CN111882170A - Multi-sensor fusion power system internet-of-things monitoring method and system - Google Patents
Multi-sensor fusion power system internet-of-things monitoring method and system Download PDFInfo
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Abstract
The invention provides a multi-sensor fusion power system internet of things monitoring method and system, which are applied to monitoring nodes and comprise the steps of obtaining a node control strategy from a monitoring master control platform; controlling a sensor monitoring network according to a first characteristic data acquisition sub-strategy and a second characteristic data acquisition sub-strategy of the node control strategy; controlling a sensor monitoring network according to an aerial photographing strategy of the node control strategy; acquiring data from a sensor monitoring network, and obtaining a first characteristic set and a second characteristic set according to the data; acquiring image data from an unmanned aerial vehicle aerial photographing module, and obtaining an antenna attitude according to the image data; and controlling uploading of the first feature set, the second feature set and the antenna attitude. The invention gives consideration to the monitoring safety of the power system and the flight safety of the unmanned aerial vehicle aerial photography module.
Description
Technical Field
The invention relates to the field of Internet of things, in particular to a multi-sensor fusion power system Internet of things monitoring method and system.
Background
With the comprehensive coverage of the mobile network, the inspection task and the maintenance task of the power system are heavy day by day, and currently, manual climbing operation is mainly adopted to inspect and maintain the power system. Obviously, there is a safety risk in the need of manual climbing for high-altitude operation, and manual inspection and maintenance are subject to the manual management strategy and the quality of personnel, the inspection quality is unstable, and the cost is very high.
Disclosure of Invention
In order to solve the technical problems, the invention provides a multi-sensor fusion power system internet of things monitoring method and system. The invention is realized by the following technical scheme:
the utility model provides a multisensor amalgamated electric power system thing allies oneself with monitoring method, is applied to monitoring node, includes:
acquiring a node control strategy from a monitoring master control platform;
controlling a sensor monitoring network according to a first characteristic data acquisition sub-strategy and a second characteristic data acquisition sub-strategy of the node control strategy;
controlling a sensor monitoring network according to an aerial photographing strategy of the node control strategy;
acquiring data from a sensor monitoring network, and obtaining a first characteristic set and a second characteristic set according to the data;
acquiring image data from an unmanned aerial vehicle aerial photographing module, and obtaining an antenna attitude according to the image data;
if the first characteristic set and the second characteristic set meet a first reporting strategy of a node control strategy, uploading the first characteristic set and the second characteristic set according to the first reporting strategy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
The present disclosure also provides a multisensor-fused power system internet of things monitoring system, including:
the system comprises a monitoring general control platform and a plurality of monitoring nodes, wherein each monitoring node is communicated with the monitoring general control platform, the monitoring nodes and the power systems are in one-to-one correspondence, and one monitoring node corresponds to one power system;
the monitoring node comprises:
the node control strategy acquisition module is used for acquiring a node control strategy from the monitoring master control platform;
the first control module is used for controlling the sensor monitoring network according to a first characteristic data acquisition sub-strategy and a second characteristic data acquisition sub-strategy of the node control strategy;
the second control module is used for controlling the sensor monitoring network according to the aerial photographing strategy of the node control strategy;
the first data processing module is used for acquiring data from a sensor monitoring network and obtaining a first characteristic set and a second characteristic set according to the data;
the second data processing module is used for acquiring image data from the unmanned aerial vehicle aerial photography module and obtaining the antenna attitude according to the image data;
the reporting control module is used for uploading the first characteristic set and the second characteristic set according to a first reporting strategy if the first characteristic set and the second characteristic set meet the first reporting strategy of the node control strategy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
The present disclosure also provides a computer-readable storage medium, where at least one instruction or at least one program is stored, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the method for monitoring the power system with multiple sensor fusion in an internet of things.
The embodiment of the invention provides a multi-sensor-fused power system internet of things monitoring method and system, which can give consideration to the monitoring safety of a power system and the flight safety of an unmanned aerial vehicle aerial photography module, so that a monitoring node can be fully suitable for controlling the operation of a sensor monitoring network, the unmanned aerial vehicle aerial photography module and a monitoring communication module with different and reasonable climates.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic diagram of a multi-sensor integrated power system internet of things monitoring system provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of a monitoring node according to an embodiment of the present invention;
FIG. 3 is a flowchart of steps executed by the monitoring master control platform according to the embodiment of the present invention;
FIG. 4 is a schematic illustration of a first control strategy and a second control strategy provided by an embodiment of the present invention;
fig. 5 is a flowchart illustrating steps performed by a monitoring node according to an embodiment of the present invention;
fig. 6 is a flowchart for obtaining a first feature set and a second feature set according to the data according to an embodiment of the present invention.
FIG. 7 is a flow chart of obtaining an antenna pose from the image data according to an embodiment of the present invention;
FIG. 8 is a flowchart of a method for querying a first feature set according to an embodiment of the present invention;
FIG. 9 is a flow chart illustrating querying data that is capable of manipulating the baseline composite data to obtain a result subset corresponding to the subset according to an embodiment of the present invention;
fig. 10 is a block diagram of a monitoring node according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to reduce the proportion of manpower in the monitoring and routing inspection of the power system, improve the automation level of the monitoring of the power system and enable the monitoring of the power system to be adaptively adjusted according to the environment where the power system is located, the embodiment of the invention discloses a multi-sensor fusion power system internet of things monitoring method and system.
Specifically, as shown in fig. 1, the system includes a monitoring master control platform 101 and a plurality of monitoring nodes 103, each monitoring node 103 is in communication with the monitoring master control platform 101, the monitoring nodes are in one-to-one correspondence with the power systems, and one monitoring node corresponds to one power system. The power system at least comprises a tower body of the power tower and an antenna arranged on the power tower.
Specifically, as shown in fig. 2, each monitoring node 103 includes:
and the sensor monitoring network 1031 is used for monitoring the parameters to be monitored of the power system.
In one possible embodiment, the sensor monitoring network comprises a tension sensor arranged on an antenna rim string, a lead wire swing monitor arranged on the power transmission line, and a temperature sensor, a humidity sensor, a wind speed sensor and a wind direction sensor arranged on an antenna supporting rod;
correspondingly, the sensor monitoring network is used for obtaining a first characteristic set and a second characteristic set of the antenna, the first characteristic set comprises a stress state after load bearing, the temperature, humidity, wind speed and wind direction of the current environment, and the second characteristic set comprises bending amplitude and frequency of the wire relative to the wire clamp at a certain distance outside the last contact point of the wire and the wire clamp. The first feature set is used for representing the external factor monitoring result of the antenna, and the second feature set is used for representing the internal factor monitoring result of the antenna.
An unmanned aerial vehicle aerial photography module 1033 configured to acquire the image data related to the power system in an aerial photography mode.
And the monitoring communication module 1035 is used for interacting with the monitoring master control platform 101 to obtain a node control strategy and uploading a processing result of data acquired by the sensor monitoring network 1031 and the unmanned aerial vehicle aerial photography module 1033.
And the monitoring control module 1037 is configured to perform data processing on the data acquired by the sensor monitoring network 1031 and the unmanned aerial vehicle aerial image module 1033, and control the sensor monitoring network 1031, the unmanned aerial vehicle aerial image module 1033, and the monitoring communication module 1035 according to a data processing result and the node control policy.
In a possible embodiment, the monitoring overall control platform 101 is configured to generate and issue an adaptive node control policy to each monitoring node, and specifically, as shown in fig. 3, the monitoring overall control platform 101 performs the following steps:
and S101, obtaining a monitoring point map according to the position of each monitoring node.
And S103, extracting historical meteorological data under the condition of rime generation corresponding to the monitoring point map.
And S105, obtaining a target condition data set under the condition of rime production according to the historical meteorological data, wherein the target condition data set comprises an area position, a ground condition, a cloud layer condition and/or a warm layer condition.
Specifically, the area position is an area where the position of the rime occurs; the ground conditions comprise a ground temperature interval; the cloud layer condition comprises a cloud region arrangement structure in the vertical direction; the warm layer condition includes presence or absence of a warm layer and a warm layer position.
In a preferred embodiment, the target condition data set includes a location of the area and at least one element of a ground condition, a cloud condition, and a warm condition. For example, according to the result of analyzing the historical meteorological data, it can be known that:
the area A of the monitoring point map is generally not high in cloud top height, the average height is below 2km, and rime is likely to be generated after precipitation under the condition of a warm layer. The regional position of the target condition data set points to A, the cloud layer condition is that the height of the cloud top is lower than 2km, and the warm layer condition is that a warm layer exists.
In a preferred embodiment, in order to summarize the climate conditions during rime production from historical weather data, the historical weather data may be preprocessed, wherein the historical weather data is a temperature and humidity data sequence with equal altitude difference
The pretreatment comprises:
s1, acquiring historical meteorological data
Filtered data sequence of
Wherein
For filtering data sequences
The value of each of the elements is,
are filter coefficients.
S3, obtaining a spread spectrum data sequence according to the filtering data sequence
Wherein
To spread the data sequence
The value of each of the elements is,
in order to be a spreading factor, the frequency of the spectrum,
is a sensitivity parameter.
S5, smoothing the historical meteorological data according to the spread spectrum data sequence to obtain a target meteorological data sequence
，
Is a smoothing parameter.
Specifically, the filter coefficient, the spreading coefficient, the smoothing parameter, and the sensitivity parameter may be set according to a user requirement, which is not specifically limited in the embodiment of the present invention.
By analyzing the target meteorological data sequence
The cloud layer condition and the warm layer condition can be obtained, and specifically, the embodiment of the invention is not described in detail, and reference can be made to the prior art.
And S107, acquiring condition data of the positions of the monitoring points in the monitoring point map.
Accordingly, the condition data set may also include regional location, ground conditions, cloud conditions, and/or warm conditions.
And S109, classifying the monitoring points, wherein the classification result comprises a first-class monitoring point and a second-class monitoring point, each condition in the condition data of the position of the first-class monitoring point correspondingly meets each condition of at least one element in the target condition data set, and the non-first-class monitoring point is the second-class monitoring point.
And S1011, generating and issuing a first control strategy to the first class of monitoring points, and generating and issuing a second control strategy to the second class of monitoring points.
The embodiment of the invention realizes that the rime can influence the normal operation of the unmanned aerial vehicle aerial photography module 1033, and the monitoring of the electric power system is really important, but the normal operation safety of the unmanned aerial vehicle aerial photography module 1033 also needs to be ensured, so that the embodiment of the invention provides that a proper control strategy is selectively implemented aiming at the probability of rime formation at different monitoring nodes, thereby taking the monitoring safety of the electric power system and the flight safety of the unmanned aerial vehicle aerial photography module into consideration. Obviously, for the area that the probability is great to the rime production, it is unsuitable to frequently use unmanned aerial vehicle module of taking photo by plane. Different from the prior art that the monitoring of the electric power system is carried out by relying on manpower, the embodiment of the invention not only provides the monitoring system for monitoring the electric power system, but also configures a sensor network for the monitoring system and an unmanned aerial vehicle aerial photography module to complement each other so as to improve the monitoring quality. And still further consider the influence of the rime to the unmanned aerial vehicle module of taking photo by plane and issue different control strategies for the monitoring node to different climatic conditions to make the monitoring node can fully adapt to the different reasonable control sensor monitoring networks of weather, unmanned aerial vehicle module of taking photo by plane and monitoring communication module's operation.
In one embodiment, to control the monitoring node 103, as shown in fig. 4, the first control policy and the second control policy both include the following:
and the first characteristic data acquisition sub-strategy 01 is used for controlling the acquisition frequency and the acquisition type of the first characteristic data.
In a possible embodiment, the monitoring node may control the on/off of the tension sensor, the temperature sensor, the humidity sensor, the wind speed sensor and the wind direction sensor and the data acquisition frequency according to the first characteristic data acquisition sub-strategy.
The person skilled in the art belongs to the common knowledge about the opening and closing of the tension sensor, the temperature sensor, the humidity sensor, the wind speed sensor and the wind direction sensor and the control of the data acquisition frequency, and the embodiment of the invention is not particularly limited and can be adaptively adjusted according to the actual situation.
And the second characteristic data acquisition sub-strategy 02 is used for controlling the acquisition frequency and the acquisition type of the second characteristic data.
In one possible embodiment, the monitoring node may control the switching of the wire sweep monitor and the data collection frequency according to the second characteristic data collection sub-strategy.
And the aerial photography strategy 03 is used for controlling the starting condition of the aerial photography module of the unmanned aerial vehicle and the shooting requirement.
In one possible embodiment, the monitoring node may control the opening and closing of the unmanned aerial vehicle aerial photography module and specifically the shooting process according to the aerial photography strategy.
The first reporting strategy 04 is used for controlling reporting conditions of data from the sensor monitoring network, wherein the reporting conditions include a first characteristic data item set, a second characteristic data item set, and a logical relationship between the first characteristic data item set and the second characteristic data item set; the reporting condition further includes a first reporting frequency.
If the first reporting strategy is a first feature data item set or a second feature data item set, if the first feature set at the monitoring node controls the first feature item set or the second feature set controls the second feature item set, the first reporting strategy is established, and data from the sensor monitoring network is reported.
If the first reporting strategy is a first feature data item set and a second feature data item set, if the first feature set controls the first feature item set and the second feature set controls the second feature item set, the first reporting strategy is established, and data from the sensor monitoring network is reported.
In the embodiment of the invention, the control relationship is defined as follows:
feature set a is said to control feature set B if and only if the value of any element of feature set a is greater than or equal to the value of the corresponding element of feature set B and the values of any element of feature set a cannot all be equal to the value of the corresponding element of feature set B.
A second reporting strategy 05, configured to control a reporting condition of data from the unmanned aerial vehicle aerial photography module; the reporting condition further comprises a second reporting frequency.
The embodiment of the invention considers that the unmanned aerial vehicle aerial photography module is not used even if the probability of forming the rime is high, if the unmanned aerial vehicle aerial photography module is used, the acquisition of data from the sensor monitoring network is correspondingly strengthened, the report of the data from the sensor monitoring network is relaxed, and the report frequency is improved, so that the monitoring loss caused by the reduction of the feeling of existence of the unmanned aerial vehicle aerial photography module can be reduced, therefore, in a feasible embodiment, the first control strategy and the second control strategy have the following relationship:
for the first feature data acquisition sub-strategy: the acquisition frequency set by the first control strategy is higher than the acquisition frequency set by the second control strategy;
for the second feature data acquisition sub-strategy: the acquisition frequency set by the first control strategy is higher than the acquisition frequency set by the second control strategy;
for an aerial photography strategy: the first control strategy does not allow aerial photography or only allows low-frequency aerial photography, and the second control strategy allows aerial photography or allows high-frequency aerial photography;
for the first reporting policy: the logic relation between the first characteristic data item set and the second characteristic data item set of the first control strategy is an OR relation; the logical relationship of the first characteristic data item set and the second characteristic data item set of the second control strategy is an and-relationship. And the conditions defined by the first set of characteristic data items and the second set of characteristic data items of the second control strategy are more stringent than the conditions defined by the first set of characteristic data items and the second set of characteristic data items of the first control strategy.
For example, the temperature is higher, the wind speed is stronger, the stress and the shake are more serious, and the like.
And the first reporting frequency of the first control strategy is higher than the first reporting frequency of the second control strategy.
For the second reporting policy: the data of the unmanned aerial vehicle aerial photography module is not allowed to be reported under the first control strategy; and allowing the data of the unmanned aerial vehicle aerial photography module to be reported under the second control strategy.
Accordingly, in one possible embodiment, as shown in fig. 5, the monitoring node 103 performs the following method:
s201, obtaining a node control strategy from a monitoring master control platform.
And S203, controlling the sensor monitoring network according to the first characteristic data acquisition sub-strategy and the second characteristic data acquisition sub-strategy of the node control strategy.
And S205, controlling a sensor monitoring network according to the aerial photographing strategy of the node control strategy.
And S207, acquiring data from the sensor monitoring network, and obtaining a first characteristic set and a second characteristic set according to the data.
Specifically, as shown in fig. 6, the acquiring data from the sensor monitoring network, and obtaining a first feature set and a second feature set according to the data includes:
s2071, acquiring first original data from a tension sensor, a temperature sensor, a humidity sensor, a wind speed sensor and a wind direction sensor;
s2073, acquiring second original data from the swing monitor;
s2075, a first feature set is obtained by performing a first processing on the first original data.
S2077, carrying out second processing on the second original data to obtain a second feature set.
In a preferred embodiment, the first process comprises a synchronization process and an sensitization process, and the second process involves only the sensitization process of the data collected by the lead wiggle monitor.
Specifically, the synchronization process includes: dividing a time window, generating a data set corresponding to the time window according to tension data, temperature data, humidity data, wind speed data and wind direction data which fall into the same time window, and replacing the data of the same type with statistical data of the same type to obtain a synchronized data set if the data of the same type in the data set is more than one.
For example, if the data set corresponding to the time window is { F1, F2, F3, T1, T2, W1, V1, D1}, that is, three tension data, two temperature data, one humidity data, one wind speed data, and one wind direction data exist in the same time window, the three tension data are replaced by the statistical data of the three tension data, and the two temperature data are replaced by the statistical data of the two temperature data, so that the synchronized data set is obtained.
Specifically, the embodiment of the present invention does not limit the method for obtaining the statistical data, and may be an average value method or a weighted average value method.
Correspondingly, the sensitization processing of the first processing is sensitization processing of a data set sequence obtained by each synchronized data set according to a time window time sequence corresponding to the synchronized data set to obtain a first feature set, specifically:
and S1, extracting the data of the same type of each data set in the data set sequence according to the type to obtain five data sequences.
Specifically, the data sequence is a tension data sequence, a temperature data sequence, a humidity data sequence, a wind speed data sequence and a wind direction data sequence.
S3, sensitizing each data sequence according to the following formula group:
wherein the content of the first and second substances,
the data are respectively data of a data sequence, corresponding output data after sensitization, time lag parameters of a sensor for acquiring the data, and a relevant sampling parameter of the sensor and a noise reduction coefficient of the sensor according to a sensitization degree parameter determined by the sensor.
Is the intermediate variable that is the variable between,
parameters related to the data source of the data sequence can be set or adjusted according to actual needs.
The sensitization processing method in the second processing is similar and is not repeated again.
And S5, extracting the latest data in each data sequence to obtain a first feature set according to each data sequence generated by the data obtained after sensitization.
And S209, acquiring image data from the unmanned aerial vehicle aerial photography module, and obtaining the antenna attitude according to the image data.
In a preferred embodiment, the obtaining the antenna pose according to the image data, as shown in fig. 7, includes:
s2091, obtaining the minimum circumscribed rectangle of the antenna target in the image data and the classification of the antenna target according to the image data.
In particular, the classification of the antenna in one possible embodiment includes a top surface of the antenna target and a side surface of the antenna target.
S2093, calculating the attitude of the antenna target according to the classification of the antenna target and the attitude of the unmanned aerial vehicle.
Specifically, the calculating the antenna attitude according to the classification of the antenna and the attitude of the drone includes:
s20931, if the antenna target is classified as the top surface of the antenna target, extracting the longest straight line in the antenna outline from the minimum circumscribed rectangle of the antenna target based on the coordinate parameters corresponding to the antenna target, and if the straight line is consistent with the horizontal direction, performing the following steps
Calculating an azimuth angle of the antenna target, wherein
Respectively corresponding to the attitude angle of the unmanned aerial vehicle and the azimuth angle of the antenna target.
S20933, if the antenna target is classified as the side face of the antenna target, extracting the longest straight line in the antenna outline from the minimum circumscribed rectangle of the antenna target based on the coordinate parameters corresponding to the antenna target, and determining the included angle of the straight line relative to the horizontal plane as the azimuth angle of the antenna target.
S2011, if the first feature set and the second feature set meet a first reporting strategy of the node control strategy, uploading the first feature set and the second feature set according to the first reporting strategy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
In the embodiment of the invention, the data can be continuously reported only when the first reporting strategy or the second reporting strategy is triggered, and the reporting is stopped after a stop instruction of the monitoring master control platform is received. Conditional reported data is convenient for the monitoring master control platform to monitor each monitoring node, meanwhile, each monitoring node is endowed with certain authority, reporting is not needed when the reporting condition is not reached, communication flow is saved, and bidirectional burden of the monitoring nodes and the monitoring master control platform is reduced.
In an embodiment of the present invention, the reporting condition of the first reporting strategy includes a first set of characteristic data items, a second set of characteristic data items, and a logical relationship between the first set of characteristic data items and the second set of characteristic data items, and whether the first reporting strategy is satisfied has been described in the foregoing.
The monitoring general control platform can collect the first feature set, the second feature set and/or the antenna attitude uploaded by each monitoring node, and in a preferred embodiment, the monitoring general control platform can further perform storage processing on the first feature set, the second feature set and/or the antenna attitude, and support query on a stored result based on a result of the storage processing.
Correspondingly, the embodiment of the present invention provides a method for querying a first feature set, as shown in fig. 8, where the first feature set relates to data of five dimensions of tension data, temperature data, humidity data, wind speed data, and wind direction data, and the method includes:
s301, classifying the first feature set into five subsets, wherein the first feature set
Of the composite data in the subset
The value of the attribute data corresponding to each attribute is larger than the values of the attribute data corresponding to other attributes, and the composite data is formed by sequentially arranging tension data, temperature data, humidity data, wind speed data and wind direction data.
S303, sorting the composite data in the five subsets, wherein the first step
The sub-sets arrange the composite data in descending order of the values of the attribute data in the corresponding reference attribute, wherein the first sub-set
The reference attribute corresponding to each subset is
An attribute.
S305, acquiring a query condition, wherein the query condition comprises reference composite data, and the reference composite data is formed by sequentially inputting tension data, temperature data, humidity data, wind speed data and wind direction data by a user.
S307, compound data capable of controlling the reference compound data are inquired in each subset to obtain a result subset corresponding to the subset.
In a preferred embodiment, a corresponding B + tree index may be constructed for each subset, each leaf node of the index stores a bidirectional pointer, the bidirectional pointer is used to quickly find its related contextual leaf node according to the leaf node, and the B + tree dynamically adaptively changes according to the data change of the subset.
Further, each subset can be marked, if the composite data meeting the query condition cannot exist in the subset, the subset is marked as an invalid subset, otherwise, the subset is marked as a valid subset; correspondingly, the querying the composite data capable of controlling the reference composite data in each subset to obtain a result subset corresponding to the subset includes:
for each subset, the following method is performed:
s3071, acquiring marks of the subsets;
s3073, if the subset is a valid subset, querying data capable of controlling the reference composite data to obtain a result subset corresponding to the subset.
Specifically, the embodiment of the invention discloses a method for updating marks for each subset, which comprises the following steps:
(1) obtaining maximum attribute values of each subset
And minimum attribute value
The maximum attribute value is the rightmost value of the B + tree index corresponding to the subsetMaximum value in each attribute data of the composite data; the minimum attribute value is the minimum value in each attribute data of the composite data pointed by the rightmost value of the B + tree index corresponding to the subset;
(2) each maximum attribute value
Is determined as a first reference, and each maximum attribute value is determined as a second reference
Is determined as the second reference.
(3) For a subset, if it corresponds to the maximum attribute value
Less than the second reference, the subset is marked as an invalid subset.
Specifically, the querying may control data of the reference composite data to obtain a result subset corresponding to the subset, as shown in fig. 9, specifically include:
s30731. the subset of initialization results is an empty set.
S30733, extracting target composite data from the subsets to form target subsets, the target composite data having attribute data that hits an identification of the subsets
Corresponding target data, identification of said subset
The corresponding target data is such data that: extracting all attribute data of all data objects in the first feature set to obtain a data set, removing data with the same value from the data set, and then performing descending order to obtain a data ordering result, wherein the first attribute data in the data ordering result
The data is instituteIdentification of the subset
Corresponding target data.
Specifically, the extracting the target composite data in the subset to form the target subset includes:
s1, initializing the target subset into an empty set; determining the node pointed by the rightmost value of the B + tree index as the current node;
s3, circularly executing the following steps: if the maximum tag value of the subset is
Adding the composite data of the current node into the target subset when the composite data is equal to the first reference; searching the left node of the current node according to the index of the subset, updating the left node of the current node to be a new current node, and marking the maximum value of the subset
And updating the maximum value of each attribute data of the composite data of the current node.
S30735, compound data capable of controlling the baseline compound data is queried in the target subset and added to the result subset.
S309, determining the union of the result subsets as the query result corresponding to the query condition.
The invention can inquire the data meeting the inquiry condition in the composite data recorded in the first characteristic set so as to facilitate the analysis of the data in the first characteristic set by a user, and can further position the related monitoring nodes pointed by the inquiry result so as to facilitate the adjustment of the first control strategy and/or the second control strategy for each monitoring point through the monitoring master control platform. Of course, the first control strategy and/or the second control strategy for monitoring the master control platform may be automatically generated or may be input by a user, which is not limited in this embodiment of the present invention.
Of course, the query method provided in the embodiment of the present invention may also be used for querying the second feature set, which is not described herein again.
The embodiment of the invention also discloses a multi-sensor fused power system internet of things monitoring system, which comprises:
the system comprises a monitoring master control platform and a plurality of monitoring nodes, wherein each monitoring node is communicated with the monitoring master control platform, the monitoring nodes and the power systems are in one-to-one correspondence, and one monitoring node corresponds to one power system;
as shown in fig. 10, the monitoring node includes:
a first control module 401, configured to control the sensor monitoring network according to a first characteristic data acquisition sub-policy and a second characteristic data acquisition sub-policy of the node control policy;
a second control module 403, configured to control a sensor monitoring network according to an aerial photography policy of the node control policy;
a first data processing module 405, configured to acquire data from a sensor monitoring network, and obtain a first feature set and a second feature set according to the data;
the second data processing module 407 is used for acquiring image data from the unmanned aerial vehicle aerial photography module and obtaining an antenna attitude according to the image data;
a reporting control module 409, configured to, if the first feature set and the second feature set meet a first reporting policy of a node control policy, upload the first feature set and the second feature set according to the first reporting policy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
The embodiments of the invention and the method embodiments are based on the same inventive concept, and are not described again.
The embodiment of the present invention further provides a computer-readable storage medium, where at least one instruction or at least one program is stored in the computer-readable storage medium, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the multi-sensor integrated power system internet of things monitoring method according to the above-mentioned embodiment.
It should be noted that: the sequence of the above embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A multi-sensor fusion power system internet of things monitoring method is applied to monitoring nodes and is characterized by comprising the following steps:
acquiring a node control strategy from a monitoring master control platform;
controlling a sensor monitoring network according to a first characteristic data acquisition sub-strategy and a second characteristic data acquisition sub-strategy of the node control strategy;
controlling a sensor monitoring network according to an aerial photographing strategy of the node control strategy;
acquiring data from a sensor monitoring network, and obtaining a first characteristic set and a second characteristic set according to the data;
acquiring image data from an unmanned aerial vehicle aerial photographing module, and obtaining an antenna attitude according to the image data;
if the first characteristic set and the second characteristic set meet a first reporting strategy of a node control strategy, uploading the first characteristic set and the second characteristic set according to the first reporting strategy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
2. The method of claim 1, wherein:
the sensor monitoring network comprises a tension sensor and a lead swing monitor which are arranged on a rim string of the antenna, and a temperature sensor, a humidity sensor, a wind speed sensor and a wind direction sensor which are arranged on an antenna supporting rod.
3. The method of claim 2, wherein:
the first feature set comprises the stress state after load bearing, the temperature, humidity, wind speed and wind direction of the current environment, and the second feature set comprises the bending amplitude and frequency of the wire relative to the wire clamp at a certain distance outside the last contact point of the wire and the wire clamp; the first feature set is used for representing the external factor monitoring result of the antenna, and the second feature set is used for representing the internal factor monitoring result of the antenna.
4. The method of claim 3, wherein:
if the first reporting strategy is a first characteristic data item set or a second characteristic data item set, if the first characteristic set at the monitoring node controls the first characteristic item set or the second characteristic set controls the second characteristic item set, the first reporting strategy is established, and data from the sensor monitoring network is reported;
if the first reporting strategy is a first feature data item set and a second feature data item set, if the first feature set controls the first feature item set and the second feature set controls the second feature item set, the first reporting strategy is established, and data from the sensor monitoring network is reported.
5. The method of claim 1, wherein said acquiring data from a sensor monitoring network, deriving a first set of features and a second set of features from said data comprises:
acquiring first original data from a tension sensor, a temperature sensor, a humidity sensor, a wind speed sensor and a wind direction sensor;
acquiring second original data from a swing monitor;
performing first processing on the first original data to obtain a first feature set;
and carrying out second processing on the second original data to obtain a second feature set.
6. The method of claim 1, wherein:
the first processing includes synchronous processing and sensitization processing, and the second processing only conducts sensitization processing.
7. The method of claim 6, wherein:
the synchronization process includes: dividing a time window, generating a data set corresponding to the time window according to tension data, temperature data, humidity data, wind speed data and wind direction data which fall into the same time window, and replacing the data of the same type with statistical data of the same type to obtain a synchronized data set if the data of the same type in the data set is more than one.
8. The system according to claim 7, wherein the sensitization process of the first process is a sensitization process of a data set sequence obtained by each synchronized data set according to a corresponding time window sequence to obtain a first feature set, and specifically comprises:
extracting the data of the same type of each data set in the data set sequence according to the type to obtain five data sequences;
for each data sequence, sensitization is performed according to the following formula:
wherein the content of the first and second substances,
respectively acquiring data of a data sequence, corresponding output data after sensitization, time lag parameters of a sensor for acquiring the data, and a relevant sampling parameter of the sensor and a noise reduction coefficient of the sensor according to the sensitization degree parameter determined by the sensor;
is a parameter associated with a data source of the data sequence;
and extracting the latest data in each data sequence to obtain a first feature set according to each data sequence generated by the data obtained after sensitization.
9. A multisensor-fused power system Internet of things monitoring system, the system comprising:
the system comprises a monitoring general control platform and a plurality of monitoring nodes, wherein each monitoring node is communicated with the monitoring general control platform, the monitoring nodes and the power systems are in one-to-one correspondence, and one monitoring node corresponds to one power system;
the monitoring node comprises:
the node control strategy acquisition module is used for acquiring a node control strategy from the monitoring master control platform;
the first control module is used for controlling the sensor monitoring network according to a first characteristic data acquisition sub-strategy and a second characteristic data acquisition sub-strategy of the node control strategy;
the second control module is used for controlling the sensor monitoring network according to the aerial photographing strategy of the node control strategy;
the first data processing module is used for acquiring data from a sensor monitoring network and obtaining a first characteristic set and a second characteristic set according to the data;
the second data processing module is used for acquiring image data from the unmanned aerial vehicle aerial photography module and obtaining the antenna attitude according to the image data;
the reporting control module is used for uploading the first characteristic set and the second characteristic set according to a first reporting strategy if the first characteristic set and the second characteristic set meet the first reporting strategy of the node control strategy;
or the like, or, alternatively,
and if the antenna attitude meets a second reporting strategy of the node control strategy, uploading the antenna attitude according to the second reporting strategy.
10. A computer-readable storage medium, wherein at least one instruction or at least one program is stored in the computer-readable storage medium, and the at least one instruction or the at least one program is loaded by a processor and executed to implement the method for monitoring the power system with multiple sensors according to any one of claims 1 to 8.
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