CN106651731B - Communication tower to-be-solved problem set generation method and system based on historical data - Google Patents
Communication tower to-be-solved problem set generation method and system based on historical data Download PDFInfo
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Abstract
The invention discloses a method and a system for generating a problem set to be solved of a communication iron tower based on historical data. The system comprises a module for setting iron tower parameter importance matrix, a module for collecting sensor data at regular time and calculating iron tower current problem coefficient matrix, a module for extracting parameter historical data and correcting current problem coefficient matrix, a module for calculating problem severity matrix, a module for arranging problem severity and a module for generating problem set to be solved. Firstly, setting an iron tower parameter importance matrix and a severity coefficient matrix of the current problem of the iron tower, then correcting the severity coefficient according to the historical occurrence frequency of the problem, and finally calculating the severity matrix of the problem to form a problem set to be solved with problem sequencing. The method and the system solve the technical problem that historical problem data are not considered when the severity of the iron tower problem is calculated.
Description
Technical Field
The invention belongs to the technical field of communication tower maintenance, and particularly relates to a method and a system for generating a problem set to be solved of a communication tower based on historical data.
Background
At present, a communication iron tower is mainly detected and maintained manually, a small amount of communication iron tower detection is completed by an iron tower online monitoring system in an auxiliary mode, and due to the fact that the number of iron tower detection indexes is large, if the system does not analyze the severity of detected iron tower problems, the problem of the iron tower which is more urgent can be processed in a non-timely mode, and therefore large loss is generated; in addition, many of the problems that have not been solved in history may be seriously lost because of the failure to be paid attention. At present, there is no technical scheme for judging the severity of the problem according to the current and historical data of the problem. Therefore, a method and a system for generating the problem set to be solved of the communication tower based on historical data are provided.
Disclosure of Invention
The invention aims to solve the problem that historical problem data is not considered when the severity of a problem of an iron tower is calculated, and provides a method and a system for generating a problem set to be solved of a communication iron tower based on historical data.
The invention relates to an iron tower system application scene based on the Internet of things, which is shown in figure 1. Sensor equipment is installed at a fixed position of a communication iron tower, the sensor collects relevant parameters of the iron tower and transmits the relevant parameters to a system through a communication module, the system stores and processes the sensor data, and a client interacts with the system to obtain required information.
The overall system architecture of the iron tower system based on the internet of things is shown in fig. 2. The system hardware part comprises a communication iron tower and sensing equipment arranged on the tower body, and a communication module of the sensing equipment is communicated with the system in real time; the system software part comprises a system database, a data processing platform and a data management publishing platform, wherein the system database receives sensor data from the sensing equipment and stores all system logs, the data processing platform calls the data in the system database for processing and analysis, and the data management publishing platform receives the data processing result of the data processing platform and corresponding records in the system database for management and publishing; the system application platform comprises management equipment and clients, wherein the management equipment comprises but is not limited to facilities such as workstations and computers, and the clients comprise but are not limited to forms of APP, WeChat, Html webpage and the like; the application personnel of the system include, but are not limited to, management personnel and maintenance personnel, and the interfaces of the system are management equipment and a client side respectively.
The implementation of the invention depends on the application scene and the system architecture, various sensors are arranged at certain positions of the tower body to detect corresponding parameters of the iron tower, and historical data of various problems are extracted from a system database.
The communication iron tower problem set generation system based on historical data comprises an iron tower parameter importance matrix setting module, a sensor data timing acquisition and iron tower current problem coefficient matrix calculation module, a parameter historical data extraction and current problem coefficient matrix correction module, a problem severity calculation module, a problem severity arrangement and generation module.
1. The iron tower parameter importance matrix setting module comprises: the system identifies index parameters and the number N of the index parameters which need to be detected by the communication tower, and the index parameters can include but are not limited to perpendicularity, stability, integrity, connection gaps, tower footing sinking and lightning grounding parameters. The system sets an importance value X of each index parameter (the importance of each index is set by experts or technicians in the field according to engineering experience, the value range is 0-M, the larger the value of X is, the more important the index parameter is), and a parameter importance matrix X is formed (X is the more important the index parameter is), wherein1,x2,x3,…,xN)。
2. The module is used for acquiring sensor data regularly and calculating the coefficient matrix of the current problem of the iron tower: the method comprises the steps that sensors deployed on an iron tower synchronously acquire sensor data at fixed time (sampling interval is T), a system calculates the current problem coefficient a (the value range is 0-1, the higher the value of a is, the higher the severity is), of the iron tower, corresponding to the sensor data according to a preset current problem coefficient function of the iron tower, wherein the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience, and a current problem coefficient matrix A (a) is formed according to the sequence of index parameters (the sequence of each index parameter in a parameter importance matrix X)1,a2,a3,…,aN) where matrix a is an N × N diagonal matrix.
3. A module for extracting parameter historical data and correcting the coefficient matrix of the current problem: the system extracts historical problem data of each index parameter, calculates a historical problem coefficient B (the value range is 0-1, the larger the value of B is, the higher the frequency and the severity of the problem history are), and forms a historical problem coefficient matrix B (B) which is flag (B) according to the sequence of the index parameters (the sequence of each index parameter in the parameter importance matrix X) through a preset historical problem coefficient function (the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience)1,b2,b3,…,bN) the sum of the historical problem coefficient B and the current problem coefficient a forms the corrected problem severity coefficient diagonal matrix Y ═ a + B ═ diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) likewise, the matrix Y is also an N × N diagonal matrix.
4. A calculate problem severity matrix module: problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiAnd i is more than or equal to 1 and less than or equal to N. The problem severity value z is obtained by multiplying the parameter importance value x and the corrected severity coefficient y corresponding to the index parameter.
5. And the problem severity ranking module generates a problem set to be solved: and (3) sequencing the elements in the matrix Z in a descending manner to obtain a matrix H (by adopting a corresponding function commonly used in MATLAB or other sequencing methods), sequencing the severity of the iron tower problems according to the iron tower problems corresponding to the elements in the matrix H, and generating a problem set to be solved with the severity sequencing.
A system block diagram of a communication tower problem set generation system to be solved based on historical data is shown in fig. 3.
The invention provides a communication iron tower problem set generation method to be solved based on historical data, which comprises the following steps:
The system identifies index parameters and the number N of the index parameters which need to be detected by the communication tower, and the index parameters can include but are not limited to perpendicularity, stability, integrity, connection gaps, tower footing sinking and lightning grounding parameters. The system sets an importance value X of each index parameter (the importance of each index is set by experts or technicians in the field according to engineering experience, the value range is 0-M, the larger the value of X is, the more important the index parameter is), and a parameter importance matrix X is formed (X is the more important the index parameter is), wherein1,x2,x3,…,xN)。
And 2, acquiring sensor data at regular time and calculating a current problem coefficient matrix of the iron tower.
The method comprises the steps that sensors deployed on an iron tower synchronously acquire sensor data at fixed time (sampling interval is T), a system calculates the current problem coefficient a (the value range is 0-1, the higher the value of a is, the higher the severity is), of the iron tower, corresponding to the sensor data according to a preset current problem coefficient function of the iron tower, wherein the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience, and a current problem coefficient matrix A (a) is formed according to the sequence of index parameters (the sequence of each index parameter in a parameter importance matrix X)1,a2,a3,…,aN) where matrix a is an N × N diagonal matrix.
And 3, extracting parameter historical data and correcting the current problem coefficient matrix.
System extractionHistorical problem data of each index parameter is calculated through a preset historical problem coefficient function (the function is obtained by experts or technicians in the field by fuzzy mathematics according to engineering experience), a historical problem coefficient B (the value range is 0-1, the larger the value of B is, the higher the frequency and the severity of the problem history are), and a historical problem coefficient matrix B (B) is formed according to the sequence of the index parameters (the sequence of each index parameter in the parameter importance matrix X) to be diag (B)1,b2,b3,…,bN) the sum of the historical problem coefficient B and the current problem coefficient a forms the corrected problem severity coefficient diagonal matrix Y ═ a + B ═ diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) likewise, the matrix Y is also an N × N diagonal matrix.
And 4, calculating a problem severity matrix.
Problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiAnd i is more than or equal to 1 and less than or equal to N. The problem severity value z is obtained by multiplying the parameter importance value x and the corrected severity coefficient y corresponding to the index parameter.
And 5, arranging the severity of the problems and generating a problem set to be solved.
And (3) sequencing the elements in the matrix Z in a descending manner to obtain a matrix H (by adopting a corresponding function commonly used in MATLAB or other sequencing methods), sequencing the severity of the iron tower problems according to the iron tower problems corresponding to the elements in the matrix H, and generating a problem set to be solved with the severity sequencing. And generating a problem set to be solved of the communication tower based on historical data.
A method flowchart of a communication tower problem set generation method based on historical data is shown in fig. 4.
The system and method of the present invention have the following two advantages:
(1) the current problem coefficient of the iron tower is corrected by adopting historical problem data, so that the processing priority of historical frequent problems is improved.
(2) The iron tower problem severity matrix is obtained by calculating the iron tower index parameter importance matrix and the corrected problem severity coefficient matrix, so that the severity of the iron tower problem is accurately calculated, and the most severe iron tower problem is solved preferentially.
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FIG. 1 is a schematic diagram of an application scenario of the present invention;
FIG. 2 is an overall system architecture diagram of an application scenario of the present invention;
FIG. 3 is a system block diagram of the present invention;
FIG. 4 is a flow chart of a method of the present invention;
FIG. 5 is a graph of a verticality parameter severity coefficient calculation used in an embodiment of the present invention;
FIG. 6 is a graph of historical problem coefficient calculations used in an embodiment of the present invention.
Detailed Description
The following describes in detail preferred embodiments of the present invention.
The invention relates to an iron tower system application scene based on the Internet of things, which is shown in figure 1. Sensor equipment is installed at a fixed position of a communication iron tower, the sensor collects relevant parameters of the iron tower and transmits the relevant parameters to a system through a communication module, the system stores and processes the sensing data, and a client interacts with the system to obtain required information.
The overall system architecture of the iron tower system based on the internet of things is shown in fig. 2. The system hardware part comprises a communication iron tower and sensing equipment arranged on the tower body, and a communication module of the sensing equipment is communicated with the system in real time; the system software part comprises a system database, a data processing platform and a data management publishing platform, wherein the system database receives sensing data from the sensing equipment and stores all system logs, the data processing platform calls the data in the system database for processing and analysis, and the data management publishing platform receives data processing results of the data processing platform and corresponding records in the system database for management and publishing; the system application platform comprises management equipment and clients, wherein the management equipment comprises but is not limited to facilities such as workstations and computers, and the clients comprise but are not limited to forms of APP, WeChat, Html webpage and the like; the application personnel of the system include, but are not limited to, management personnel and maintenance personnel, and the interfaces of the system are management equipment and a client side respectively.
The implementation of the invention depends on the application scene and the system architecture, various sensors are arranged at certain positions of the tower body to detect corresponding parameters of the iron tower, and historical data of various iron tower problems are extracted from a system database. The embodiment of the method and the system of the invention is realized as follows:
the communication iron tower problem set generation system based on historical data comprises an iron tower parameter importance matrix setting module, a sensor data timing acquisition and iron tower current problem coefficient matrix calculation module, a parameter historical data extraction and current problem coefficient matrix correction module, a problem severity calculation module, a problem severity arrangement and generation module.
1. The iron tower parameter importance matrix setting module comprises: the system identifies index parameters and the number N of the index parameters to be detected of the communication iron tower, and in the embodiment, the 6 index parameters to be detected are arranged according to the sequence of perpendicularity, stability, integrity, connection gaps, tower footing sinking and lightning protection grounding. The system sets an importance value X of each index (the importance of each index is set by experts or technicians in the field according to engineering experience, the value range is 0-M, the larger the value of X is, the more important the index parameter is), in this embodiment, M is 10, and an importance matrix X is formed (X is1,x2,x3,…,xN)＝(10,10,9,8,8,6)。
2. The module is used for acquiring sensor data regularly and calculating the coefficient matrix of the current problem of the iron tower: the method comprises the steps that sensor data are synchronously acquired at fixed time (sampling interval is T) by each sensor deployed on an iron tower, a system calculates a current problem coefficient value a (the value range is 0-1, the larger the value of a is, the higher the severity is), corresponding to the sensor data, according to a preset current problem coefficient function (the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience) of each index parameter, and a problem severity coefficient matrix A (a is) is formed1,a2,…,aN) for example, fig. 5 is a graph diagram corresponding to the current problem coefficient function of the perpendicularity in this embodiment (the function is visually displayed by using the graph diagram), the abscissa is the inclination data value detected by the sensor, the ordinate is the current problem coefficient of the perpendicularity, and the current problem coefficients of the other index parameters are similarly calculated.
3. A module for extracting parameter historical data and correcting the coefficient matrix of the current problem: the system extracts historical problem data of each index parameter, calculates a historical problem coefficient B (the value range is 0-1, the larger the value of B is, the higher the historical occurrence frequency of the problem is) through a preset historical problem coefficient function (the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience), and forms a historical problem coefficient matrix B (a flag (B) according to the sequence of the index parameters (the sequence of each index parameter in the parameter importance matrix X)1,b2,b3,…,bN) the sum of the historical problem coefficient B and the current problem coefficient a forms the corrected problem severity coefficient diagonal matrix Y ═ a + B ═ diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) for example, fig. 6 is a graph diagram corresponding to the history problem coefficient function of the present embodiment (the function is visually displayed using the graph diagram), the abscissa is the number of times that the index history has a problem (more than 10 times, which is expressed as 10 times), and the ordinate is the history problem coefficient, in this embodiment, the number of times that each parameter history problem has occurred is (2,0,1,0,4,3), and then the history problem coefficient matrix B is calculated from the function shown in fig. 6 to obtain the history problem coefficient matrix B (0.3,0,0.15,0,0.8,0.5), and the corrected problem severity coefficient matrix Y is a + B (Y + B) which is diag (Y)1,y2,y3,…,yN)＝diag(1,0.1,0.65,0.2,0.8,0.5)。
4. A calculate problem severity matrix module: problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiAnd i is more than or equal to 1 and less than or equal to N. The problem severity value z is obtained by multiplying the parameter importance value x and the problem severity coefficient y corresponding to the parameter after correction. In this example, Z ═ X · Y ═ (10,1,5.85,1.6,6.4, 3).
5. And the problem severity ranking module generates a problem set to be solved: and (3) sequencing the elements in the matrix Z in a descending manner to obtain a matrix H (by adopting a corresponding function commonly used in MATLAB or other sequencing methods), sequencing the severity of the iron tower problems according to the iron tower problems corresponding to the elements in the matrix H, and generating a problem set to be solved. In this embodiment, matrix Z is sorted in descending order by using the sort function in MATLAB, that is, H ═ sort (Z, 'descan') (10,6.4,5.85,3,1.6,1), and if the iron tower problem corresponding to each element in matrix H is identified, the severity of the iron tower problem is sorted as follows: the problem set to be solved with the problem severity order generated is the problem set { perpendicularity, tower footing subsidence, integrity, lightning grounding, non-maintenance personnel going to the tower, connection structure gap, stability }.
The invention provides a communication iron tower problem set generation method to be solved based on historical data, which comprises the following steps:
The system identifies index parameters and the number N of the index parameters to be detected of the communication iron tower, and in the embodiment, the 6 index parameters to be detected are arranged according to the sequence of perpendicularity, stability, integrity, connection gaps, tower footing sinking and lightning protection grounding. The system sets an importance value X of each index according to a certain order (the importance of each index is set by experts or technicians in the field according to engineering experience, the value range is 0-M, the larger the value of X is, the more important the index parameter is), in this embodiment, M is 10, and an importance matrix X is formed (X is1,x2,x3,…,xN)＝(10,10,9,8,8,6)。
And 2, acquiring sensor data at regular time and calculating a current problem coefficient matrix of the iron tower.
The method comprises the steps that sensor data are synchronously acquired at fixed time (sampling interval is T) by each sensor deployed on an iron tower, a system calculates a current problem coefficient value a (the value range is 0-1, the larger the value of a is, the higher the severity is), corresponding to the sensor data, according to a preset current problem coefficient function (the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience) of each index parameter, and a problem severity coefficient matrix A (a is) is formed1,a2,…,aN) for example, fig. 5 is a graph diagram corresponding to the current problem coefficient function of the perpendicularity in this embodiment (the function is visually displayed by using the graph diagram), the abscissa is the inclination data value detected by the sensor, the ordinate is the current problem coefficient of the perpendicularity, and the current problem coefficients of the other index parameters are similarly calculated.
And 3, extracting parameter historical data and correcting the current problem coefficient matrix.
The system extracts historical problem data of each index parameter, calculates a historical problem coefficient B (the value range is 0-1, the larger the value of B is, the higher the historical occurrence frequency of the problem is) through a preset historical problem coefficient function (the function is obtained by experts or technicians in the field by adopting fuzzy mathematics according to engineering experience), and forms a historical problem coefficient matrix B (a flag (B) according to the sequence of the index parameters (the sequence of each index parameter in the parameter importance matrix X)1,b2,b3,…,bN) the sum of the historical problem coefficient B and the current problem coefficient a forms the corrected problem severity coefficient diagonal matrix Y ═ a + B ═ diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) for example, fig. 6 is a graph diagram corresponding to the history problem coefficient function of the present embodiment (the function is visually displayed using the graph diagram), the abscissa is the number of times that the index history has a problem (more than 10 times, which is expressed as 10 times), and the ordinate is the history problem coefficient, in this embodiment, the number of times that each parameter history problem has occurred is (2,0,1,0,4,3), and then the history problem coefficient matrix B is calculated from the function shown in fig. 6 to obtain the history problem coefficient matrix B (0.3,0,0.15,0,0.8,0.5), and the corrected problem severity coefficient matrix Y is a + B (Y + B) which is diag (Y)1,y2,y3,…,yN)＝diag(1,0.1,0.65,0.2,0.8,0.5)。
And 4, calculating a problem severity matrix.
Problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiAnd i is more than or equal to 1 and less than or equal to N. The problem severity value z is obtained by multiplying the parameter importance value x and the problem severity coefficient y corresponding to the parameter after correction. In this example, Z ═ X · Y ═ (10,1,5.85,1.6,6.4, 3).
And 5, arranging the severity of the problems and generating a problem set to be solved.
And (3) sequencing the elements in the matrix Z in a descending manner to obtain a matrix H (by adopting a corresponding function commonly used in MATLAB or other sequencing methods), sequencing the severity of the iron tower problems according to the iron tower problems corresponding to the elements in the matrix H, and generating a problem set to be solved. In this embodiment, matrix Z is sorted in descending order by using the sort function in MATLAB, that is, H ═ sort (Z, 'descan') (10,6.4,5.85,3,1.6,1), and if the iron tower problem corresponding to each element in matrix H is identified, the severity of the iron tower problem is sorted as follows: the problem set to be solved with the problem severity order generated is the problem set { perpendicularity, tower footing subsidence, integrity, lightning grounding, non-maintenance personnel going to the tower, connection structure gap, stability }. And generating a problem set to be solved of the communication tower based on historical data.
Of course, those skilled in the art should realize that the above embodiments are only used for illustrating the present invention, and not as a limitation to the present invention, and that the changes and modifications of the above embodiments will fall within the protection scope of the present invention as long as they are within the scope of the present invention.
Claims (2)
1. The communication iron tower problem set generation system to be solved based on historical data is characterized by comprising an iron tower parameter importance matrix setting module, a sensor data timing acquisition and iron tower current problem coefficient matrix calculation module, a parameter historical data extraction and current problem coefficient correction matrix correction module, a problem severity calculation module, a problem severity arrangement module and a problem set generation module to be solved;
the iron tower parameter importance matrix setting module is characterized in that: the system identifies index parameters and the number N of the index parameters to be detected of the communication iron tower, sets the importance value X of each index parameter, and forms a parameter importance matrix X ═ X1,x2,x3,…,xN)；
The module for regularly collecting sensor data and calculating the current problem coefficient matrix of the iron tower is characterized in that: the method comprises the steps that sensors deployed on an iron tower synchronously acquire sensor data at regular time, then a system calculates the current problem coefficient a of the iron tower corresponding to the sensor data according to a preset current problem coefficient function of the iron tower, and a current problem coefficient matrix A (a) is formed according to the sequence of index parameters1,a2,a3,…,aN) wherein the matrix A is an N multiplied by N diagonal matrix;
the module for extracting parameter historical data and correcting the current problem coefficient matrix is characterized in that: the system extracts the historical problem data of each index parameter, calculates the historical problem coefficient B through the preset historical problem coefficient function, and forms a historical problem coefficient matrix B which is diag (B) according to the sequence of the index parameters1,b2,b3,…,bN) the matrix B is a diagonal matrix of NXN, and the sum of the historical problem coefficient B and the current problem coefficient a forms the corrected problemThe weight coefficient diagonal matrix Y ═ a + B ═ diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) the matrix Y is also an N × N diagonal matrix;
the calculate problem severity matrix module is characterized by: problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiI is more than or equal to 1 and less than or equal to N, and the problem severity value z is obtained by multiplying the parameter importance value x and the corrected severity coefficient y corresponding to the index parameter;
the module for ranking the severity of the problem and generating the problem set to be solved is characterized in that: and (4) sequencing all the elements in the matrix Z in a descending manner to obtain a matrix H, sequencing the severity of the iron tower problems according to the iron tower problems corresponding to all the elements in the matrix H, and generating a problem set to be solved with the severity sequencing.
2. The method for generating the problem set to be solved of the communication tower based on historical data is characterized by comprising the following steps of:
step 1, setting an iron tower parameter importance matrix;
the system identifies index parameters and the number N of the index parameters to be detected of the communication iron tower, sets the importance value X of each index parameter, and forms a parameter importance matrix X ═ X1,x2,x3,…,xN)；
Step 2, collecting sensor data at regular time and calculating a current problem coefficient matrix of the iron tower;
the method comprises the steps that sensors deployed on an iron tower synchronously acquire sensor data at regular time, then a system calculates the current problem coefficient a of the iron tower corresponding to the sensor data according to a preset current problem coefficient function of the iron tower, and a current problem coefficient matrix A (a) is formed according to the sequence of index parameters1,a2,a3,…,aN) wherein the matrix A is an N multiplied by N diagonal matrix;
step 3, extracting parameter historical data and correcting a current problem coefficient matrix;
the system extracts the historical problem data of each index parameter, calculates the historical problem coefficient B through the preset historical problem coefficient function, and forms a historical problem coefficient matrix B which is diag (B) according to the sequence of the index parameters1,b2,b3,…,bN) the matrix B is an N multiplied by N diagonal matrix, the sum of the historical problem coefficient B and the current problem coefficient a forms a corrected problem severity coefficient diagonal matrix Y which is A + B diag (Y)1,y2,y3,…,yN)＝diag(a1+b1,a2+b2,a3+b3,…,aN+bN) the matrix Y is also an N × N diagonal matrix;
step 4, calculating a problem severity matrix;
problem severity matrix Z ═ X · Y ═ Z1,z2,z3,…,zN) Wherein z isi＝xi·yiI is more than or equal to 1 and less than or equal to N, and the problem severity value z is obtained by multiplying the parameter importance value x set in the step 1 by the severity coefficient y corrected in the step 2 corresponding to the index parameter;
step 5, arranging the severity of the problems and generating a problem set to be solved;
and (4) sequencing all the elements in the matrix Z in a descending manner to obtain a matrix H, sequencing the severity of the iron tower problems according to the iron tower problems corresponding to all the elements in the matrix H, and generating a problem set to be solved with the severity sequencing.
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| CN108388984A (en) * | 2018-02-10 | 2018-08-10 | 杭州后博科技有限公司 | Based on inspection project steel tower patrol plan method of adjustment of problems and system |
| CN108346001A (en) * | 2018-02-10 | 2018-07-31 | 杭州后博科技有限公司 | A kind of steel tower regular visit project order method of adjustment and system |
| CN108416469B (en) * | 2018-02-10 | 2021-02-02 | 杭州后博科技有限公司 | Method and system for predicting potential safety hazard of iron tower caused by extreme weather |
| CN108416510B (en) * | 2018-02-10 | 2021-04-27 | 杭州后博科技有限公司 | Iron tower inspection task list real-time adjustment method and system |
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