CN118013445B - Ultrasonic thickness measurement data cloud management system - Google Patents
Ultrasonic thickness measurement data cloud management system Download PDFInfo
- Publication number
- CN118013445B CN118013445B CN202410415372.4A CN202410415372A CN118013445B CN 118013445 B CN118013445 B CN 118013445B CN 202410415372 A CN202410415372 A CN 202410415372A CN 118013445 B CN118013445 B CN 118013445B
- Authority
- CN
- China
- Prior art keywords
- data
- networking
- maintenance
- data set
- abnormal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000009683 ultrasonic thickness measurement Methods 0.000 title claims abstract description 10
- 230000006855 networking Effects 0.000 claims abstract description 98
- 238000012423 maintenance Methods 0.000 claims abstract description 79
- 230000002159 abnormal effect Effects 0.000 claims abstract description 66
- 238000012545 processing Methods 0.000 claims abstract description 36
- 238000005259 measurement Methods 0.000 claims abstract description 23
- 238000009434 installation Methods 0.000 claims abstract description 16
- 238000004891 communication Methods 0.000 claims abstract description 14
- 238000007405 data analysis Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims description 37
- 238000007726 management method Methods 0.000 claims description 19
- 238000001514 detection method Methods 0.000 claims description 16
- 238000011835 investigation Methods 0.000 claims description 12
- 238000012546 transfer Methods 0.000 claims description 11
- 230000006378 damage Effects 0.000 claims description 8
- 238000013024 troubleshooting Methods 0.000 claims description 6
- 238000012544 monitoring process Methods 0.000 claims description 4
- 231100000279 safety data Toxicity 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 3
- 238000013523 data management Methods 0.000 claims 1
- 238000002604 ultrasonography Methods 0.000 claims 1
- 230000005856 abnormality Effects 0.000 description 10
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
Landscapes
- Length Measuring Devices Characterised By Use Of Acoustic Means (AREA)
Abstract
The invention discloses an ultrasonic thickness measurement data cloud management system, which relates to the technical field of pipeline thickness measurement and comprises a management center, wherein the management center is in communication connection with a sensor module, a data processing module, a data analysis module and a data operation and maintenance module; selecting a plurality of arrangement points through a sensor module to perform installation work and debugging work of different types of sensors, and further establishing a sensing networking to collect sensing related data; carrying out data exploration and data classification on the sensing related data through a data processing module so as to generate a plurality of types of data sets; traversing and analyzing each data set through a data analysis module, positioning an abnormal data set and a normal data set, generating an abnormal early warning according to the abnormal data set, and generating a pipeline thickness measurement data report according to the normal data set; and arranging corresponding overhauling personnel to carry out fault overhauling according to the abnormal early warning through the data operation and maintenance module, and carrying out data operation and maintenance according to the pipeline thickness measurement data report.
Description
Technical Field
The invention relates to the technical field of pipeline thickness measurement, in particular to an ultrasonic thickness measurement data cloud management system.
Background
The thickness of a pipe is usually measured by using ultrasonic measurement technology, and an ultrasonic sensor is an instrument specially designed for measuring the thickness of a material, and the ultrasonic sensor transmits ultrasonic pulses, receives the ultrasonic pulses back through the wall of the pipe, and calculates the propagation distance of a signal so as to obtain the thickness of the wall of the pipe.
The accuracy of the acquired data is directly affected by selecting the arrangement point positions of the ultrasonic sensors in the corresponding pipeline buried pipe areas, when the pipeline has abnormal problems, the problems cannot be found timely, an maintainer is informed of the abnormal problems to check, and an effective management means is lacking for the operation and maintenance of the acquired pipeline related data.
Disclosure of Invention
In order to solve the problems, the invention aims to provide an ultrasonic thickness measurement data cloud management system.
The aim of the invention can be achieved by the following technical scheme: the ultrasonic thickness measurement data cloud management system comprises a management center, wherein the management center is in communication connection with a sensor module, a data processing module, a data analysis module and a data operation and maintenance module;
the sensor module is used for selecting a plurality of arrangement points, performing installation work and debugging work of different types of sensors at the arrangement points, further establishing a sensing networking, and collecting sensing related data through the sensing networking;
The data processing module is used for carrying out data exploration on the sensing related data, and carrying out data classification on the sensing related data after the data exploration is completed, so as to generate a plurality of types of data sets;
The data analysis module is used for acquiring data sets of different categories, traversing and analyzing each data set, further locating an abnormal data set and a normal data set, generating an abnormal early warning according to the abnormal data set, and generating a pipeline thickness measurement data report according to the normal data set;
the data operation and maintenance module is provided with a fault maintenance unit and an operation and maintenance management unit; the fault maintenance unit is used for receiving the abnormal early warning and arranging corresponding maintenance personnel to carry out fault maintenance; and the operation and maintenance management unit is used for carrying out data operation and maintenance according to the pipeline thickness measurement data report.
Further, the process of selecting a plurality of arrangement points to perform the installation work and the debugging work of the sensor comprises the following steps:
Positioning a pipeline exploration area, installing a plurality of pipelines, selecting a plurality of arrangement points in the pipeline exploration area, numbering the arrangement points, namely i, i=1, 2,3,4, … … and n, wherein n is a natural number larger than 0, installing different types of sensors at the plurality of arrangement points, wherein the types of the sensors comprise ultrasonic sensors and environment sensors, after the installation work is completed, debugging the sensors, acquiring the overall detection area of each ultrasonic sensor and the environment sensor, mapping the overall detection area with the pipeline exploration area, positioning a detection blind spot area, debugging the positions of the arrangement points when the detection blind spot area appears, and stopping the debugging work until the detection blind spot area is eliminated.
Further, the process of establishing the sensing networking to collect the sensing related data comprises the following steps:
Marking each arrangement point as a group point, marking an ultrasonic sensor and an environment sensor corresponding to each group point as networking equipment, wherein the networking equipment is provided with corresponding networking identification codes, and different networking identification codes are associated with corresponding networking states; the sensing related data includes ultrasonic pulse data, temperature data, humidity data, and pressure data.
Further, the process of performing data exploration on the sensing related data comprises the following steps:
Setting a data receiving period, namely T, T= [ T1, T2], receiving the sensing related data according to a preset receiving speed by the set data receiving area at the moment corresponding to T1, stopping the receiving operation of the data receiving area at the moment corresponding to T2, obtaining a receiving duration, namely TL, wherein TL=T2-T1, setting a monitoring frequency corresponding to the receiving duration, namely f, wherein f=TL/Sc, wherein Sc is a single safe encryption duration, and encrypting the received sensing related data in the single safe encryption duration;
The total data quantity of the sensing related data is obtained and marked as D Total (S) , the unit quantity of investigation is set and marked as D', the concurrency number of the data investigation required is obtained and marked as bf, and the data investigation of the sensing related data with the number represented by the concurrency number is executed at the same time.
Further, the process of classifying the data related to the sensing, and generating a plurality of classes of data sets further includes:
Setting a data classification program, initializing a classification function of the data classification program through a preset program configuration code, associating preset classification rules with the data classification program after the initialization is completed, and further classifying data through the classification rules to locate the class of the data group, wherein the class of the data group comprises a safety data group, a suspicious data group and a dangerous data group.
Further, the process of locating the abnormal data set and the normal data set and generating the corresponding abnormal early warning and pipeline thickness measuring data report comprises the following steps:
The data analysis module traverses all data groups of different categories in sequence, and associates a processing identifier for the data group synchronously when traversing the data group for the first time, and synchronously generates a processing progress bar when the data group is associated with the processing identifier, wherein the processing progress bar is used for representing the processing progress of the current data group, and the numerical value range of the processing progress is 0-100%;
The method comprises the steps of obtaining a data set with the processing progress of 100%, locating the data set, when traversing to a safe data set, locating the safe data set as a normal data set, when traversing to a dangerous data set, locating the dangerous data set as an abnormal data set, when traversing to a suspicious data set, obtaining the variance of a data value corresponding to the suspicious data set, comparing the variance with a preset judging threshold, recording the variance as tau 1, judging the variance as tau 2, locating the suspicious data set as the abnormal data set if tau 1≥τ2, and locating the suspicious data set as the normal data set if tau 1<τ2;
when an abnormal data set is generated, generating abnormal early warning synchronously according to the abnormal data set;
and when the normal data set is generated, synchronously generating a pipeline thickness measurement data report according to the normal data set.
Further, the process of the troubleshooting unit receiving the abnormal early warning and arranging the corresponding maintainer to perform the troubleshooting includes:
the fault overhaul unit is provided with an early warning receiving period and a shutdown maintenance period;
the method comprises the steps of receiving abnormal early warning in an early warning receiving period, setting different early warning grades, wherein the early warning grades comprise red early warning, yellow early warning and blue early warning, arranging an maintainer for fault maintenance when the abnormal early warning is blue early warning and yellow early warning, setting maintenance priority as a second grade, arranging two maintainers and a manager for fault maintenance when the abnormal early warning is red early warning, and setting the maintenance priority as a first grade;
And in the shutdown maintenance period, judging whether the fault maintenance unit has a fault problem or not, judging whether the fault problem can be repaired by itself, if so, starting a built-in maintenance program of the fault maintenance unit for repairing, otherwise, arranging corresponding maintenance personnel for repairing.
Further, the process of performing data operation and maintenance by the operation and maintenance management unit according to the pipeline thickness measurement data report comprises the following steps:
the pipeline thickness measurement data report records ultrasonic pulse data corresponding to a plurality of pipelines, wherein the ultrasonic pulse data of each pipeline comprises pipeline inner wall pulse reflection time, pipeline outer wall pulse reflection time, inner wall pulse speed, outer wall pulse speed, inner wall pulse echo signal receiving time and outer wall pulse echo signal receiving time which are respectively recorded as T Inner part 、t Outer part 、V Inner part 、V Outer part 、T Inner part and T Outer part ;
Acquiring an inner wall pulse distance and an outer wall pulse distance which are respectively marked as L Inner part and L Outer part ,L Inner part =(T Inner part -t Inner part )×V Inner part ,L Outer part =(T Outer part -t Outer part )×V Outer part , and then acquiring the thickness of the pipeline as pipeline thickness data, marking as H, and acquiring pipeline thickness data corresponding to the pipelines according to ultrasonic pulse data of each pipeline, and inputting the pipeline thickness data corresponding to all the pipelines into a set operation and maintenance database;
And acquiring the in-store time length of the pipeline thickness data in the operation and maintenance database, recording the in-store time length as T In the warehouse , setting the data destruction time length and the data transfer time length as T Destroying and T Transfer of respectively, wherein when the T In the warehouse =T Transfer of is carried out, transferring the pipeline thickness data to a data terminal correspondingly arranged at an administrator for storage, and when the T In the warehouse =T Destroying is carried out, carrying out destruction processing on the pipeline thickness data stored in the operation and maintenance database.
Compared with the prior art, the invention has the beneficial effects that:
1. The sensor module selects a plurality of arrangement points to perform installation work and debugging work of different types of sensors, so that a sensing networking is established to collect sensing related data, a good data collection foundation is laid, and the accuracy of the data is ensured; the accuracy of the data is further improved through data investigation, the abnormal data set and the normal data set are positioned through data classification, and corresponding overhauling personnel are arranged for carrying out fault overhauling, so that the abnormal problems are timely found and detected.
2. And carrying out data operation and maintenance according to the pipeline thickness measurement data report, acquiring pipeline thickness data corresponding to each pipeline, acquiring the in-store time of the pipeline thickness data in the operation and maintenance database, setting data destruction time and data transfer time, comparing the in-store time with the data destruction time and the data transfer time, and further transferring and destroying the pipeline thickness data in the operation and maintenance database, thereby achieving the purpose of efficiently managing the operation and maintenance data.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
As shown in fig. 1, the ultrasonic thickness measurement data cloud management system comprises a management center, wherein the management center is in communication connection with a sensor module, a data processing module, a data analysis module and a data operation and maintenance module;
the sensor module is used for selecting a plurality of arrangement points, performing installation work and debugging work of different types of sensors at the arrangement points, further establishing a sensing networking, and collecting sensing related data through the sensing networking;
The data processing module is used for carrying out data exploration on the sensing related data, and carrying out data classification on the sensing related data after the data exploration is completed, so as to generate a plurality of types of data sets;
The data analysis module is used for acquiring data sets of different categories, traversing and analyzing each data set, further locating an abnormal data set and a normal data set, generating an abnormal early warning according to the abnormal data set, and generating a pipeline thickness measurement data report according to the normal data set;
the data operation and maintenance module is provided with a fault maintenance unit and an operation and maintenance management unit; the fault maintenance unit is used for receiving the abnormal early warning and arranging corresponding maintenance personnel to carry out fault maintenance; and the operation and maintenance management unit is used for carrying out data operation and maintenance according to the pipeline thickness measurement data report.
It should be further noted that, in the specific implementation process, the process of selecting a plurality of placement points and performing the installation work and the debugging work of the sensors of different types at the placement points includes:
Positioning a pipeline exploration area, wherein a plurality of pipelines to be inspected are installed in the pipeline exploration area, a plurality of arrangement points are selected in the pipeline exploration area, the arrangement points are numbered, i=1, 2,3,4, … … and n are recorded as i, and n is a natural number greater than 0;
The method comprises the steps of performing installation work of different types of sensors at a plurality of arrangement points, wherein the types of the sensors comprise ultrasonic sensors and environment sensors, and the environment sensors comprise temperature sensing units, humidity sensing units and pressure sensing units;
The installation work of the sensor is carried out by corresponding to a preset equipment installation manual, the equipment installation manual records specific installation steps of the ultrasonic sensor and the environment sensor, and when the installation work is finished, corresponding debugging work is carried out, wherein the content of the debugging work is as follows: acquiring initial detection areas of each ultrasonic sensor and each environmental sensor, summarizing to generate an overall detection area, mapping and comparing the overall detection area with a pipeline exploration area, locating a detection blind spot area, debugging the positions of the arrangement points when the detection blind spot area appears, and stopping debugging work until the detection blind spot area is eliminated.
It should be further noted that, in the specific implementation process, the process of establishing the sensing networking and collecting the sensing related data through the sensing networking includes:
Marking each arrangement point as a group point, marking an ultrasonic sensor and an environment sensor corresponding to each group point as networking equipment, wherein the networking equipment is provided with corresponding networking identification codes, and different networking identification codes are associated with corresponding networking states;
The networking identification codes comprise S1 codes, S2 codes, S3 codes and S4 codes, the networking states comprise a first state, a second state, a third state and a fourth state, and the corresponding relation between the networking identification codes and the networking states is as follows:
when the networking identification code is an S1 code, the corresponding networking state is a state one, and the content of the state one is as follows: the networking equipment corresponding to each networking point has no abnormal problem, and the networking equipment starts a networking request to establish a sensing networking;
When the networking identification code is an S2 code, the corresponding networking state is a state II, and the content of the state II is as follows: the networking equipment corresponding to the networking point has an abnormal problem, and the networking equipment is forbidden to send a networking request;
When the networking identification code is an S3 code, the corresponding networking state is a state III, and the content of the state III is as follows: establishing networking communication among a plurality of networking points through networking requests, wherein the networking communication has abnormal problems, and further, the sensing networking is failed to be established through the networking communication;
When the networking identification code is the S4 code, the corresponding networking state is the state four, and the content of the state four is as follows: the networking communication among the plurality of networking points does not have abnormal problems, and then the plurality of networking points establish sensing networking successfully through networking communication;
when the networking state is state four, a plurality of networking points establish the sensing networking successfully, and other networking states are the conditions that the establishment of the sensing networking fails, and after the establishment of the sensing networking is successful, the sensing related data are acquired through the sensing networking;
The sensing related data comprise ultrasonic pulse data, temperature data, humidity data and pressure data, the ultrasonic pulse data are acquired through an ultrasonic sensor, and the temperature data, the humidity data and the pressure data are acquired through a temperature sensing unit, a humidity sensing unit and a pressure sensing unit which are included in an environment sensor respectively.
It should be further noted that, in the implementation process, the process of performing data exploration on the sensing related data includes:
The data processing module sets a data receiving period, and records the data receiving period as T, T= [ T1, T2], wherein T1 is the starting time point of the data receiving period, and T2 is the ending time point of the data receiving period;
At the moment corresponding to the T1, the set data receiving area receives the sensing related data according to the preset receiving speed, at the moment corresponding to the T2, the receiving operation of the data receiving area is stopped, the receiving duration is obtained and marked as TL, TL=T2-T1 is provided, the monitoring frequency corresponding to the receiving duration is set, the monitoring frequency is marked as f, and f=TL/Sc is provided, wherein Sc is a single safe encryption duration, and the received sensing related data is encrypted within the single safe encryption duration so as to prevent the sensing related data from being illegally tampered by the outside;
Acquiring the total data quantity of the sensing related data, namely D Total (S) , setting a unit quantity of investigation, namely D ', further acquiring the concurrency number of the data investigation required to be carried out, namely bf, wherein the concurrency number is bf=D Total (S) /D', simultaneously executing the data investigation of the sensing related data with the number represented by the concurrency number, acquiring the data format and the data content of the sensing related data, comparing the data format and the data content with the preset standard format and the compliance content, and if the data format and the data content are consistent, carrying out no operation, otherwise, converting the data format and the data content of the sensing related data into the corresponding standard format and the compliance content.
It should be further noted that, in the implementation process, the process of classifying the sensing related data after the data investigation is completed, and further generating the data sets of several categories includes:
Acquiring sensing related data after data investigation is completed, setting a data classification program, initializing a classification function of the data classification program through a preset program configuration code, and associating a preset classification rule with the data classification program after the initialization is completed;
The content of the classification rule is as follows: traversing all sensing related data, wherein each sensing related data is associated with a corresponding potential risk factor coefficient, the potential risk factor coefficient is marked as gamma, the gamma is marked as [0,1], a data grouping interval is set, the data grouping interval comprises a safety class interval, a dangerous class interval and a suspected dangerous class interval, the different data grouping intervals correspond to data groups of different classes, wherein the safety class interval is marked as omega 1, the corresponding interval numerical range is marked as omega 1= [0,0.4], the suspected dangerous class interval is marked as omega 2, the corresponding interval numerical range is marked as omega 2= (0.4,0.75), the dangerous class interval is marked as omega 3, and the corresponding interval numerical range is marked as omega 3= (0.75,1);
when gamma is epsilon omega 1, the class of the generated data set is a safety data set;
when gamma is epsilon omega 2, the class of the generated data set is suspicious data set;
When gamma is epsilon omega 3, the class of the generated data set is a dangerous data set.
It should be further noted that, in the specific implementation process, each data set is traversed and analyzed, so that an abnormal data set and a normal data set are located, an abnormal early warning is generated according to the abnormal data set, and a process of generating a pipeline thickness measurement data report according to the normal data set includes:
Acquiring data sets of different categories, namely a safety data set, a suspicious data set and a dangerous data set, sequentially traversing all the data sets of different categories by a data analysis module, and synchronously associating a processing identifier for the data sets when traversing the data sets for the first time, and marking the processing identifier as SID;
When the data group is associated with a processing identifier, a processing progress bar is synchronously generated, the processing progress bar is used for representing the processing progress of the current data group, the numerical value range of the processing progress is 0-100%,0% represents that the processing of the data group is just started, and 100% represents that the processing of the data group is completed;
The method comprises the steps of obtaining a data set with the processing progress of 100%, locating the data set, when traversing to a safe data set, locating the safe data set as a normal data set, when traversing to a dangerous data set, locating the dangerous data set as an abnormal data set, when traversing to a suspicious data set, obtaining the variance of a data value corresponding to the suspicious data set, comparing the variance with a preset judging threshold, recording the variance as tau 1, judging the variance as tau 2, locating the suspicious data set as the abnormal data set if tau 1≥τ2, and locating the suspicious data set as the normal data set if tau 1<τ2;
when an abnormal data set is generated, generating abnormal early warning synchronously according to the abnormal data set;
and when the normal data set is generated, synchronously generating a pipeline thickness measurement data report according to the normal data set.
It should be further noted that, in the implementation process, the process of receiving the abnormal early warning by the troubleshooting unit and arranging the corresponding maintainer to perform the troubleshooting includes:
the fault overhaul unit is provided with an early warning receiving period and a shutdown maintenance period;
The method comprises the steps of receiving abnormal early warning in an early warning receiving period, wherein different early warning grades are set for the abnormal early warning, the early warning grades comprise red early warning, yellow early warning and blue early warning, an abnormal fluctuation interval is set, and the abnormal fluctuation interval is recorded as omega Abnormality of ;
Recording temperature data, humidity data and pressure data corresponding to the sensing related data in the abnormal data set as D Warm temperature 、D Wet state and D Pressing respectively, generating a red early warning if three conditions of D Warm temperature ∈Ω Abnormality of ,D Wet state ∈Ω Abnormality of and D Pressing ∈Ω Abnormality of are met, generating a yellow early warning if any two conditions of D Warm temperature ∈Ω Abnormality of ,D Wet state ∈Ω Abnormality of and D Pressing ∈Ω Abnormality of are met, generating a blue early warning if any one condition of D Warm temperature ∈Ω Abnormality of ,D Wet state ∈Ω Abnormality of and D Pressing ∈Ω Abnormality of is met, and otherwise, not generating an abnormal early warning;
When the abnormal early warning is blue early warning and yellow early warning, arranging an maintainer for fault maintenance, setting the maintenance priority as a second level, and when the abnormal early warning is red early warning, arranging two maintainers and a manager for fault maintenance, and setting the maintenance priority as a first level;
judging whether the fault maintenance unit has a fault problem or not in the shutdown maintenance period, if the working parameters of the fault maintenance unit are inconsistent with the preset normal working parameters, indicating that the fault problem exists, otherwise, not;
Judging whether the fault problem can be repaired by itself, if so, starting a built-in maintenance program of the fault maintenance unit for repairing, otherwise, arranging corresponding maintenance personnel for repairing;
In the overhaul priority, the overhaul priority of the first stage is greater than that of the second stage.
It should be further noted that, in the specific implementation process, the process of performing data operation and maintenance by the operation and maintenance management unit according to the pipeline thickness measurement data report includes:
the pipeline thickness measurement data report records ultrasonic pulse data corresponding to a plurality of pipelines, wherein the ultrasonic pulse data of each pipeline comprises pipeline inner wall pulse reflection time, pipeline outer wall pulse reflection time, inner wall pulse speed, outer wall pulse speed, inner wall pulse echo signal receiving time and outer wall pulse echo signal receiving time which are respectively recorded as T Inner part 、t Outer part 、V Inner part 、V Outer part 、T Inner part and T Outer part ;
Acquiring an inner wall pulse distance and an outer wall pulse distance which are respectively marked as L Inner part and L Outer part , wherein L Inner part =(T Inner part -t Inner part )×V Inner part ,L Outer part =(T Outer part -t Outer part )×V Outer part is adopted, the thickness of the pipeline is further acquired as pipeline thickness data, H is marked as H, H= |L Inner part -L Outer part |, pipeline thickness data corresponding to the pipelines are further acquired according to the ultrasonic pulse data of each pipeline, and the pipeline thickness data corresponding to all the pipelines are input into a set operation and maintenance database;
And acquiring the in-store time length of the pipeline thickness data in the operation and maintenance database, recording the in-store time length as T In the warehouse , setting the data destruction time length and the data transfer time length as T Destroying and T Transfer of respectively, wherein when the T In the warehouse =T Transfer of is carried out, transferring the pipeline thickness data to a data terminal correspondingly arranged at an administrator for storage, and when the T In the warehouse =T Destroying is carried out, carrying out destruction processing on the pipeline thickness data stored in the operation and maintenance database.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (5)
1. The ultrasonic thickness measurement data cloud management system comprises a management center and is characterized in that the management center is in communication connection with a sensor module, a data processing module, a data analysis module and a data operation and maintenance module;
the sensor module is used for selecting a plurality of arrangement points, performing installation work and debugging work of different types of sensors at the arrangement points, further establishing a sensing networking, and collecting sensing related data through the sensing networking;
The data processing module is used for carrying out data exploration on the sensing related data, and carrying out data classification on the sensing related data after the data exploration is completed, so as to generate a plurality of types of data sets;
The data analysis module is used for acquiring data sets of different categories, traversing and analyzing each data set, further locating an abnormal data set and a normal data set, generating an abnormal early warning according to the abnormal data set, and generating a pipeline thickness measurement data report according to the normal data set;
The data operation and maintenance module is provided with a fault maintenance unit and an operation and maintenance management unit; the fault maintenance unit is used for receiving the abnormal early warning and arranging corresponding maintenance personnel to carry out fault maintenance; the operation and maintenance management unit is used for carrying out data operation and maintenance according to the pipeline thickness measurement data report;
the process for selecting a plurality of arrangement points to perform the installation work and the debugging work of the sensor comprises the following steps:
Positioning a pipeline exploration area, installing a plurality of pipelines, selecting a plurality of arrangement points in the pipeline exploration area, numbering the arrangement points, namely i, i=1, 2,3,4, … … and n, wherein n is a natural number larger than 0, installing different types of sensors at the plurality of arrangement points, wherein the types of the sensors comprise ultrasonic sensors and environment sensors, debugging the sensors after the installation is completed, acquiring the overall detection area of each ultrasonic sensor and environment sensor, mapping the overall detection area with the pipeline exploration area, positioning a detection blind spot area, debugging the positions of the arrangement points when the detection blind spot area appears, and stopping the debugging until the detection blind spot area is eliminated;
the process for establishing the sensing networking to collect the sensing related data comprises the following steps:
marking each arrangement point as a group point, marking an ultrasonic sensor and an environment sensor corresponding to each group point as networking equipment, wherein the networking equipment is provided with corresponding networking identification codes, different networking identification codes are associated with corresponding networking states, the networking identification codes comprise S1 codes, S2 codes, S3 codes and S4 codes, and the networking states comprise a state one, a state two, a state three and a state four;
When the networking identification code is an S1 code, the corresponding networking state is a state I, the networking equipment corresponding to each networking point has no abnormal problem, and the networking equipment starts a networking request to establish a sensing networking;
when the networking identification code is an S2 code, the corresponding networking state is a second state, the networking equipment corresponding to the networking point has an abnormal problem, and the networking equipment is forbidden to send a networking request;
when the networking identification code is an S3 code, the corresponding networking state is a state III, networking communication among a plurality of networking points is established through networking requests, the networking communication has an abnormal problem, and further the establishment of sensing networking through networking communication fails;
When the networking identification code is the S4 code, the corresponding networking state is the state four, no abnormal problem exists in networking communication among a plurality of networking points, and then the networking points establish sensing networking successfully through networking communication;
After the sensing networking is established successfully, acquiring sensing related data through the sensing networking, wherein the sensing related data comprises ultrasonic pulse data, temperature data, humidity data and pressure data;
The process of data exploration on the sensing related data comprises the following steps:
Setting a data receiving period, namely T, T= [ T1, T2], receiving the sensing related data according to a preset receiving speed by the set data receiving area at the moment corresponding to T1, stopping the receiving operation of the data receiving area at the moment corresponding to T2, obtaining a receiving duration, namely TL, wherein TL=T2-T1, setting a monitoring frequency corresponding to the receiving duration, namely f, wherein f=TL/Sc, wherein Sc is a single safe encryption duration, and encrypting the received sensing related data in the single safe encryption duration;
The total data quantity of the sensing related data is obtained and marked as D Total (S) , the unit quantity of investigation is set and marked as D', the concurrency number of the data investigation required is obtained and marked as bf, and the data investigation of the sensing related data with the number represented by the concurrency number is executed at the same time.
2. The ultrasonic thickness data cloud management system of claim 1, wherein the process of data classifying the sensor-related data to generate a plurality of categories of data sets comprises:
Setting a data classification program, initializing a classification function of the data classification program through a preset program configuration code, associating preset classification rules with the data classification program after the initialization is completed, and further classifying data through the classification rules to locate the class of the data group, wherein the class of the data group comprises a safety data group, a suspicious data group and a dangerous data group.
3. The ultrasonic thickness measurement data cloud management system of claim 2, wherein the process of locating the abnormal data set and the normal data set and generating the corresponding abnormal early warning and pipeline thickness measurement data report comprises:
The data analysis module traverses all data groups of different categories in sequence, and associates a processing identifier for the data group synchronously when traversing the data group for the first time, and synchronously generates a processing progress bar when the data group is associated with the processing identifier, wherein the processing progress bar is used for representing the processing progress of the current data group, and the numerical value range of the processing progress is 0-100%;
The method comprises the steps of obtaining a data set with the processing progress of 100%, locating the data set, when traversing to a safe data set, locating the safe data set as a normal data set, when traversing to a dangerous data set, locating the dangerous data set as an abnormal data set, when traversing to a suspicious data set, obtaining the variance of a data value corresponding to the suspicious data set, comparing the variance with a preset judging threshold, recording the variance as tau 1, judging the variance as tau 2, locating the suspicious data set as the abnormal data set if tau 1≥τ2, and locating the suspicious data set as the normal data set if tau 1<τ2;
when an abnormal data set is generated, generating abnormal early warning synchronously according to the abnormal data set;
and when the normal data set is generated, synchronously generating a pipeline thickness measurement data report according to the normal data set.
4. A cloud ultrasound thickness data management system according to claim 3, wherein the process of the troubleshooting unit receiving an anomaly early warning and scheduling the corresponding service personnel for troubleshooting comprises:
the fault overhaul unit is provided with an early warning receiving period and a shutdown maintenance period;
the method comprises the steps of receiving abnormal early warning in an early warning receiving period, setting different early warning grades, wherein the early warning grades comprise red early warning, yellow early warning and blue early warning, arranging an maintainer for fault maintenance when the abnormal early warning is blue early warning and yellow early warning, setting maintenance priority as a second grade, arranging two maintainers and a manager for fault maintenance when the abnormal early warning is red early warning, and setting the maintenance priority as a first grade;
And in the shutdown maintenance period, judging whether the fault maintenance unit has a fault problem or not, judging whether the fault problem can be repaired by itself, if so, starting a built-in maintenance program of the fault maintenance unit for repairing, otherwise, arranging corresponding maintenance personnel for repairing.
5. The ultrasonic thickness measurement data cloud management system of claim 4, wherein the operation and maintenance management unit performs data operation and maintenance according to the pipeline thickness measurement data report, and the operation and maintenance comprises:
the pipeline thickness measurement data report records ultrasonic pulse data corresponding to a plurality of pipelines, wherein the ultrasonic pulse data of each pipeline comprises pipeline inner wall pulse reflection time, pipeline outer wall pulse reflection time, inner wall pulse speed, outer wall pulse speed, inner wall pulse echo signal receiving time and outer wall pulse echo signal receiving time which are respectively recorded as T Inner part 、t Outer part 、V Inner part 、V Outer part 、T Inner part and T Outer part ;
Acquiring an inner wall pulse distance and an outer wall pulse distance which are respectively marked as L Inner part and L Outer part ,L Inner part =(T Inner part -t Inner part )×V Inner part ,L Outer part =(T Outer part -t Outer part )×V Outer part , and then acquiring the thickness of the pipeline as pipeline thickness data, marking as H, and acquiring pipeline thickness data corresponding to the pipelines according to ultrasonic pulse data of each pipeline, and inputting the pipeline thickness data corresponding to all the pipelines into a set operation and maintenance database;
And acquiring the in-store time length of the pipeline thickness data in the operation and maintenance database, recording the in-store time length as T In the warehouse , setting the data destruction time length and the data transfer time length as T Destroying and T Transfer of respectively, wherein when the T In the warehouse =T Transfer of is carried out, transferring the pipeline thickness data to a data terminal correspondingly arranged at an administrator for storage, and when the T In the warehouse =T Destroying is carried out, carrying out destruction processing on the pipeline thickness data stored in the operation and maintenance database.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202410415372.4A CN118013445B (en) | 2024-04-08 | 2024-04-08 | Ultrasonic thickness measurement data cloud management system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202410415372.4A CN118013445B (en) | 2024-04-08 | 2024-04-08 | Ultrasonic thickness measurement data cloud management system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN118013445A CN118013445A (en) | 2024-05-10 |
CN118013445B true CN118013445B (en) | 2024-06-25 |
Family
ID=90958945
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202410415372.4A Active CN118013445B (en) | 2024-04-08 | 2024-04-08 | Ultrasonic thickness measurement data cloud management system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN118013445B (en) |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110332463A (en) * | 2019-06-14 | 2019-10-15 | 南京理工大学 | Pipeline structure damage monitoring system based on wireless sensor network |
CN115573697A (en) * | 2022-09-08 | 2023-01-06 | 中国石油大学(华东) | Multiphase flow pipeline silt particle content and erosion monitoring and early warning device and method |
Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
RU2212660C1 (en) * | 2001-12-25 | 2003-09-20 | ЗАО "Нефтегазкомплектсервис" | Method of intratube ultrasonic testing |
CN102630302B (en) * | 2009-09-18 | 2014-11-05 | 科诺科菲利浦公司 | High precision ultrasonic corrosion rate monitoring |
KR101499612B1 (en) * | 2014-06-25 | 2015-03-06 | 주식회사 피레타 | Wall-thinning condition management system and method using ultrasonic scanning |
CN107607321B (en) * | 2017-09-06 | 2019-11-05 | 成都大汇物联科技有限公司 | A kind of equipment fault accurate positioning method |
RU2687086C1 (en) * | 2018-10-11 | 2019-05-07 | Акционерное общество "ИнтроСкан Технолоджи" | Method of ultrasonic monitoring of pipeline wall thickness |
CN110322110A (en) * | 2019-05-09 | 2019-10-11 | 福建省锅炉压力容器检验研究院 | A kind of petrochemical industry pressure pipeline management system |
CN110849972A (en) * | 2019-11-27 | 2020-02-28 | 孙文龙 | Pipeline internal corrosion condition ultrasonic monitoring system and method based on Internet of things |
CN116026389A (en) * | 2023-03-07 | 2023-04-28 | 湖南科技学院 | Intelligent sensor operation detection system based on data analysis |
CN117197998A (en) * | 2023-10-10 | 2023-12-08 | 深圳市麦驰物联股份有限公司 | Sensor integrated nursing system of thing networking |
CN117268961B (en) * | 2023-11-23 | 2024-02-20 | 宁波市特种设备检验研究院 | Fatigue failure early warning method for metal parts |
CN117807877A (en) * | 2023-12-29 | 2024-04-02 | 昆明理工大学 | Pipeline detection system based on digital twin, system construction method and detection method |
-
2024
- 2024-04-08 CN CN202410415372.4A patent/CN118013445B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110332463A (en) * | 2019-06-14 | 2019-10-15 | 南京理工大学 | Pipeline structure damage monitoring system based on wireless sensor network |
CN115573697A (en) * | 2022-09-08 | 2023-01-06 | 中国石油大学(华东) | Multiphase flow pipeline silt particle content and erosion monitoring and early warning device and method |
Also Published As
Publication number | Publication date |
---|---|
CN118013445A (en) | 2024-05-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101894595B (en) | Fault detection method applied to nuclear power plant system | |
US20200200943A1 (en) | Methods and systems for providing access to interferometric system data | |
CN106485805A (en) | A kind of pipeline inspection management method and system | |
CN114997682B (en) | Construction site safety monitoring system and method based on big data | |
CN112380242A (en) | Optical cable test active alarm method based on OTDR | |
CN109738014A (en) | The intelligent diagnosing method and system of city integrated piping lane equipment fault | |
CN107657390A (en) | A kind of special safety equipment hidden danger management and control big data monitoring system and monitoring method | |
US20150204752A1 (en) | Method for detecting at least one variable associated with the formation of at least one joint and/or a machine during assembly of a pipeline system | |
CN116203362B (en) | Distribution panel state monitoring system | |
CN107643147A (en) | A kind of steam leaks track and localization detection method and device | |
US11755007B2 (en) | System and method for determining a health condition and an anomaly of an equipment using one or more sensors | |
CN116823220A (en) | Cable running state monitoring platform and equipment | |
CN118013445B (en) | Ultrasonic thickness measurement data cloud management system | |
CN111707377B (en) | Body temperature detection cloud platform system | |
CN116823192A (en) | Iron tower intelligent detection system | |
CN116398824A (en) | Buried pipeline micro-leakage monitoring and early warning system and early warning method | |
CN116858364A (en) | Digital environmental noise monitoring instrument online metering detection device and system based on electrostatic actuator method | |
CN114355969B (en) | Intelligent heat supply pipe network leakage detection method and system by using unmanned aerial vehicle inspection | |
CN107765123A (en) | Detected rule update method and Electrical Safety monitoring system | |
CN111800754A (en) | Self-sensing and self-early warning temporary support system and construction method thereof | |
CN105656990A (en) | Instrument monitoring method and system | |
CN212486800U (en) | Self-sensing and self-early warning temporary support system | |
CN117353807B (en) | Optical cable remote monitoring system and method based on artificial intelligence | |
CN112650611B (en) | Method and system for diagnosing server faults in batches | |
CN109308040A (en) | A kind of petroleum chemical enterprise's intelligent patrol detection device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |