CN111078786A - Edge operation system - Google Patents
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- CN111078786A CN111078786A CN201910999780.8A CN201910999780A CN111078786A CN 111078786 A CN111078786 A CN 111078786A CN 201910999780 A CN201910999780 A CN 201910999780A CN 111078786 A CN111078786 A CN 111078786A
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- 238000004364 calculation method Methods 0.000 claims abstract description 54
- 239000000126 substance Substances 0.000 claims description 16
- 230000005540 biological transmission Effects 0.000 claims description 10
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 claims description 9
- 239000002184 metal Substances 0.000 claims description 9
- 229910052710 silicon Inorganic materials 0.000 claims description 9
- 239000010703 silicon Substances 0.000 claims description 9
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000002159 abnormal effect Effects 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 4
- 238000005034 decoration Methods 0.000 description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Abstract
The application provides an arithmetic chip system for abnormal vibration of mechanical equipment, and relates to the field of electric data processing. The calculation chip system comprises: the vibration sensing device comprises N vibration sensing elements, an operation module, a storage module, an algorithm calculation module, a power supply module and an input/output module, wherein the algorithm calculation module is respectively connected with the operation module, the input/output module and the storage module, the storage module is respectively connected with the operation module, the input/output module and the vibration sensing elements. The vibration energy of equipment can be known in real time, and the safety of the vibration energy of mechanical equipment in use is guaranteed.
Description
Technical Field
The application belongs to the field of electric data processing, and particularly relates to an edge operation system.
Background
At present, with the continuous development of the 5G technology, the computation of the Internet of things related to 5G is also greatly increased, the operation speed of equipment can be slowed down by the greatly increased computation, poor use experience is brought to clients, only large-scale equipment with high integration can be increased in order to solve the increase of the computation, the increased equipment inevitably causes the maximization of the equipment, and the use of the equipment is not flexible and convenient any more.
Disclosure of Invention
The embodiment of the invention mainly aims to provide an edge operation system, and through the scheme of the embodiment of the invention, more complex calculation can be performed on the equipment side, so that the large-scale of cloud equipment is avoided, and the flexibility and convenience of the cloud equipment are ensured.
In a first aspect, an edge calculation system is provided, including:
the device comprises a parameter sensing module, an operation module, a storage module, an algorithm calculation module, a power supply module and an input/output module, wherein the algorithm calculation module is respectively connected with the operation module, the input/output module and the storage module, the storage module is respectively connected with the operation module, the input/output module and the temperature sensing module, the power supply module is respectively used for supplying power for the parameter sensing module, the operation module, the storage module, the algorithm calculation module and the input/output module, the parameter sensing module acquires physical/chemical parameters, the operation module sends the physical/chemical parameters to the algorithm calculation module, the algorithm calculation module selects a corresponding algorithm to calculate the physical/chemical parameters to acquire calculation parameters and sends the calculation parameters to the operation module, the operation module compares the calculation parameters with preset parameters and determines optimal parameters according to comparison results, and the storage module stores the calculation parameters and preset parameters.
In one possible implementation, the physical/chemical information includes: temperature information, humidity information, vibration information, magnetic force information.
In another possible implementation manner, the edge operation system further includes: and the conversion module is connected with the parameter sensing module and is used for converting the analog signal into a digital signal.
In yet another possible implementation manner, the algorithm in the algorithm calculation module includes: a neural network algorithm implemented by the silicon wafer MOS structure using the metal interconnects, a fuzzy algorithm implemented by the silicon wafer MOS structure using the metal interconnects, and a pseudo-affine transformation algorithm implemented by the silicon wafer MOS structure using the metal interconnects.
In yet another possible implementation, the storage module includes: the fixed storage submodule is used for storing preset parameters, and the floating storage submodule is used for storing calculation parameters.
In yet another possible implementation manner, the input-output module is configured to: inputting a preset parameter updating signal and inputting a reset signal.
In yet another possible implementation manner, the transmission manner of the input/output module is wired transmission or wireless transmission.
In yet another possible implementation, the wireless transmission includes: zigbee, Wireless, ISA100.11a, Wi-Fi and Bluetooth.
In yet another possible implementation manner, the edge computing system further includes:
and the display module is connected with the input and output module and is used for displaying parameter information.
The beneficial effect that technical scheme that this application provided brought is: through carrying out more complicated calculation at the equipment side, avoided the maximization of high in the clouds equipment, guaranteed the flexibility, the convenience of high in the clouds equipment.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.
Fig. 1 is a block diagram of an edge computing system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar modules or modules having the same or similar functionality throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, modules, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, modules, components, and/or groups thereof. It will be understood that when a module is referred to as being "connected" or "coupled" to another module, it can be directly connected or coupled to the other module or intervening modules may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
At present, with the continuous development of the 5G technology, the computation of the Internet of things related to 5G is also greatly increased, the operation speed of equipment can be slowed down by the greatly increased computation, poor use experience is brought to clients, only large-scale equipment with high integration can be increased in order to solve the increase of the computation, the increased equipment inevitably causes the maximization of the equipment, and the use of the equipment is not flexible and convenient any more.
The present application provides an edge calculation system, which aims to solve the above technical problems in the prior art.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a block diagram of an edge computing system according to an embodiment of the present invention, including:
the device comprises a parameter sensing module 101, an operation module 102, a storage module 103, an algorithm calculation module 104, a power supply module 105 and an input/output module 106, wherein the algorithm calculation module is respectively connected with the operation module, the input/output module and the storage module, the storage module is respectively connected with the operation module, the input/output module and the temperature sensing module, the power supply module respectively supplies power for the parameter sensing module, the operation module, the storage module, the algorithm calculation module and the input/output module, the parameter sensing module acquires physical/chemical parameters, the operation module sends the physical/chemical parameters to the algorithm calculation module, the algorithm calculation module selects a corresponding algorithm to calculate the physical/chemical parameters to acquire calculation parameters and sends the calculation parameters to the operation module, and the operation module compares the calculation parameters with preset parameters, and determining an optimal parameter according to the comparison result, and storing the calculation parameter and the preset parameter by a storage module.
In the embodiment of the invention, the circuit board is provided with a parameter sensing module which can sense and record the surrounding physical/chemical information in real time, wherein the physical/chemical information comprises but is not limited to: the temperature information, the humidity information, the vibration information, the magnetic force information and the like are correspondingly and respectively acquired through equipment such as a temperature sensing element, a humidity sensing element, a vibration sensing element, a magnetic force sensing element and the like.
Optionally, in order to facilitate subsequent operations, the computing system further includes: and the conversion module is connected with the parameter sensing module and is used for converting the analog signal into a digital signal.
The physical/chemical information acquired by the parameter sensing module enters the algorithm calculation module through the operation module, and the physical/chemical information is calculated by different algorithms stored in the algorithm calculation module due to the fact that the physical/chemical information is more in types, and calculation parameters are acquired through calculation. It should be noted that there are many algorithms available for calculation, and the user can select the algorithm according to the actual use requirement, and the algorithm is not limited in the present invention. Preferably, the algorithm in the algorithm calculation module comprises: a neural network algorithm implemented by the silicon wafer MOS structure using the metal interconnects, a fuzzy algorithm implemented by the silicon wafer MOS structure using the metal interconnects, and a pseudo-affine transformation algorithm implemented by the silicon wafer MOS structure using the metal interconnects.
The storage module stores preset parameters which are preset, the calculation parameters obtained after calculation of the algorithm calculation module can be stored in the storage module, and correspondingly, the storage module stores the parameters through two different areas, and the method comprises the following steps: the fixed storage submodule stores preset parameters, and the floating storage submodule stores calculation parameters.
The operation module acquires preset parameters and calculation parameters from the storage module, compares the preset parameters with the calculation parameters, and determines optimal parameters according to a comparison result, wherein the operation module specifically comprises the following steps: and if the calculation parameter is better than the preset parameter, setting the calculation parameter as a new preset parameter.
The power supply module is used for supplying power for the parameter sensing module, the operation module, the storage module, the algorithm calculation module and the input and output module respectively, is the basis for ensuring the normal operation of the management system, and can only use a built-in battery or an external power supply or can be a combination of the built-in battery and the external power supply.
The input and output module can transmit signals through wireless transmission or wired transmission, and the functions of the input and output module include but are not limited to: inputting a preset parameter updating signal and inputting a reset signal. In terms of use, signals transmitted by a wire are more stable, wireless transmission is more convenient, a wire technology or a wireless technology can be selected according to actual use requirements, and the transmission mode is not limited in the application. Wherein, the wireless transmission includes but is not limited to: zigbee, Wireless, ISA100.11a, Wi-Fi and Bluetooth. As an alternative embodiment of the present invention, the edge computing system further comprises: and the display module is connected with the input and output module and is used for displaying parameter information.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (9)
1. An edge calculation system, comprising:
the device comprises a parameter sensing module, an operation module, a storage module, an algorithm calculation module, a power supply module and an input/output module, wherein the algorithm calculation module is respectively connected with the operation module, the input/output module and the storage module, the storage module is respectively connected with the operation module, the input/output module and the temperature sensing module, the power supply module is respectively used for supplying power for the parameter sensing module, the operation module, the storage module, the algorithm calculation module and the input/output module, the parameter sensing module acquires physical/chemical parameters, the operation module sends the physical/chemical parameters to the algorithm calculation module, the algorithm calculation module selects a corresponding algorithm to calculate the physical/chemical parameters to acquire calculation parameters and sends the calculation parameters to the operation module, the operation module compares the calculation parameters with preset parameters and determines optimal parameters according to comparison results, and the storage module stores the calculation parameters and preset parameters.
2. The edge computing system of claim 1, wherein the physical/chemical information comprises: temperature information, humidity information, vibration information, magnetic force information.
3. The edge computing system of claim 1, wherein the edge computing system further comprises: and the conversion module is connected with the parameter sensing module and is used for converting the analog signal into a digital signal.
4. The edge computing system of claim 1, wherein the algorithm in the algorithm calculation module comprises: a neural network algorithm implemented by the silicon wafer MOS structure using the metal interconnects, a fuzzy algorithm implemented by the silicon wafer MOS structure using the metal interconnects, and a pseudo-affine transformation algorithm implemented by the silicon wafer MOS structure using the metal interconnects.
5. The edge computing system of claim 1, wherein the storage module comprises: the fixed storage submodule is used for storing preset parameters, and the floating storage submodule is used for storing calculation parameters.
6. The edge computing system of any one of claims 1 to 5, wherein the input-output module is configured to: inputting a preset parameter updating signal and inputting a reset signal.
7. The edge computing system of claim 6, wherein the input/output module is configured to transmit in a wired or wireless manner.
8. The edge computing system of claim 7, wherein the wireless transmission comprises: zigbee, Wireless, ISA100.11a, Wi-Fi and Bluetooth.
9. The edge computing system of claim 1, wherein the edge computing system further comprises:
and the display module is connected with the input and output module and is used for displaying parameter information.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910999780.8A CN111078786A (en) | 2019-10-21 | 2019-10-21 | Edge operation system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910999780.8A CN111078786A (en) | 2019-10-21 | 2019-10-21 | Edge operation system |
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| CN1491441A (en) * | 2001-06-22 | 2004-04-21 | ���µ�����ҵ��ʽ���� | Semiconductor device and its driving method |
| KR20090122603A (en) * | 2008-05-26 | 2009-12-01 | 엘에스산전 주식회사 | Module and method for controlling temperature |
| CN108549341A (en) * | 2018-04-19 | 2018-09-18 | 广州裕申电子科技有限公司 | Workshop Production approaches to IM, system and device based on Internet of Things |
| CN110221567A (en) * | 2019-07-08 | 2019-09-10 | 中国电力工程顾问集团中南电力设计院有限公司 | Intelligent managing and control system based on 5G technology of Internet of things |
| CN110225116A (en) * | 2019-06-12 | 2019-09-10 | 上海阿刻忒科技有限公司 | A kind of adaptive robust control method and system under uncertain network environment based on edge calculations framework |
-
2019
- 2019-10-21 CN CN201910999780.8A patent/CN111078786A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1491441A (en) * | 2001-06-22 | 2004-04-21 | ���µ�����ҵ��ʽ���� | Semiconductor device and its driving method |
| KR20090122603A (en) * | 2008-05-26 | 2009-12-01 | 엘에스산전 주식회사 | Module and method for controlling temperature |
| CN108549341A (en) * | 2018-04-19 | 2018-09-18 | 广州裕申电子科技有限公司 | Workshop Production approaches to IM, system and device based on Internet of Things |
| CN110225116A (en) * | 2019-06-12 | 2019-09-10 | 上海阿刻忒科技有限公司 | A kind of adaptive robust control method and system under uncertain network environment based on edge calculations framework |
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