CN209783731U - Power equipment anomaly detection wireless vibration sensor based on edge calculation - Google Patents
Power equipment anomaly detection wireless vibration sensor based on edge calculation Download PDFInfo
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- CN209783731U CN209783731U CN201920896012.5U CN201920896012U CN209783731U CN 209783731 U CN209783731 U CN 209783731U CN 201920896012 U CN201920896012 U CN 201920896012U CN 209783731 U CN209783731 U CN 209783731U
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Abstract
the utility model discloses a can realize the power equipment anomaly detection wireless vibration sensor based on edge calculation of low-power consumption when guaranteeing wireless sensor module performance. The wireless vibration sensor comprises a shell and a power supply device; a top cover is arranged at the upper end of the shell; the lower end of the shell is provided with a waterproof joint, and one side of the shell is provided with a wireless communication antenna; a connector is arranged at the waterproof joint; the lower end of the connector is provided with a sealing cover; a sensor circuit board is arranged in the shell; the sensor circuit board is provided with a sensor unit, a signal processing unit and a communication unit; the sensor unit comprises a vibration detection module and a signal conditioning module; the signal processing unit adopts a low-power-consumption edge calculation processor; the communication unit comprises a debugging interface and a wireless communication module. The wireless vibration sensor can be miniaturized, the power consumption is greatly reduced, and the cost is low.
Description
Technical Field
The utility model relates to a sensor especially relates to a power equipment detects wireless vibration sensor unusually based on edge calculation.
Background
With the rapid development and the gradual maturity of wireless technologies, wireless communication is also developed to a certain stage, the developed technologies are more and more mature, the directions are more and more, and the application schemes are more and more important, and a large number of application schemes begin to adopt wireless technologies for data acquisition and communication. In recent years, wireless sensor networks are widely used in large-scale fields such as intelligent transportation, environmental monitoring and warehousing management. With the continuous increase of the unit capacity of the power plant, the automation degree is improved, the requirement on the operation safety performance of the power plant is higher and higher, and the serious consequence that equipment such as a fan, a pump and the like in many power plants are damaged and tripped or even a generator set is stopped due to overlarge vibration occurs successively. Therefore, in modern industrial production such as power production, a vibration monitoring device which is low in cost, reliable and capable of flexibly arranging measuring points is urgently needed for vibration monitoring of a large number of auxiliary mechanical equipment with scattered positions.
The development of micro-electromechanical systems and low-power-consumption high-integration digital equipment enables the realization of low-cost, low-power-consumption and small-volume sensor nodes. The nodes are matched with various types of sensors to form the WSN. The method is widely applied to the fields of battlefield monitoring, large-scale environment monitoring, target tracking in a large area and the like. The wireless sensor network nodes are generally powered by batteries, the working environment is usually severe, the number is large, and the replacement is very difficult, so that the low power consumption is one of the most important design criteria of the wireless sensor. Today, wireless sensing technology is widely applied, and the realization that low-power consumption can be realized when guaranteeing wireless sensing module performance has certain realistic meaning.
SUMMERY OF THE UTILITY MODEL
The utility model discloses the technical problem that will solve is: provided is an edge calculation-based power equipment abnormality detection wireless vibration sensor capable of realizing low power consumption while ensuring wireless sensor module performance.
In order to achieve the above object, the utility model adopts the following technical scheme: a wireless vibration sensor for detecting abnormality of electric power equipment based on edge calculation comprises a shell and a power supply device; a top cover is arranged at the upper end of the shell; the lower end of the shell is provided with a waterproof joint, and one side of the shell is provided with a wireless communication antenna; a connector is arranged at the waterproof joint; the lower end of the connector is provided with a sealing cover;
a sensor circuit board is arranged in the shell; the sensor circuit board is provided with a sensor unit, a signal processing unit and a communication unit;
the sensor unit comprises a vibration detection module and a signal conditioning module; the signal processing unit adopts a low-power-consumption edge calculation processor; the communication unit comprises a debugging interface and a wireless communication module;
a power supply conversion module is arranged between the power supply device and the signal conditioning module; the power supply conversion module is electrically connected with the signal conditioning module; the vibration detection module is electrically connected with the signal conditioning module; an AD conversion module is arranged between the signal conditioning module and the low-power-consumption edge computing processor;
A data cache module is arranged on the low-power-consumption edge computing processor; the debugging interface and the wireless communication module are respectively and electrically connected with the low-power-consumption edge computing processor; the wireless communication module is electrically connected with the wireless communication antenna.
specifically, the data caching module adopts an ARAM or FRAM data caching module.
Preferably, the low-power edge calculation processor employs an embedded AI chip GAP 8.
Preferably, the wireless communication module is a LORA wireless communication module or a NBiot wireless communication module.
preferably, the AD conversion module adopts a 16-bit AD converter.
furthermore, a super capacitor is arranged between the power supply device and the power conversion module.
further, the power supply device adopts a solar panel or a high-energy battery.
preferably, the debugging interface adopts an RS485 debugging interface.
The utility model has the advantages that: the utility model discloses a power equipment anomaly detection wireless vibration sensor based on edge calculation can realize the miniaturization of sensor, and data transmission time shortens greatly simultaneously, and the radio live time shortens, and the consumption will greatly reduce; and the device has the advantages of small volume, light weight, good firmness, large temperature and frequency measurement range, high reliability and low cost.
Drawings
Fig. 1 is a perspective view of a wireless vibration sensor for detecting abnormality of power equipment based on edge calculation in an embodiment of the present invention;
Fig. 2 is a hardware schematic diagram of the wireless vibration sensor for detecting abnormality of power equipment based on edge calculation in the embodiment of the present invention;
Fig. 3 is a high-voltage measuring point distribution diagram of the power equipment abnormality detection wireless vibration sensor based on edge calculation in the embodiment of the present invention;
Fig. 4 is a low-voltage measuring point distribution diagram of the wireless vibration sensor for power equipment anomaly detection based on edge calculation in the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples, but the embodiments of the present invention are not limited thereto.
As shown in fig. 1 to 2, a wireless vibration sensor for detecting abnormality of electric power equipment based on edge calculation includes a housing 1 and a power supply device; a top cover 12 is arranged at the upper end of the shell 1; the lower end of the shell 1 is provided with a waterproof joint 11, and one side of the shell 1 is provided with a wireless communication antenna 3; the waterproof connector 11 is provided with a connector 2; the lower end of the connector 2 is provided with a sealing cover 21;
A sensor circuit board is arranged inside the shell 1; the sensor circuit board is provided with a sensor unit, a signal processing unit and a communication unit;
The sensor unit comprises a vibration detection module 42 and a signal conditioning module 43; the signal processing unit adopts a low-power edge calculation processor 45; the communication unit comprises a debugging interface 48 and a wireless communication module 47;
a power conversion module 41 is arranged between the power supply device and the signal conditioning module 43; the power conversion module 41 is electrically connected with the signal conditioning module 43; the vibration detection module 42 is electrically connected with the signal conditioning module 43; an AD conversion module 44 is arranged between the signal conditioning module 43 and the low-power-consumption edge computing processor 45;
the low-power-consumption edge computing processor 45 is provided with a data cache module 46; the debugging interface 48 and the wireless communication module 47 are respectively electrically connected with the low-power edge computing processor 45; the wireless communication module 47 is electrically connected with the wireless communication antenna 3.
Specifically, the data caching module 46 is an ARAM or FRAM data caching module. Specifically, the AD conversion module 44 adopts a 16-bit AD converter. Specifically, the debugging interface 48 adopts an RS485 debugging interface.
Specifically, the low-power edge calculation processor 45 employs an embedded AI chip GAP 8. The low-power-consumption edge calculation processor 45 adopts a low-power-consumption edge calculation processor GAP8 embedded AI chip with a global first-payment open source RISC-V framework, and endows the AI capability to the front-end intelligent equipment through the GAP8, so that data acquisition, calculation and decision making are all carried out on the front-end equipment, namely AI localization is carried out, and the constraint of the network is eliminated. GAP8 is 20 times more energy efficient than the existing microprocessors in the market, and GAP8 is 16 times more energy efficient compared to ARM-M7 processors. Assuming that batteries can last 6 months using ARM-M7, GAP8 can last at least 96 months and 8 years. After the edge calculation, the data volume is reduced in a geometric time, and the data transmission volume is greatly reduced. Data transmission may employ a lower rate network that is more power efficient and less expensive. Such as NB-IoT, LoRa, Sigfox, etc. Moreover, the data transmission time is greatly shortened, the service time of the most power-consuming part in the wireless IoT system is shortened, and the power consumption is greatly reduced.
Specifically, the wireless communication module 47 is an LORA wireless communication module or an NBiot wireless communication module. The wireless module 47 employs LORA wireless communication or NBiot wireless communication. The LORA module carrier frequency is 470MHz or 433MHz, and the data transmission air baud rate is 115.2 kbps; the open transmission distance reaches 700 meters, the transmitting power can be set to be 10-20 dBm, the receiving current and the transmitting current are respectively 16mA and 130mA, and the maximum receiving sensitivity is 138.5 dBm. The working voltage of the NBiot module is 3.1-4.2V, the maximum transmitting power is 23dBm, the typical receiving sensitivity is-128 dBm, and the transmission distance can basically meet the requirement as long as an area covered by the Nboot base station exists.
Specifically, a super capacitor 6 is disposed between the power supply device and the power conversion module 41. The power supply device adopts a solar panel 5 or a high-energy battery. Preferably, the power supply device is divided into a solar power supply mode and a standby high-energy battery mode. The principle of solar power supply is that solar photovoltaic is converted into electric energy to charge a super capacitor, the super capacitor provides a power supply for a circuit, the requirement of a communication module on instantaneous working pulse large current is met, ultralow electricity leakage is realized, and the super charging times are realized. The standby high-energy battery is a disposable lithium thionyl chloride battery, so that the safety is high, the ultralow electric leakage is realized, the battery is used as supplementary power supply when the solar power supply is seriously insufficient, alarm information can be uploaded when an extremely weak light or device fault occurs, and the battery is informed to be maintained.
The power supply device adopts a solar cell panel 5 for the type selection of the power supply part, and the solar cell panel 5 adopts a weak light amorphous silicon photovoltaic panel with a higher light absorption coefficient. Especially in the visible light wave band of 0.3-0.75 μm, the absorption coefficient is higher by an order of magnitude than that of monocrystalline silicon. The absorption efficiency of solar radiation is about 40 times higher, and 90% of useful solar energy can be absorbed by a thin amorphous silicon film about 1 μm thick. At present, the mainstream of the amorphous silicon battery is cadmium telluride, and the conversion efficiency can reach more than 23%. A lithium thionyl chloride battery is used as a standby power supply, and is a disposable non-rechargeable battery. The voltage is 3.6V, and the temperature range is-55-85 ℃; the specific energy is as high as 430Wh/kg, which is the highest in lithium batteries, and the storage performance is more than 5 years.
Specifically, the vibration detection module 42 selects a piezoelectric accelerometer, and the principle thereof is to convert the mechanical energy of vibration into an electrical signal; and processing the electric signal transmitted by the sensor by using a signal processing part. The sensor module measures parameters such as vibration and temperature of equipment according to actual needs, and the sensor in the sensor module is required to be small in size, low in power consumption and simple in peripheral circuit. Compare the sensor that adopts the IEPE technique with traditional sensor and have small, light in weight, tightness good, adaptation temperature and measurement frequency range big, the reliability is high and advantage such as with low costs, so the utility model discloses an IEPE piezoelectricity acceleration sensor.
Vibration detection module 42 adopts vibration data acquisition 1 time every day, and 1 time is reported in the communication, the mode of other time dormancy. The voiceprint vibration frequency of the vibration detection module 42 is 50hz-20khz, the data sampling rate is 20khz, and the single sampling duration can reach more than 5 seconds. At present, the analysis frequency band of a transformer and a GIS is usually less than 5k, but the future expansion to 20k is not excluded, so the sampling rate range can be expanded to 10k-40 k. The RAM or FRAM data buffer device is adopted, the capacity of the reserved space can reach 512kByte, and the data amount of the RAM buffer is 20k times/s 5s 2B/time-200 kByte.
furthermore, the connector 2 can be connected by steel column bolts, and the installation mode is suitable for the screw hole environment due to the fact that the self-resonant frequency of installation is high. The magnetic base can also be adopted for installation, and the installation mode is suitable for smooth and iron materials of the measured surface due to the fact that the position of the measuring point is easy to select, and is matched with ERGO1690 strong glue for bonding and fixing. The solar photovoltaic is fixed and can be directly installed with the integration of the photovoltaic panel and the sensor, the angle of the photovoltaic panel can be adjusted and locked, and the installation mode is suitable for the better condition of light. The photovoltaic panel and the sensor can be installed in a split mode. The photovoltaic board is installed and is satisfied the light condition region, through cable junction sensor body. The fixing mode is suitable for the condition of weak light.
Claims (8)
1. An electric power equipment abnormality detection wireless vibration sensor based on edge calculation is characterized in that: comprises a shell (1) and a power supply device; a top cover (12) is arranged at the upper end of the shell (1); the lower end of the shell (1) is provided with a waterproof joint (11), and one side of the shell (1) is provided with a wireless communication antenna (3); a connector (2) is arranged at the waterproof connector (11); the lower end of the connector (2) is provided with a sealing cover (21);
A sensor circuit board is arranged in the shell (1); the sensor circuit board is provided with a sensor unit, a signal processing unit and a communication unit;
the sensor unit comprises a vibration detection module (42) and a signal conditioning module (43); the signal processing unit adopts a low-power-consumption edge calculation processor (45); the communication unit comprises a debugging interface (48) and a wireless communication module (47);
A power supply conversion module (41) is arranged between the power supply device and the signal conditioning module (43); the power supply conversion module (41) is electrically connected with the signal conditioning module (43); the vibration detection module (42) is electrically connected with the signal conditioning module (43); an AD conversion module (44) is arranged between the signal conditioning module (43) and the low-power-consumption edge computing processor (45);
A data cache module (46) is arranged on the low-power-consumption edge computing processor (45); the debugging interface (48) and the wireless communication module (47) are respectively and electrically connected with the low-power-consumption edge computing processor (45); the wireless communication module (47) is electrically connected with the wireless communication antenna (3).
2. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: the data caching module (46) adopts an ARAM or FRAM data caching module.
3. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: the low-power edge calculation processor (45) employs an embedded AI chip GAP 8.
4. the edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: the wireless communication module (47) adopts an LORA wireless communication module or an NBiot wireless communication module.
5. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: the AD conversion module (44) adopts a 16-bit AD converter.
6. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: and a super capacitor (6) is arranged between the power supply device and the power conversion module (41).
7. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 6, characterized in that: the power supply device adopts a solar panel (5) or a high-energy battery.
8. The edge calculation-based power equipment abnormality detection wireless vibration sensor according to claim 1, characterized in that: and the debugging interface (48) adopts an RS485 debugging interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201920896012.5U CN209783731U (en) | 2019-06-14 | 2019-06-14 | Power equipment anomaly detection wireless vibration sensor based on edge calculation |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201920896012.5U CN209783731U (en) | 2019-06-14 | 2019-06-14 | Power equipment anomaly detection wireless vibration sensor based on edge calculation |
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| CN209783731U true CN209783731U (en) | 2019-12-13 |
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| CN201920896012.5U Active CN209783731U (en) | 2019-06-14 | 2019-06-14 | Power equipment anomaly detection wireless vibration sensor based on edge calculation |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111174905A (en) * | 2020-02-13 | 2020-05-19 | 欧朗电子科技有限公司 | Low-power consumption Internet of things vibration abnormality detection device and detection method thereof |
| CN114172907A (en) * | 2021-12-27 | 2022-03-11 | 重庆忽米网络科技有限公司 | Edge computing system for monitoring equipment state |
-
2019
- 2019-06-14 CN CN201920896012.5U patent/CN209783731U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111174905A (en) * | 2020-02-13 | 2020-05-19 | 欧朗电子科技有限公司 | Low-power consumption Internet of things vibration abnormality detection device and detection method thereof |
| CN111174905B (en) * | 2020-02-13 | 2023-10-31 | 欧朗电子科技有限公司 | Low-power consumption device and method for detecting vibration abnormality of Internet of things |
| CN114172907A (en) * | 2021-12-27 | 2022-03-11 | 重庆忽米网络科技有限公司 | Edge computing system for monitoring equipment state |
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