CN117857261B - Industrial intelligent gateway based on edge calculation - Google Patents
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Abstract
The invention relates to the technical field of intelligent gateways, and particularly discloses an industrial intelligent gateway based on edge calculation, which comprises: the acquisition target management module: acquiring each target object needing to acquire data and acquiring nodes; node classification management module: dividing the acquisition nodes into a plurality of major classes according to the target objects corresponding to the acquisition nodes; dividing the collection nodes in the same major class into a plurality of minor classes; and a data recording module: generating a change curve f (t) of data with time; acquiring a monitoring point; and a fault identification module: judging whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t); and judging whether the fluctuation quantity of the monitoring point meets the requirement. According to the invention, the possibility of faults of the acquisition nodes is judged at multiple angles in an edge computing mode, and the response speed of the system to the faults can be effectively improved.
Description
Technical Field
The invention relates to the technical field of intelligent gateways, in particular to an industrial intelligent gateway based on edge calculation.
Background
The industrial intelligent gateway is an internet of things wireless sensor network product, and is also called an industrial internet of things intelligent gateway, a wireless data acquisition gateway, a communication acquisition gateway, a PLC wireless gateway, an industrial communication gateway and the like. It is a device for transmitting industrial device data to a cloud platform or local server. The industrial intelligent gateway can realize data collection in various modes, such as serial ports, ethernet, wireless networks and the like.
Edge computing refers to providing near-end services by adopting an open platform with integrated network, computing, storage and application core capabilities on the side close to the object or data source. The application program is initiated at the edge side, and faster network service response is generated, so that the basic requirements of the industry in the aspects of real-time service, application intelligence, security, privacy protection and the like are met. Edge computation is between a physical entity and an industrial connection, or at the top of a physical entity. The cloud computing can still access the historical data of the edge computing.
Different acquisition nodes may have different transmission protocols, such as temperature and pressure. The gateway acts as a converter to convert the information from the different protocols into a unified standard format to enable communication between devices. In a specific use process, the problems of ageing, damage and the like of the acquisition node can occur, so that the acquired data is inaccurate or has larger error; in this case, if the resolution is performed by cloud computing, there is a certain delay, and the response speed is slow.
Disclosure of Invention
The invention aims to provide an industrial intelligent gateway based on edge calculation, which solves the technical problems.
The aim of the invention can be achieved by the following technical scheme:
An industrial intelligent gateway based on edge computing, comprising:
the acquisition target management module: acquiring target objects needing to acquire data and acquisition nodes used for executing acquisition tasks;
Node classification management module: dividing the acquisition nodes into a plurality of major classes according to the target objects corresponding to the acquisition nodes; dividing the acquisition nodes in the same major class into a plurality of minor classes according to the data types acquired by the acquisition nodes;
and a data recording module: acquiring data from an acquisition node, and generating a change curve f (t) of the data along with time; setting a judging condition when the data is abnormal, and taking a coordinate point meeting the judging condition as a monitoring point;
And a fault identification module: when the monitoring point is extracted, defining an acquisition node corresponding to the monitoring point as a node to be identified, and acquiring a change curve f n (t) of other acquisition nodes in the same subclass as the node to be identified, wherein n represents the number of the acquisition node, and n is a positive integer;
judging whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t); and judging whether the fluctuation quantity of the monitoring point meets the requirement on the premise that the data fluctuation trend meets the requirement.
As a further scheme of the invention: in the data recording module, the specific steps of extracting the monitoring points from the change curve f (t) are as follows;
setting a judging condition when the data is abnormal, wherein the monitoring points meet the following constraint:
|f（t1）-f（t2）|≥ΔS；
t1＞t2；
t1-t2≤Δt；
Wherein t1 represents the abscissa of the monitoring point, Δs represents a preset detection fluctuation value, Δt represents a preset monitoring period, and t2 represents the abscissa of the reference point corresponding to the monitoring point.
As a further scheme of the invention: in the fault recognition module, the specific steps of judging whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t) are as follows:
Intercepting an image of a change curve f n (t) in a section (t 1-delta t, t 1), judging the change trend of the image, and assigning a value of 1 when the image is in an ascending trend; when the image is in a descending trend, assigning a value of-1; when the image has no rising or falling trend, the value is set to 0; calculating the overall change coefficient ; Wherein K n represents the assignment of the nth acquisition node, and N represents the total number of the acquisition nodes;
comparing (f (t 1) -f (t 2)) with the integral change coefficient K', and judging whether the numerical signs of the two are the same; if the signs are the same, judging that the fluctuation trend of the acquisition node corresponding to the monitoring point meets the requirement; if the signs are different, judging that the acquisition nodes corresponding to the monitoring points have faults, and arranging the workers to go to overhaul.
As a further scheme of the invention: the specific steps for judging the change trend of the image of the change curve f n (t) in the section (t 1- Δt, t 1) are as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-delta t, t 1), and intercepting a plurality of coordinate points from the image at preset abscissa intervals, wherein the coordinate points comprise (t 1, f n (t 1));
Calculating a vertical coordinate difference value delta D m=Dm+1-Dm of adjacent coordinate points, wherein D m represents the vertical coordinate of the mth coordinate point along the horizontal axis direction;
If all the longitudinal coordinate differences meet the delta D m & gt 0, the corresponding change curve images are in an ascending trend;
If all the longitudinal coordinate differences meet the delta D m < 0, the corresponding change curve images show a descending trend;
if the difference of the vertical coordinates does not meet the conditions, the corresponding change curve image has no rising or falling trend.
As a further scheme of the invention: in the fault recognition module, when the integral change coefficient K' does not meet the following constraint conditions, the fluctuation trend of the monitoring point is judged to be in accordance with the requirement, the fluctuation amount of the monitoring point is detected, and the constraint conditions are as follows: and I, K' is less than or equal to lambda, max (n), wherein lambda represents a preset proportionality coefficient, and max (n) represents the total number of other acquisition nodes in the same subclass as the node to be identified.
As a further scheme of the invention: in the fault identification module, on the premise that the data fluctuation trend meets the requirement, the specific steps of judging whether the fluctuation quantity of the monitoring point meets the requirement are as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-deltat, t 1);
Calculating a fluctuation value delta S n=fn（t1）-fn (t 1 '), t1' epsilon (t 1-delta t, t 1);
Calculating the maximum fluctuation quantity max (delta S) of a change curve f (t) corresponding to the monitoring point;
When the maximum fluctuation amount max (Δs) > 0, the fluctuation value with the largest value is obtained as the maximum fluctuation amount max (Δs n) of the change curve f n (t), and it is judged whether the following constraint condition is satisfied:
max（ΔSn）≥max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
As a further scheme of the invention: when the maximum fluctuation amount max (Δs) < 0, the fluctuation value with the largest absolute value is obtained as the maximum fluctuation amount max (Δs n) of the change curve f n (t), and it is judged whether the following constraint condition is satisfied:
max（ΔSn）≤max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
As a further scheme of the invention: the data types include temperature, pressure, load bearing, vibration, displacement and humidity.
The invention has the beneficial effects that: for a given target, if the related data is to be acquired, a plurality of acquisition nodes are set on the target, and most of the acquisition nodes are common sensors or other devices with the same or similar devices, and the acquisition nodes can acquire the required data, such as temperature, humidity or pressure; in the scheme of the invention, different acquisition nodes are classified according to the related information, so that the subsequent data processing is convenient;
In the specific technical scheme of the invention, the acquisition nodes which are possibly faulty are detected mainly from a triggering standard and two detection conditions; one of the triggering criteria refers to whether the data acquired by the acquisition node has larger fluctuation range in a limited time period, and it can be understood that in most of the practical scenes of linear change, the stepwise or cliff type ascending or descending is not in accordance with the practical situation; in a stable operation scene, the fluctuation of the data of the device is also in a stable section, so that the device sets a trigger standard based on the two conditions;
After triggering is completed, aiming at monitoring points with possible faults, screening the monitoring points according to the fluctuation trend and the fluctuation amount; for the collection nodes of the same subclass, the fluctuation trend of the monitoring points is consistent with the overall rising or falling trend; therefore, if the overall change trend is violated, the possibility of faults of the acquisition nodes is higher; in the case of conforming to the overall variation trend, it should be considered whether the magnitude of the fluctuation amount in the trend satisfies the same type of maximum variation; therefore, in summary, the possibility of the failure of the acquisition node is determined at multiple angles by the edge calculation mode, so that the response speed of the system to the failure can be effectively improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow operation diagram of an industrial intelligent gateway based on edge computing according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention is an industrial intelligent gateway based on edge computing, including:
the acquisition target management module: acquiring target objects needing to acquire data and acquisition nodes used for executing acquisition tasks;
Node classification management module: dividing the acquisition nodes into a plurality of major classes according to the target objects corresponding to the acquisition nodes; dividing the acquisition nodes in the same major class into a plurality of minor classes according to the data types acquired by the acquisition nodes;
and a data recording module: acquiring data from an acquisition node, and generating a change curve f (t) of the data along with time; setting a judging condition when the data is abnormal, and taking a coordinate point meeting the judging condition as a monitoring point;
And a fault identification module: when the monitoring point is extracted, defining an acquisition node corresponding to the monitoring point as a node to be identified, and acquiring a change curve f n (t) of other acquisition nodes in the same subclass as the node to be identified, wherein n represents the number of the acquisition node, and n is a positive integer;
judging whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t); and judging whether the fluctuation quantity of the monitoring point meets the requirement on the premise that the data fluctuation trend meets the requirement.
It will be appreciated that for a given target, if it is desired to obtain data related to the target, a plurality of acquisition nodes are set on the target, and most of the acquisition nodes are common sensors or other devices with the same or similar devices, and the acquisition nodes can acquire the desired data, such as temperature, humidity or pressure; in the scheme of the invention, different acquisition nodes are classified according to the related information, so that the subsequent data processing is convenient;
As one skilled in the art will readily appreciate, edge computation is faster than cloud computation because it is closer to the side of the object or data source; when the collected data and the actual result have larger errors due to the faults of the collection nodes, the method of edge calculation is adopted instead to be faster;
In the specific technical scheme of the invention, the acquisition nodes which are possibly faulty are detected mainly from a triggering standard and two detection conditions; one of the triggering criteria refers to whether the data acquired by the acquisition node has larger fluctuation range in a limited time period, and it can be understood that in most of the practical scenes of linear change, the stepwise or cliff type ascending or descending is not in accordance with the practical situation; in a stable operation scene, the fluctuation of the data of the device is also in a stable section, so that the device sets a trigger standard based on the two conditions;
After triggering is completed, aiming at monitoring points with possible faults, screening the monitoring points according to the fluctuation trend and the fluctuation amount; for the collection nodes of the same subclass, the fluctuation trend of the monitoring points is consistent with the overall rising or falling trend; therefore, if the overall change trend is violated, the possibility of faults of the acquisition nodes is higher; in the case of conforming to the overall variation trend, it should be considered whether the magnitude of the fluctuation amount in the trend satisfies the same type of maximum variation; therefore, in summary, the possibility of the failure of the acquisition node is determined at multiple angles by the edge calculation mode, so that the response speed of the system to the failure can be effectively improved.
In a preferred embodiment of the present invention, in the data recording module, the specific steps of extracting the monitoring points from the change curve f (t) are as follows;
setting a judging condition when the data is abnormal, wherein the monitoring points meet the following constraint:
|f（t1）-f（t2）|≥ΔS；
t1＞t2；
t1-t2≤Δt；
Wherein t1 represents the abscissa of the monitoring point, Δs represents a preset detection fluctuation value, Δt represents a preset monitoring period, and t2 represents the abscissa of the reference point corresponding to the monitoring point.
In a preferred embodiment of the present invention, in the fault identification module, the specific steps for determining whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t) are as follows:
Intercepting an image of a change curve f n (t) in a section (t 1-delta t, t 1), judging the change trend of the image, and assigning a value of 1 when the image is in an ascending trend; when the image is in a descending trend, assigning a value of-1; when the image has no rising or falling trend, the value is set to 0; calculating the overall change coefficient ; Wherein K n represents the assignment of the nth acquisition node, and N represents the total number of the acquisition nodes;
comparing (f (t 1) -f (t 2)) with the integral change coefficient K', and judging whether the numerical signs of the two are the same; if the signs are the same, judging that the fluctuation trend of the acquisition node corresponding to the monitoring point meets the requirement; if the signs are different, judging that the acquisition nodes corresponding to the monitoring points have faults, and arranging the workers to go to overhaul.
In a preferred embodiment of the present invention, the specific steps for determining the trend of the image of the change curve f n (t) within the interval (t 1- Δt, t 1) are as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-delta t, t 1), and intercepting a plurality of coordinate points from the image at preset abscissa intervals, wherein the coordinate points comprise (t 1, f n (t 1));
Calculating a vertical coordinate difference value delta D m=Dm+1-Dm of adjacent coordinate points, wherein D m represents the vertical coordinate of the mth coordinate point along the horizontal axis direction;
If all the longitudinal coordinate differences meet the delta D m & gt 0, the corresponding change curve images are in an ascending trend;
If all the longitudinal coordinate differences meet the delta D m < 0, the corresponding change curve images show a descending trend;
if the difference of the vertical coordinates does not meet the conditions, the corresponding change curve image has no rising or falling trend.
In a preferred embodiment of the present invention, in the fault recognition module, when the overall change coefficient K' does not meet the following constraint conditions, it is determined that the fluctuation trend of the monitoring point meets the requirement, and the fluctuation amount of the monitoring point is detected, where the constraint conditions are as follows: and I, K' is less than or equal to lambda, max (n), wherein lambda represents a preset proportionality coefficient, and max (n) represents the total number of other acquisition nodes in the same subclass as the node to be identified.
In a preferred embodiment of the present invention, in the fault identification module, on the premise that the trend of data fluctuation meets the requirement, the specific steps for determining whether the fluctuation amount of the monitoring point meets the requirement are as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-deltat, t 1);
Calculating a fluctuation value delta S n=fn（t1）-fn (t 1 '), t1' epsilon (t 1-delta t, t 1);
Calculating the maximum fluctuation quantity max (delta S) of a change curve f (t) corresponding to the monitoring point;
When the maximum fluctuation amount max (Δs) > 0, the fluctuation value with the largest value is obtained as the maximum fluctuation amount max (Δs n) of the change curve f n (t), and it is judged whether the following constraint condition is satisfied:
max（ΔSn）≥max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
In a preferred embodiment of the present invention, when the maximum fluctuation amount max (Δs) < 0, the fluctuation value with the largest absolute value is obtained as the maximum fluctuation amount max (Δs n) of the change curve f n (t), and it is determined whether the following constraint condition is satisfied:
max（ΔSn）≤max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
In a preferred embodiment of the invention, the data types include temperature, pressure, load bearing, vibration, displacement and humidity.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. An industrial intelligent gateway based on edge computing, comprising:
the acquisition target management module: acquiring target objects needing to acquire data and acquisition nodes used for executing acquisition tasks;
Node classification management module: dividing the acquisition nodes into a plurality of major classes according to the target objects corresponding to the acquisition nodes; dividing the acquisition nodes in the same major class into a plurality of minor classes according to the data types acquired by the acquisition nodes;
and a data recording module: acquiring data from an acquisition node, and generating a change curve f (t) of the data along with time; setting a judging condition when the data is abnormal, and taking a coordinate point meeting the judging condition as a monitoring point;
And a fault identification module: when the monitoring points are extracted, defining the acquisition nodes corresponding to the monitoring points as nodes to be identified, and acquiring a change curve f n (t) of other acquisition nodes in the same subclass as the nodes to be identified, wherein n represents the numbers of the acquisition nodes, and n is a positive integer;
judging whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t); and judging whether the fluctuation quantity of the monitoring point meets the requirement on the premise that the data fluctuation trend meets the requirement.
2. The industrial intelligent gateway based on edge calculation according to claim 1, wherein the specific steps of extracting the monitoring points from the change curve f (t) in the data recording module are as follows;
setting a judging condition when the data is abnormal, wherein the monitoring points meet the following constraint:
|f（t1）-f（t2）|≥ΔS；
t1＞t2；
t1-t2≤Δt；
Wherein t1 represents the abscissa of the monitoring point, Δs represents a preset detection fluctuation value, Δt represents a preset monitoring period, and t2 represents the abscissa of the reference point corresponding to the monitoring point.
3. The industrial intelligent gateway based on edge calculation according to claim 2, wherein in the fault identification module, the specific step of determining whether the data fluctuation of the monitoring point meets the requirement according to the fluctuation trend of the change curve f n (t) is as follows:
Intercepting an image of a change curve f n (t) in a section (t 1-delta t, t 1), judging the change trend of the image, and assigning a value of 1 when the image is in an ascending trend; when the image is in a descending trend, assigning a value of-1; when the image has no rising or falling trend, the value is set to 0; calculating the overall change coefficient ; Wherein K n represents the assignment of the nth acquisition node, and N represents the total number of the acquisition nodes;
comparing (f (t 1) -f (t 2)) with the integral change coefficient K', and judging whether the numerical signs of the two are the same; if the signs are the same, judging that the fluctuation trend of the acquisition node corresponding to the monitoring point meets the requirement; if the signs are different, judging that the acquisition nodes corresponding to the monitoring points have faults, and arranging the workers to go to overhaul.
4. An industrial intelligent gateway based on edge calculation according to claim 3, wherein the specific steps of determining the trend of the image of the change curve f n (t) in the interval (t 1- Δt, t 1) are as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-delta t, t 1), and intercepting a plurality of coordinate points from the image at preset abscissa intervals, wherein the coordinate points comprise (t 1, f n (t 1));
Calculating a vertical coordinate difference value delta D m=Dm+1-Dm of adjacent coordinate points, wherein D m represents the vertical coordinate of the mth coordinate point along the horizontal axis direction;
If all the longitudinal coordinate differences meet the delta D m & gt 0, the corresponding change curve images are in an ascending trend;
If all the longitudinal coordinate differences meet the delta D m < 0, the corresponding change curve images show a descending trend;
if the difference of the vertical coordinates does not meet the conditions, the corresponding change curve image has no rising or falling trend.
5. The industrial intelligent gateway based on edge computing according to claim 3, wherein in the fault identification module, when the overall change coefficient K' does not meet the following constraint conditions, it is determined that the fluctuation trend of the monitoring point meets the requirement, and the fluctuation amount of the monitoring point is detected, where the constraint conditions are that: and I, K' is less than or equal to lambda, max (n), wherein lambda represents a preset proportionality coefficient, and max (n) represents the total number of other acquisition nodes in the same subclass as the node to be identified.
6. The industrial intelligent gateway based on edge calculation according to claim 2, wherein in the fault identification module, on the premise that the trend of data fluctuation meets the requirement, the specific step of judging whether the fluctuation amount of the monitoring point meets the requirement is as follows:
Acquiring an image of a change curve f n (t) in a section (t 1-deltat, t 1);
Calculating a fluctuation value delta S n=fn（t1）-fn (t 1 '), t1' epsilon (t 1-delta t, t 1);
Calculating the maximum fluctuation quantity max (delta S) of a change curve f (t) corresponding to the monitoring point;
When the maximum fluctuation amount max (Δs) > 0, the fluctuation value with the largest value is obtained as the maximum fluctuation amount max (Δs n) of the change curve f n (t), and it is judged whether the following constraint condition is satisfied:
max（ΔSn）≥max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
7. The edge-based industrial intelligent gateway according to claim 6, wherein when the maximum fluctuation amount max (Δs) < 0, the maximum fluctuation amount max (Δs n) of the absolute value maximum is obtained as the maximum fluctuation amount of the change curve f n (t), and it is determined whether the following constraint condition is satisfied:
max（ΔSn）≤max（ΔS）；
When the maximum fluctuation amount max (delta S) meets constraint conditions, the fluctuation amount of the monitoring point meets the requirements; when the maximum fluctuation amount max (delta S) does not meet the constraint condition, the fluctuation amount of the monitoring point does not meet the requirement.
8. The edge-based industrial intelligent gateway of claim 1, wherein the data types include temperature, pressure, load-bearing, vibration, displacement, and humidity.
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