CN117560303A - Power information transmission network fault detection method based on transmission energy consumption - Google Patents
Power information transmission network fault detection method based on transmission energy consumption Download PDFInfo
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- CN117560303A CN117560303A CN202311505267.1A CN202311505267A CN117560303A CN 117560303 A CN117560303 A CN 117560303A CN 202311505267 A CN202311505267 A CN 202311505267A CN 117560303 A CN117560303 A CN 117560303A
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- 230000005540 biological transmission Effects 0.000 title claims abstract description 132
- 238000005265 energy consumption Methods 0.000 title claims abstract description 42
- 238000001514 detection method Methods 0.000 title claims abstract description 15
- 230000008054 signal transmission Effects 0.000 claims abstract description 37
- 230000007774 longterm Effects 0.000 claims abstract description 24
- 230000002159 abnormal effect Effects 0.000 claims description 36
- 238000000034 method Methods 0.000 claims description 23
- 230000005856 abnormality Effects 0.000 abstract description 7
- 230000002688 persistence Effects 0.000 abstract description 4
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0876—Network utilisation, e.g. volume of load or congestion level
- H04L43/0888—Throughput
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/16—Threshold monitoring
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Environmental & Geological Engineering (AREA)
- Computing Systems (AREA)
- Small-Scale Networks (AREA)
Abstract
The invention provides a power information transmission network fault detection method based on transmission energy consumption, which comprises the following steps: (1): acquiring the data volume acquired by each node at the time t; (2): acquiring the transmission power level of each node according to the Internet of things; (3): calculating signal transmission power of each node; (4): judging whether abnormality exists according to the signal transmission power; (5): calculating the information throughput of each node at the time t; (6): judging whether an abnormality exists according to the information throughput; (7): calculating signal backlog of each node; (8): judging whether an abnormality exists according to the signal backlog; (9): calculating long-term transmission energy consumption of each node; (10): judging whether abnormality exists or not according to the long-term transmission energy consumption. The invention provides a power information transmission network fault detection method based on transmission energy consumption, which can timely discover the abnormality of an information transmission network and ensure timeliness, reliability and persistence of information transmission.
Description
Technical Field
The invention belongs to the technical field of power detection, and particularly relates to a power information transmission network fault detection method based on transmission energy consumption.
Background
Along with the continuous development of communication technology, information transmission of a power system is more and more timely and accurate, and along with the development of the Internet of things, power information transmission and analysis become more and more convenient, and power equipment, power working states and even power behaviors in various environments can be mastered timely and effectively. In order to ensure the accuracy and reliability of information transmission, entry detection of the information transmission network is also required, so that the problem of information transmission caused by faults of the information transmission network is prevented. The accuracy and reliability of the information transmission network is an important guarantee that everything depends on it.
The invention provides a power information transmission network fault detection method based on transmission energy consumption, which is characterized in that whether the power information transmission network node is abnormal is respectively judged according to signal transmission power, information throughput and signal backlog conditions of each node, then the long-term transmission energy consumption of each node is calculated, the power information transmission network is further judged according to the long-term condition, and further timeliness, reliability and persistence of information transmission are ensured.
Disclosure of Invention
The invention provides a power information transmission network fault detection method based on transmission energy consumption, which can timely find out the abnormality of an information transmission network and ensure timeliness, reliability and persistence of information transmission.
The invention particularly relates to a power information transmission network fault detection method based on transmission energy consumption, which comprises the following steps:
step (1): acquiring the data volume acquired by each node at the time t;
step (2): acquiring the transmission power level of each node according to the Internet of things;
step (3): calculating signal transmission power of each node;
step (4): judging whether the electric power information transmission network is abnormal or not according to the signal transmission power;
step (5): calculating the information throughput of each node at the time t;
step (6): judging whether the power information transmission network is abnormal or not according to the information throughput;
step (7): calculating signal backlog of each node;
step (8): judging whether the electric power information transmission network is abnormal or not according to the signal backlog;
step (9): calculating long-term transmission energy consumption of each node;
step (10): and judging whether the power information transmission network is abnormal or not according to the long-term transmission energy consumption.
The specific method for acquiring the transmission power level of each node according to the Internet of things comprises the following steps:
and dividing the transmission power of each node into I grades, transmitting the transmission power grade signals of each node to the Internet of things, and storing the transmission power grade signals in the electronic tags corresponding to each node.
The specific algorithm for calculating the signal transmission power of each node is as follows:
wherein P is k，min Minimum signal transmission power, P k，max Signal transmission power maximum.
The specific method for judging whether the electric power information transmission network is abnormal according to the signal transmission power comprises the following steps:
and judging whether the signal transmission power of each node is larger than a signal transmission power reference value, and if so, judging that the signal transmission of the power information transmission network is abnormal.
The algorithm for calculating the information throughput of each node at the time t is as follows:
wherein B is k For signal transmission broadband between node k and base station, P k (t) is the signal transmission power of node k, h k (t) is the channel increase between node k and base stationBenefit, e k (t) is electromagnetic interference between node k and base station, Q k (t) is the signal backlog of node k, A k And (t) is the data quantity acquired by the node k at the time t.
The specific method for judging whether the power information transmission network is abnormal according to the information throughput comprises the following steps:
and judging whether the information throughput of each node is larger than an information throughput reference value, and if so, judging that the power information transmission network is abnormal.
The algorithm for calculating the signal backlog of each node is as follows:
Q k (t+1)＝max{Q k (t)-U k (t)+A k (t),0}。
the specific method for judging whether the electric power information transmission network is abnormal according to the signal backlog comprises the following steps:
and judging whether the signal backlog is larger than a signal backlog reference value, and if so, judging that the electric power information transmission network is abnormal.
The specific algorithm for calculating the long-term transmission energy consumption of each node is as follows:
wherein->And unloading decision variables for the tasks of the node k at the time t, wherein L is the decision unloading times of the tasks.
The specific method for judging whether the power information transmission network is abnormal according to the long-term transmission energy consumption comprises the following steps:
and judging whether the long-term transmission energy consumption is larger than a long-term transmission energy consumption reference value, and if so, judging that the power information transmission network is abnormal.
Compared with the prior art, the beneficial effects are that: the power information transmission network fault detection method is mainly used for judging whether the power information transmission network nodes are abnormal according to the signal transmission power, the information throughput and the signal backlog conditions of all the nodes, calculating the long-term transmission energy consumption of all the nodes, further judging the power information transmission network from the long-term condition, and further guaranteeing the timeliness, the reliability and the persistence of information transmission.
Drawings
Fig. 1 is a flowchart of a power information transmission network fault detection method based on transmission energy consumption according to the present invention.
Detailed Description
The following describes a specific embodiment of a power information transmission network fault detection method based on transmission energy consumption in detail with reference to the accompanying drawings.
As shown in fig. 1, the power information transmission network fault detection method of the present invention includes the steps of:
step (1): acquiring the data volume acquired by each node at the time t;
step (2): acquiring the transmission power level of each node according to the Internet of things;
step (3): calculating signal transmission power of each node;
step (4): judging whether the electric power information transmission network is abnormal or not according to the signal transmission power;
step (5): calculating the information throughput of each node at the time t;
step (6): judging whether the power information transmission network is abnormal or not according to the information throughput;
step (7): calculating signal backlog of each node;
step (8): judging whether the electric power information transmission network is abnormal or not according to the signal backlog;
step (9): calculating long-term transmission energy consumption of each node;
step (10): and judging whether the power information transmission network is abnormal or not according to the long-term transmission energy consumption.
The specific method for acquiring the transmission power level of each node according to the Internet of things comprises the following steps:
and dividing the transmission power of each node into I grades, transmitting the transmission power grade signals of each node to the Internet of things, and storing the transmission power grade signals in the electronic tags corresponding to each node.
The specific algorithm for calculating the signal transmission power of each node is as follows:
wherein P is k，min Minimum signal transmission power, P k，max Signal transmission power maximum.
The specific method for judging whether the electric power information transmission network is abnormal according to the signal transmission power comprises the following steps:
and judging whether the signal transmission power of each node is larger than a signal transmission power reference value, and if so, judging that the signal transmission of the power information transmission network is abnormal.
The algorithm for calculating the information throughput of each node at the time t is as follows:
wherein B is k For signal transmission broadband between node k and base station, P k (t) is the signal transmission power of node k, h k (t) is the channel gain between node k and base station, e k (t) is electromagnetic interference between node k and base station, Q k (t) is the signal backlog of node k, A k And (t) is the data quantity acquired by the node k at the time t.
The specific method for judging whether the power information transmission network is abnormal according to the information throughput comprises the following steps:
and judging whether the information throughput of each node is larger than an information throughput reference value, if so, judging that the signal throughput of the power information transmission network node is large and abnormal exists.
The algorithm for calculating the signal backlog of each node is as follows:
Q k (t+1)＝max{Q k (t)-U k (t)+A k (t),0}。
the specific method for judging whether the electric power information transmission network is abnormal according to the signal backlog comprises the following steps:
and judging whether the signal backlog is larger than a signal backlog reference value, if so, the signal backlog of the power information transmission network node is excessive and has abnormality.
The specific algorithm for calculating the long-term transmission energy consumption of each node is as follows:wherein->Task unloading decision variables of the node k at the time t, and L is task unloading decision times;
if node k unloads information at time t, thenOtherwise, go (L)>
The specific method for judging whether the power information transmission network is abnormal according to the long-term transmission energy consumption comprises the following steps: and judging whether the long-term transmission energy consumption is larger than a long-term transmission energy consumption reference value, and if so, judging that the power information transmission network is abnormal.
Finally, it should be noted that the above-mentioned embodiments are merely illustrative of the technical solution of the invention and not limiting thereof. It will be understood by those skilled in the art that modifications and equivalents may be made to the particular embodiments of the invention, which are within the scope of the claims appended hereto.
Claims (10)
1. The power information transmission network fault detection method based on transmission energy consumption is characterized by comprising the following steps of:
step (1): acquiring the data volume acquired by each node at the time t;
step (2): acquiring the transmission power level of each node according to the Internet of things;
step (3): calculating signal transmission power of each node;
step (4): judging whether the electric power information transmission network is abnormal or not according to the signal transmission power;
step (5): calculating the information throughput of each node at the time t;
step (6): judging whether the power information transmission network is abnormal or not according to the information throughput;
step (7): calculating signal backlog of each node;
step (8): judging whether the electric power information transmission network is abnormal or not according to the signal backlog;
step (9): calculating long-term transmission energy consumption of each node;
step (10): and judging whether the power information transmission network is abnormal or not according to the long-term transmission energy consumption.
2. The method for detecting the fault of the power information transmission network based on the transmission energy consumption according to claim 1, wherein the specific method for obtaining the transmission power level of each node according to the internet of things is as follows: and dividing the transmission power of each node into I grades, transmitting the transmission power grade signals of each node to the Internet of things, and storing the transmission power grade signals in the electronic tags corresponding to each node.
3. The method for detecting a fault in an electric power information transmission network based on transmission energy consumption according to claim 2, wherein the specific algorithm for calculating the signal transmission power of each node is as follows:
wherein P is k，min Minimum signal transmission power, P k，max Signal transmission power maximum.
4. The method for detecting a fault in a power information transmission network based on transmission energy consumption according to claim 3, wherein the specific method for judging whether the power information transmission network is abnormal according to the signal transmission power is as follows: and judging whether the signal transmission power of each node is larger than a signal transmission power reference value, and if so, judging that the signal transmission of the power information transmission network is abnormal.
5. The method for detecting a failure of an electric power information transmission network based on transmission energy consumption according to claim 4, wherein the algorithm for calculating the information throughput of each node at time t is:
wherein B is k For signal transmission broadband between node k and base station, P k (t) is the signal transmission power of node k, h k (t) is the channel gain between node k and base station, e k (t) is electromagnetic interference between node k and base station, Q k (t) is the signal backlog of node k, A k And (t) is the data quantity acquired by the node k at the time t.
6. The method for detecting a fault in a power information transmission network based on transmission energy consumption according to claim 5, wherein the specific method for judging whether the power information transmission network is abnormal according to the information throughput is as follows: and judging whether the information throughput of each node is larger than an information throughput reference value, and if so, judging that the power information transmission network is abnormal.
7. The method for detecting a failure of an electric power information transmission network based on transmission energy consumption according to claim 6, wherein the algorithm for calculating the signal backlog of each node is as follows: q (Q) k (t+1)＝max{Q k (t)-U k (t)+A k (t),0}。
8. The method for detecting a fault in an electrical power information transmission network based on transmission energy consumption according to claim 7, wherein it is determined whether the signal backlog is greater than a signal backlog reference value, and if so, the electrical power information transmission network is abnormal.
9. The method for detecting a fault in an electrical power information transmission network based on transmission energy consumption according to claim 8, wherein the specific algorithm for calculating the long-term transmission energy consumption of each node is as follows:wherein->And unloading decision variables for the tasks of the node k at the time t, wherein L is the decision unloading times of the tasks.
10. The method for detecting a fault in an electrical power information transmission network based on transmission energy consumption according to claim 9, wherein the specific method for judging whether the electrical power information transmission network is abnormal according to the long-term transmission energy consumption is as follows: and judging whether the long-term transmission energy consumption is larger than a long-term transmission energy consumption reference value, and if so, judging that the power information transmission network is abnormal.
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| CN202311505267.1A CN117560303A (en) | 2023-11-13 | 2023-11-13 | Power information transmission network fault detection method based on transmission energy consumption |
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