CN114997759A - Heat supply pipeline support and hanger stability early warning method and system - Google Patents
Heat supply pipeline support and hanger stability early warning method and system Download PDFInfo
- Publication number
- CN114997759A CN114997759A CN202210939155.6A CN202210939155A CN114997759A CN 114997759 A CN114997759 A CN 114997759A CN 202210939155 A CN202210939155 A CN 202210939155A CN 114997759 A CN114997759 A CN 114997759A
- Authority
- CN
- China
- Prior art keywords
- hanger
- support
- stability
- instability
- pipeline
- 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.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Human Resources & Organizations (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Software Systems (AREA)
- Computational Mathematics (AREA)
- Economics (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- Computational Linguistics (AREA)
- Biophysics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Biomedical Technology (AREA)
- Computing Systems (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Pure & Applied Mathematics (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Artificial Intelligence (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Probability & Statistics with Applications (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Game Theory and Decision Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Marketing (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
Abstract
The invention relates to a heat supply pipeline support and hanger stability early warning method and system, obtain descending height, deformation degree, vibration information and pipeline of the support and hanger to each support and hanger pressure of the vibration information; obtaining the state index and the stability influence index of each hanger, and determining the instability of each hanger; grouping the hangers based on instability and pressure to obtain three hanger groups, wherein the three hanger groups comprise a hanger group with good stability and poor stability and neutralization stability; for the support hanger group with poor stability and neutral stability, acquiring the horizontal change degree of the pipeline at the position of the support pipeline of each support hanger in the group, and combining the instability of the corresponding support hanger to obtain the instability degree of each support hanger; and comparing the unstable degree with a set threshold value, and alarming when the unstable degree is greater than the set threshold value. Namely, the stability of the support and hanger is evaluated according to the environmental factors of the support and hanger, the self-changing factors and the pipeline factors.
Description
Technical Field
The invention relates to the field of detection of a heat supply pipeline support and hanger system, in particular to a heat supply pipeline support and hanger stability early warning method and system.
Background
The popularization of the support and hanger system greatly improves the safety of an overground heat supply pipeline and reduces secondary disasters caused by the safety, however, some accident cases still show that even if the support and hanger system is installed, accidents still cannot be avoided, and most of the reasons are that the support and hanger system is long in installation year, parts are aged, bolts are loosened, and the support and hanger system is not subjected to necessary maintenance in the long-term service process, so that the support and hanger system is out of work.
Therefore, not only is the correct installation of the support and hanger required by design, but also the necessary routine maintenance of the support and hanger system during service, such as replacement of corroded or corroded parts, tightening of loose bolts, etc., is required. Because the particularity of the mounting position of the supporting and hanging frame makes the state of the equipment checked by simply depending on manual patrol very laborious, especially for the large-scale project, the number of the supporting and hanging frames is extremely large, and the manual check is very inconvenient, a supporting and hanging frame monitoring and early warning system with complete functions and reliable performance needs to be established very necessary and urgently needed.
At present, vibration monitoring is generally introduced into the field of monitoring a support and hanger structure, and a vibration acceleration sensor or a vibration displacement sensor is utilized to monitor the state of the structure. However, only starting from the vibration detection angle of a certain hanger, the considered parameters are too single, and the stability of the monitored hanger of the section of heat supply pipeline cannot be accurately analyzed.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a method and a system for early warning the stability of a support and hanger of a heat supply pipeline, and the adopted technical scheme is as follows:
the invention discloses a stability early warning method for a heat supply pipeline support and hanger, which comprises the following steps of:
the method comprises the steps of obtaining descending heights of N supports and hangers corresponding to a section of heat supply pipeline at different moments in a set time period, deformation degrees of the supports and hangers, vibration information and pressure of the pipeline to each support and hanger, wherein N is more than or equal to 2;
obtaining the state index of each hanger according to the descending height and the deformation degree; obtaining a stability influence index of each hanger according to the vibration information and the pressure of the pipeline to each hanger;
determining instability of each hanger based on the state index and the stability influence index; grouping the hangers corresponding to the section of heat supply pipeline based on the instability and the pressure to obtain three hanger groups, wherein the three hanger groups comprise a hanger group with good stability, poor stability and poor stability;
for the support hanger group with poor stability and neutral stability, acquiring the horizontal change degree of the pipeline at the position where each support hanger supports the pipeline in the group, and combining the instability of the corresponding support hanger to obtain the instability degree of each support hanger; and comparing the instability degree with a set threshold value, and alarming when the instability degree is greater than the set threshold value.
Preferably, the state index is a ratio of a calculated standard deviation of the descent height within a set time period to a difference between a maximum value and a minimum value in the sequence of the deformation of the support hanger.
Preferably, the stability factor indicator is determined by calculating a product of a degree of change in the vibration information and a degree of change in pressure of the pipe against the strut.
Preferably, the instability of each hanger is the product of a state index and a stability influence index.
Preferably, the grouping is performed by using a K-Means clustering algorithm.
Preferably, the instability level is a product of the calculated degree of change in the pipeline level on each cradle and the instability of the cradle.
The invention also provides a heat supply pipeline support and hanger stability early warning system which comprises a processor and a memory, wherein the processor executes the technical scheme of the heat supply pipeline support and hanger stability early warning method stored in the memory.
The invention has the following beneficial effects:
according to the method and the device, the plurality of parameter information is obtained, the state index and the stability influence index of the support and hanger are respectively obtained according to the parameter information, the state index and the stability influence index of the support and hanger are used for reflecting the self state of the support and hanger and the index of the support and hanger influenced by the environment, the deformation information of the pipeline is combined, the instability degree of each support and hanger is comprehensively analyzed, the parameters considered by the analysis are more comprehensive, and the stability evaluation of the support and hanger is more accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for warning stability of a heat supply pipeline hanger of the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the embodiments, structures, features and effects thereof according to the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
As shown in FIG. 1, the method for warning the stability of the heat supply pipeline support hanger comprises the following steps:
acquiring the descending height of N supports and hangers corresponding to a section of heat supply pipeline in a set time period, the deformation degree of the supports and hangers, vibration information and the pressure of the pipeline to each support and hanger, wherein N is more than or equal to 2;
obtaining the state index of each hanger according to the descending height and the deformation degree; obtaining a stability influence index of each hanger according to the vibration information and the pressure of the pipeline to each hanger;
determining instability of each hanger based on the state index and the stability influence index;
grouping the hangers corresponding to the section of heat supply pipeline based on the instability and the pressure to obtain three hanger groups, wherein the three hanger groups comprise a hanger group with good stability, poor stability and poor stability;
for the support hanger group with poor stability and neutral stability, acquiring the deformation change condition of the pipeline at the position where each support hanger supports the pipeline in the group, and combining the instability of the corresponding support hanger to obtain the instability degree of each support hanger; and comparing the instability degree with a set threshold value, and alarming when the instability degree is greater than the set threshold value.
The method of the invention considers vibration information and pressure information brought by environmental factors, deformation information of the support and hanger and deformation information of the pipeline, comprehensively analyzes the support and hanger of the heat supply pipeline at multiple angles, and determines the instability degree of the support and hanger, thereby early warning is carried out in time, and the follow-up timely maintenance is convenient.
The following describes an embodiment of a heat supply pipeline hanger stability early warning method according to the present invention, with 10 hangers of a section of heat supply pipeline erected on the ground in a certain residential quarter or in the vicinity of a certain street as monitoring objects.
Specifically, the method for early warning the stability of the heat supply pipeline support hanger comprises the following steps:
step 1, obtaining descending heights of 10 supports and hangers corresponding to the monitored heat supply pipeline at different moments in a set time period, deformation degrees of the supports and hangers, vibration information and pressure of the pipeline to the supports and hangers.
The descending height is measured by an infrared distance meter, the infrared distance meter is arranged in the middle of each support and hanger, the descending height of each support and hanger in a set time period is detected in real time, the data refreshing frequency of the infrared distance meter is 5s, ten minutes is taken as the time length, and 120 data sequences of the descending heights can be obtained
。
It should be noted that, when laying a pipeline, the road surface is usually excavated and then the support is embedded, or the support is directly fixed on the road surface by punching, and no matter what way, the load of road traffic can cause the road surface to suddenly drop after a long time, so that the pipeline support laid on the road surface also drops. Once the support is lowered, it will have an effect on the pipeline, and therefore it is necessary to collect the height of the descent of each cradle.
The deformation degree of the support and hanger is measured by using an angle instrument to measure the angle change of the support, and the change sequence L of the angle deformation in a set time period is obtained
。
It should be noted that, as the support descends, the force of the pipeline on the support changes, and the angle of the support deforms, and as the descending height and the deformation angle of the support change, the stability of the pipeline support is also affected.
The vibration information of the support and hanger can be acquired by acquiring the vibration state of the support and hanger structure through a vibration sensor which is usually arranged at the middle position of an inclined rod of the support and hanger so that the vibration state of the support and hanger can be captured when the support and hanger is excited; specifically, the data refresh frequency of the vibration sensor is 5s, the vibration data change in a certain time can be recorded, and a vibration change sequence is obtained by taking ten minutes as the time length
。
It should be noted that the vibration state of the support and hanger mainly comes from environmental vibration, such as physical damage caused by excitation of force in the environment, such as bolt loosening caused by excitation force generated when the water pipe vibrates, or such as vibration generated when the automobile runs, and meanwhile, also from chemical damage caused by environmental factors, such as water mist in the air, cyclic temperature change, bolt corrosion or bolt loosening caused by corrosive gas.
In which the pressure of the conduit against the hangersThe pressure of each bracket is read by the pressure sensor through the pipeline, and the pressure sensor is arranged at the contact point of the pipeline and the bracket to detect the pressure change in real time. Wherein, the data refreshing frequency of the pressure sensor is 5s each time, and the time length is ten minutes uniformly, so that 120 pressures can be obtained
。
When laying the heat supply pipeline, the support is before descending, and the pipeline is certain to the pressure of support effect, and when along with the decline of support, the pipeline will change to the pressure of support effect, and the more that the support descends, the change of pressure is big more.
The set time period in this embodiment may also be one day, and then data collection is performed according to a set time interval, which is set according to actual conditions, and is not limited to the set time period in the above example.
Step 2, obtaining the state index of each hanger according to the descending height and the deformation degree; and obtaining the stability influence index of each hanger according to the vibration information and the pressure of the pipeline to each hanger.
The state index of each support and hanger in the embodiment is a ratio of a calculated standard deviation of the descent height in a set time period to a difference value between a maximum value and a minimum value in a support and hanger deformation sequence.
Specifically, the condition index of each hanger is
Wherein the content of the first and second substances,
and the standard deviation of the descending height at all times in a set time period represents the fluctuation condition of the descending height data, and the larger the fluctuation is, the larger the influence on the deformation state of the bracket is.
The difference value between the maximum value and the minimum value of the change degree of the angle of the bracket in unit time is larger, and the larger the difference value is, the larger the influence on the deformation state of the bracket is.
The stability influence index of each hanger in the present embodiment is determined by calculating the product of the degree of change of the vibration information and the degree of change of the pressure of the pipe to the hanger.
The degree of change of the vibration information in the above is a standard deviation of the vibration information in the calculation setting time period.
The pressure change degree of the pipeline to the support and hanger in the above is the standard deviation of the vibration information in the set time period, and as another embodiment, the present embodiment may also perform data processing on the pressure sequence of the pipeline to the support and hanger to obtain the pressure change degree; the specific data processing is as follows:
firstly, performing median filtering processing on a pressure sequence, and secondly, performing linear fitting on the filtered pressure sequence to obtain the slope of the pressure sequence in a set time period; and obtaining the pressure change degree Q according to the slope obtained by fitting.
It should be noted that, since the pressure change is gradually increased linearly with time, the obtained pressure change sequence is represented linearly; in an ideal experimental condition, the pressure changes linearly, and the reliability of the detected data is expressed linearly; the pressure change rate per unit time was linearly expressed, and the obtained data was subjected to least square fitting to form a straight line.
Step 3, determining the instability of each hanger based on the state index and the stability influence index; and grouping the hangers corresponding to the section of heat supply pipeline based on the instability and the pressure sequence to obtain three hanger groups, including the hanger group with good stability, poor stability and neutralization stability.
The instability of each hanger in this embodiment is a product of a state index and a stability influence index, and it is a product of various factors to characterize the stability of the hanger, thereby obtaining the stability of each hanger in a monitored section of heat supply pipeline.
In this embodiment, based on the instability of each hanger and the corresponding pressure sequence, the similarity between any two hangers is calculated:
wherein A and B are two different supports and hangers, F A Pressure, Y, for a set period of time of cradle A A For instability in a set period of time of cradle A, F B Pressure, Y, for a set period of time of cradle B B Instability in a set period of time for cradle B.
Wherein DTW is dynamic time warping, and the value range of DTW is [0,1 ]]When the two sequences of scaffold pressure changes are close, the value of DTW tends to 1, indicating that the more similar; otherwise, the trend is 0;
) The difference is the difference of the fluctuation standard deviations of the pressure change sequences of the two brackets, the larger the difference is, the lower the similarity is, otherwise, the higher the similarity is;
) The absolute value of the difference value of the instability indexes of the two brackets is shown, and the larger the difference value is, the smaller the similarity is; thus obtaining the similarity relation of two brackets.
Based on the similarity of any two hangers, calculating the corresponding difference distance:
and D is the difference distance of different support instabilities, the sample distance of different support instabilities is determined according to the similarity relation, the lower the similarity is, the farther the distance is, and the higher the similarity is, the closer the distance is.
And according to the obtained difference distance, grouping different scaffolds by using a K-Means clustering algorithm.
The k value was defined as 3 and the different scaffolds were grouped into three groups according to instability, from low to high.
The first group has good stability, the stability of the bracket of the group is relatively good, the influence of surrounding factors is low, and the descending deformation of the bracket is not obvious.
In the second group, stability, the stability of the stent in this group is general, and the stent falling deformation has little effect on stability.
And the third group has poor stability, the stability of the bracket of the group is poor, the descending deformation is obvious, the influence on the pipeline is great, and the serious deformation of the pipeline is caused.
In the above, the hangers are grouped based on the instability of each hanger, and the hangers in the similar state are grouped into one group by grouping, so that the specific stability of the hangers in each group is analyzed.
Step 4, for the support hanger group with the stability and the stability being poor, acquiring the horizontal change degree of the pipeline at the position where each support hanger supports the pipeline in the group, and combining the instability of the corresponding support hanger to obtain the instability degree of each support hanger; and comparing the instability degree with a set threshold value, and alarming when the instability degree is greater than the set threshold value.
The instability level in this embodiment is the calculated product of the degree of change in the pipe level on each hanger and the instability of the hanger.
The horizontal change degree of the pipeline at the position where each support hanger supports the pipeline is measured by an infrared horizontal testing device,
wherein i is the serial number of the support and hanging frame; of course, the deformation sensor may be used to calculate the variation of the pipe level within the set time period, and the variation of the pipe level is actually the variance of the calculated variation of the pipe level at all times within the set time period.
It should be noted that the horizontal deformation of the pipeline is generated by the height change of the supporting and hanging bracket; the invention monitors that a section of heat supply pipeline is provided with 10 hangers, the hangers have chain reaction due to the reason that the hangers support a heat supply pipeline together, namely, if the height of one hanger is reduced, the pressure born by two adjacent hangers is increased, the height of the hanger is changed due to the influence of the reduced hangers, and the pipeline above the hanger is deformed based on the reduced hanger, so that the height of one hanger is changed to change other hangers, and each hanger is corrected according to the deformation condition of the pipeline supported by each hanger, thus the unstable hanger can be accurately extracted, and the alarm and subsequent adjustment can be carried out on the unstable hanger.
The gallows group in this embodiment has three groups, good stability, stability in and poor stability's group, wherein to good stability's group, no longer carry out the analysis to it in this embodiment, to stability in and poor stability's group, in this embodiment, analyze it, to the instability of each gallows of organizing, combine corresponding pipeline deformation condition with it, confirm the unstable degree of each gallows, compare unstable degree and settlement threshold value, judge whether this gallows needs the early warning, and then overhaul it.
The set threshold in the above embodiment is a threshold corresponding to the degree of instability when the support hanger of the heat supply pipeline is normal, which may be obtained by statistics according to historical data, or may be obtained by determining a standard support hanger, calculating the degree of instability in the current state, and using the calculated degree of instability as the set threshold.
Based on the early warning, the invention can also adjust the state of each monitored hanger, improve the stability of the monitored hanger, and the specific maintenance method comprises the following steps: adjusting the height of the support and hanger, overhauling bolts on the support and hanger or replacing the support and hanger, and the like.
Further, the invention can predict the instability degree of the heat supply pipeline in a future period, and specifically comprises the following steps:
obtaining an instability degree sequence of the support hangers in each group within a set time based on the obtained plurality of groups;
inputting the stability degree sequence into the constructed TCN network to predict the instability degree of the supports and hangers, and obtaining the predicted instability degree of each support and hanger in the next set time period;
and when the predicted instability degree is larger than the set threshold value, reminding workers.
In the training of the TCN network, the obtained support instability sequence is used as the former part of the characteristic sequence and is input into the TCN neural network for training, and the obtained next value is used as a label, so that the TCN can learn the next predicted value of the current sequence; the loss function adopted by the method is a mean square error loss function, and since the specific training process is the prior art, redundant description is omitted here.
The loss function in the above can be further improved according to the pressure, so as to obtain an improved loss function:
firstly, calculating the difference ratio of the pressure at the t-th moment and the pressure at the t-1 th moment in a set time period in each hanger, and calculating the mean value of the difference ratios, and recording the mean value as the influence degree of the corresponding hanger:
and Ft is the pressure corresponding to the t-th moment in the set time period, and Ft-1 is the pressure corresponding to the t-1-th moment in the set time period.
Secondly, the influence degree of all the hangers in each group is obtained and normalized to ensure that the value range is in [0,1 ]]Get confidence coefficient
；
Finally, the confidence level is determined
As the mass fraction improves the loss function, an improved loss function is obtained:
wherein C is the mass fraction after normalization, as a loss weight,
in order to predict the samples, the samples are,
is a feature sample.
The purpose is to ensure the convergence of the loss function, reduce the loss through continuous training and predict the accurate trend.
The invention also provides a heat supply pipeline support and hanger stability early warning system which comprises a memory and a processor, wherein the processor executes the technical scheme of the heat supply pipeline support and hanger stability early warning method stored by the memory. Since the method for warning the stability of the hanger of the heat supply pipeline is described in detail above, the method is not described in detail herein.
It should be noted that: the above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
Claims (7)
1. A heat supply pipeline support and hanger stability early warning method is characterized by comprising the following steps:
the method comprises the steps of obtaining descending heights of N supports and hangers corresponding to a section of heat supply pipeline at different moments in a set time period, deformation degrees of the supports and hangers, vibration information and pressure of the pipeline to each support and hanger, wherein N is more than or equal to 2;
obtaining the state index of each hanger according to the descending height and the deformation degree; obtaining a stability influence index of each hanger according to the vibration information and the pressure of the pipeline to each hanger;
determining instability of each hanger based on the state index and the stability influence index; grouping the hangers corresponding to the section of heat supply pipeline based on the instability and the pressure to obtain three hanger groups, wherein the three hanger groups comprise a hanger group with good stability, poor stability and poor stability;
for the support hanger group with poor stability and neutral stability, acquiring the horizontal change degree of the pipeline at the position where each support hanger supports the pipeline in the group, and combining the instability of the corresponding support hanger to obtain the instability degree of each support hanger; and comparing the instability degree with a set threshold value, and alarming when the instability degree is greater than the set threshold value.
2. The method as claimed in claim 1, wherein the status indicator is a ratio of a standard deviation of a calculated descending height in a set time period to a difference between a maximum value and a minimum value in a deformation sequence of the hanger.
3. The method as claimed in claim 2, wherein the stability impact indicator is determined by calculating the product of the variation degree of the vibration information and the variation degree of the pressure of the pipe to the hanger.
4. The method as claimed in claim 3, wherein the instability of each hanger is a product of a state index and a stability influence index.
5. The heat supply pipeline support and hanger stability early warning method as claimed in claim 1, wherein the grouping is performed by grouping each support and hanger by using a K-Means clustering algorithm.
6. The method as claimed in claim 5, wherein the instability degree is a product of calculated variation degree of the pipeline level on each hanger and instability of the hanger.
7. A heat supply pipeline hanger stability early warning system comprising a processor and a memory, wherein the processor executes the steps of the heat supply pipeline hanger stability early warning method according to any one of claims 1 to 6 stored in the memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210939155.6A CN114997759B (en) | 2022-08-05 | 2022-08-05 | Heat supply pipeline support and hanger stability early warning method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210939155.6A CN114997759B (en) | 2022-08-05 | 2022-08-05 | Heat supply pipeline support and hanger stability early warning method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114997759A true CN114997759A (en) | 2022-09-02 |
| CN114997759B CN114997759B (en) | 2022-10-14 |
Family
ID=83022997
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210939155.6A Active CN114997759B (en) | 2022-08-05 | 2022-08-05 | Heat supply pipeline support and hanger stability early warning method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114997759B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001084103A1 (en) * | 2000-05-02 | 2001-11-08 | Vista Research, Inc. | Improved methods for detecting leaks in pressurized piping with a pressure measurement system |
| CN107220755A (en) * | 2017-05-23 | 2017-09-29 | 大连理工大学 | The high ferro quick early warning system of arch bridge rigid hanger abnormality and its method |
| CN108267306A (en) * | 2018-01-15 | 2018-07-10 | 江苏壹鼎崮机电科技有限公司 | Subway engineering antidetonation suspension and support anti-seismic performance exception localization method |
| CN111104718A (en) * | 2019-12-24 | 2020-05-05 | 苏州热工研究院有限公司 | Piping system and support and hanger health state quantitative evaluation method |
| CN112014096A (en) * | 2020-09-16 | 2020-12-01 | 江苏万路机电科技有限公司 | Method and system for monitoring health state of support and hanger |
| CN114776892A (en) * | 2022-04-21 | 2022-07-22 | 深圳万茂环境建设发展有限公司 | Method and system for monitoring support and hanger for building electromechanical installation |
-
2022
- 2022-08-05 CN CN202210939155.6A patent/CN114997759B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001084103A1 (en) * | 2000-05-02 | 2001-11-08 | Vista Research, Inc. | Improved methods for detecting leaks in pressurized piping with a pressure measurement system |
| CN107220755A (en) * | 2017-05-23 | 2017-09-29 | 大连理工大学 | The high ferro quick early warning system of arch bridge rigid hanger abnormality and its method |
| CN108267306A (en) * | 2018-01-15 | 2018-07-10 | 江苏壹鼎崮机电科技有限公司 | Subway engineering antidetonation suspension and support anti-seismic performance exception localization method |
| CN111104718A (en) * | 2019-12-24 | 2020-05-05 | 苏州热工研究院有限公司 | Piping system and support and hanger health state quantitative evaluation method |
| CN112014096A (en) * | 2020-09-16 | 2020-12-01 | 江苏万路机电科技有限公司 | Method and system for monitoring health state of support and hanger |
| CN114776892A (en) * | 2022-04-21 | 2022-07-22 | 深圳万茂环境建设发展有限公司 | Method and system for monitoring support and hanger for building electromechanical installation |
Non-Patent Citations (1)
| Title |
|---|
| 郝伟: "压力管道支吊架的分类及定期检验要点", 《辽宁化工》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114997759B (en) | 2022-10-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108922123B (en) | mine slope slip stability monitoring and early warning method | |
| CN116105802B (en) | Underground facility safety monitoring and early warning method based on Internet of things | |
| CN102699302B (en) | Bleed-out forecasting system and forecasting method of slab continuous casting crystallizer | |
| US11035712B2 (en) | Metering system for calculating real-time profit or loss of gas stations | |
| CN106556498A (en) | Damage Identification Methods for Bridge Structures and system | |
| CN104019849B (en) | Steel penstock and telescopic joint operating parameter automatic monitoring system and monitoring method thereof | |
| CN110455517B (en) | Tower barrel health monitoring method of wind generating set | |
| CN116227752B (en) | Park facility management system based on Internet of things | |
| CN109211390B (en) | Safety test and evaluation method for vibration and strength of power transmission tower | |
| CN112861350A (en) | Temperature overheating defect early warning method for stator winding of water-cooled steam turbine generator | |
| CN114997759B (en) | Heat supply pipeline support and hanger stability early warning method and system | |
| CN116295637A (en) | Intelligent monitoring method and system for safety of high-altitude building | |
| CN115165725A (en) | Data-driven marine equipment corrosion monitoring and safety early warning system | |
| CN113313291A (en) | Power grid wind disaster ensemble forecasting and verifying method based on initial disturbance | |
| CN111238427A (en) | Method for monitoring damage of tower body steel structure of tower crane in real time | |
| CN116127816A (en) | Method for evaluating actual service state of gas tank based on laser point cloud mapping technology | |
| CN114970273A (en) | Transmission tower strain time sequence prediction and instability early warning method based on ARIMA-LSTM combined model | |
| CN210088474U (en) | Real-time state information acquisition and risk prediction system for steam pipeline of thermal power plant | |
| CN114666361A (en) | Fire-fighting Internet of things-based water system overall fault detection system and method | |
| CN113606500A (en) | Method for monitoring burst leakage of gas courtyard pipe network in real time | |
| CN107578185B (en) | Health detection method and device for industrial building | |
| CN114964456B (en) | Beam bridge steel structure vibration safety monitoring system utilizing vehicle speed monitoring | |
| CN114941995B (en) | Beam bridge steel structure deformation monitoring system based on distributed optical fiber strain test | |
| CN117874687B (en) | Data interaction method of industrial tablet personal computer | |
| CN117989472A (en) | Gas pipeline pressure monitoring and analyzing system and method |
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 |