CN112016206A - Method and system for judging instability state of tower, computer equipment and application - Google Patents
Method and system for judging instability state of tower, computer equipment and application Download PDFInfo
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Abstract
The invention belongs to the technical field of tower state monitoring, and discloses a method, a system, computer equipment and application for judging a tower instability state through a structural mechanics data model, wherein an original swing angle value set is obtained based on a specified time window; calculating a unit time swing center value set; calculating a motion speed change set according to the swing center value set data; constructing a structural mechanics data model, identifying mutation points according to speed change, identifying the mutation points by using a movement speed change set, extracting and analyzing data after data filtering according to tower operation big data, and respectively selecting the states of a homotypic normal tower and a destabilizing tower for comparison to obtain the distribution range of abnormal variation values; and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state. The method analyzes abnormal characteristics caused by the structural state change of the tower and accurately identifies the internal potential safety hazard of the tower in the unstable state.
Description
Technical Field
The invention belongs to the technical field of tower state monitoring, and particularly relates to a method, a system, computer equipment and application for judging a tower instability state through a structural mechanics data model.
Background
At present, along with the rapid development of domestic economy, a large number of various towers are built in the basic industries such as communication, electric power and the like and are used for bearing communication equipment, electric power transmission cables and the like, and if the electric power iron tower and the high-rise towers in other industries are added into a counting range, the number is larger. With the deployment and operation of a large number of towers, the safety problem of the towers is increasingly prominent under the action and influence of various factors such as time factors, natural factors, human factors, load change factors and the like, and particularly becomes important for safety prevention in three-high areas represented by high-speed lines, high-speed lines and personnel-dense areas. In view of the current situation of tower safety guarantee, a manager also begins to provide new requirements for safety management, and the method mainly comprises two aspects, namely, on one hand, the tower is monitored in real time by adopting the technology of internet of things, and passive safety protection is changed into active safety protection; the second aspect is that the technical means is applied, which towers are accurately analyzed and judged to lose the stable state, so that the dangerous towers are accurately rectified and processed in advance, and the post-processing after accidents are avoided. In order to meet and solve the new requirements of tower safety protection, the decision technology of tower safety detection is also increasingly concerned. In recent years, related professionals propose various methods for detecting the tower state, and the methods are different in implementation, operation details and the like, but the core principle of the method is to determine whether the tower state is normal by using a method for judging whether the tower inclination angle exceeds a normal range. The method comprises the steps of performing weighted calculation by using an inclination angle and an original inclination angle in a corresponding area to obtain a final inclination angle of the corresponding area, and constructing an environment state space by using environment parameters, so that each iron tower inclination state can be analyzed based on a corresponding environment parameter value, thereby accurately judging the state of the iron tower (the invention is different from the invention of the method and the system for detecting the iron tower state, and an inventor of the invention comprises Liuyang, Yangyuan and Yuanyuan). The tower state obtained based on the mechanics and the model of the measurement can only be the current tower state metering value, and the essential working condition state of the tower cannot be accurately reflected. If the system mode is obtained in a manual mode and a system mode, the system mode can only be a time point value, and the system mode has extremely limited significance for engineering protection of the tower.
Researches find that the tower in the actual operation environment is influenced by various factors such as time factors, natural factors, human factors, load change factors, the tower body factors and the like, the superposition of the factors causes the tower to present a non-static and constantly-swinging state, the intuitive expression is that the inclination angle of the tower is changed constantly, the change range of the inclination angle is closely related to the characteristics of the material, external wind power, external vibration, sunlight irradiation, temperature change, corrosion, connection looseness, foundation subsidence and other factors, and different combinations can generate different influences on the value of the inclination angle, so that the change of the inclination angle of the tower is only the expression of the tower state, and the quality state of the tower structure cannot be completely reflected. The existing method based on the tower inclination angle standard exceeding judgment principle can only partially show the state of the tower at a certain moment, and cannot judge whether the state is caused by the change of external factors or the abnormity (instability) of the tower, even if the invention has environmental parameters for reference, the combination of the environmental parameters is complicated and changeable, and the determination of the effective threshold value is a work which is difficult to ensure the accuracy and verify, so the existing method cannot accurately judge whether the state of the tower is stable. Through the above analysis, the problems and defects of the prior art are as follows: the potential safety hazard of the tower cannot be accurately identified through the change of the inclination angle of the tower, which is the most important and difficult technical subject at present.
The difficulty in solving the above problems and defects is:
as mentioned above, the tower is in a complex environment, both internal and external factors can induce the change of the tower state, and under such a complex condition, it is difficult to accurately identify the condition that the inclination angle exceeds the standard due to corrosion, loose connection, sinking of the foundation and other factors. The prior art mechanisms based on measurements only see the appearance of the problem and cannot find the nature of the tower operating conditions. Therefore, the method based on measurement is used singly to judge that the working stability of the tower structure is damaged, a strong basis is lacked, whether the tower is influenced by external factors or the tower body structure is damaged is judged, the tower cannot be calculated by only the inclination angle, and the essential state of the tower cannot be reflected, but the judgment of the state is the most technical subject to be solved.
The significance of solving the problems and the defects is as follows:
therefore, the judgment of the unstable operation state of the tower needs to add an innovative 'structural mechanics data model' technical mechanism and method on the basis of the existing judgment method principle to analyze the abnormal characteristics caused by the structural state change of the tower, so as to accurately identify the internal potential safety hazard of the unstable state of the tower. The system depending on the new judgment method becomes an initial system for analyzing the instability state of the tower, meets new requirements and core requirements of a tower management party, becomes a new tool for safety control of tower management, and achieves theoretical innovation, technical innovation, method innovation and application innovation.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method, a system, computer equipment and application for judging the instability state of a tower through a structural mechanics data model.
The invention is realized in such a way that a method for judging the instability state of the tower through a structural mechanics data model comprises the following steps:
acquiring an original swing angle value set based on a specified time window;
calculating a unit time swing center value set;
calculating a motion speed change set according to the swing center value set data;
constructing a structural mechanics data model, identifying mutation points according to speed change, identifying the mutation points by using a movement speed change set, extracting and analyzing data after data filtering according to tower operation big data, and respectively selecting a homotypic normal tower and a destabilizing tower for comparison to obtain a distribution range of abnormal variation values;
and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state.
Further, the method for judging the tower instability state through the structural mechanics data model realizes the judgment of the tower instability state through analyzing the sudden change condition of the tower movement speed transformation curve in the appointed time window.
Further, the original swing angle value set is obtained based on the specified time window, swing data x and y of the detection tower in the TT time are obtained through a front device, and the unit of { TT |1 is not less than TT and not more than 30 }: day; x and Y are X-axis swing angle and Y-axis swing angle respectively, and an original swing angle value set is constructed:
t actual acquisition time.
Further, the unit time swing center value set is calculated, the obtained original swing angle value set data are grouped according to the minute level T, the swing center value ST of unit time T1-Tm is calculated, and the algorithm formula is as follows:
k is the number of monitoring data in unit time, and through the data calculation in the process, the original data set is sorted into the swing center value set in the following form:
further, the motion speed change set is calculated according to the swing center value set data, and an algorithm formula W is ST-ST-1And performing data conversion on the swing center value set, wherein S is the swing center value, and { T | T1 is more than or equal to T and less than or equal to Tm }, and obtaining the following movement speed change set:
t unit time.
Further, the movement speed change mutation point identification is carried out by using a movement speed change set, the mutation point identification adopts different thresholds a and a |0.13 ≤ a ≤ 0.8} according to different tower types, the threshold a is a key mutation point judgment value of an algorithm, the mutation judgment values of different tower types are different, according to tower operation big data and data extraction and analysis after data filtration, a homotypic normal tower and a destabilization tower are respectively selected for comparison to obtain the distribution range of abnormal variation values, and the movement speed change set data extraction is carried out according to W > ═ a to form a mutation point data set;
and finally judging the stable state by calculating whether the number of the catastrophe points in the TT time period exceeds a judgment threshold value M, { M |3 is less than or equal to M and less than or equal to 5}, and judging the tower exceeding the M threshold value as the unstable state. And (3) judging that the nature of the threshold M is the maximum allowable value of the catastrophe point of the specified time window, and obtaining different value intervals of the values presented in the maximum and minimum time window ranges according to the extraction, comparison and analysis of the operation big data of the homotypic normal tower and the instability tower.
It is a further object of the invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:
acquiring an original swing angle value set based on a specified time window;
calculating a unit time swing center value set;
calculating a motion speed change set according to the swing center value set data;
identifying a speed change mutation point, identifying the mutation point by using a motion speed change set, extracting and analyzing data after data filtering according to tower operation big data, and respectively selecting a homotypic normal tower and a destabilization tower for comparison to obtain a distribution range of an abnormal variation value;
and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state.
Another object of the present invention is to provide a system for determining a tower unstable state, which implements the method for determining a tower unstable state by a structural mechanics data model, the system for determining a tower unstable state including:
the original swing angle value set acquisition module is used for acquiring an original swing angle value set based on a specified time window;
the unit time swing center value set calculating module is used for calculating a unit time swing center value set;
the motion speed change set calculation module is used for calculating a motion speed change set according to the swing center value set data;
the catastrophe point identification module is used for identifying catastrophe points by using the movement speed change set, and respectively selecting a homotypic normal tower and a homotypic instability tower for comparison according to tower operation big data and data extraction and analysis after data filtration to obtain the distribution range of abnormal variation values;
and the instability state judgment module is used for finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, and the tower exceeding the threshold value is judged to be in the instability state.
Further, the system for determining the tower instability state further comprises:
the data acquisition device is internally provided with a posture chip and is used for acquiring real-time swing data of the tower, wherein the real-time swing data comprises an X-axis swing angle, a Y-axis swing angle and wind speed information;
the data acquisition device sends the obtained swing data to a system data cloud service through the 4G communication module, and the transmission data is sent in an internal agreed message format;
a data receiving interface program built in the data cloud service is responsible for receiving messages, and the message content is analyzed through a message analyzer to obtain an X-axis swing angle, a Y-axis swing angle and wind speed information;
the data receiving interface program submits the analyzed original swing data to a data storage warehouse management system, and the data storage warehouse completes physical storage of data cloud;
the method comprises the steps that a system-level timer is built in a computing cloud service, the working period of the timer is configured according to the setting of system parameters, when the starting time of the timer is up, the timer is started by a system, all tower information to be analyzed is extracted, a judgment algorithm is executed on each tower until all towers are analyzed, and the operation of the timer is stopped;
the instability judgment algorithm arithmetic unit software module extracts original tower swing angle information, sequentially carries out data sorting and calculation according to five processes defined by an algorithm, finally gives a judgment result, and submits the judgment result to a data storage warehouse for physical storage;
calculating an external service interface program in the cloud service, obtaining formed judgment result information by accessing data storage warehouse data, forming alarm information according to the judgment result, and preparing the alarm information sent to a corresponding terminal according to the terminal deployment condition;
the external service interface program issues the alarm information to the designated terminal;
and the terminal software acquires corresponding alarm information and presents the alarm information to a user, and the user performs corresponding treatment on the specified tower according to the alarm condition.
Another object of the present invention is to provide a tower state detection method for a carrier communication device and a power transmission cable, which uses the tower instability state determination system according to claim 8.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the method, the abnormal characteristics caused by the structural state change of the tower are analyzed through a new judgment method, and the internal potential safety hazard of the instability state of the tower is accurately identified. The system based on the new judgment method meets the new requirements and core appeal of a tower management party, becomes a new tool for safety control of tower management, and truly achieves the purposes of accurately replacing fuzziness and abandoning the appearance recognition essence.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
FIG. 1 is a flowchart of a method for determining a tower instability state through a structural mechanics data model according to an embodiment of the present invention.
FIG. 2 is a schematic structural diagram of a tower instability state determination system provided by an embodiment of the present invention;
in fig. 2: 1. an original swing angle value set acquisition module; 2. a unit time swing center value set calculation module; 3. a motion speed change set calculation module; 4. a mutation point identification module; 5. and a destabilization state determination module.
FIG. 3 is a schematic diagram of a method for determining a tower instability state through a structural mechanics data model according to an embodiment of the present invention.
Fig. 4 is a flowchart of a determination method according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of a system for determining a tower instability condition provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a method, a system, a computer device and an application for determining a tower instability state through a structural mechanics data model, and the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the method for determining the tower instability state through the structural mechanics data model provided by the present invention includes the following steps:
s101: acquiring an original swing angle value set based on a specified time window;
s102: calculating a unit time swing center value set;
s103: calculating a motion speed change set according to the swing center value set data;
s104: identifying a mutation point by using a movement speed change set, extracting and analyzing data after filtering according to tower operation big data and the data, and respectively selecting a homotypic normal tower and a destabilizing tower for comparison to obtain a distribution range of an abnormal variation value;
s105: and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state.
The method for determining the tower instability state through the structural mechanics data model provided by the invention can also be implemented by other steps by persons skilled in the art, and the method for determining the tower instability state through the structural mechanics data model provided by the invention in fig. 1 is only one specific embodiment.
As shown in fig. 2, the system for determining a tower instability state provided by the present invention includes:
an original swing angle value set acquisition module 1, configured to acquire an original swing angle value set based on a specified time window;
the unit time swing central value set calculating module 2 is used for calculating a unit time swing central value set;
the movement speed change set calculation module 3 is used for calculating a movement speed change set according to the swing center value set data;
the catastrophe point identification module 4 is used for identifying catastrophe points by using the movement speed change set, and respectively selecting a homotypic normal tower and a homotypic instability tower for comparison according to tower operation big data and data extraction and analysis after data filtration to obtain a distribution range of abnormal variation values;
and the instability state judgment module 5 is used for finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, and the tower exceeding the threshold value is judged to be in the instability state.
The technical solution of the present invention is further described below with reference to the accompanying drawings.
According to the defects of the prior art, the invention abandons the judgment principle of comparing the swing angle with the threshold value, and provides a new method for judging the instability state of the tower. The schematic diagram is shown in fig. 3.
According to structural mechanics, under the condition that the tower structure is stable, the structural body stress presents a stable change state in the working environment range, so that a smooth and uniform motion speed change curve is ensured to present in the tower motion, even under the influence of factors such as strong wind and the like, the swing amplitude of the tower is only increased, and the motion speed change curve is not damaged, but when the internal structure of the tower is changed, such as under the conditions of screw loosening, material loss, foundation subsidence and the like, the motion speed change curve at the moment can present abnormal 'sudden change burrs', and according to the distribution state of the 'sudden change burrs', the invention can accurately determine whether the tower is subjected to substantial motion change, loses the original stable state and becomes the tower in the unstable state.
1. Determination method
Based on the above principle description, to implement the method for determining the tower instability state through the structural mechanics data model, the calculation and determination are performed in 5 processes, and a process block diagram is shown in fig. 4.
In the flow chart, the 1 st to 3 rd processes are data sorting processes, the 4 th process is an abnormal data extraction process, and the 5 th process is a judgment process. The following describes in detail the algorithms and processes involved in each process.
Process 1: a set of raw swing angle values is obtained based on a specified time window. Swing data X and Y (X and Y are an X-axis swing angle and a Y-axis swing angle respectively) of the detection tower in TT time ({ TT |1 is not less than TT is not more than 30, unit: day) are obtained through a front device, and an original swing angle value set is constructed:
t actual acquisition time
And (2) a process: computingA set of unit time swing center values. Using the original swinging angle value set data obtained in the process 1, grouping the data in the set according to the minute level (T), and calculating the swinging center value ST in unit time (T1-Tm), wherein the algorithm formula is as follows:
(where k is the number of monitored data per unit time), the raw data set is sorted into a set of wobble center values in the form described below by this process data calculation.
And 3, process: and calculating a motion speed change set according to the swing center value set data. According to the formula W ═ ST-ST-1(S is a swing center value, { T | T1 ≦ T ≦ Tm }) the set of swing center values is subjected to data conversion, and the following set of motion speed variations can be obtained.
T unit time
And 4, process: and identifying the motion speed change catastrophe points. The method comprises the steps of identifying catastrophe points by using a motion speed change set, adopting different threshold values a ({ a |0.13 is less than or equal to a and less than or equal to 0.8}) according to different tower types, wherein the threshold value a is a key catastrophe point judgment value of an algorithm, the catastrophe judgment values of different tower types are different, and respectively selecting a homotypic normal tower and a destabilization tower for comparison according to tower operation big data and data extraction and analysis after data filtration to obtain the distribution range of the abnormal variation values. Based on the above, the motion speed change set data is extracted according to W ═ a, and the mutation point data set can be formed.
And (5) a process: and (5) judging a conclusion of the instability state. The unstable state judgment is the final process of the method, the stable state is finally judged by calculating whether the number of the catastrophe points in the TT time period exceeds a judgment threshold value M ({ M |3 is less than or equal to M and less than or equal to 5}), and the tower exceeding the M threshold value is judged to be the unstable state. And (3) judging that the nature of the threshold M is the maximum allowable value of the catastrophe point of the specified time window, and obtaining different value intervals of the value presented in the range of the maximum and minimum time windows according to the extraction, comparison and analysis of the large operation data of the homotypic normal tower and the instability tower.
2. System implementation
For effective application of the tower instability state determination method, the system combines an IOT mode to complete the implementation scheme, and adopts an advanced mode of a preposed data acquisition terminal and a cloud computing system (including a determination algorithm), and a schematic diagram is shown in FIG. 5.
The system implementation mainly comprises 9 processes, which are specifically described as follows:
process 1: and (6) data acquisition. And an attitude chip arranged in the data acquisition device acquires real-time swing data of the tower, and the data mainly comprises information such as an X-axis swing angle, a Y-axis swing angle and wind speed.
And (2) a process: and (6) data transmission. The data acquisition device sends the obtained swing data to a system data cloud service through the 4G communication module, and the transmission data are sent in an internal agreed message format.
And 3, process: and receiving data. And a data receiving interface program built in the data cloud service is responsible for receiving the message, and the message content is analyzed through a message analyzer to obtain information such as the X-axis swing angle, the Y-axis swing angle and the wind speed.
And 4, process: and (4) storing data. And the data receiving interface program submits the analyzed original swing data to a data storage warehouse management system, and the data storage warehouse completes physical storage of the data cloud.
And (5) a process: and polling a timer. The method comprises the steps that a system-level timer is built in a computing cloud service, the working period of the timer is configured according to the setting of system parameters, when the starting time of the timer is up, the timer is started by the system, all tower information to be analyzed is extracted, a judgment algorithm is executed on each tower, and the operation of the timer is stopped until all towers are analyzed.
And 6, a process: the data is analyzed. And the instability judgment algorithm arithmetic unit software module extracts the original tower swing angle information, sequentially carries out data sorting and calculation according to five processes defined by the algorithm, finally gives a judgment result, and submits the judgment result to a data storage warehouse for physical storage.
And (7) a process: and acquiring push information. And an external service interface program in the cloud service is calculated, formed judgment result information is obtained by accessing data storage warehouse data, alarm information is formed according to the judgment result, and the alarm information sent to the corresponding terminal is prepared according to the terminal deployment condition.
And (8) a process: and pushing an alarm. And the external service interface program issues the alarm information to the appointed terminal.
And a process 9: and acquiring an alarm. And the terminal software acquires the corresponding alarm information and presents the alarm information to the user. And the customer carries out corresponding treatment on the specified tower according to the alarm condition.
By implementing the process, the system applying the method can complete real-time analysis of the attitude of the tower to be detected only by executing the algorithm regularly, accurately analyze the steady state change condition of all the towers to be detected, and distinguish the tower with the instability state among a plurality of towers.
The technical effects of the present invention will be described in detail with reference to experiments.
The invention provides a brand-new tower instability state determination method aiming at the problems in the traditional method for determining the tower state based on the inclination angle. Compared with the traditional method, the method has the following three advantages and application effects.
1. The unstable tower is accurately judged
The method has the advantage of accurately capturing the intrinsic instability change of the tower because the instability state caused by the change of the internal factors of the tower is judged instead of the judgment of the instability of the tower through the exceeding of the swing amplitude. In order to verify the advantage, the system applying the method analyzes and calculates 30 communication towers monitored on line in a certain city, 30 tower judgment results are given, comparison is carried out on the results of on-site inspection by professionals, and finally the algorithm judgment is verified to be consistent with the actual state and accurate in judgment.
Raw data and decision results as shown in table 1:
the data in table 1 are monitored data from month 1 in 2019 to month 5 in 2020.
According to the verification, 30 towers are selected, obtained 14958183-minute data are calculated and judged according to the method, 3 towers are judged to be in a destabilization state, the towers are obviously distorted at joint joints through field investigation of professionals, and the tower body has safety problems, so that the judgment of the 3 towers is proved to be in line with reality, and the accuracy of the method is verified. The rest 27 towers basically work normally in field investigation, and the tower body is not abnormal. In the period, the tower of the eastern side apartment building in the new treasure in the city with the inclination angle exceeding the threshold is especially selected for verification, although the tower has problems according to the judgment standard of the prior art, the tower body is found to be stable through field investigation, the case additionally verifies that certain false alarm phenomenon exists by using the prior art for judgment, and the method of the invention also proves the accuracy of the judgment of the instability of the tower. Therefore, compared with the existing method, the method has the advantage of more accurate judgment.
2. Zero modeling difficulty
The existing method carries out modeling according to environmental factors, which requires that the model is highly matched with the actual environment, and needs to carry out combined modeling according to factors such as regions, sunlight, wind power, tower types, installation environments and the like, so that the model is complex to establish and has long consumption period. The method of the invention is a model built by the intrinsic law of the tower, the tower in the stable state can present an intrinsic stable change model no matter under any external environment, and the tower in the stable state can follow the data model of the stable change even if the swing amplitude exceeds the standard. Therefore, the method provided by the invention grasps the intrinsic change rule of the tower during modeling, and is a universal and unified model, so that the modeling work is concentrated on the method, model details are not required to be concerned during application, and the method has the advantage of zero modeling difficulty compared with the existing method.
3. Good problem tower prevention effect
In the traditional method, the tower abnormity is judged when the inclination exceeds the standard, but the stability of the tower is damaged before days and months, and the tower cannot be shown until the induction condition is generated, or the tower can be a superposition effect caused by the combination of a plurality of factors, and the tower is not changed in stability, and in any case, the system applying the existing method cannot well meet the pre-prevention requirement of the unstable tower. The system of the method ensures the capability of finding and early warning at the first time once the tower foundation and the tower are in the instability state, is efficient and accurate, provides sufficient pretreatment time for a tower manager, really has the capability of preventing the instability tower in advance, and brings good application effect.
The software and hardware system applying the invention is successfully deployed and applied in iron tower companies. The system deployment and application goes through five stages:
the first stage is as follows: and determining and monitoring the communication tower and installing the communication tower. On the basis of meeting the communication requirements of 4G full networks and full systems, 30 sets of data acquisition units which are deployed and used are respectively installed on iron towers in the range of 7 counties and districts in total of 5 tower types, and typical iron towers and typical areas in the district of a certain iron tower company are covered.
And a second stage: system deployment and initial commissioning. And the early warning cloud platform and the deployment equipment perform joint debugging of initial data, relevant personnel input basic data for the system, and initial monitoring data of the equipment are corrected. And the system APP is deployed to the designated maintenance personnel and starts to receive the system monitoring data.
And a third stage: the system is operated on line. The whole system receives terminal monitoring data in real time, judges the instability state of the iron tower according to the invention algorithm, and pops up an alarm information popup window on the monitoring terminal of the system in time for the discovered instability iron tower to inform a monitoring center worker. Meanwhile, in a mobile phone APP of a maintenance representative, alarm information is synchronously displayed. And the related personnel arrange and process in time after receiving the alarm information.
A fourth stage: and (6) analyzing the data. The online of the system is accumulated for more than 500 days, more than 2 hundred million pieces of monitoring data are acquired, and after multidimensional analysis is carried out by acquiring the data, abundant and high-value analysis reports are provided for a manager, so that effective help is provided for the safety management of the iron tower.
The fifth stage: and (4) commercial acceptance. In the acceptance check, a certain iron tower company applying the system highly evaluates the system, and obtains good application effect in a plurality of practical application scenes such as detection of iron tower verticality, iron tower safety early warning, abnormal shaking monitoring, prevention of unauthorized tower climbing operation, guidance of iron tower correction and the like, and provides a corresponding acceptance report.
Therefore, the system applying the method plays a great role in practice, and is approved by the user only after being more suitable for the core requirements of the user according to higher accuracy in practical application compared with the traditional method.
The method of the invention fundamentally realizes the identification mode of the tower instability state, is not limited to instantaneous judgment on points, and can analyze the intrinsic essential change of the tower, extract the essential data from complex external factors, and reflect the state of the tower more truly.
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for judging the instability state of a tower through a structural mechanics data model is characterized by comprising the following steps:
acquiring an original swing angle value set based on a specified time window;
calculating a unit time swing center value set;
calculating a motion speed change set according to the swing center value set data;
constructing a structural mechanics data model, identifying mutation points according to speed change, identifying the mutation points by using a movement speed change set, extracting and analyzing data after data filtering according to tower operation big data, and respectively selecting the states of a homotypic normal tower and a destabilizing tower for comparison to obtain the distribution range of abnormal variation values;
and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state.
2. The method for determining the tower instability state through the structural mechanics data model of claim 1, wherein the method for determining the tower instability state through the structural mechanics data model achieves the determination of the tower instability state by analyzing the tower motion speed transformation curve abrupt change condition within a specified time window.
3. The method for determining the unstable state of the tower through the structural mechanics data model according to claim 1, wherein the original swing angle value set is obtained based on the specified time window, swing data x and y of the tower in TT time are obtained through a front-end device, and the unit is { TT |1 ≦ TT ≦ 30 }: day; x and Y are X-axis swing angle and Y-axis swing angle respectively, and an original swing angle value set is constructed:
t actual acquisition time.
4. The method for determining the tower instability state through the structural mechanics data model according to claim 1, wherein the set of unit time swing center values is calculated, the raw swing angle value set data is obtained, the data in the set is grouped according to the minute level T, the swing center value ST of the unit time T1-Tm is calculated, and the algorithm formula is as follows:
wherein k is a unitMonitoring the data quantity in time, and through the data calculation in the process, arranging the original data set into a swing center value set in the following form:
5. the method for determining tower instability through a structural mechanics data model of claim 1, wherein the set of motion speed variations is calculated from the set of swing center values, according to the algorithm W-ST-ST-1And performing data conversion on the swing center value set, wherein S is the swing center value, and { T | T1 is more than or equal to T and less than or equal to Tm }, and obtaining the following movement speed change set:
t unit time.
6. The method for determining the unstable state of the tower according to claim 1, wherein the method for determining the unstable state of the tower through the structural mechanics data model is characterized in that the structural mechanics data model is constructed, the abrupt point is identified according to the movement speed change, the movement speed change set is used for identifying the abrupt point, different thresholds a, { a |0.13 ≦ a ≦ 0.8} are adopted for identifying the abrupt point according to different tower types, the threshold a is a critical abrupt point determination value of the algorithm, the abrupt determination values of different tower types are different, the states of the homotypic normal tower and the unstable tower are respectively selected for comparison according to the tower operation big data and the data extraction and analysis after the data filtration, the distribution range of the abnormal variation value is obtained, the movement speed change set data extraction is carried out according to W ═ a, and the abrupt point data set is formed;
finally judging a stable state by calculating whether the number of catastrophe points in the TT time period exceeds a judgment threshold value M, { M |3 is less than or equal to M and less than or equal to 5}, and judging the tower exceeding the M threshold value as a destabilization state; and (3) judging that the nature of the threshold M is the maximum allowable value of the catastrophe point of the specified time window, and obtaining different value intervals of the values presented in the maximum and minimum time window ranges according to the extraction, comparison and analysis of the operation big data of the homotypic normal tower and the instability tower.
7. A computer device, characterized in that the computer device comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of:
acquiring an original swing angle value set based on a specified time window;
calculating a unit time swing center value set;
calculating a motion speed change set according to the swing center value set data;
identifying a speed change mutation point, identifying the mutation point by using a motion speed change set, extracting and analyzing data after data filtering according to tower operation big data, and respectively selecting a homotypic normal tower and a destabilization tower for comparison to obtain a distribution range of an abnormal variation value;
and finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, wherein the tower exceeding the threshold value is judged to be in the unstable state.
8. A method for determining the tower instability state through the structural mechanics data model and a loaded facility determination system for implementing the method for determining the tower instability state according to any one of claims 1 to 6, wherein the tower instability state determination system comprises:
the original swing angle value set acquisition module is used for acquiring an original swing angle value set based on a specified time window;
the unit time swing center value set calculating module is used for calculating a unit time swing center value set;
the motion speed change set calculation module is used for calculating a motion speed change set according to the swing center value set data;
the catastrophe point identification module is used for identifying catastrophe points by using the movement speed change set, and respectively selecting a homotypic normal tower and a homotypic instability tower for comparison according to tower operation big data and data extraction and analysis after data filtration to obtain the distribution range of abnormal variation values;
and the instability state judgment module is used for finally judging the stable state by calculating whether the number of the catastrophe points in the time period exceeds a judgment threshold value, and the tower exceeding the threshold value is judged to be in the instability state.
9. A tower destabilizing condition facility determination system according to claim 8, wherein said tower destabilizing condition determination system further comprises:
the data acquisition device is internally provided with a posture chip and is used for acquiring real-time swing data of the tower, wherein the real-time swing data comprises an X-axis swing angle, a Y-axis swing angle and wind speed information;
the data acquisition device sends the obtained swing data to a system data cloud service through the 4G communication module, and the transmission data is sent in an internal agreed message format;
a data receiving interface program built in the data cloud service is responsible for receiving messages, and the message content is analyzed through a message analyzer to obtain an X-axis swing angle, a Y-axis swing angle and wind speed information;
the data receiving interface program submits the analyzed original swing data to a data storage warehouse management system, and the data storage warehouse completes physical storage of data cloud;
the method comprises the steps that a system-level timer is built in a computing cloud service, the working period of the timer is configured according to the setting of system parameters, when the starting time of the timer is up, the timer is started by a system, all tower information to be analyzed is extracted, a judgment algorithm is executed on each tower until all towers are analyzed, and the operation of the timer is stopped;
the instability judgment algorithm arithmetic unit software module extracts original tower swing angle information, sequentially carries out data sorting and calculation according to five processes defined by an algorithm, finally gives a judgment result, and submits the judgment result to a data storage warehouse for physical storage;
calculating an external service interface program in the cloud service, obtaining formed judgment result information by accessing data storage warehouse data, forming alarm information according to the judgment result, and preparing the alarm information sent to a corresponding terminal according to the terminal deployment condition;
the external service interface program issues the alarm information to the designated terminal;
and the terminal software acquires corresponding alarm information and presents the alarm information to a user, and the user performs corresponding treatment on the specified tower according to the alarm condition.
10. A tower state detection method for carrying communication equipment and power transmission cables, characterized in that the tower state detection method for carrying communication equipment and power transmission cables uses the tower instability state determination system of claim 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114626131A (en) * | 2022-03-23 | 2022-06-14 | 武汉北曦盛科技有限公司 | Power grid power infrastructure security assessment analysis method, system and storage medium |
| CN116204022A (en) * | 2023-05-04 | 2023-06-02 | 南京施密特光学仪器有限公司 | High-precision control system of biaxial positioning platform |
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2020
- 2020-08-26 CN CN202010882327.1A patent/CN112016206A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114626131A (en) * | 2022-03-23 | 2022-06-14 | 武汉北曦盛科技有限公司 | Power grid power infrastructure security assessment analysis method, system and storage medium |
| CN114626131B (en) * | 2022-03-23 | 2023-12-19 | 新风光电力科技(北京)有限公司 | Power grid power infrastructure safety evaluation analysis method, system and storage medium |
| CN116204022A (en) * | 2023-05-04 | 2023-06-02 | 南京施密特光学仪器有限公司 | High-precision control system of biaxial positioning platform |
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