A power station operation monitoring system based on Internet of Things terminals

Abstract

The present invention discloses a power station operation monitoring system based on an Internet of Things terminal, relates to the technical field of power station operation monitoring, and improves the accuracy of operation monitoring results. The present invention establishes a logical operation function of each power generation device according to historical operation records, and binds the logical operation function under each time dimension to the device operation logic node, and then connects each device operation logic node in sequence according to the energy flow direction to generate an operation logic relationship tree, and forms an operation logic subtree with each device operation logic node as the center, collects real-time operation data of each power device and inputs it into the operation logic relationship tree and the operation logic subtree, and then generates a macro logic monitoring result and a micro logic monitoring result, matches and compares the macro logic monitoring result with the micro logic monitoring result, and generates and executes the equipment maintenance decision according to the comparison result.

Description

Technical Field

[0001] The present invention relates to the technical field of power station operation monitoring, and in particular to a power station operation monitoring system based on an Internet of Things terminal. Background Art

[0002] Power station operation monitoring technology refers to the process of real-time monitoring and analysis of the operating status, equipment performance and environmental conditions of a power station. By collecting, processing and analyzing various data, the safe, efficient and reliable operation of the power station can be monitored and managed.

[0003] The existing power station operation monitoring technology has the following defects:

[0004] Fault warning accuracy: Intelligent diagnosis and warning systems rely on data analysis and algorithm models, and their accuracy is limited by the precision and reliability of the models. In some cases, the system may have false positives or false negatives, affecting the timely discovery and handling of potential faults.

[0005] Data processing complexity: Power plants generate a large amount of data, such as temperature, pressure, vibration, etc., which need to be effectively processed and analyzed. There are still challenges in large-scale data processing, including the complexity of data storage, transmission, cleaning and modeling.

[0006] Therefore, how to ensure the credibility of the power plant operation data processing results while improving the accuracy of the operation monitoring results is a difficulty in the prior art. For this purpose, a power plant operation monitoring system based on an Internet of Things terminal is provided. Summary of the invention

[0007] In order to solve the above technical problems, the purpose of the present invention is to provide a power station operation monitoring system based on an Internet of Things terminal.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] A power station operation monitoring system based on an Internet of Things terminal comprises a cloud computing platform, wherein the cloud computing platform is communicatively connected with a historical operation data analysis module, an operation monitoring module and a power station regulation module;

[0010] The historical operation data analysis module is provided with a logic data extraction unit and a logic relationship tree establishment unit;

[0011] The logic data extraction unit is used to extract the historical operation records of each power generation equipment from a plurality of pre-stored power station historical operation data, and then establish the logic operation function of each power generation equipment according to the historical operation records;

[0012] The logic relationship tree establishment unit is used to establish a device operation logic node, bind the logic operation function under each time dimension to the device operation logic node, and then connect each device operation logic node in sequence according to the energy flow direction to generate an operation logic relationship tree;

[0013] The operation monitoring module is provided with a macro logic monitoring unit and a plurality of micro logic monitoring units;

[0014] The macro logic monitoring unit is used to form an operation logic subtree with each device operation logic node as the center according to the spatial position distribution of each power generation device, and send each operation logic subtree to each micro logic monitoring unit, and generate a monitoring directed connection line group according to the real-time operation data of all power devices, and input the monitoring directed connection line group into the operation logic relationship tree, so as to judge the real-time operation status of each power device and generate a macro logic monitoring result;

[0015] The micro-logic monitoring unit is used to obtain the real-time operation data of the corresponding power equipment according to the equipment operation logic node in the operation logic subtree and input it into the operation logic subtree, and then generate the micro-logic monitoring result according to the monitoring directed connection line group;

[0016] The power plant regulation module is used to operate the corresponding relationship between the logic relationship tree and each operation logic subtree, match and compare the macro logic monitoring result with the micro logic monitoring result, and generate and execute equipment maintenance decisions based on the comparison results.

[0017] Further, the power station historical operation data is composed of historical operation records of n power generation equipment, and the historical operation records include the number of the power generation equipment, the energy interaction process between other power equipment and the event timeline, and Num and n are natural numbers greater than 0;

[0018] The energy interaction process between the power devices includes the energy interaction direction, energy interaction amount, interaction duration, historical status data of the power devices during the interaction process, and the number of the corresponding power devices. The event timeline is marked with the interaction time points of each interaction process.

[0019] Furthermore, the generation process of the logic operation function includes:

[0020] Establish Num three-dimensional coordinate systems, and according to the spatial position distribution of each power generation equipment in the power station, set n device nodes on the plane coordinate system composed of any two coordinate axes in the three-dimensional coordinate system, and map the event time axis to another coordinate axis, and record the coordinate axis as the time axis;

[0021] According to the power equipment corresponding to the device node, the historical operation records corresponding to the event timeline are bound to each device node;

[0022] According to the interaction time points on the event time axis in each historical operation record, a number of event time points are divided on the time axis, and then according to the energy interaction process between the power equipment corresponding to each event time point, an energy interaction event vector is set at each device node, and the starting device node and the end device node of the energy interaction event vector are set according to the energy interaction direction, and according to the energy interaction process between the power equipment, the starting device node and the end device node of the energy interaction event vector are respectively marked with the historical status data of the corresponding power equipment, and the energy interaction amount is set as the modulus length of the energy interaction event vector;

[0023] Summarize the energy interaction event vectors of the same starting device node and end device node in different three-dimensional coordinate systems, and then generate corresponding event data sets according to the energy interaction event vectors;

[0024] Then, the various state data of the starting device node and the terminal device node in the interaction process are used as dependent variables, and the interaction duration and energy interaction amount are used as independent variables, and then a multi-segment energy interaction linear regression equation between the corresponding starting device node and the terminal device node is generated;

[0025] Each multi-segment energy interaction linear regression equation is marked with the corresponding starting device node and end device node number, and then the logical operation function between each power device is determined.

[0026] Furthermore, the process of establishing the operation logic relationship tree includes:

[0027] The logical operation function of each power device is bound to the corresponding device node, and then the corresponding device operation logic node is generated. According to the historical operation records of each power device under the same time dimension, multiple directed connection lines are set between each device operation logic node, and the directed connection lines are set with time labels. The above process of setting multiple directed connection lines between the device operation logic nodes is repeated to obtain the operation logic relationship tree.

[0028] Furthermore, the process of establishing the running logic subtree includes:

[0029] The operation monitoring module sets n micro-logic monitoring units according to the number of power equipment, and binds each micro-logic monitoring unit to each power equipment;

[0030] Install multiple sensors on each power device, and then the micro-logic monitoring unit communicates with each sensor on the power device it is bound to;

[0031] According to the spatial distribution of each power generation equipment, several 3*3 operation logic subtrees are extracted from the operation logic relationship tree with each equipment operation logic node as the center;

[0032] If there are directed connection lines between the device operation logic nodes in the operation logic subtree, they are retained; if not, the directed connection lines on the device operation logic nodes are removed.

[0033] Furthermore, the generation process of monitoring the directed connection line group includes:

[0034] Each micro-logical monitoring unit collects the real-time status data and real-time energy interaction amount of the relevant power equipment from the sensors connected to it, and obtains the real-time status data of the corresponding power equipment from the micro-logical monitoring unit with the corresponding power equipment number according to the power equipment number of the equipment operation logic node at the edge position in the operation logic subtree. At the same time, each micro-logical monitoring unit synchronously sends the real-time status data and real-time energy interaction amount it collects to the macro-logical monitoring unit;

[0035] The micro-logic monitoring unit maps the real-time status data collected from each power device to the corresponding device operation logic node in the operation logic subtree, and the macro-logic monitoring unit maps the real-time status data of each power device to the corresponding device operation logic node in the operation logic relationship tree;

[0036] According to the real-time status data of each power device, the real-time energy interaction direction between each power device is obtained, and then the macro logic monitoring unit generates a corresponding energy interaction direction chain according to the real-time energy interaction direction between each power device;

[0037] The energy interaction direction chain is mapped into the operation logic relationship tree, and the energy interaction direction of each power device in the energy interaction direction chain is compared with the directed connection lines under each group of time dimensions in the operation logic relationship tree, and the number of directed connection lines with the same direction between the two is counted, and the similarity is calculated;

[0038] Set a similarity threshold. If the similarity is greater than or equal to the similarity threshold, the directed connection lines under the time dimension of the corresponding group are retained. Otherwise, the directed connection lines under the time dimension of the corresponding group are removed.

[0039] Then, the group with the greatest similarity is selected from the directed connection lines retained in each group of time dimensions and recorded as the monitoring directed connection line group.

[0040] Furthermore, the generation process of the macro logic monitoring result and the micro logic monitoring result includes:

[0041] The micro-logic monitoring unit removes irrelevant directed connections in the operation logic subtree according to the monitoring directed connection group, and determines whether the remaining directed connections are consistent with the real-time energy interaction direction;

[0042] According to the judgment result, it is determined whether the energy transmission direction between the corresponding power equipment is abnormal, and then the multi-segment energy interaction linear regression equation of the corresponding energy transmission direction is retrieved according to the equipment operation logic node with a directed connection line in the operation logic subtree, and the various expected status data of the corresponding power equipment are obtained according to the real-time energy interaction amount between the relevant power equipment;

[0043] A deviation threshold is set for each type of status data, and by judging whether there are less than three types of expected status data and the deviation values ​​between the corresponding real-time status data are less than or equal to the deviation threshold, it is judged whether the energy transmission process between the corresponding power equipment is normal, and then a micro-logic monitoring result is generated;

[0044] At the same time, the macro logic monitoring unit generates macro logic monitoring results according to the generation process of micro logic monitoring results.

[0045] Furthermore, the matching and comparison process between the macro logic monitoring result and the micro logic monitoring result includes:

[0046] The power station regulation module compares each micro-logic monitoring result with the macro-logic monitoring result based on the corresponding relationship between the operation logic relationship tree and each operation logic subtree;

[0047] If there is a consistent part between the micro-logic monitoring result and the macro-logic monitoring result, the micro-logic monitoring result is judged to be correct. If there is no consistent part between the micro-logic monitoring result and the macro-logic monitoring result, the macro-logic monitoring unit and the micro-logic monitoring unit re-judge the abnormality of the energy transmission direction and the abnormality of the energy transmission process of the corresponding two power equipment until the micro-logic monitoring result is consistent with the macro-logic monitoring result.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention establishes the logical operation function of each power generation equipment according to the historical operation records, and binds the logical operation function under each time dimension to the equipment operation logic node, and then connects each equipment operation logic node in sequence according to the energy flow direction to generate an operation logic relationship tree, and forms an operation logic subtree with each equipment operation logic node as the center, collects the real-time operation data of each power equipment and inputs it into the operation logic relationship tree and the operation logic subtree, and then generates macro logic monitoring results and micro logic monitoring results, matches and compares the macro logic monitoring results with the micro logic monitoring results, and determines the accuracy of the operation monitoring results according to the judgment results, thereby achieving the improvement of the accuracy of the operation monitoring results while ensuring the credibility of the power station operation data processing results. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0051] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0052] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0053] like Figure 1 As shown, a power station operation monitoring system based on an Internet of Things terminal includes a cloud computing platform, and the cloud computing platform is communicatively connected to a historical operation data analysis module, an operation monitoring module, and a power station adjustment module;

[0054] The historical operation data analysis module is provided with a logic data extraction unit and a logic relationship tree establishment unit;

[0055] The logic data extraction unit is used to extract the historical operation records of each power generation equipment from a plurality of pre-stored power station historical operation data, and then establish the logic operation function of each power generation equipment according to the historical operation records;

[0056] The logic relationship tree establishment unit is used to establish a device operation logic node, bind the logic operation function under each time dimension to the device operation logic node, and then connect each device operation logic node in sequence according to the energy flow direction to generate an operation logic relationship tree, and send the operation logic relationship tree to the operation monitoring module;

[0057] The operation monitoring module is provided with a macro logic monitoring unit and a plurality of micro logic monitoring units;

[0058] The macro logic monitoring unit is used to form a 3*3 operation logic subtree with each device operation logic node as the center according to the spatial position distribution of each power generation equipment, and send each operation logic subtree to the micro logic monitoring unit bound to the central device operation logic node, and generate a monitoring directed connection line group according to the real-time operation data of all power equipment, and input the monitoring directed connection line group into the operation logic relationship tree, so as to judge the real-time operation status of each power equipment and generate a macro logic monitoring result;

[0059] The micro-logic monitoring unit is bound to each power generation equipment, and there is a one-to-one relationship between the micro-logic monitoring unit and the power generation equipment, wherein the micro-logic monitoring unit is used to obtain the real-time operation data of the corresponding power equipment according to the equipment operation logic node in the operation logic subtree and input it into the operation logic subtree, and then generate the micro-logic monitoring result according to the monitoring directed connection line group;

[0060] The power plant regulation module is used to operate the corresponding relationship between the logic relationship tree and each operation logic subtree, match and compare the macro logic monitoring result with the micro logic monitoring result, and generate and execute equipment maintenance decisions based on the comparison results.

[0061] Further, the working principle of the present invention is described below by way of examples:

[0062] The logical data extraction unit in the historical operation data analysis module pre-stores Num copies of the power station historical operation data, which consists of the historical operation records of n power generation equipment, and the historical operation records include the number of the power generation equipment, the energy interaction process between other power equipment and the event timeline, where the number of the power equipment is s 1 、s 2 、s 3 ,……,s n , Num and n are natural numbers greater than 0;

[0063] The energy interaction process between the power devices includes the energy interaction direction, energy interaction amount, interaction duration, historical status data of the power devices during the interaction process, and the serial number of the corresponding power devices, and the interaction time point of each interaction process is marked on the event timeline;

[0064] It should be noted that the start and end time of the event time axis of each historical operation record in the same power station historical operation data is the same, and the historical status data of the power equipment includes a temperature change curve, a voltage change curve, etc.;

[0065] The logic data extraction unit performs data analysis on each historical operation record under the same time dimension and generates a logic operation function. The specific process includes:

[0066] Establish Num three-dimensional coordinate systems, and according to the spatial position distribution of each power generation equipment in the power station, set n device nodes on the plane coordinate system composed of any two coordinate axes in the three-dimensional coordinate system, and map the event time axis to another coordinate axis, and record the coordinate axis as the time axis;

[0067] According to the power equipment corresponding to the device node, the historical operation records corresponding to the event timeline are bound to each device node;

[0068] According to the interaction time points on the event time axis in each historical operation record, a number of event time points are divided on the time axis, and then according to the energy interaction process between the power equipment corresponding to each event time point, an energy interaction event vector is set at each device node, and the starting device node and the end device node of the energy interaction event vector are set according to the energy interaction direction, and according to the energy interaction process between the power equipment, the starting device node and the end device node of the energy interaction event vector are respectively marked with the historical status data of the corresponding power equipment, and the energy interaction amount is set as the modulus length of the energy interaction event vector;

[0069] The energy interaction event vectors of the same starting device node and the end device node in different three-dimensional coordinate systems are summarized, and then a corresponding event data set S is generated according to the energy interaction event vectors, wherein the event data set S={(interaction duration, energy interaction amount, various state data of the starting device node in the interaction process, various state data of the end device node in the interaction process), ...};

[0070] Then, the various state data of the starting device node and the terminal device node in the interaction process are used as dependent variables, and the interaction duration and energy interaction amount are used as independent variables, and then a multi-segment energy interaction linear regression equation between the corresponding starting device node and the terminal device node is generated;

[0071] Each multi-segment energy interaction linear regression equation is marked with the corresponding starting device node and end device node number, and then the logical operation function between each power device is determined.

[0072] Further, the logic relationship tree establishment unit binds the logic operation function of each power device to the corresponding device node, thereby generating a corresponding device operation logic node, and according to the historical operation records between each power device in the same time dimension, further sets a plurality of directed connection lines between each device operation logic node, wherein the directed connection lines are set with time labels;

[0073] It should be noted that there are multiple directed connection lines for the same pair of device operation logical nodes, but the time labels of each directed connection line are completely different, and the directed connection lines between different pairs of device operation logical nodes have the same type of time labels;

[0074] Repeat the above process of setting multiple directed connection lines between the device operation logic nodes to obtain the operation logic relationship tree.

[0075] Furthermore, the historical operation data analysis module sends the operation logic relationship tree to the operation monitoring module;

[0076] The operation monitoring module sets n micro-logic monitoring units according to the number of power equipment, and binds each micro-logic monitoring unit to each power equipment;

[0077] Install multiple sensors on each power device, and then the micro-logic monitoring unit communicates with each sensor on the power device it is bound to;

[0078] It should be noted that there is a corresponding relationship between the data collected by the sensors on the power equipment and the types of historical status data in the historical operation records;

[0079] The macro logic monitoring unit in the operation monitoring module is connected to each micro logic monitoring unit for communication, and a corresponding power equipment number is set for each micro logic monitoring unit according to the power equipment bound to each micro logic monitoring unit;

[0080] The operation monitoring module sends the operation logic relationship tree to the macro logic monitoring unit, and then the macro logic monitoring unit extracts several 3*3 operation logic subtrees from the operation logic relationship tree based on the spatial location distribution of each power generation equipment and the operation logic node of each equipment as the center;

[0081] It should be noted that if the number of peripheral device operation logic nodes is insufficient to form a 3*3 operation logic subtree, the device operation logic node will be automatically ignored;

[0082] If there are directed connection lines between the device operation logic nodes in the operation logic subtree, they are retained; if not, the directed connection lines on the device operation logic nodes are removed.

[0083] Further, the macro logic monitoring unit sends the operation logic subtree to the micro logic monitoring unit of the corresponding power equipment number according to the power equipment number corresponding to the equipment operation logic node at the center of the operation logic subtree;

[0084] Each micro-logical monitoring unit collects the real-time status data and real-time energy interaction amount of the relevant power equipment from the sensors connected to it, and obtains the real-time status data of the corresponding power equipment from the micro-logical monitoring unit with the corresponding power equipment number according to the power equipment number of the equipment operation logic node at the edge position in the operation logic subtree. At the same time, each micro-logical monitoring unit synchronously sends the real-time status data and real-time energy interaction amount it collects to the macro-logical monitoring unit;

[0085] The micro-logic monitoring unit maps the real-time status data collected from each power device to the corresponding device operation logic node in the operation logic subtree, and the macro-logic monitoring unit maps the real-time status data of each power device to the corresponding device operation logic node in the operation logic relationship tree;

[0086] According to the real-time status data of each power device, the real-time energy interaction direction between each power device is obtained, and then the macro logic monitoring unit generates a corresponding energy interaction direction chain according to the real-time energy interaction direction between each power device;

[0087] The energy interaction direction chain is mapped into the operation logic relationship tree, and the energy interaction direction of each power device in the energy interaction direction chain is compared with the directed connection lines under each group of time dimensions in the operation logic relationship tree, and the number of directed connection lines with the same direction between the two is counted, and the similarity is calculated;

[0088] Set a similarity threshold. If the similarity is greater than or equal to the similarity threshold, the directed connection lines under the time dimension of the corresponding group are retained. Otherwise, the directed connection lines under the time dimension of the corresponding group are removed.

[0089] Then, a group with the largest similarity is selected from the directed connection lines retained in each group of time dimensions as a monitoring directed connection line group, and the monitoring directed connection line group is sent to each micro-logic monitoring unit;

[0090] It should be noted that if there is no directed connection line in the time dimension with a similarity greater than or equal to the similarity threshold, the corresponding power station historical operation data is generated after the energy interaction of the power station is completed, and the operation logic relationship tree is retrained.

[0091] Furthermore, the micro-logic monitoring unit removes irrelevant directed connections in the operation logic subtree according to the monitoring directed connection group, and determines whether the remaining directed connections are consistent with the real-time energy interaction direction;

[0092] If they are inconsistent, it is determined that the energy transmission direction between the corresponding power equipment is abnormal. Otherwise, the micro-logic monitoring unit retrieves the multi-segmented energy interaction linear regression equation of the corresponding energy transmission direction according to the equipment operation logic node with a directed connection line in the operation logic subtree, and obtains the various expected status data of the corresponding power equipment according to the real-time energy interaction amount between the relevant power equipment;

[0093] A deviation threshold is set for each type of status data. If the deviation value between less than three types of expected status data and the corresponding real-time status data is less than or equal to the deviation threshold, it is determined that the energy transmission process between the corresponding power equipment is normal;

[0094] If the deviation between the three predicted state data and the corresponding real-time state data is greater than or equal to the deviation threshold, it is determined that the energy transmission process between the corresponding power equipment is abnormal;

[0095] Then the micro logic monitoring unit generates micro logic monitoring results;

[0096] The macro logic monitoring unit determines whether there is an abnormality in the energy transmission direction between the various power devices based on the monitoring directed connection line group, and retrieves the relevant multi-segment energy interaction linear regression equation based on the judgment result, and then determines whether the energy transmission process between the power devices is abnormal. The process of the macro logic monitoring unit performing abnormal energy transmission direction judgment and energy transmission process judgment is the same as that of the micro logic monitoring unit;

[0097] Then the macro logic monitoring unit generates corresponding macro logic monitoring results according to the judgment result;

[0098] The operation monitoring module sends the macro logic monitoring result and the micro logic monitoring result to the power station regulation module, wherein the macro logic monitoring result and the micro logic monitoring result include the serial numbers of two power equipments with abnormal energy transmission direction or abnormal energy transmission process.

[0099] Further, the power station regulation module compares each micro-logic monitoring result with the macro-logic monitoring result according to the corresponding relationship between the operation logic relationship tree and each operation logic subtree;

[0100] If there is a consistent part between the micro-logical monitoring result and the macro-logical monitoring result, then the micro-logical monitoring result is judged to be correct;

[0101] If there is no consistent part between the micro-logic monitoring result and the macro-logic monitoring result, the macro-logic monitoring unit and the micro-logic monitoring unit re-judge the energy transmission direction abnormality and the energy transmission process abnormality of the corresponding two power devices until there is a consistent part between the micro-logic monitoring result and the macro-logic monitoring result;

[0102] The power station regulation module generates corresponding equipment maintenance decisions based on the correct micro-logic monitoring results, and sends the equipment maintenance decisions to the staff for execution;

[0103] The equipment maintenance decision includes the number of the power equipment, the type of abnormal status data, or the abnormal prompt of the energy transmission direction.

[0104] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A power station operation monitoring system based on an Internet of Things terminal, including a cloud computing platform, It is characterized in that The cloud computing platform is communicatively connected with a historical operation data analysis module, an operation monitoring module and a power station regulation module; The historical operation data analysis module is provided with a logic data extraction unit and a logic relationship tree establishment unit; The logic data extraction unit is used to extract the historical operation records of each power generation equipment from a plurality of pre-stored power station historical operation data, and then establish the logic operation function of each power generation equipment according to the historical operation records; The logic relationship tree establishment unit is used to establish a device operation logic node, bind the logic operation function under each time dimension to the device operation logic node, and then connect each device operation logic node in sequence according to the energy flow direction to generate an operation logic relationship tree; The operation monitoring module is provided with a macro logic monitoring unit and a micro logic monitoring unit; The macro logic monitoring unit is used to form an operation logic subtree with each device operation logic node as the center, and send each operation logic subtree to each micro logic monitoring unit, and generate a monitoring directed connection line group according to the real-time operation data of all power equipment, and input the monitoring directed connection line group into the operation logic relationship tree, so as to judge the real-time operation status of each power equipment and generate a macro logic monitoring result; The micro-logic monitoring unit is used to obtain the real-time operation data of the corresponding power equipment according to the equipment operation logic node in the operation logic subtree and input it into the operation logic subtree, and then generate the micro-logic monitoring result according to the monitoring directed connection line group; The power plant regulation module is used to operate the corresponding relationship between the logic relationship tree and each operation logic subtree, match and compare the macro logic monitoring result with the micro logic monitoring result, and generate and execute equipment maintenance decisions based on the comparison results.

2. According to claim 1, a power station operation monitoring system based on an Internet of Things terminal, It is characterized in that The power station historical operation data consists of historical operation records of n power generation equipment, and the historical operation records include the number of the power generation equipment, the energy interaction process between other power equipment and the event timeline, and Num and n are natural numbers greater than 0; The energy interaction process between the power devices includes the energy interaction direction, energy interaction amount, interaction duration, historical status data of the power devices during the interaction process, and the number of the corresponding power devices. The event timeline is marked with the interaction time points of each interaction process.

3. According to claim 2, a power station operation monitoring system based on an Internet of Things terminal, It is characterized in that The generation process of the logic operation function includes: Establish Num three-dimensional coordinate systems, and according to the spatial position distribution of each power generation equipment in the power station, set n device nodes on the plane coordinate system composed of any two coordinate axes in the three-dimensional coordinate system, and map the event time axis on another coordinate axis and record it as the time axis; According to the interaction time points on the event time axis in each historical operation record, a number of event time points are divided on the time axis, and then the starting device node and the end device node of the energy interaction event vector are set according to the energy interaction process between the power equipment corresponding to each event time point, so as to generate the corresponding energy interaction event vector; The energy interaction event vectors of the same starting device node and terminal device node in different three-dimensional coordinate systems are summarized, and the various state data of the starting device node and the terminal device node in the interaction process are used as dependent variables, and the interaction duration and energy interaction amount are used as independent variables, thereby generating a multi-segment energy interaction linear regression equation between the corresponding starting device node and the terminal device node; Each multi-segment energy interaction linear regression equation is marked with the corresponding starting device node and end device node number, and then the logical operation function between each power device is determined.

4. A power station operation monitoring system based on an Internet of Things terminal according to claim 3, It is characterized in that The process of establishing the operation logic relationship tree includes: The logical operation function of each power device is bound to the corresponding device node, and then the corresponding device operation logic node is generated. According to the historical operation records between each power device in the same time dimension, multiple directed connection lines are set between each device operation logic node, and the directed connection lines are set with time annotations. The process of setting multiple directed connection lines between the above-mentioned device operation logic nodes is repeated to obtain an operation logic relationship tree.

5. A power station operation monitoring system based on an Internet of Things terminal according to claim 4, It is characterized in that The process of establishing the operation logic subtree includes: The operation monitoring module sets n micro-logic monitoring units according to the number of power equipment, and binds each micro-logic monitoring unit to each power equipment, installs multiple sensors on each power equipment, and the micro-logic monitoring unit communicates with each sensor on the corresponding power equipment; According to the spatial distribution of each power generation equipment, several 3*3 operation logic subtrees are extracted from the operation logic relationship tree with each equipment operation logic node as the center; If there are directed connection lines between the device operation logic nodes in the operation logic subtree, they are retained; if not, the directed connection lines on the device operation logic nodes are removed.

6. A power station operation monitoring system based on an Internet of Things terminal according to claim 5, It is characterized in that The generation process of monitoring the directed connection line group includes: Each micro-logical monitoring unit obtains the real-time status data and real-time energy interaction amount of the relevant power equipment from the sensor, and obtains the real-time status data of the corresponding power equipment from the micro-logical monitoring unit with the corresponding power equipment number according to the power equipment number of the equipment operation logic node at the edge position in the operation logic subtree. At the same time, each micro-logical monitoring unit synchronously sends the real-time status data and real-time energy interaction amount it collects to the macro-logical monitoring unit; According to the real-time status data of each power device, the real-time energy interaction direction between each power device is obtained, and then the macro logic monitoring unit generates a corresponding energy interaction direction chain according to the real-time energy interaction direction between each power device; The energy interaction direction chain is mapped into the operation logic relationship tree, and the energy interaction direction of each power device in the energy interaction direction chain is compared with the directed connection lines under each group of time dimensions in the operation logic relationship tree, and the number of directed connection lines with the same direction between the two is counted, and the similarity is obtained; Set a similarity threshold. If the similarity is greater than or equal to the similarity threshold, the directed connection lines under the time dimension of the corresponding group are retained. Otherwise, they are removed, and the directed connection lines with the greatest similarity are selected from the retained directed connection lines under the time dimension of each group as the monitoring directed connection line group.

7. A power station operation monitoring system based on an Internet of Things terminal according to claim 6, It is characterized in that The generation process of the macro logic monitoring result and the micro logic monitoring result includes: The micro-logic monitoring unit removes irrelevant directed connections in the operation logic subtree according to the monitoring directed connection group, and determines whether the remaining directed connections are consistent with the real-time energy interaction direction; According to the judgment result, it is determined whether the energy transmission direction between the corresponding power equipment is abnormal, and then the multi-segment energy interaction linear regression equation of the corresponding energy transmission direction is retrieved according to the equipment operation logic node with a directed connection line in the operation logic subtree, and the various expected status data of the corresponding power equipment are obtained according to the real-time energy interaction amount between the relevant power equipment; A deviation threshold is set for each type of status data, and by judging whether there are less than three types of expected status data and the deviation values ​​between the corresponding real-time status data are less than or equal to the deviation threshold, it is judged whether the energy transmission process between the corresponding power equipment is normal, and then a micro-logic monitoring result is generated; At the same time, the macro logic monitoring unit generates macro logic monitoring results according to the generation process of micro logic monitoring results.

8. A power station operation monitoring system based on an Internet of Things terminal according to claim 7, It is characterized in that The matching and comparison process between the macro logic monitoring result and the micro logic monitoring result includes: The power station regulation module compares each micro-logic monitoring result with the macro-logic monitoring result based on the corresponding relationship between the operation logic relationship tree and each operation logic subtree; If there is a consistent part between the micro-logic monitoring result and the macro-logic monitoring result, the micro-logic monitoring result is judged to be correct. If there is no consistent part between the micro-logic monitoring result and the macro-logic monitoring result, the macro-logic monitoring unit and the micro-logic monitoring unit re-judge the abnormality of the energy transmission direction and the abnormality of the energy transmission process of the corresponding two power equipment until the micro-logic monitoring result is consistent with the macro-logic monitoring result.

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