CN113309990B - Pipeline detection early warning method and system - Google Patents
Pipeline detection early warning method and system Download PDFInfo
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- CN113309990B CN113309990B CN202110590876.6A CN202110590876A CN113309990B CN 113309990 B CN113309990 B CN 113309990B CN 202110590876 A CN202110590876 A CN 202110590876A CN 113309990 B CN113309990 B CN 113309990B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
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Abstract
The application discloses a detection early warning method and a system of a pipeline, wherein the method comprises the steps of acquiring and cleaning monitoring data of monitoring points; in the monitoring data of the monitoring points obtained and cleaned at one time, if the monitoring points are unsuccessfully positioned, the obtained monitoring data are discarded, if the monitoring points are successfully positioned and the monitoring data have gross errors, the monitoring data of the monitoring points are obtained and cleaned again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the obtaining and cleaning of the monitoring data for a preset number of times are completed; if the monitoring point is successfully positioned and the monitoring data has no gross error, storing the monitoring data in a preset database; acquiring early warning levels of all monitoring data; and outputting corresponding early warning information according to the early warning grade of each monitored data. The detection early warning method obtains credible monitoring data by cleaning the data, then stores the cleaned monitoring data, and carries out early warning based on the stored monitoring data.
Description
Technical Field
The invention relates to the technical field of engineering construction, in particular to a pipeline detection and early warning method and a pipeline detection and early warning system.
Background
With the rapid development of urban economy, the problems of insufficient pipeline construction scale, low management level and the like are highlighted, and if events such as heavy rain and waterlogging, pipeline leakage and explosion, road surface collapse and the like occur, the life and property safety and urban operation order can be seriously influenced.
The existing pipeline detection and alarm system can acquire a large amount of monitoring data with different data types during pipeline detection, how to screen useless data from the monitoring data and perform better early warning, and is one of the problems to be solved or improved at present.
Disclosure of Invention
An embodiment of the invention discloses a detection and early warning method for a pipeline, which comprises the following steps:
for any monitoring point in at least one monitoring point on the pipeline, acquiring and cleaning monitoring data of the monitoring point, wherein the cleaning of the monitoring data comprises the steps of identifying whether the monitoring point is successfully positioned and judging whether the monitoring data has gross errors;
in the monitoring data of the monitoring points are obtained and cleaned at one time, if the monitoring points are unsuccessfully positioned, the obtained monitoring data are discarded, if the monitoring points are successfully positioned and the monitoring data have gross errors, the monitoring data of the monitoring points are obtained and cleaned again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the obtaining and cleaning of the monitoring data for the preset times are completed; if the monitoring point is successfully positioned and the monitoring data has no gross error, storing the monitoring data in a preset database;
for each monitoring data stored in the database, acquiring the early warning level of each monitoring data;
and outputting corresponding early warning information according to the early warning grade of each monitored data.
In some embodiments, the identifying whether the monitoring point is successfully located includes:
acquiring coordinate information of the monitoring data acquisition position;
identifying whether the monitoring point is successfully positioned according to the coordinate information; or
And acquiring the equipment information of the detection equipment for sending the monitoring data, and identifying whether the monitoring point is successfully positioned according to the equipment information.
In some embodiments, the device information includes at least codes corresponding to the detection devices, and one of the codes is used to identify one of the detection devices.
In some embodiments, the manner of obtaining the monitoring data of the monitoring point includes: obtaining the monitoring data by at least one of: the device comprises gas detection equipment, water level detection equipment, a temperature/humidity meter, pipeline flow detection equipment, PH value detection equipment, acoustic emission detection equipment and ultrasonic guided wave detection equipment.
In some embodiments, the warning levels are preset with different colors, and outputting the corresponding warning information includes:
and outputting early warning information of corresponding colors according to the early warning level of the monitoring data.
In some embodiments, the obtaining of the early warning level of the monitoring data stored in the database comprises
In some embodiments, the obtaining of the early warning level of the monitoring data stored in the database comprises:
acquiring a type code used for representing a data type in the monitoring data;
invoking at least one threshold range associated with the type code based on the type code;
determining a threshold range within which the monitoring data falls;
and determining the early warning level of the monitoring data according to the threshold range in which the monitoring data falls.
In some embodiments, the preset number of times is two, where the monitoring data of the monitoring point obtained for the first time is first monitoring data, the monitoring data of the monitoring point obtained for the second time is second monitoring data, and after the monitoring data of the monitoring point is obtained and cleaned for the first time and stored in a preset database, the method further includes:
acquiring the danger level of the first monitoring data;
if the danger level of the first monitoring data exceeds a threshold value, acquiring and cleaning the monitoring data of the monitoring point for the second time;
in the monitoring data of the monitoring points are obtained and cleaned for the second time, if the positioning of the monitoring points of the second monitoring data fails or the second monitoring data has gross errors, the second monitoring data are discarded, and if the positioning of the monitoring points of the second monitoring data is successful and the second monitoring data does not have gross errors, the monitoring data of the monitoring points in the database are updated according to the second monitoring data;
and if the monitoring data of the monitoring points in the database are updated according to the second monitoring data, acquiring the danger level of the second monitoring data, and if the danger level of the second monitoring data exceeds a threshold value, generating alarm information for emergency management.
In some embodiments, the generating alarm information for emergency management includes at least one of:
and writing an alarm event and/or an alarm record and displaying alarm information by a popup into the database.
In another embodiment of the present invention, a detection and early warning system for a pipeline is disclosed, comprising:
a database;
the data acquisition module is used for receiving monitoring data of any monitoring point in at least one monitoring point on the pipeline, which is sent by the detection equipment;
the data processing module is used for cleaning the acquired monitoring data, wherein the cleaning of the monitoring data comprises the following steps: identifying whether the monitoring point is successfully positioned and judging whether the monitoring data has gross errors or not, in the process of acquiring and cleaning the monitoring data of the monitoring point at one time, if the monitoring point is unsuccessfully positioned, discarding the acquired monitoring data, and if the monitoring point is successfully positioned and the monitoring data has gross errors, acquiring and cleaning the monitoring data of the monitoring point again until the monitoring point is successfully positioned and the monitoring data has no gross errors or the acquisition and cleaning of the monitoring data of the preset times are completed; if the monitoring points are successfully positioned and the monitoring data do not have gross errors, storing the monitoring data in the database;
the grading early warning module is used for acquiring the early warning grade of each monitoring data stored in the database;
and the output module is used for outputting corresponding early warning information according to the early warning grade of each monitored data.
In certain embodiments, the detection device comprises at least one of: the device comprises gas detection equipment, water level detection equipment, a temperature/humidity meter, pipeline flow detection equipment, PH value detection equipment, acoustic emission detection equipment and ultrasonic guided wave detection equipment.
In the above embodiment, the monitoring data acquired at the plurality of monitoring points on the pipeline is not directly stored in the database, but the monitoring data is cleaned, and the cleaning includes two aspects: firstly, confirm whether the monitoring point is fixed a position correctly, secondly confirm whether this monitoring data scope itself is reasonable to obtain the monitoring data that correct position and scope are reasonable, carried out hierarchical early warning again based on this monitoring data, thereby can let the user grasp the detection early warning condition of pipeline better, in order to make effectual emergency management.
Drawings
FIG. 1 is a schematic diagram of a pipeline detection and early warning system according to an embodiment;
FIG. 2 is a schematic diagram of a detection device acquiring monitoring data at a monitoring point according to an embodiment;
fig. 3 is a flowchart of a detection and early warning method of a pipeline according to an embodiment.
10. A data acquisition module;
20. a data processing module;
30. a grading early warning module;
40. an output module;
50. a database.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. Wherein like elements in different embodiments have been given like element numbers associated therewith. In the following description, numerous details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the description of the methods may be transposed or transposed in order, as will be apparent to a person skilled in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.
The ordinal numbers used herein for the components, such as "first," "second," etc., are used merely to distinguish between the objects described, and do not have any sequential or technical meaning. The term "connected" and "coupled" when used in this application, unless otherwise indicated, includes both direct and indirect connections (couplings).
The first embodiment is as follows:
referring to fig. 1, the present embodiment provides a pipeline detection and early warning system, which includes a database 50, a data acquisition module 10, a data processing module 20, a grading early warning module 30, and an output module 40.
The data acquisition module 10 is configured to receive monitoring data of any monitoring point of the at least one monitoring point on the pipeline 1, which is sent by the detection device 2. The monitoring point on above-mentioned pipeline 1 is preset usually, and most monitoring point department all is fixed with check out test set 2, to receiving environmental restriction, unable fixed mounting's monitoring point, then can the manual work carry check out test set 2 to monitoring point department and acquire the monitoring data, behind check out test set 2 acquireed the monitoring data, with monitoring data transmission to data acquisition module 10.
The detection device 2 includes, but is not limited to, a gas detection device, a water level detection device, a temperature/humidity meter, a pipeline flow detection device, a PH detection device, an acoustic emission detection device, and an ultrasonic guided wave detection device, and the types of the obtained monitoring data are different according to the difference of the detection devices. Fig. 2 is a schematic diagram of the detection devices 2 of one monitoring point, and it can be seen that a plurality of detection devices 2 are arranged at one monitoring point.
The data acquisition module 10 can be connected with other modules in the system through the internet of things technology, for example, can be connected to a LoRa gateway through a LoRa technology wireless transmission, and then is connected to an intranet/extranet through a network port, WIFI, 4G/5G and the like, so that automatic power supply, automatic acquisition, automatic storage, automatic transmission, automatic control, automatic processing, automatic warehousing, automatic early warning and automatic emergency online detection/monitoring of multi-system equipment monitoring information are realized.
The internet of things technology adopted in this embodiment is briefly introduced below, and the data transmission method of this embodiment includes, but is not limited to, the contents described below.
The Internet of Things (Internet of Things, abbreviated as IOT) originated in the media field and is the third revolution of the information technology industry. The internet of things is that any object is connected with a network through information sensing equipment according to an agreed protocol, and the object performs information exchange and communication through an information transmission medium so as to realize functions of intelligent identification, positioning, tracking, supervision and the like. Aiming at the traditional detection/monitoring equipment, because the information acquisition and transmission of the traditional detection/monitoring equipment are different in data form, transmission mode, communication protocol and the like, in order to facilitate uniform data acquisition and management, the information of multi-system equipment is completely converted into a TCP/UDP data packet which can be accessed through an IP address, so that remote intelligent online acquisition is realized.
Z206-L-C is a LoRa private protocol node, and realizes the function of converting RS232/485 to LoRa; low power consumption, 2000 meters long distance data transmission; support for concentrator communication protocols; the support node actively reports, wakes up polling, server issues and other working modes; the multi-mode application field is wide, and the time division multiplexing interference is small; support MQTT/Socket protocol, data encryption transmission, hardware watchdog and the like.
Z220 is a LoRa private protocol concentrator, which can connect thousands of LoRa nodes simultaneously; low power consumption, 2000 m long distance data transmission; supporting Ethernet, 4G and Wi-Fi networking; the support node actively reports, wakes up polling, server issues and other work modes; the multi-mode application field is wide, and the time division multiplexing interference is small; support MQTT/Socket protocol and the like.
In this embodiment, the data acquisition module 10 may adopt a LoRa wireless acquisition module, and realize functions such as high-speed data acquisition, data real-time processing, and process control, and all devices under the internet of things access the internet of things devices through a network IP address, and acquire data, and automatically obtain the unique code inside the system through the network IP and the device MAC address. By means of an optical fiber intranet and a 5G network of 100Mb/s or more, real-time data acquisition can be completely realized, and for data acquisition with large data volume or detection data needing time interval monitoring and relevant analysis, the data acquisition interval of instrument equipment needs to be adjusted and can be set from 1 millisecond to 1 month.
The data processing module 20 is configured to clean the acquired monitoring data, where the cleaning monitoring data includes: and identifying whether the monitoring points are successfully positioned and judging whether the monitoring data have gross errors.
In some embodiments, after the detection device 2 is installed at each monitoring point, the detection device 2 corresponding to each monitoring point may be uniformly encoded, and then the codes are compiled into an information table and stored in the database 50. When the detection device 2 sends the monitoring data, it also sends its own device information, which at least includes the above-mentioned unique code, and after receiving the monitoring information and the device information, if the corresponding code is found in the information table in the database 50, it represents that the monitoring point corresponding to the code is successfully located. Of course, the information table may further include device attribute information, spatial information, and the like, where the device attribute information, the spatial information, and the codes correspond to one another one to one, and therefore, the type of the device and the specific location of the monitoring point may also be identified according to the codes.
In other embodiments, for a monitoring point where the detection device 2 is not fixedly installed, manual periodic monitoring is required, a monitoring person needs to reach a specified position to perform monitoring, and the data processing module 20 matches the monitoring point according to coordinate information returned by the monitoring to determine whether the monitoring point reaches the position to perform detection (the position may be set according to specific conditions, for example, an effective position within a few meters from the origin). If the matching result shows that the specified place is reached, the positioning is successful. In addition, the monitoring point can be matched according to returned equipment information and the like.
In this embodiment, the monitoring data further includes a type code for characterizing a data type, and after receiving the monitoring data, the data processing device can identify what type of data is through the type code, and then can perform corresponding processing.
By setting the type code in the monitoring data, the data processing module 20 can determine the type of the monitoring data when receiving the monitoring data, so that various types of monitoring data can be processed.
In some embodiments, determining whether gross errors exist in the monitored data comprises:
calling a standard value and a gross error range (pre-stored in the database 50) related to the type code according to the type code, calculating a difference value between a value in the monitoring data and the standard value, comparing the difference value with the gross error range, if the gross error range is exceeded, representing that the monitoring data has gross errors, the monitoring data is not credible, and if the gross error range is not exceeded, representing that the monitoring data does not have gross errors, the data is credible. The standard values and the gross error ranges of the monitoring data of different types are different, the type of the detection equipment 2 is firstly identified through the type code, and then the gross error judgment is carried out, so that invalid data can be effectively removed.
In the monitoring data of the monitoring points obtained and cleaned at one time, if the monitoring points are unsuccessfully positioned, the obtained monitoring data are discarded, if the monitoring points are successfully positioned and the monitoring data have gross errors, the monitoring data of the monitoring points are obtained and cleaned again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the obtaining and cleaning of the monitoring data for a preset number of times are completed; if the monitoring point location is successful and there is no gross error in the monitored data, the monitored data is stored in the database 50.
That is, the monitoring data with positioning failure or gross error belongs to invalid data, the invalid data is discarded without being put into a database (stored in the database 50), and if one monitoring point acquires the invalid data, the monitoring data is acquired at the monitoring point again until the acquired monitoring data is valid data or the number of acquiring the monitoring data reaches a predetermined number. The effective data mentioned above refers to data that the monitoring point is successfully positioned and has no gross errors, and the data can truly reflect the condition of the pipeline 1, so that the effective data can be used as the basis of subsequent early warning. Valid monitoring data is stored in the database 50.
In consideration of actual operation, in this embodiment, the predetermined number of times is two, that is, if the monitoring data acquired for the second time is still invalid data, the third time of acquiring the monitoring data is not performed. Hereinafter, monitoring data acquired by one monitoring point for the first time is defined as first monitoring data, and monitoring data acquired by the monitoring point for the second time is defined as second monitoring data. (some monitoring points acquire valid data for the first time, so that no second monitoring data exists).
The hierarchical warning module 30 obtains a warning level of each monitoring data stored in the database 50.
In some embodiments, a method of obtaining a predetermined level of each monitored data, comprises:
the method comprises the steps of obtaining a type code used for representing a data type in monitoring data, calling at least one threshold range related to the type code according to the type code, determining the threshold range in which the monitoring data falls, and determining the early warning level of the monitoring data according to the threshold range in which the monitoring data falls. The difference between the threshold range and the gross error range is that the range of the gross error range is larger, and the monitoring data exceeding the gross error range is intuitively 'off-spectrum' data.
In this embodiment, five warning levels are set, which are normal, primary warning, secondary warning, tertiary warning and quaternary warning.
The output module 40 is configured to output corresponding early warning information according to the early warning level of each monitored data. For example, the output module 40 includes a display, a three-dimensional model of the pipeline 1 is displayed in a display interface of the display, after the early warning level of each monitoring data is obtained, the early warning information is displayed in different colors at each monitoring point on the three-dimensional model of the pipeline, for example, if the early warning level is normal, the monitoring data is displayed in green, and the monitoring data is displayed in blue, pink, orange and red respectively at the first-stage early warning, the second-stage early warning, the third-stage early warning and the fourth-stage early warning.
In some embodiments, the output module 40 further generates different pre-warning interfaces for different users, where the different pre-warning interfaces can display different pre-warning information, and the people at different levels can see the interface most concerned by themselves after logging in the system. All warning interfaces are visible to the highest level of personnel.
In some embodiments, after storing the first monitoring data, the method further comprises:
and similarly, the first monitoring data can be compared with a preset danger value, and if the difference between the first monitoring data and the danger value is less than the preset value, the danger level of the first monitoring data is higher. And if the danger level of the first monitoring data exceeds the threshold value, acquiring and cleaning the monitoring data of the monitoring point for the second time. The threshold is used to represent a risk level, for example, when the difference between the first monitoring data and the risk value is smaller than a preset value, the risk level is greater than 0, and the second monitoring data is acquired and cleaned at this time, that is, after the first monitoring data is stored, if the first monitoring data reaches a risk level, the monitoring data of the monitoring point is acquired again, that is, the second monitoring data is acquired. If the danger level of the first monitoring data is less than the threshold, the data processing module 20 may scan the historical alarm state of the monitoring point in the database 50, set the alarm state to be resolved, and the output module 40 may output the alarm state, so that the user may visually see the historical alarm state of each monitoring point on the three-dimensional model of the pipeline 1.
Similar to the first monitoring data, in the monitoring data of the monitoring points are obtained and cleaned for the second time, if the positioning of the monitoring points of the second monitoring data fails or the second monitoring data has gross errors, the second monitoring data are discarded, and if the positioning of the monitoring points of the second monitoring data succeeds and the second monitoring data does not have gross errors, the monitoring data of the monitoring points in the database 50 are updated according to the second monitoring data. That is, if the second monitored data is valid data, the data corresponding to the monitoring point in the database 50 is updated to the second monitored data.
If the monitoring data of the monitoring points in the database 50 are updated according to the second monitoring data, the danger level of the second monitoring data is obtained, wherein the danger level is obtained in the same way as the first monitoring data. And if the danger level of the second monitoring data exceeds a threshold value, generating alarm information for emergency management. If the danger level of the second monitoring data is less than the threshold, the data processing module 20 may scan the historical alarm state of the monitoring point in the database 50, set the alarm state to be resolved, and the output module 40 may output the alarm state, so that the user may visually see the historical alarm state of each monitoring point on the three-dimensional model of the pipeline 1. The manner of emergency handling includes, but is not limited to, writing alarm events and/or alarm records to the database 50 and displaying the alarm information in a pop-up window, from which the user may re-evaluate the security level.
As can be seen from the above description, in this embodiment, if the first monitoring data is invalid data, the second monitoring data is obtained, and if it is found that the risk level is higher after the first monitoring data is stored, the second monitoring data is also obtained, and meanwhile, the risk level is also determined for the second monitoring data, so as to confirm the alarm state of the monitoring point, and facilitate emergency management in the following process. That is to say, in this embodiment, not only the warning is performed according to the acquired monitoring data, but also the danger level of the monitoring data is determined and the warning is performed in time. The monitoring data of the same monitoring point is obtained twice, so that the error can be reduced, and the reliability of the data is improved.
The invention also provides a detection and early warning method of the pipeline, which comprises the following steps as shown in figure 3:
The monitoring point on above-mentioned pipeline 1 is preset usually, and most monitoring point department all is fixed with check out test set 2, to receiving the environmental restriction, unable fixed mounting's monitoring point, then can artificially carry check out test set 2 to the acquisition of monitoring point department monitoring data.
The detection device 2 includes, but is not limited to, a gas detection device, a water level detection device, a temperature/humidity meter, a pipeline flow detection device, a PH detection device, an acoustic emission detection device, and an ultrasonic guided wave detection device, and the type of the obtained monitoring data is different according to the different detection devices.
The cleaning monitoring data includes: and identifying whether the monitoring points are successfully positioned or not and judging whether the monitoring data have gross errors or not.
In some embodiments, after the detection device 2 is installed at each monitoring point, the detection device 2 corresponding to each monitoring point may be uniformly encoded, and then the codes are compiled into an information table and stored in the database 50. When the detection device 2 sends the monitoring data, it also sends its own device information, which at least includes the above-mentioned unique code, and after receiving the monitoring information and the device information, if the corresponding code is found in the information table in the database 50, it represents that the monitoring point corresponding to the code is successfully located. Of course, the information table may further include device attribute information, spatial information, and the like, where the device attribute information, the spatial information, and the codes correspond to one another one to one, and therefore, the type of the device and the specific location of the monitoring point may also be identified according to the codes.
In other embodiments, for a monitoring point where the detection device 2 is not fixedly installed, manual regular monitoring is required, a monitoring person needs to reach a specified position to monitor, match the monitoring point according to coordinate information returned by monitoring, and determine whether the monitoring point reaches the position to detect (the position may be set according to specific situations, for example, an effective position within a few meters from the origin). If the matching result shows that the specified place is reached, the positioning is successful. In addition, the monitoring point can be matched according to returned equipment information and the like.
In this embodiment, the monitoring data further includes a type code for characterizing a data type, and the type code can identify what type of data is, and then corresponding processing can be performed.
By setting the type code in the monitoring data, the type of the monitoring data can be judged when the monitoring data is acquired, so that various types of monitoring data can be processed.
In some embodiments, determining whether gross errors exist in the monitored data comprises:
calling a standard value and a gross error range (pre-stored in the database 50) related to the type code according to the type code, calculating a difference value between a numerical value in the monitoring data and the standard value, comparing the difference value with the gross error range, if the gross error range is exceeded, representing that the monitoring data has gross errors, the monitoring data is not credible, and if the gross error range is not exceeded, representing that the monitoring data does not have gross errors, the data is credible. The standard values and the gross error ranges of the different types of monitoring data are different, the types of the detection equipment 2 are firstly identified through the type codes, and then the gross error judgment is carried out, so that invalid data can be effectively removed.
In the monitoring data of the monitoring points obtained and cleaned at one time, if the monitoring points are unsuccessfully positioned, the obtained monitoring data are discarded, if the monitoring points are successfully positioned and the monitoring data have gross errors, the monitoring data of the monitoring points are obtained and cleaned again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the obtaining and cleaning of the monitoring data for a preset number of times are completed; if the monitoring point location is successful and there is no gross error in the monitored data, the monitored data is stored in the database 50.
That is, the monitoring data with positioning failure or gross error belongs to invalid data, the invalid data is discarded without being stored in a database (stored in the database 50), and if one monitoring point acquires the invalid data, the monitoring data is acquired at the monitoring point again until the acquired monitoring data is valid data or the number of times of acquiring the monitoring data reaches a predetermined number of times. The effective data mentioned above refers to data that the monitoring point is successfully positioned and has no gross errors, and the data can truly reflect the condition of the pipeline 1, so that the effective data can be used as the basis of subsequent early warning. Valid monitoring data is stored in the database 50.
In consideration of actual operation, in this embodiment, the predetermined number of times is two, that is, if the monitoring data acquired for the second time is still invalid data, the third time of acquiring the monitoring data is not performed. Hereinafter, monitoring data acquired by one monitoring point for the first time is defined as first monitoring data, and monitoring data acquired by the monitoring point for the second time is defined as second monitoring data. (some monitoring points acquire valid data for the first time, so that no second monitoring data exists).
In some embodiments, a method of obtaining a predetermined level of each monitored datum comprises:
the method comprises the steps of obtaining a type code used for representing a data type in monitoring data, calling at least one threshold value range related to the type code according to the type code, determining the threshold value range in which the monitoring data falls, and determining the early warning level of the monitoring data according to the threshold value range in which the monitoring data falls. The difference between the threshold range and the gross error range is that the range of the gross error range is larger, and the monitoring data exceeding the gross error range is visually off-spectrum data.
In this embodiment, five warning levels are set, which are normal, primary warning, secondary warning, tertiary warning and quaternary warning.
And 300, outputting corresponding early warning information according to the early warning level of each monitored data.
In this embodiment, a three-dimensional model about the pipeline 1 is generated first, and then the early warning information can be displayed in different colors at each monitoring point on the three-dimensional model of the pipeline 1, for example, if the monitoring data is normal, the monitoring data is displayed in green, and the monitoring data is displayed in blue, pink, orange and red respectively by first-stage early warning, second-stage early warning, third-stage early warning and fourth-stage early warning.
In some embodiments, different early warning interfaces can be generated for different users, different early warning information can be displayed on different early warning interfaces, and people in different levels can see the interface which is most concerned by the people after logging in the system. All the warning interfaces are visible to the highest level of personnel.
In some embodiments, after storing the first monitoring data, the method further comprises:
and similarly, the first monitoring data can be compared with a preset danger value, and if the difference between the first monitoring data and the danger value is less than the preset value, the danger level of the first monitoring data is higher. And if the danger level of the first monitoring data exceeds the threshold value, acquiring and cleaning the monitoring data of the monitoring point for the second time. The threshold is used to represent a risk level, for example, when the difference between the first monitoring data and the risk value is smaller than a preset value, the risk level is greater than 0, and the second monitoring data is acquired and cleaned at this time, that is, after the first monitoring data is stored, if the first monitoring data reaches a risk level, the monitoring data of the monitoring point is acquired again, that is, the second monitoring data is acquired. If the danger level of the first monitoring data is less than the threshold value, the historical alarm state of the monitoring point in the database 50 can be scanned and set to be solved, then the alarm state can be output, and a user can visually see the historical alarm state of each monitoring point on the three-dimensional model of the pipeline 1.
Similar to the first monitoring data, in the monitoring data of the monitoring points are obtained and cleaned for the second time, if the positioning of the monitoring points of the second monitoring data fails or the second monitoring data has gross errors, the second monitoring data are discarded, and if the positioning of the monitoring points of the second monitoring data succeeds and the second monitoring data does not have gross errors, the monitoring data of the monitoring points in the database 50 are updated according to the second monitoring data. That is, if the second monitored data is valid data, the data corresponding to the monitoring point in the database 50 is updated to the second monitored data.
If the monitoring data of the monitoring points in the database 50 are updated according to the second monitoring data, the danger level of the second monitoring data is obtained, wherein the danger level is obtained in the same way as the first monitoring data. And if the danger level of the second monitoring data exceeds a threshold value, generating alarm information for emergency management. If the risk level of the second monitoring data is less than the threshold value, the historical alarm state of the monitoring point in the database 50 can be scanned and set to be solved, and the alarm state can be output, so that the user can visually see the historical alarm state of each monitoring point on the three-dimensional model of the pipeline 1. The manner of emergency handling includes, but is not limited to, writing alarm events and/or alarm records to the database 50 and displaying the alarm information in a pop-up window, from which the user may re-evaluate the security level.
As can be seen from the above description, in this embodiment, if the first monitoring data is invalid data, the second monitoring data is obtained, and if it is found that the risk level is higher after the first monitoring data is stored, the second monitoring data is also obtained, and meanwhile, the risk level is also determined for the second monitoring data, so as to confirm the alarm state of the monitoring point, and facilitate emergency management in the following process. That is to say, in this embodiment, not only the warning is performed according to the acquired monitoring data, but also the danger level of the monitoring data is determined and the warning is performed in time. The error can be reduced by acquiring the monitoring data of the same monitoring point twice, and the reliability of the data is improved.
Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments may be implemented by hardware, or may be implemented by computer programs. When all or part of the functions of the above embodiments are implemented by a computer program, the program may be stored in a computer-readable storage medium, and the storage medium may include: a read only memory, a random access memory, a magnetic disk, an optical disk, a hard disk, etc., and the program is executed by a computer to realize the above functions. For example, the program may be stored in a memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above can be implemented. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and may be downloaded or copied to a memory of a local device, or may be version-updated in a system of the local device, and when the program in the memory is executed by a processor, all or part of the functions in the above embodiments may be implemented.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.
Claims (9)
1. A detection early warning method for a pipeline is characterized by comprising the following steps:
for any monitoring point in at least one monitoring point on the pipeline, acquiring and cleaning monitoring data of the monitoring point, wherein the cleaning of the monitoring data comprises the steps of identifying whether the monitoring point is successfully positioned and judging whether the monitoring data has gross errors;
in the monitoring data of the monitoring points are obtained and cleaned at one time, if the monitoring points are unsuccessfully positioned, the obtained monitoring data are discarded, if the monitoring points are successfully positioned and the monitoring data have gross errors, the monitoring data of the monitoring points are obtained and cleaned again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the obtaining and cleaning of the monitoring data for the preset times are completed; if the monitoring point is successfully positioned and the monitoring data has no gross error, storing the monitoring data in a preset database;
for each monitoring data stored in the database, acquiring an early warning level of each monitoring data, specifically comprising: acquiring a type code used for representing a data type in the monitoring data; invoking at least one threshold range associated with the type code based on the type code; determining a threshold range within which the monitoring data falls; determining the early warning level of the monitoring data according to the threshold range in which the monitoring data falls;
and outputting corresponding early warning information according to the early warning grade of each monitored data.
2. The method of claim 1, wherein said identifying whether said monitoring point was located successfully comprises:
acquiring coordinate information of the monitoring data acquisition position;
identifying whether the monitoring points are successfully positioned or not according to the coordinate information; or
And acquiring the equipment information of the detection equipment for sending the monitoring data, and identifying whether the monitoring point is successfully positioned according to the equipment information.
3. The method of claim 2, wherein the device information includes at least codes corresponding to the detection devices, one of the codes identifying one of the detection devices.
4. The method of claim 1, wherein obtaining the monitoring data for the monitoring point comprises: obtaining the monitoring data by at least one of: the device comprises gas detection equipment, water level detection equipment, a temperature/humidity meter, pipeline flow detection equipment, PH value detection equipment, acoustic emission detection equipment and ultrasonic guided wave detection equipment.
5. The method of claim 1, wherein the warning levels are preset with different colors, and the outputting corresponding warning information comprises:
and outputting early warning information of corresponding colors according to the early warning level of the monitoring data.
6. The method of claim 1, wherein the predetermined number of times is two, wherein the first time the monitoring data of the monitoring point is obtained as first monitoring data, and the second time the monitoring data of the monitoring point is obtained as second monitoring data, and after the first time the monitoring data of the monitoring point is obtained and cleaned and the monitoring data is stored in a preset database, the method further comprises:
acquiring the danger level of the first monitoring data;
if the danger level of the first monitoring data exceeds a threshold value, acquiring and cleaning the monitoring data of the monitoring point for the second time;
in the monitoring data of the monitoring points are obtained and cleaned for the second time, if the positioning of the monitoring points of the second monitoring data fails or the second monitoring data has gross errors, the second monitoring data are discarded, and if the positioning of the monitoring points of the second monitoring data is successful and the second monitoring data does not have gross errors, the monitoring data of the monitoring points in the database are updated according to the second monitoring data;
and if the monitoring data of the monitoring points in the database are updated according to the second monitoring data, acquiring the danger level of the second monitoring data, and if the danger level of the second monitoring data exceeds a threshold value, generating alarm information for emergency management.
7. The method of claim 6, wherein the generating alarm information for emergency management comprises at least one of:
and writing an alarm event and/or an alarm record into the database and displaying alarm information by a popup window.
8. A detection and early warning system for a pipeline, comprising:
a database;
the data acquisition module is used for receiving monitoring data of any monitoring point in at least one monitoring point on the pipeline, which is sent by the detection equipment;
the data processing module is used for cleaning the acquired monitoring data, wherein the cleaning of the monitoring data comprises the following steps: identifying whether the monitoring points are successfully positioned and judging whether the monitoring data have gross errors or not, in the process of acquiring and cleaning the monitoring data of the monitoring points at one time, if the monitoring points are unsuccessfully positioned, discarding the acquired monitoring data, and if the monitoring points are successfully positioned and the monitoring data have gross errors, acquiring and cleaning the monitoring data of the monitoring points again until the monitoring points are successfully positioned and the monitoring data have no gross errors or the acquisition and cleaning of the monitoring data for a preset number of times are completed; if the positioning of the monitoring points is successful and the monitoring data does not have gross errors, storing the monitoring data in the database;
the hierarchical early warning module is used for acquiring the early warning level of each monitoring data stored in the database, and specifically comprises: acquiring a type code used for representing a data type in the monitoring data; invoking at least one threshold range associated with the type code according to the type code; determining a threshold range within which the monitoring data falls; determining the early warning level of the monitoring data according to the threshold range of the monitoring data;
and the output module is used for outputting corresponding early warning information according to the early warning grade of each monitored data.
9. The system of claim 8, wherein the detection device comprises at least one of: the device comprises gas detection equipment, water level detection equipment, a temperature/humidity meter, pipeline flow detection equipment, PH value detection equipment, acoustic emission detection equipment and ultrasonic guided wave detection equipment.
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