CN113806843A - Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank - Google Patents
Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank Download PDFInfo
- Publication number
- CN113806843A CN113806843A CN202111035451.5A CN202111035451A CN113806843A CN 113806843 A CN113806843 A CN 113806843A CN 202111035451 A CN202111035451 A CN 202111035451A CN 113806843 A CN113806843 A CN 113806843A
- Authority
- CN
- China
- Prior art keywords
- sedimentation
- curve
- depth
- processing module
- preset
- 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.)
- Pending
Links
- 238000004062 sedimentation Methods 0.000 title claims abstract description 161
- 238000000034 method Methods 0.000 title claims abstract description 89
- 238000004458 analytical method Methods 0.000 title claims abstract description 23
- 238000005070 sampling Methods 0.000 claims abstract description 60
- 230000008859 change Effects 0.000 claims abstract description 40
- 238000012544 monitoring process Methods 0.000 claims abstract description 38
- 230000002159 abnormal effect Effects 0.000 claims abstract description 24
- 230000036962 time dependent Effects 0.000 claims abstract 2
- 238000010276 construction Methods 0.000 claims description 103
- 230000008569 process Effects 0.000 claims description 55
- 230000000737 periodic effect Effects 0.000 claims description 16
- 239000000284 extract Substances 0.000 claims description 9
- 230000004044 response Effects 0.000 claims description 4
- 230000001419 dependent effect Effects 0.000 claims 1
- 230000002596 correlated effect Effects 0.000 abstract description 2
- 230000000875 corresponding effect Effects 0.000 description 21
- 238000009412 basement excavation Methods 0.000 description 9
- 238000009826 distribution Methods 0.000 description 6
- 238000005304 joining Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 5
- 238000012806 monitoring device Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 238000006073 displacement reaction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 239000002689 soil Substances 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000002349 favourable effect Effects 0.000 description 2
- 238000004904 shortening Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000009933 burial Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000003449 preventive effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 239000004984 smart glass Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001550 time effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Abstract
The invention relates to a deformation analysis system and a method based on dynamic fluctuation of a settling tank bottom, wherein the system at least comprises a monitoring module, a first processing module and a second processing module, the first processing module establishes a first association curve of preset settling depth and time correlation based on settling sample information and sends the first association curve to the second processing module, the second processing module establishes a second association curve of real-time preset settling depth and time correlation based on settling information collected by the monitoring module and correlated with time, and under the condition that the second association curve is different from the first association curve, the second processing module updates the second association curve in a mode of updating the preset settling depth and judges the dynamic abnormal condition of the settling tank bottom; the time-dependent sedimentation information is recorded with a preset sedimentation depth of the sedimentation tank as a driving event. The change of the settling tank is monitored by taking the time of the preset settling depth as a sampling period, so that the risk of the settling tank can be found in time and the risk can be predicted.
Description
Technical Field
The invention relates to the technical field of tunnel construction, in particular to a deformation analysis system and method based on dynamic fluctuation of a settling tank bottom.
Background
The PBA construction method is characterized in that a small pilot hole is firstly constructed at the position of a stand column, and after the small pilot hole is made, a bottom beam is constructed in the hole to form a thin and high longitudinal structure.
The settling tank is produced in foundation pit and shield tunnel engineering. In the foundation pit engineering, the excavation of the foundation pit influences the soil body around the pit, so that the soil body outside the pit slides into the pit, and a settling tank is generated around the foundation pit; in the same way, the shield tunnel excavation process is accompanied with the loss of surrounding soil mass, so that a subsidence groove is generated within a certain range. When the control on the settling tank is improper, the settling tank generated in the foundation pit and the shield tunnel engineering often has adverse effects on the surrounding environment, mainly causes deformation and even damage to surrounding roads, buildings and various facilities, even causes casualties, and particularly plays an important role in protecting lives and properties by reducing the range and settling volume of the settling tank.
Chinese patent CN112380757A discloses an analysis method of offset distance of peak point of surface subsider during construction of curved tunnel, which is used to determine offset distance of peak point of surface subsider under different line radius conditions; the method is based on the phenomenon that the curve type shield tunnel causes the peak point offset of the surface subsidence groove, adopts a numerical simulation means, and determines the functional relation between the curve type tunnel line radius and the peak point offset distance of the surface subsidence groove by fitting the calculation results under different working conditions, thereby providing a novel calculation method for the peak point offset distance of the surface subsidence groove during the construction of the curve type tunnel; the scheme considers the overbreak area of the curve type tunnel and simulates by using the elastic equivalent substitution layer, so that the simulation condition is more accordant with the actual situation of site construction, the analysis result is more accurate, and a basis is provided for the control of uneven settlement of the overlying building and the settlement treatment of the earth surface, thereby ensuring the normal use of the building and the safe construction of the tunnel. However, the invention cannot analyze the cause of deformation based on the deformation of the surface subsider, and does not take the actual construction time and working procedures of the working conditions into the deformation consideration, so that the deformation difference between the obtained subsider and the actual construction is large.
Chinese patent CN104295304B discloses a method for generating a subway tunnel settling tank to realize different settling distribution guarantee rates, which mainly includes settling tank curve generation; generating a settlement tank envelope line and calculating settlement prediction parameters, specifically, obtaining the distance between each monitoring point and a tunnel central line and the settlement value of the monitoring point; calculating a regression settling tank curve; setting the envelope proportion of the monitoring points, and adjusting to obtain a maximum envelope line and a minimum envelope line on the basis of a regression settling tank curve; and (3) given the diameter and the burial depth of the tunnel, calculating the maximum settling tank coefficient, the minimum settling tank coefficient, the regression settling tank coefficient, the maximum area loss rate, the minimum area loss rate and the regression area loss rate of the 3 curves. The method takes actual monitoring data as a basis, considers the probability distribution of the settlement, forms the distribution rule and the distribution range of the surface settlement caused by the underground excavation or the shield tunnel, forms the prediction parameters of the distribution range, and has strong practicability, convenient use and wide application prospect. However, the settling process of the settling tank is a dynamic process, the invention still only calculates and predicts the settling result, and does not consider the influence of the gradual dynamic change process, the engineering sequence and the working procedure implementation time in the deformation process of the settling tank, so that the actual result of the settling tank has larger deviation with the predicted result.
Furthermore, on the one hand, due to the differences in understanding to the person skilled in the art; on the other hand, since the applicant has studied a great deal of documents and patents in the process of making the present invention, the extent of which is not limited to the details and contents listed, it is by no means the present invention has all the features of the prior art but the present invention has all the features of the prior art, and the applicant reserves the right to increase the related prior art in the background.
Disclosure of Invention
In the prior art, a three-dimensional earth surface settlement prediction model considering time effect is established through a normal distribution cumulative function and a random medium theory, and a settlement-time model is obtained. However, the dynamic fluctuation of the settling tank is influenced not only by geology and time but also by the construction process and the construction sequence. For example, in the PBA construction method, the PBA construction method causes buckling deviation due to asymmetric construction. In the process of asymmetrical opening of 8 pilot tunnels in the practical engineering of a PBA typical station, the distributed construction of a plurality of pilot tunnels causes uneven change of stratum space, so that the space form of a surface subsider swings left and right along with the excavation of the pilot tunnels. Therefore, how to adjust the construction sequence according to the monitored space form change of the surface settling tank to reduce or even eliminate the offset of the bottom of the surface settling tank is a technical problem which is not solved at present.
Moreover, in the calculation simulation of the settling tank in the prior art, data statistics and offset analysis can be performed only on the settlement which has already occurred, the settlement risk of the settling tank cannot be evaluated and predicted, and a suggested scheme of construction procedures and procedure connection time cannot be provided for the abnormality of the settling velocity of the settling tank. In the construction process of the actual construction method, the procedures are converted a lot, the construction sequence is not strictly standard, the time sequence relation is not clear, and a plurality of fuzzy places exist in the design details. In actual construction, slight changes to the construction sequence can have great influence on formation deformation. The simulation prediction has insufficient reflection on the construction stress process, and the actual monitoring work has more uncertainty, which greatly influences the accuracy of the prediction of the pre-alarm. Many times, the monitored data still do not reach the alarm condition, but still accidents occur. Currently, deformation degree is difficult to evaluate only through general selected and measured items, and accurate engineering early warning and forecasting cannot be carried out.
The invention hopefully provides a prediction system which can monitor the sedimentation velocity of the sedimentation tank in the construction process, can analyze the safety degree based on the sedimentation velocity of the sedimentation tank, space deformation, construction process, process connection time and other factors, and can give out construction early warning.
Aiming at the defects of the prior art, the invention provides a deformation analysis system based on dynamic fluctuation of a settling tank bottom, which at least comprises a monitoring module, a first processing module and a second processing module, wherein the first processing module establishes a first association curve of a preset settling depth and time correlation based on settling sample information and sends the first association curve to the second processing module, the second processing module establishes a second association curve of a real-time preset settling depth and time correlation based on settling information collected by the monitoring module and correlated with time, and under the condition that the second association curve is different from the first association curve, the second processing module updates the second association curve in a mode of updating the preset settling depth and judges the dynamic abnormal condition of the settling tank bottom; wherein the sedimentation information related to time is recorded by taking the preset sedimentation depth of the sedimentation tank as a driving event.
In the prior art, the sedimentation depth of a sedimentation tank is monitored by a fixed sampling time period. When the subsider takes place unusual settlement, the risk of collapsing increases, and monitoring facilities can find only after arriving sampling time cycle and obtaining the sampling data, makes the acquirement of unusual data appear delaying undoubtedly. Moreover, for the time period without settlement or with unobvious settlement, the construction safety degree at this stage is high, the frequently-collected settlement data of the monitoring device has limited effect, and the frequently-collected data of the monitoring device is transmitted to the data processing module, so that the transmission quantity of the data, the data calculation quantity of the data processing module and the data storage quantity are increased. The delay effect of the data is necessarily aggravated by the transmission of a large amount of data, so that the time for the data processing module to find the exception is delayed by millisecond unit, even 1 second. This is clearly disadvantageous for underground works to prevent the risk of landslide.
The invention monitors the sedimentation condition of the sedimentation tank by taking the time of the preset sedimentation depth as the sampling time period, thereby being beneficial to monitoring the abnormity of the sedimentation speed in time. When the settling tank is slowly settled, the monitoring device can reduce the frequency of sending data and the data volume. When the subsider descends fast, monitoring devices can send settlement data and time data to data processing module. Even under the condition that the preset settlement depth is determined, the monitoring device only needs to send the time data of the preset settlement depth to the first data processing module and the second data processing module, the data amount is small, the data delay phenomenon of the data in the transmission process is reduced, the data analysis module can quickly respond to abnormal data, and early warning information and/or construction suggestions are/is sent out in time.
Preferably, the preset sedimentation depth for sampling is set in such a manner that the sampling time period is shortened as the depth becomes larger. The deeper the settling depth of the settling tank, the higher the chance of risk. Therefore, the depth of the settling tank is increased, the preset settling depth is reduced, namely the sampling time period is shortened, and the effectiveness of the settling monitoring of the settling tank is improved.
Preferably, in the case that the second correlation curve is different from the first correlation curve, the second processing module shortens the sampling time period in a manner of reducing the preset sedimentation depth; wherein, the time of the preset sedimentation depth is the sampling time period. The advantage that so set up lies in, when taking place to subside unusually, can increase sampling frequency through shortening sampling time cycle to in time discover the danger of the unusual settlement of subsider, in time send out the early warning.
Preferably, the first processing module extracts corresponding dynamic fluctuation track information of the bottom of the settling tank based on the input geological parameters, the parameters of the settling tank and the construction sequence information, and extracts a first association curve corresponding to a preset settling depth based on the dynamic fluctuation track information of the bottom of the settling tank. In the invention, in the sedimentation sample data, the sedimentation depth and the data sampling time form a curve with a slope. The curve in the invention can be a fitted curve or a bent curve. As the geological parameters, the parameters of the settling tank and the construction sequence information are all related to the slope of the time curve in a preset depth, the abnormal settlement can be more objectively seen by comparing the slope change. For a settling tank with similar geological conditions, the correlation curves are similar, and the settlement risk of subsequent construction can be timely found and predicted through comparison.
Preferably, in response to the preset sedimentation depth update information and/or the construction process update information sent by the second processing module, the first processing module updates a sampling time period corresponding to the preset sedimentation depth so as to synchronously update the first association curve information. When the two correlation curves are compared, the same construction process sequence, the same preset settlement depth and the geological parameters are similar, so that the slope of the curves is similar. When the slopes of the curves are different and exceed the difference threshold value, the abnormity of the settlement can be found in time. Therefore, it is necessary to adjust the first correlation curve to the same preset sedimentation depth as the second correlation curve, which can result in better comparison results.
Preferably, the second processing module compares the periodic variation difference value of the second correlation curve and the first correlation curve in the settling tank of the same construction process based on the real-time sampling time period variation rate, and sends out early warning information when the periodic variation difference value is greater than the periodic variation threshold value. In the invention, each construction process is provided with a corresponding cycle difference threshold value of the abnormal settlement. When the periodic variation difference value is abnormal, the settlement of the settling tank is indicated to be abnormal, a constructor needs to investigate and adjust the current construction progress in time, and the current construction risk is reduced.
Preferably, the second processing module adjusts the predicted part of the second correlation curve based on the sampling time period change rate of the first correlation curve, and sends out early warning information when the settlement depth of the predicted part of the second correlation curve is greater than a depth threshold corresponding to the construction process. Because the height of the underground project is determined, the depth threshold at which danger can occur is also determined. When the subsequent settlement condition is predicted according to the current settlement depth and the slope of the sample data, the settlement depth is larger than the depth threshold value, and the penetration and the collapse of the underground tunnel are inevitably caused. Therefore, the construction method can adjust the current construction process and the process connection duration based on early warning, and avoid the future construction risk as much as possible.
Preferably, when the second association curve is different from the first association curve for one time, the second processing module decreases and updates the preset sedimentation depth for one time, compares the updated first association curve with the second association curve, and when the second association curve is different from the first association curve for the nth time, if a cycle variation difference value corresponding to the current preset sedimentation depth is greater than a cycle difference threshold value, the second processing module sends out early warning information to at least one terminal. And when the difference occurs once, the value of the preset sedimentation depth is reduced, so that the sampling time period is shortened, the sedimentation depth is closely monitored, the association curve is wirelessly close to a smooth curve, a more accurate sedimentation-time association curve is obtained, abnormal points on the curve can be timely monitored, and timely early warning is realized. Compared with the prior art, the method can find the settlement anomaly in time as soon as the settlement anomaly occurs, so that early warning is given to a construction party to reduce the current and future construction risks.
The invention also provides a deformation analysis method based on the dynamic fluctuation of the bottom of the settling tank, which at least comprises the following steps: establishing a first association curve related to preset sedimentation depth and time based on sedimentation sample information, establishing a second association curve related to real-time preset sedimentation depth and time based on collected sedimentation information related to time, and updating the second association curve in a mode of updating the preset sedimentation depth and judging the dynamic abnormal condition of the bottom of the sedimentation tank under the condition that the second association curve is different from the first association curve; wherein the sedimentation information related to time is recorded by taking the preset sedimentation depth of the sedimentation tank as a driving event.
Preferably, the method further comprises: the preset sedimentation depth for sampling is set so that the sampling time period is shortened as the depth becomes larger.
Preferably, the method further comprises: in the case of a difference between the second correlation curve and the first correlation curve, the second processing module shortens the sampling time period in such a way as to reduce the preset sedimentation depth; wherein, the time of the preset sedimentation depth is the sampling time period.
Preferably, the method further comprises: the first processing module extracts corresponding sedimentation tank bottom dynamic fluctuation track information based on input geological parameters, sedimentation tank parameters and construction sequence information, and extracts a first association curve corresponding to a preset sedimentation depth based on the sedimentation tank bottom dynamic fluctuation track information.
Preferably, the method further comprises: and in response to the preset sedimentation depth updating information and/or construction process updating information sent by the second processing module, the first processing module updates the sampling time period corresponding to the preset sedimentation depth so as to synchronously update the first association curve information.
Preferably, the method further comprises: the second processing module compares the second correlation curve with the first correlation curve on the basis of the change rate of the real-time sampling time period in the period change difference value of the settling tank of the same construction process, and sends out early warning information when the period change difference value is larger than a period difference threshold value.
Preferably, the method further comprises: the second processing module adjusts a predicted portion of the second correlation curve based on a sample time period rate of change of the first correlation curve,
and sending early warning information when the periodic variation difference value of the predicted part of the second association curve and the corresponding part of the first association curve is greater than a periodic variation threshold value.
Preferably, the method further comprises: when the second association curve is different from the first association curve for one time, the second processing module reduces and updates the preset sedimentation depth for one time, the updated first association curve is compared with the second association curve, and when the second association curve is different from the first association curve for the Nth time, if the periodic variation difference value corresponding to the current preset sedimentation depth is larger than the periodic variation threshold value, the second processing module sends out early warning information to at least one terminal.
The method can reduce the data transmission quantity between the monitoring equipment and the data processing module, reduce the data delay and enable the abnormity early warning to respond in time; the method can also increase the monitoring data and correlate the monitoring data with the curve for many times, so that early warning is sent out in advance when construction danger can be caused by abnormal settlement, and a construction party can adjust the construction process sequence in advance. The process connection time is used for changing the sedimentation speed, namely changing the sampling time period of the sedimentation with the preset depth, thereby eliminating the future construction risk.
Drawings
FIG. 1 is a schematic diagram of the logic blocks of the deformation analysis system based on the dynamic fluctuation of the bottom of a settling tank of the present invention;
FIG. 2 is a schematic perspective view of the underground construction of the present invention;
fig. 3 is a diagram showing the dynamic trajectory of the bottom of a settling tank in a certain construction process.
FIG. 4 is a graph illustrating a preset sedimentation depth versus sampling time;
FIG. 5 is a schematic illustration of a comparison of a second correlation curve to a first correlation curve in real time.
List of reference numerals
10: a monitoring module; 21: a first processing module; 22: a second processing module; 30: and (4) a terminal.
Detailed Description
The following detailed description is made with reference to the accompanying drawings.
The prior art focuses on predicting the final displacement result of the settling tank bottom after construction, ignores that the change of the settling tank bottom is dynamic in the construction process, and the dynamic change of the settling tank bottom is different along with the difference of construction processes, the difference of construction time of each process and the difference of construction sequence, finally leads to that the predicted position and the actual position of the settling tank bottom can only be completely fitted, and can not be completely fitted. Geological parameters of all places are not completely the same, so that the construction procedures are not completely the same, and the curve tracks of the dynamic fluctuation of the bottom of the settling tank are not completely the same. The reason why the fitting algorithm for the deformation curves of various settling tanks is only suitable for geological construction of a certain province and a certain city, and dynamic deformation analysis of the bottom of the settling tank cannot be realized in tunnel construction of various geological features throughout the country is also considered.
The invention provides a deformation analysis system and a method based on dynamic fluctuation of a settling tank bottom, and also provides a monitoring system and an early warning system based on dynamic fluctuation of the settling tank bottom.
A deformation analysis system based on the dynamic fluctuation of the bottom of a settling tank is shown in figure 1 and at least comprises a monitoring module 10, a first processing module 21 and a second processing module 22. The monitoring module 10, the first processing module 21 and the second processing module 22 establish a data connection with each other. The first processing module 21 and the second processing module 22 also establish a connection with at least one terminal 30 to display the first association curve and/or the second association curve, respectively.
The first processing module 21 and the second processing module 22 may be one or more of a processor, a server, a cloud server, and an application-specific integrated chip.
The terminal 30 may be one or more of a computer, a display, a portable mobile terminal, and a smart device. The portable mobile terminal is, for example, one or more of a portable computer, a smart watch, smart glasses, a smart bracelet, and a tablet computer.
The monitoring module 10 is used to collect the sedimentation parameters of the construction section geology and their associated time parameters. The monitoring module 10 comprises several sensing units. The plurality of sensing units are distributed in the construction section, and parameters such as the width of the sedimentation tank, the depth of the bottom of the sedimentation tank, the horizontal displacement of the bottom of the sedimentation tank and the like of the construction section are acquired.
Preferably, the monitoring modules 10 include at least a surface monitoring module 11 and a subsurface monitoring module 12. The earth surface monitoring module 11 is arranged on the geological surface of the construction section and used for monitoring the settlement parameters of the earth surface. The underground monitoring module 12 is arranged on the geological middle layer of the construction section and used for monitoring the sedimentation parameter of the geological middle layer. The settlement parameters in the invention comprise longitudinal settlement parameters, horizontal settlement parameters and three-dimensional settlement parameters in the construction direction. Namely, the sedimentation parameter in the invention is the sedimentation parameter of the three-dimensional space.
The preset sedimentation depth is the preset sedimentation depth. Wherein the sedimentation information related to time is recorded by taking a preset sedimentation depth of the sedimentation tank as a driving event. The time used when the settling tank settles to each preset settling depth is the sampling time period. When the settling velocity of the settling tank changes, the sampling time period corresponding to the occurrence of a preset settling time changes. The ratio of the sampling time period to the preset sedimentation depth is the curve slope of the correlation curve of the preset sedimentation depth and time. The larger the slope of the curve is, the longer the sampling time period corresponding to the preset sedimentation time of the sedimentation tank is, the sedimentation speed of the sedimentation tank is low, and the construction safety degree is high. On the contrary, the smaller the slope of the curve is, the shorter the sampling time period corresponding to the preset settling time of the settling tank is, the higher the settling speed of the settling tank is, the lower the safety degree of construction is and the higher the danger degree is.
Preferably, the preset sedimentation depth for sampling is set in such a manner that the sampling time period is shortened as the depth becomes larger. The larger the sedimentation depth value of the sedimentation tank is, the smaller the preset sedimentation depth value is, so that the sampling time period is shortened. The greater the depth of the settler, the higher the probability of an accident. Shortening the sampling time period is beneficial to improving the time density of monitoring the settling tank, thereby finding out the abnormal settling of the settling tank in time.
The invention detects the sedimentation speed change of the sedimentation tank by monitoring the change of the sampling time period, and analyzes whether the sedimentation of the sedimentation tank is abnormal or not by monitoring the slope change of the correlation curve. Under the condition of abnormal sedimentation, the sampling time change of the preset sedimentation depth occurs, and the slope of the curve is abnormal. Therefore, the preset sedimentation depth is adjusted in time through the slope abnormity of the curve, so that the slope change of the associated curve is further monitored, the sedimentation depth of the sedimentation tank is determined in time, and early warning is generated.
The first processing module 21 establishes a first correlation curve of the preset sedimentation depth and time based on the sedimentation sample information and sends the first correlation curve to the second processing module 22.
The first processing module 21 is configured to predict a dynamic fluctuation trajectory of the bottom of the settling tank according to the dynamic fluctuation model of the bottom of the settling tank, and extract a first association curve according to the settling sample data of the settling tank. The dynamic fluctuation model of the settling tank bottom predicts the dynamic fluctuation track of the settling tank bottom based on six factors of construction sequence, duration of a joining procedure, length, width, height and time of three-dimensional space parameters, obtains time corresponding to unit settling displacement and forms a first association curve of association of preset settling depth and time.
In the invention, as the sedimentation speed of the sedimentation tank is related to the construction sequence, the duration of the joining procedure and the three-dimensional space parameters, the slope of the curve formed by the ratio of the sampling time period to the preset sedimentation depth is also related to the six factors of the construction sequence, the duration of the joining procedure and the length, width, height and time of the three-dimensional space parameters.
As shown in fig. 2, the PBA construction method performs asymmetric excavation through eight small pilot tunnels, and the construction sequence is different in the construction process, so that the settlement tracks of the settling tanks are also different. Settlement mainly occurs in the stages of pilot tunnel excavation and arch buckling construction. The accumulated settlement of the earth surface in the two stages is respectively 55 percent and 80 percent of the total settlement, and is a key process for controlling the earth surface settlement. Therefore, in the excavation process, it is very important to predict whether the sedimentation of the sedimentation tank in the subsequent excavation process is abnormal or not according to the current sedimentation depth by the abnormity of the slope of the curve and the slope sample of the curve in time. When the settlement abnormity of the settlement tank in the subsequent excavation process is predicted, the current construction sequence is adjusted in time to adjust the settlement speed, and the slope of the curve is changed, so that the predicted correlation curve can be normal, and the engineering safety accident is avoided.
Under the conditions that the construction sequence, the duration of the connection process and the three-dimensional space parameters are known, the slope of the curve should be similar, so that the settlement speed of the subsequent settling tank can be predicted.
Preferably, the first processing module 21 is able to extract dynamic fluctuation trajectory data of the bottom of the settling tank from the connected storage module.
Preferably, the first processing module 21 associates and stores the geological parameters, the preset sedimentation depth, the sampling time period and construction type, the construction time, the procedure connection time, and the sedimentation tank space parameters in a corresponding association manner. The first processing module establishes an incidence relation between the geological parameters and the first incidence curve, and is beneficial to extracting a first incidence curve sample based on the geological parameters.
For example, the first processing module 21 extracts corresponding settling tank bottom dynamic fluctuation trajectory information based on the input geological parameters, settling tank parameters, and construction sequence information, and extracts a first association curve corresponding to a preset settling depth based on the settling tank bottom dynamic fluctuation trajectory information. In the case of identical or similar geological parameters, the settling velocity of the settler is similar. The first correlation curve is obtained based on geological parameters, so that a data sample similar to a second correlation curve of the current construction can be obtained, and the change of the second correlation curve of the settling tank can be predicted based on the change of the slope of the curve.
In the present invention, the second processing module 22 establishes a real-time second correlation curve of the preset sedimentation depth and time based on the sedimentation information related to time collected by the monitoring module 10. According to the arrangement, under the condition that the preset sedimentation depth is known, the monitoring module only needs to send the time information of the preset sedimentation depth to the second processing module, so that the data transmission quantity between the monitoring module and the second processing module is reduced, and the delay degree of data is reduced.
Under the condition that the second correlation curve is different from the first correlation curve, the second processing module 22 updates the second correlation curve in a manner of updating the preset sedimentation depth and judges the dynamic abnormal condition of the bottom of the sedimentation tank.
Specifically, as shown in fig. 4, the first processing module extracts time data of a settling tank with a settling depth of a from the settling sample data according to the received information with a preset settling depth of a and a millimeter per unit. The time interval between two time data is the sampling time period. A first correlation curve a is formed from the correlation of the time data and the preset sedimentation depth.
As shown in fig. 5, the preset sedimentation depth is a in mm. The monitoring module 10 sends time data every time the settling tank settles to a depth. The time interval between two time data is the sampling time period. A second correlation curve B is formed from the correlation of the time data and the preset sedimentation depth.
In the case of the same predetermined sedimentation depth, the first correlation curve a is compared with the second correlation curve B, in particular with respect to the difference in the slope of the curves. When the slope of the curve is different, whether the second association curve B has a safety risk needs to be further judged.
Preferably, in the case that the second correlation curve is different from the first correlation curve, the second processing module 22 shortens the sampling time period in a manner of reducing the preset sedimentation depth; wherein, the time of the preset sedimentation depth is the sampling time period.
Specifically, the second processing module 22 reduces the preset sedimentation depth value to shorten the sampling time period, so that the curve slope change of the second association curve B is more obvious. Meanwhile, the first processing module updates the first association curve A according to the new preset sedimentation depth, so that the first association curve A and the second association curve B can be compared in a more intuitive curve slope change mode, and the difference between the first association curve A and the second association curve B is more obvious.
If whether the sedimentation of the sedimentation tank is abnormal or not is judged only according to the current difference, result deviation is likely to occur, the sedimentation process is normal in the process of the preset sedimentation depth of the sedimentation tank, and a plurality of errors of sedimentation cause the overall error of the current curve slope. Therefore, when the slope of the curve is found to be abnormal, the change of the slope of the curve is further micronized, and the difference between the real-time sedimentation of the sedimentation tank and the sedimentation sample can be reflected, so that the adjustment of the current construction sequence and the connection time of the construction process by a constructor is facilitated.
In the invention, the number of times of updating the preset sedimentation depth is not limited to one time, and can be two times or more, so that the second association curve B forms an approximately smooth curve, which is beneficial to displaying whether the slope difference between the second association curve B and the first association curve A exceeds the difference threshold value, thereby timely sending out early warning information.
For example, the slope difference of the second correlation curve from the first correlation curve is-0.35 and the difference threshold is-0.2. Obviously, the slope of the second correlation curve is abnormal, namely the settling velocity of the settling tank is increased, the sampling time period is shortened, and the slope of the curve is reduced. At this time, when the second processing module sends the warning information to the at least one terminal, the preset sedimentation depth needs to be further reduced to increase the data acquisition density of the sedimentation tank. Until the preset sedimentation depth is adjusted to the minimum sedimentation depth value, if the slope of the second association curve is still abnormal, the second processing module can increase the grade of the early warning information and send the early warning information to at least one terminal 30.
Preferably, in response to the preset sedimentation depth update information and/or the construction process update information sent by the second processing module 22, the first processing module 21 updates the sampling time period corresponding to the preset sedimentation depth so as to synchronously update the first association curve information.
Specifically, when the set sedimentation depth or the construction process information of the second correlation curve is updated, the second processing module sends the update information to the first processing module. The first processing module receives the updating information and adjusts the first association curve according to the updating information, so that the preset depth information or the construction process sequence and the construction process connection duration of the two association curves are consistent or approximate. So set up, when the second associated curve is compared with first associated curve, predetermine the difference that the degree of depth of subsidence is unanimous and can show second associated curve and first associated curve better to be favorable to constructor in time to discover unusually and adjust the construction situation.
Preferably, the second processing module 22 compares the second correlation curve with the first correlation curve in the period variation difference value of the settling tank of the same construction process, and sends out the warning information when the period variation difference value is greater than the period difference threshold value.
The rate of change of a sample time period is the rate of change of the next sample time period compared to the previous sample time period. Although the second processing module monitors the change of the curve slope of the second correlation curve in real time, the real-time data is compared with the sample data, only the difference between the current construction process and the sample project can be obtained, and the change condition of the current construction project cannot be obtained. Therefore, the second processing module simultaneously monitors the sampling period change rate in real time, and when the sampling period change rate exceeds a preset change rate threshold, the second processing module compares the periodic change difference value of the second association curve and the first association curve in the settling tank of the same construction process whether the slope of the curve is abnormal or not. For example, in a certain construction process stage, the sampling time period of the first correlation curve settlement 0.1mm is six days, the sampling time period of the second correlation curve settlement 0.1mm is three days, the period change difference value is three days, and is more than the period difference threshold value for two days. And the constructor evaluates the period difference and the current settlement depth according to the early warning information received by the terminal to determine the safety degree of the current construction process.
The method not only monitors the difference between the slope of the curve and the sample data, but also monitors the change difference of the associated curve and the specific difference numerical value, thereby avoiding the defect of larger difference of the specific depth numerical value caused by only monitoring the slope of the curve.
Preferably, the second processing module 22 adjusts the predicted portion of the second correlation curve based on the rate of change of the sampling time period of the first correlation curve. The second correlation curve not only displays the current real-time sampling time period of the settling tank, but also continues according to the curve slope change of the first correlation curve to form the second correlation curve with the prediction content. So set up, be favorable to observing whether the change of subsiding of present settling tank exists safety risk to subsequent construction process.
And sending early warning information when the periodic variation difference value of the predicted part of the second correlation curve and the corresponding part of the first correlation curve is larger than the periodic variation threshold value. When the safety risk exists in the prediction part of the second correlation curve, constructors can carry out preventive construction and adjustment of the construction process in advance, and the safety risk formed by the fact that the current settling tank continuously changes according to the first correlation curve is avoided.
Preferably, when the second association curve is different from the first association curve for one time, the second processing module performs reduction and update of the preset sedimentation depth for one time, compares the updated first association curve with the second association curve, and when the second association curve is different from the first association curve for the nth time, if a cycle change difference value corresponding to the current preset sedimentation depth is greater than a cycle difference threshold value, the second processing module sends out early warning information to at least one terminal. Where N is a positive integer.
When the second processing module adjusts the preset sedimentation depth for a plurality of times based on the slope difference of the curve, the second correlation curve is closer to a smooth curve, and the change of the sedimentation depth of the sedimentation tank along with the time can be reflected.
According to the invention, the data acquisition amount and the acquisition time density are increased only when the curve slope is abnormal, so that the effective data acquisition can be increased, and the effective rate of data acquisition is improved.
After the construction process is completed, the second processing module stores information such as time, settlement depth, geological parameters, construction procedures, construction procedure connection duration, settling tank three-dimensional space parameters and the like related to the second correlation curve to the storage module connected with the first processing module to form new sample data.
Preferably, in the case where the geological parameters are similar and the at least two correlation curves are similar, the first processing module fits the at least two correlation curves to form a reference correlation curve relating reference preset sedimentation depth to time.
When the process joining duration of the current construction process is adjusted, the first processing module can respond to the updating information of the process joining duration and select sample data with the closest process joining duration from the sample data forming the reference association curve to update the reference association curve. By the arrangement, the second correlation curve which is currently constructed can predict the change of the subsequent sampling time period of the settling tank according to the curve slope of the effective reference correlation curve.
It should be noted that the above-mentioned embodiments are exemplary, and that those skilled in the art, having benefit of the present disclosure, may devise various arrangements that are within the scope of the present disclosure and that fall within the scope of the invention. It should be understood by those skilled in the art that the present specification and drawings are illustrative only and are not limiting upon the claims. The scope of the invention is defined by the claims and their equivalents. The present description contains several inventive concepts, such as "preferably", "according to a preferred embodiment" or "optionally", each indicating that the respective paragraph discloses a separate concept, the applicant reserves the right to submit divisional applications according to each inventive concept.
Claims (10)
1. A deformation analysis system based on the dynamic fluctuation of the bottom of a settling tank at least comprises a monitoring module (10), a first processing module (21) and a second processing module (22), and is characterized in that,
the first processing module (21) establishes a first correlation curve of preset sedimentation depth and time based on sedimentation sample information and sends the first correlation curve to the second processing module (22),
the second processing module (22) establishes a real-time preset sedimentation depth-time-dependent second correlation curve based on the time-dependent sedimentation information acquired by the monitoring module (10), and
under the condition that the second correlation curve is different from the first correlation curve, the second processing module (22) updates the second correlation curve in a mode of updating the preset sedimentation depth and judges the dynamic abnormal condition of the bottom of the sedimentation tank;
wherein the sedimentation information related to time is recorded by taking the preset sedimentation depth of the sedimentation tank as a driving event.
2. The system for deformation analysis based on dynamic fluctuation of the bottom of a settling tank according to claim 1,
the preset sedimentation depth for sampling is set so that the sampling time period is shortened as the depth becomes larger.
3. The system for deformation analysis based on the dynamic fluctuation of the bottom of a settling tank according to claim 1 or 2,
-in the case of a difference between the second correlation curve and the first correlation curve, the second processing module (22) shortens the sampling time period in such a way as to reduce the preset sedimentation depth;
wherein, the time of the preset sedimentation depth is the sampling time period.
4. The system for deformation analysis based on the dynamic fluctuation of the bottom of a settling tank according to any one of claims 1 to 3,
the first processing module (21) extracts corresponding sedimentation tank bottom dynamic fluctuation track information based on the input geological parameters, sedimentation tank parameters and construction sequence information, and
and extracting a first association curve corresponding to a preset sedimentation depth based on the dynamic fluctuation track information of the bottom of the sedimentation tank.
5. The system for deformation analysis based on the dynamic fluctuation of the bottom of the settling tank as claimed in any one of claims 1 to 4,
in response to the preset sedimentation depth updating information and/or construction process updating information sent by the second processing module (22), the first processing module (21) updates the sampling time period corresponding to the preset sedimentation depth so as to synchronously update the first association curve information.
6. The system for deformation analysis based on the dynamic fluctuation of the bottom of the settling tank according to any one of claims 1 to 5,
the second processing module (22) compares the periodic variation difference value of the second correlation curve and the first correlation curve in the settling tank of the same construction process based on the real-time sampling time period change rate, and sends out early warning information when the periodic variation difference value is larger than a periodic variation threshold value.
7. The system for deformation analysis based on the dynamic fluctuation of the bottom of the settling tank according to any one of claims 1 to 6,
the second processing module (22) adjusts a predicted portion of the second correlation curve based on a sample time period rate of change of the first correlation curve,
and sending early warning information when the periodic variation difference value of the predicted part of the second association curve and the corresponding part of the first association curve is larger than a periodic variation threshold value.
8. The system for deformation analysis based on the dynamic fluctuation of the bottom of the settling tank according to any one of claims 1 to 7,
when the second correlation curve has a difference compared with the first correlation curve, the second processing module (22) reduces and updates the preset sedimentation depth once, compares the updated first correlation curve with the second correlation curve,
when the Nth difference occurs between the second association curve and the first association curve, if the cycle variation difference value corresponding to the current preset sedimentation depth is larger than the cycle difference threshold value, the second processing module (22) sends early warning information to at least one terminal.
9. A deformation analysis method based on dynamic fluctuation of a bottom of a settling tank, characterized in that the method at least comprises the following steps:
establishing a first correlation curve of the preset sedimentation depth and time based on the sedimentation sample information,
establishing a real-time second correlation curve of preset sedimentation depth and time based on the collected sedimentation information related to time, and
under the condition that the second correlation curve is different from the first correlation curve, updating the second correlation curve in a mode of updating the preset sedimentation depth and judging the dynamic abnormal condition of the bottom of the sedimentation tank;
wherein the sedimentation information related to time is recorded by taking the preset sedimentation depth of the sedimentation tank as a driving event.
10. The method of claim 9 for deformation analysis based on dynamic fluctuation of the bottom of a settling tank, the method further comprising:
the preset sedimentation depth for sampling is set so that the sampling time period is shortened as the depth becomes larger.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111035451.5A CN113806843A (en) | 2021-09-01 | 2021-09-01 | Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111035451.5A CN113806843A (en) | 2021-09-01 | 2021-09-01 | Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113806843A true CN113806843A (en) | 2021-12-17 |
Family
ID=78894744
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111035451.5A Pending CN113806843A (en) | 2021-09-01 | 2021-09-01 | Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113806843A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114278313A (en) * | 2021-12-31 | 2022-04-05 | 北京住总集团有限责任公司 | Supporting system based on interval different excavation construction method conversion and construction method |
| CN114278383A (en) * | 2021-12-31 | 2022-04-05 | 北京住总集团有限责任公司 | Method for dismantling supporting structure of underground excavation section and monitoring system |
| CN114320311A (en) * | 2021-12-31 | 2022-04-12 | 北京住总集团有限责任公司 | Interval underground excavation method and support framework based on surrounding rock grade |
| CN116026267A (en) * | 2022-12-12 | 2023-04-28 | 中铁西北科学研究院有限公司 | Sliding surface position accurate determination method based on multi-sliding-surface B-type deep hole inclinometry curve |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104295304A (en) * | 2014-08-13 | 2015-01-21 | 北京城建集团有限责任公司 | Subway tunnel subsider production method capable of achieving different sedimentation distribution guarantee rates |
| CN104965994A (en) * | 2015-07-17 | 2015-10-07 | 青岛理工大学 | Determining and estimating method for surface subsidence characteristic parameters caused by subway tunnel construction |
| CN109145463A (en) * | 2018-08-27 | 2019-01-04 | 北京住总集团有限责任公司 | A kind of deformation analysis method for during tunnel excavation |
| CN109322705A (en) * | 2018-11-28 | 2019-02-12 | 中国矿业大学(北京) | Shield tunnel ground settlement automatic monitoring and alarming system and method for early warning |
| CN109508353A (en) * | 2018-12-11 | 2019-03-22 | 深圳市城市公共安全技术研究院有限公司 | City target InSAR monitoring risk prompting method and system |
| AU2019101263A4 (en) * | 2018-10-19 | 2019-11-28 | Mthing Pty Ltd | Device, System and Method for Monitoring Settlement and Structural Health |
| CN111259560A (en) * | 2020-02-04 | 2020-06-09 | 武汉轻工大学 | Shield construction ground surface settlement form classification method and system |
| CN112035940A (en) * | 2020-09-17 | 2020-12-04 | 交通运输部公路科学研究所 | Prediction method of highway subgrade settlement data |
| CN112380757A (en) * | 2020-12-14 | 2021-02-19 | 青岛理工大学 | Analysis method for offset distance of surface subsider peak point during construction of curved tunnel |
| CN112434359A (en) * | 2020-11-11 | 2021-03-02 | 东华理工大学 | High-speed railway pier settlement curve prediction method and system |
| CN112729232A (en) * | 2021-01-13 | 2021-04-30 | 中铁十一局集团有限公司 | Method for predicting surface settlement outside pit and considering whole process of foundation pit excavation in soft soil area |
| AU2021101917A4 (en) * | 2021-04-14 | 2021-06-03 | China Construction Third Engineering Bureau Co.,Ltd | Intelligent prediction and multi-objective optimization control method for ground settlement induced by subway tunnel construction |
| CN113239439A (en) * | 2021-05-21 | 2021-08-10 | 上海大学 | Shield construction ground surface settlement prediction system and method |
-
2021
- 2021-09-01 CN CN202111035451.5A patent/CN113806843A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104295304A (en) * | 2014-08-13 | 2015-01-21 | 北京城建集团有限责任公司 | Subway tunnel subsider production method capable of achieving different sedimentation distribution guarantee rates |
| CN104965994A (en) * | 2015-07-17 | 2015-10-07 | 青岛理工大学 | Determining and estimating method for surface subsidence characteristic parameters caused by subway tunnel construction |
| CN109145463A (en) * | 2018-08-27 | 2019-01-04 | 北京住总集团有限责任公司 | A kind of deformation analysis method for during tunnel excavation |
| AU2019101263A4 (en) * | 2018-10-19 | 2019-11-28 | Mthing Pty Ltd | Device, System and Method for Monitoring Settlement and Structural Health |
| CN109322705A (en) * | 2018-11-28 | 2019-02-12 | 中国矿业大学(北京) | Shield tunnel ground settlement automatic monitoring and alarming system and method for early warning |
| CN109508353A (en) * | 2018-12-11 | 2019-03-22 | 深圳市城市公共安全技术研究院有限公司 | City target InSAR monitoring risk prompting method and system |
| CN111259560A (en) * | 2020-02-04 | 2020-06-09 | 武汉轻工大学 | Shield construction ground surface settlement form classification method and system |
| CN112035940A (en) * | 2020-09-17 | 2020-12-04 | 交通运输部公路科学研究所 | Prediction method of highway subgrade settlement data |
| CN112434359A (en) * | 2020-11-11 | 2021-03-02 | 东华理工大学 | High-speed railway pier settlement curve prediction method and system |
| CN112380757A (en) * | 2020-12-14 | 2021-02-19 | 青岛理工大学 | Analysis method for offset distance of surface subsider peak point during construction of curved tunnel |
| CN112729232A (en) * | 2021-01-13 | 2021-04-30 | 中铁十一局集团有限公司 | Method for predicting surface settlement outside pit and considering whole process of foundation pit excavation in soft soil area |
| AU2021101917A4 (en) * | 2021-04-14 | 2021-06-03 | China Construction Third Engineering Bureau Co.,Ltd | Intelligent prediction and multi-objective optimization control method for ground settlement induced by subway tunnel construction |
| CN113239439A (en) * | 2021-05-21 | 2021-08-10 | 上海大学 | Shield construction ground surface settlement prediction system and method |
Non-Patent Citations (2)
| Title |
|---|
| 付春青;田世文;刘波;张功;: "Peck修正公式在北京地区砂卵石地层沉降预测中的应用", 施工技术, no. 09 * |
| 孙海涛;: "采动地表沉降时间函数的确定方法及其应用", 煤矿安全, no. 01 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114278313A (en) * | 2021-12-31 | 2022-04-05 | 北京住总集团有限责任公司 | Supporting system based on interval different excavation construction method conversion and construction method |
| CN114278383A (en) * | 2021-12-31 | 2022-04-05 | 北京住总集团有限责任公司 | Method for dismantling supporting structure of underground excavation section and monitoring system |
| CN114320311A (en) * | 2021-12-31 | 2022-04-12 | 北京住总集团有限责任公司 | Interval underground excavation method and support framework based on surrounding rock grade |
| CN116026267A (en) * | 2022-12-12 | 2023-04-28 | 中铁西北科学研究院有限公司 | Sliding surface position accurate determination method based on multi-sliding-surface B-type deep hole inclinometry curve |
| CN116026267B (en) * | 2022-12-12 | 2023-09-08 | 中铁西北科学研究院有限公司 | Sliding surface position accurate determination method based on multi-sliding-surface B-type deep hole inclinometry curve |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113806843A (en) | Deformation analysis system and method based on dynamic fluctuation of bottom of sedimentation tank | |
| US11043101B2 (en) | Multi-system, multi-parameter, integrated, comprehensive early warning method and system for coal and rock dynamic disaster | |
| Xue et al. | A two-step comprehensive evaluation model for rockburst prediction based on multiple empirical criteria | |
| Hudyma | Analysis and interpretation of clusters of seismic events in mines | |
| CN103743441B (en) | The polynary of a kind of side slope safety is coupling in line monitoring system and method | |
| CN111042143B (en) | Foundation pit engineering early warning method and system based on analysis of large amount of monitoring data | |
| CN106205060B (en) | For outdoor pit Tailings Dam slope and land slide early alarming and forecasting method | |
| CN104408899B (en) | Mountain highway granite residual colluvial soil landslide remote real-time early-warning method | |
| CN111042866B (en) | Multi-physical-field cooperative water inrush monitoring method | |
| CN107727737A (en) | One kind excavates the unknown geological structure activation recognition methods of underground engineering under Unloading Effect | |
| CN106203724B (en) | A kind of forecasting procedure of superficial layer landslide o earth slope | |
| CN111060022B (en) | Laser automatic analysis system and method for deformation of shield underpass structure | |
| CN106295040B (en) | Landslide disaster monitoring and warning earth's surface inclinometer threshold determination method | |
| CN110132218B (en) | Multi-level early warning determination method based on slope stability monitoring | |
| US11487030B2 (en) | Methods and systems for earthquake detection and prediction | |
| Bell et al. | Volcanic eruptions, real-time forecasting of | |
| Chang et al. | Bayesian prediction of tunnel convergence combining empirical model and relevance vector machine | |
| CN115688046A (en) | Rock burst prediction method and device and computer equipment | |
| CN111738501B (en) | Medium-short term prediction method for mining area earth surface deformation caused by underground mining | |
| Zhu et al. | The application of MsPSO in the rockfill parameter inversion of CFRD | |
| Fantini et al. | Investigating rock mass failure precursors using a multi-sensor monitoring system: preliminary results from a test-site (Acuto, Italy) | |
| Chandarana et al. | Monitoring and predicting slope instability: a review of current practices from a mining perspective | |
| CN112946740A (en) | Intelligent earthquake focus searching and positioning system | |
| CN112668865A (en) | Urban subway risk dynamic analysis method | |
| CN113279746A (en) | Method for determining deformation risk area of casing and application |
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 |