Intelligent Supervision Methods for Power Facilities

Abstract

The present invention relates to an intelligent supervision method for electric power facilities, comprising: using a network video recording device to obtain a corresponding customized scene image; using a primary enhancement device to obtain and output a corresponding sorting filter image; using a secondary enhancement device to obtain and output a corresponding exponential enhancement image; using a final enhancement device to obtain and output a corresponding airspace enhancement image; and using an identification recognition mechanism for subsequent processing. The intelligent supervision method for electric power facilities of the present invention can use a custom-designed convolutional neural network model to complete the intelligent identification of whether an insulating soft ladder and an anti-soft ladder frame detachment device are connected, thereby realizing intelligent supervision and real-time positioning during the maintenance of electric power facilities.

Description

Technical Field

[0001] The present invention relates to the field of electric power facilities, and in particular to an intelligent supervision method for electric power facilities. Background Art

[0002] Power facilities refer to power generation, transmission, transformation, distribution, power dispatching, power communication and other facilities in operation, standby and maintenance status and related auxiliary facilities. Power facilities are mainly used in various transmission and distribution lines to ensure the convenience of long-distance power transmission. It can be seen that power facilities are mainly related to the supply, transmission and use of electric energy, and there are a large number of related facility types that require different security monitoring processes.

[0003] For example, there is currently a lack of a reliable intelligent detection solution to perform intelligent identification on whether the insulating soft ladder and the anti-ladder frame detachment device are connected. As a result, the insulating soft ladder is suspended on the power distribution network and is in a dangerous situation where it is easy to fall due to the lack of necessary safety components. Therefore, it needs to be focused on prevention.

[0004] In the prior art, CN118209079A discloses a Beidou high-precision positioning power facility deformation monitoring system, including a Beidou module and a solution module, wherein the Beidou module is used to collect original observation data of power facilities; the solution module is configured to perform the following steps: obtaining the original observation data of power facilities provided by the Beidou module; using the original observation data of power facilities, calculating different feature results in different feature models; obtaining environmental impact factors; judging whether the environmental impact factors are greater than the environmental critical threshold; if greater than, calculating the difference between the feature results to obtain the feature difference, otherwise no calculation is performed; calculating the final displacement coordinate value of the monitoring point by the feature difference, and obtaining the displacement deviation solution of the power facility according to the final displacement coordinate value of the monitoring point, which is used to monitor the deformation degree of the power facility. The problem of inaccurate data results caused by the influence of external environmental factors in the prior art is overcome, and a more accurate judgment of whether the power facility is deformed is achieved by reducing data errors.

[0005] CN118209827A discloses a power grid partial discharge monitoring method based on a dual-mode monitoring system, comprising: a power supply, a plurality of monitoring devices, an alarm and a remote host, wherein the monitoring devices are equidistantly installed on a cable, the monitoring devices comprising a gas sensor, a signal amplifier, an acoustic imaging module, an ultraviolet imaging module, an A / D conversion module and a microprocessor, the gas sensor is connected to the signal amplifier in sequence, the microprocessor is connected to the alarm and the remote host via a network, and a plurality of gas sensors are provided to monitor the partial discharge phenomenon in power facilities, which causes rubber and other parts to generate gas under high temperature, and the generated gas can be detected and a detection signal can be outputted externally, and by detecting the gas, the problem that the existing monitoring device uses a sound amplification function and a decibel value to distinguish the difference in partial discharge is solved, and the initial partial discharge and the partial discharge of the closed switch cannot be detected, which affects the detection accuracy.

[0006] The above-mentioned existing technologies are unable to provide intelligent supervision and real-time positioning during the maintenance of power facilities. Summary of the invention

[0007] In order to solve the technical problems in related fields, the present invention provides an intelligent supervision method for power facilities, which can screen reliable and comprehensive multiple basic data for the convolutional neural network model, and on this basis, an identification recognition mechanism including an ASIC device, a parameter extraction component and a network application component is used to complete the intelligent identification of whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected, and a network notification mechanism is used to wirelessly transmit notification data including reminder information that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected and the positioning information of the insulating soft ladder to a remote power facility safety management server through a wireless communication network when the identification mark representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected indicates that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected, thereby improving the reliability of the hanging of the insulating soft ladder and realizing intelligent supervision and real-time positioning during the maintenance of power facilities.

[0008] According to the present invention, a method for intelligent supervision of electric power facilities is provided, the method comprising:

[0009] The network recording device is arranged opposite to the power distribution network provided with the insulating software, and is used to determine whether to perform a recording operation on the power distribution network provided with the insulating software based on the network control instruction, and when it is determined to perform a recording operation on the power distribution network provided with the insulating software, obtain a corresponding customized scene image;

[0010] Connecting the primary enhancement device to the network video recording device to perform statistical sorting and filtering processing on the received customized scene image to obtain and output a corresponding sorting and filtering image;

[0011] Connecting a secondary enhancement device to the primary enhancement device to perform image content enhancement processing based on exponential transformation on the received sorted filtered image to obtain and output a corresponding exponentially enhanced image;

[0012] Connecting the final enhancement device to the secondary enhancement device to perform image spatial domain enhancement processing on the received exponentially enhanced image to obtain and output a corresponding spatial domain enhanced image;

[0013] The identification recognition mechanism is connected to the final enhancement device and includes an ASIC device, a parameter extraction component and a network application component. The parameter extraction component is connected to the network application component. The ASIC device is connected to the parameter extraction component and the network application component respectively, so as to realize the on-site configuration of the working parameters of the parameter extraction component and the network application component respectively. The identification recognition mechanism is used to obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the insulating soft ladder in the received spatial domain enhancement image, and to obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the anti-soft ladder frame detachment device in the received spatial domain enhancement image. The number of pixels of the spatial domain enhancement image, the signal-to-noise ratio of the spatial domain enhancement image, the various curvature values ​​corresponding to the insulating soft ladder and the various curvature values ​​corresponding to the anti-soft ladder frame detachment device are input into the convolutional neural network model in parallel to execute the convolutional neural network model to obtain the identification mark outputted by the convolutional neural network model, which represents whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected;

[0014] The network notification mechanism is connected to the identification recognition mechanism to wirelessly transmit notification data including reminder information that the insulating ladder and the anti-ladder frame detachment device are not connected and location information of the insulating ladder to a remote power facility safety management server via a wireless communication network when the identification mark representing whether the insulating ladder and the anti-ladder frame detachment device are connected indicates that the insulating ladder and the anti-ladder frame detachment device are not connected;

[0015] Among them, the convolutional neural network model is a convolutional neural network that has completed multiple learnings, and the number of learnings is monotonically positively correlated with the resolution of the spatial domain enhanced image.

[0016] Therefore, the present invention has the following outstanding technical effects:

[0017] First, an identification mechanism including an ASIC device, a parameter extraction component, and a network application component is used to complete an intelligent identification of whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected, wherein a convolutional neural network model is used to perform the intelligent identification process, and the convolutional neural network is a convolutional neural network that has completed multiple learnings and the number of learnings is monotonically positively correlated with the resolution of the spatial domain enhanced image;

[0018] Second, multiple reliable and comprehensive basic data are selected for the convolutional neural network model, including the number of pixels of the spatial enhancement image, the signal-to-noise ratio of the spatial enhancement image, the curvature values ​​corresponding to the insulating soft ladder, and the curvature values ​​corresponding to the anti-soft ladder frame detachment device;

[0019] Third: A network notification mechanism is used to wirelessly transmit notification data including reminder information that the insulating ladder and the anti-ladder frame detachment device are not connected and the positioning information of the insulating ladder to a remote power facility safety management server through a wireless communication network when the identification mark representing whether the insulating ladder and the anti-ladder frame detachment device are connected indicates that the insulating ladder and the anti-ladder frame detachment device are not connected, thereby improving the reliability of the insulating ladder suspension and realizing intelligent supervision and real-time positioning during the maintenance of power facilities.

[0020] The intelligent supervision method for electric power facilities of the present invention can use a custom-designed convolutional neural network model to complete the intelligent identification of whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected, thereby realizing intelligent supervision and real-time positioning during the maintenance process of electric power facilities. DETAILED DESCRIPTION

[0021] The following is a detailed description of an embodiment of the method for intelligent supervision of electric power facilities of the present invention.

[0022] Embodiment 1

[0023] According to the first embodiment of the present invention, a method for intelligent supervision of electric power facilities is shown, and the method comprises the following steps:

[0024] S1. Setting a network recording device opposite to a power distribution network provided with insulating software, for determining whether to perform a recording operation on the power distribution network provided with insulating software based on a network control instruction, and obtaining a corresponding customized scene image when deciding to perform a recording operation on the power distribution network provided with insulating software;

[0025] Specifically, the network video recording device is arranged opposite to the power distribution network with insulation software, and is used to determine whether to perform a video recording operation on the power distribution network with insulation software based on a network control instruction, and when it is determined to perform a video recording operation on the power distribution network with insulation software, obtaining a corresponding customized scene image includes: the network video recording device includes a network transceiver interface for receiving the network control instruction;

[0026] S2, connecting the primary enhancement device to the network video recording device to perform statistical sorting and filtering processing on the received customized scene image to obtain and output a corresponding sorting and filtering image;

[0027] S3, connecting a secondary enhancement device to the primary enhancement device to perform image content enhancement processing based on exponential transformation on the received sorted filtered image to obtain and output a corresponding exponentially enhanced image;

[0028] S4, connecting the final enhancement device to the secondary enhancement device to perform image spatial domain enhancement processing on the received exponentially enhanced image to obtain and output a corresponding spatial domain enhanced image;

[0029] S5. Connect the identification mechanism to the final enhancement device and include an ASIC device, a parameter extraction component and a network application component. The parameter extraction component is connected to the network application component. The ASIC device is connected to the parameter extraction component and the network application component respectively, so as to realize the on-site configuration of the working parameters of the parameter extraction component and the network application component respectively. The identification mechanism is used to obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the insulating soft ladder in the received spatial domain enhancement image, and to obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the anti-soft ladder frame detachment device in the received spatial domain enhancement image. The number of pixels of the spatial domain enhancement image, the signal-to-noise ratio of the spatial domain enhancement image, the various curvature values ​​corresponding to the insulating soft ladder and the various curvature values ​​corresponding to the anti-soft ladder frame detachment device are input in parallel to the convolutional neural network model to execute the convolutional neural network model to obtain the identification mark outputted by the convolutional neural network model, which represents whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected.

[0030] S6, connecting the network notification mechanism with the identification recognition mechanism, so as to wirelessly transmit notification data including reminder information that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected and location information of the insulating soft ladder to a remote power facility safety management server through a wireless communication network when the identification mark representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected indicates that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected;

[0031] The convolutional neural network model is a convolutional neural network that has completed multiple learnings, and the number of learnings is monotonically positively correlated with the resolution of the spatial domain enhanced image;

[0032] Wherein, when the identification mark representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected indicates that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected, the notification data including the reminder information that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected and the location information of the insulating soft ladder are wirelessly transmitted to the remote power facility safety management server through the wireless communication network, including: the remote power facility safety management server is a cloud server, a big data server or a blockchain server;

[0033] Among them, the network recording device is set opposite to the distribution network laid with insulating software, and is used to decide whether to perform the recording operation on the distribution network laid with insulating software based on the network control instruction, and when deciding to perform the recording operation on the distribution network laid with insulating software, obtaining the corresponding customized scene image includes: the network recording device has a built-in network transceiver interface for receiving the network control instruction.

[0034] Embodiment 2

[0035] According to the second embodiment of the present invention, another implementation method of the intelligent supervision method of power facilities is shown.

[0036] Compared with the first embodiment, the intelligent supervision method of electric power facilities in the second embodiment may further include:

[0037] The volume detection component is connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to measure the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively;

[0038] Wherein, the volume detection component is connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification mechanism respectively to measure the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification mechanism respectively, which includes: the volume detection component includes a plurality of volume measurement units, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification mechanism respectively to complete the measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification mechanism respectively;

[0039] Wherein, the volume detection component includes a plurality of volume measurement units, which are respectively connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to complete the respective measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, including: the plurality of volume measurement units are a plurality of visual detectors, which are respectively connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to complete the respective measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism;

[0040] Wherein, the plurality of volume measurement units are a plurality of visual detectors, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to complete the respective measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, including: the structures of the plurality of visual detectors are the same;

[0041] Among them, the multiple volume measurement units are multiple visual detectors, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to complete the separate measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, and also include: each of the multiple visual detectors includes a stereo camera.

[0042] Embodiment 3

[0043] According to the third embodiment of the present invention, another implementation method of the intelligent supervision method of electric power facilities is shown.

[0044] Compared with the first and second embodiments, the smart supervision method for electric power facilities of the third embodiment may further include:

[0045] The synchronous operation mechanism is connected to the plurality of volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to perform synchronous operation between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism;

[0046] Wherein, the synchronous operation mechanism is respectively connected to the plurality of volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to perform the synchronous operation between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, which includes: the synchronous operation mechanism performs the synchronous operation between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism based on a square wave waveform;

[0047] Among them, the synchronous operation mechanism is connected to multiple volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, and is used to perform synchronous operations between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, including: using an insulating soft ladder SIC chip to realize the synchronous operation mechanism.

[0048] In addition, in the intelligent supervision method of electric power facilities, the network notification mechanism is also used to stop wirelessly transmitting notification data including reminder information that the insulating ladder and the anti-ladder frame detachment device are not connected and positioning information of the insulating ladder to a remote electric power facility safety management server through the wireless communication network when the identification mark representing whether the insulating ladder and the anti-ladder frame detachment device are connected indicates that the insulating ladder and the anti-ladder frame detachment device are connected.

[0049] And wherein, when the identification mark representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected indicates that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected, notification data including reminder information that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected and positioning information of the insulating soft ladder are wirelessly transmitted to a remote power facility safety management server through a wireless communication network, including: the wireless communication network is based on a time division duplex communication mode or a frequency division duplex communication mode.

[0050] Although the examples of the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various other modifications may be made without departing from the true scope of the present invention, and equivalents may be substituted. In addition, many modifications may be made to adapt a particular situation to the teachings of the present invention without departing from the inventive concept described herein. Therefore, the present invention is not limited to the disclosed particular embodiments, but the present invention includes all embodiments falling within the scope of the appended claims.

Claims

1. A method for intelligent supervision of electric power facilities, characterized in that: The method comprises: The network video recording device is arranged opposite to the power distribution network on which the insulating flexible ladder is laid, and is used to determine whether to perform a video recording operation on the power distribution network on which the insulating flexible ladder is laid based on the network control instruction, and when it is determined to perform a video recording operation on the power distribution network on which the insulating flexible ladder is laid, obtain a corresponding customized scene image; Connecting the primary enhancement device to the network video recording device to perform statistical sorting and filtering processing on the received customized scene image to obtain and output a corresponding sorting and filtering image; Connecting a secondary enhancement device to the primary enhancement device to perform image content enhancement processing based on exponential transformation on the received sorted filtered image to obtain and output a corresponding exponentially enhanced image; Connecting the final enhancement device to the secondary enhancement device to perform image spatial domain enhancement processing on the received exponentially enhanced image to obtain and output a corresponding spatial domain enhanced image; Connecting the identification mechanism to the final enhancement device, the identification mechanism includes an ASIC device, a parameter extraction component and a network application component, the parameter extraction component is connected to the network application component, and the ASIC device is respectively connected to the parameter extraction component and the network application component to realize the on-site configuration of the working parameters of the parameter extraction component and the network application component respectively, the identification mechanism is used to obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the insulating soft ladder in the received spatial domain enhancement image, and obtain the various curvature values ​​of the geometric curve corresponding to the imaging area occupied by the anti-soft ladder frame detachment device in the received spatial domain enhancement image, and input the number of pixels of the spatial domain enhancement image, the signal-to-noise ratio of the spatial domain enhancement image, the various curvature values ​​corresponding to the insulating soft ladder, and the various curvature values ​​corresponding to the anti-soft ladder frame detachment device into the convolutional neural network model in parallel to execute the convolutional neural network model to obtain the identification mark output by the convolutional neural network model representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected; The network notification mechanism is connected to the identification recognition mechanism to wirelessly transmit notification data including reminder information that the insulating ladder and the anti-ladder frame detachment device are not connected and location information of the insulating ladder to a remote power facility safety management server via a wireless communication network when the identification mark representing whether the insulating ladder and the anti-ladder frame detachment device are connected indicates that the insulating ladder and the anti-ladder frame detachment device are not connected; Among them, the convolutional neural network model is a convolutional neural network that has completed multiple learnings, and the number of learnings is monotonically positively correlated with the resolution of the spatial domain enhanced image.

2. The method for intelligent supervision of electric power facilities according to claim 1, characterized in that: When the identification mark representing whether the insulating soft ladder and the anti-soft ladder frame detachment device are connected indicates that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected, wirelessly transmitting notification data including reminder information that the insulating soft ladder and the anti-soft ladder frame detachment device are not connected and location information of the insulating soft ladder to a remote power facility safety management server through a wireless communication network includes: the remote power facility safety management server is a cloud server, a big data server or a blockchain server; Among them, the network recording device is arranged opposite to the distribution network on which the insulating ladder is laid, and is used to decide whether to perform the recording operation on the distribution network on which the insulating ladder is laid based on the network control instruction, and when deciding to perform the recording operation on the distribution network on which the insulating ladder is laid, obtaining the corresponding customized scene image includes: the network recording device has a built-in network transceiver interface for receiving the network control instruction.

3. The intelligent monitoring method for electric power facilities according to claim 2, characterized in that: The method further comprises: The volume detection component is connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to measure the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively; Among them, the volume detection component is connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively to respectively measure the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, which includes: the volume detection component includes a plurality of volume measurement units, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively to complete the respective measurements of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism.

4. The method for intelligent supervision of electric power facilities according to claim 3, characterized in that: The volume detection component includes a plurality of volume measurement units, which are used to respectively connect with the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to complete the respective measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, including: the plurality of volume measurement units are a plurality of visual detectors, which are used to respectively connect with the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to complete the respective measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism.

5. The method for intelligent supervision of electric power facilities according to claim 4, characterized in that: The multiple volume measurement units are multiple visual detectors, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, so as to complete the separate measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively, including: the structures of the multiple visual detectors are the same.

6. The method for intelligent supervision of electric power facilities according to claim 5, characterized in that: The multiple volume measurement units are multiple visual detectors, which are used to be connected to the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism respectively to complete the separate measurement of the current real-time volume values ​​of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism. It also includes: each of the multiple visual detectors includes a stereo camera.

7. The intelligent monitoring method for electric power facilities according to any one of claims 3 to 6, characterized in that: The method further comprises: The synchronous operation mechanism is respectively connected to the multiple volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to perform synchronous operations between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism.

8. The method for intelligent supervision of electric power facilities according to claim 7, characterized in that: The synchronous operation mechanism is respectively connected to multiple volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to perform synchronous operations between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, including: the synchronous operation mechanism performs synchronous operations between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism based on a square wave waveform.

9. The method for intelligent supervision of electric power facilities according to claim 7, characterized in that: The synchronous operation mechanism is respectively connected to the multiple volume measurement units of the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism to perform synchronous operations between the primary enhancement device, the secondary enhancement device, the final enhancement device and the identification recognition mechanism, including: using an insulating soft ladder SIC chip to realize the synchronous operation mechanism.