application capabilities of various inverter protocol adaptations. Local feature protocol modeling realizes cloud file synchronization. During the synchronization process, the control terminal protocol status can be fully described through the file model. In view of the complexity of the link, the protocol library is first used to directly connect the terminal to complete the protocol synchronization of the cloud master station and the terminal. The protocol file description model is studied on the terminal to complete the mapping and matching of the cloud master station information model. On this basis, the study realizes the transparent transmission of protocol maintenance through edge devices such as fusion terminals.

[0035] Through the cloud control module, information collection module, information verification module, scene adjustment module, and APP implantation module, the APP framework technology that meets the characteristics of platform independence and low coupling is designed, and the test and verification are completed in combination with different hardware types. The current hardware platform architecture is diverse, and the requirements of various application scenarios for hardware are different. The complexity of the scene requires the design of platform-independent APPs to cope with various scenarios. The photovoltaic APP can be quickly implanted. The underlying interface environment and architecture system of various hardware platforms are different. To build upper-end applications on different platforms, it is necessary to study the low-coupling interface packaging technology of the platform on the hardware abstraction layer HAL or the board support package BSP. How to achieve the compatibility packaging of the platform interface to meet the rapid changes in hardware types in different scenarios and the ability of APP to quickly migrate and deploy is the difficulty of this topic. The typical design completed by the mainstream ARM and X86 systems is selected to complete the upper-level APP platform-independent packaging, and first meet the program development and trial application under the mainstream hardware type. Then select the interface parts such as ESAM encryption chip and carrier communication chip to complete the verification and correction.

[0036] The cloud control module is bidirectionally connected to the cloud update and maintenance module, and the output end of the cloud control module is connected to the input end of the information collection module.

[0037] There is a bidirectional connection between the cloud update and maintenance module and the cloud storage module, and there is a bidirectional connection between the cloud storage module and the cloud detection module.

[0038] The output end of the information acquisition module is connected to the input end of the information verification module, and the output end of the information verification module is connected to the input end of the scene adjustment module.

[0039] The scene adjustment module includes an automatic adjustment module and a manual adjustment module. A judgment module is arranged at one end of the automatic adjustment module.

[0040] The output end of the scene adjustment module is connected to the input end of the automatic adjustment module, and the output end of the automatic adjustment module is connected to the input end of the judgment module.

[0041] After the information verification module verifies the information collected by the information collection module, the scene adjustment module automatically adjusts to the appropriate scene according to the collected information through the automatic adjustment module, and after the judgment module makes a judgment, if the result is yes, the scene adjustment module is automatically adjusted to the appropriate scene through the automatic adjustment module; if the result is no, the signal is transmitted to the manual adjustment module, and the scene adjustment module is manually adjusted to the appropriate scene through the manual adjustment module, so that automatic adjustment is performed on most scenes, thereby increasing work efficiency. At the same time, in the scenes recorded in the cloud storage module, they can be manually adjusted to the most appropriate scene by the operator for use.

[0042] The output end of the scene adjustment module is connected to the input end of the APP implantation module, and a recording module is provided at one end of the APP implantation module.

[0043] A storage module is provided at one end of the recording module, and the output end of the APP implantation module is connected to the input end of the recording module.

[0044] The output end of the recording module is connected to the input end of the storage module, and the output end of the storage module is connected to the input end of the cloud control module.

[0045] After the APP implantation module implants the system into the photovoltaic master station, the information implanted by the APP is recorded through the recording module, and then the recorded information is stored through the storage module, so as to facilitate query records after an error occurs later, thereby facilitating maintenance and repairs at the same time.

[0046] An operating method of a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration includes the following steps:

[0047] S1: Verify the collected information through the information verification module;

[0048] S2: The scene adjustment module adjusts to a suitable scene according to the information verified by the information verification module;

[0049] S3: After implanting the module through the APP, input the system to be implanted into the main station;

[0050] S4: Detecting the internal system of the cloud storage module through the cloud detection module;

[0051] S5: Updating or maintaining the system in the cloud storage module through the cloud update and maintenance module.

[0052] The working principle of the high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration provided by the present invention is as follows:

[0053] When in use, after the cloud control module controls the information collection module to collect scene information, the information collected by the information collection module is verified and confirmed by the information verification module, and the scene adjustment module is adjusted to a suitable scene according to the information verified by the information verification module, and then the system to be implanted is input into the main station through the APP implantation module;

[0054] After long-term use, the cloud detection module detects the system stored in the cloud storage module to see if it is the latest system version and if any operational failure occurs. If it is not the latest system version or an operational failure occurs, the cloud control module controls the cloud update and maintenance module to update or maintain the system in the cloud storage module.

[0055] Compared with related technologies, the high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration provided by the present invention has the following beneficial effects:

[0056] The present invention provides a high-end equipment fault intelligent diagnosis system and method based on edge-cloud collaboration. Through the cloud control module, an information collection module, an information verification module, a scene adjustment module, and an APP implantation module, signals of distributed photovoltaic access points are collected and then information verification is performed. After adjusting to a suitable scene through the scene adjustment module, the APP is implanted, so that the photovoltaic APP can be quickly implanted to cope with various scenarios. At the same time, the cloud detection module cooperates with the cloud storage module and the cloud update and maintenance module to update and maintain the system in the cloud storage module.

[0057] The above are only embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration, characterized in that: include: A cloud control module, wherein one end of the cloud control module is provided with a cloud update and maintenance module, one end of the cloud update and maintenance module is provided with a cloud storage module, and one end of the cloud storage module is provided with a cloud detection module; An information collection module, wherein the information collection module is arranged at one end of the cloud control module, and an information verification module is arranged at one end of the information collection module; A scene adjustment module is provided at one end of the information verification module, and an APP implantation module is provided at one end of the scene adjustment module.

2. According to claim 1, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The cloud control module is bidirectionally connected to the cloud update and maintenance module, and the output end of the cloud control module is connected to the input end of the information acquisition module.

3. According to claim 2, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The cloud update and maintenance module is bidirectionally connected to the cloud storage module, and the cloud storage module is bidirectionally connected to the cloud detection module.

4. According to claim 3, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The output end of the information acquisition module is connected to the input end of the information verification module, and the output end of the information verification module is connected to the input end of the scene adjustment module.

5. According to claim 4, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The scene adjustment module includes an automatic adjustment module and a manual adjustment module, and a judgment module is arranged at one end of the automatic adjustment module.

6. According to claim 5, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The output end of the scene adjustment module is connected to the input end of the automatic adjustment module, and the output end of the automatic adjustment module is connected to the input end of the judgment module.

7. According to claim 6, a high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration is characterized in that: The output end of the scene adjustment module is connected to the input end of the APP implantation module, and a recording module is provided at one end of the APP implantation module.

8. The high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration according to claim 7 is characterized in that: A storage module is provided at one end of the recording module, and the output end of the APP implantation module is connected to the input end of the recording module.

9. The high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration according to claim 8 is characterized in that: The output end of the recording module is connected to the input end of the storage module, and the output end of the storage module is connected to the input end of the cloud control module.

10. An operating method of the high-end equipment fault intelligent diagnosis system based on edge-cloud collaboration as claimed in claim 1, characterized in that: The following steps are involved: S1: Verify the collected information through the information verification module; S2: adjusting to the required scene through the scene adjustment module according to the information verified by the information verification module; S3: After implanting the module through the APP, input the system to be implanted into the main station server; S4: Detecting the internal system of the cloud storage module through the cloud detection module; S5: Updating or maintaining the system in the cloud storage module through the cloud update and maintenance module.

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