CN117423224A - Data acquisition method of slope monitoring internet of things equipment - Google Patents
Data acquisition method of slope monitoring internet of things equipment Download PDFInfo
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- CN117423224A CN117423224A CN202311263580.9A CN202311263580A CN117423224A CN 117423224 A CN117423224 A CN 117423224A CN 202311263580 A CN202311263580 A CN 202311263580A CN 117423224 A CN117423224 A CN 117423224A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 82
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- 238000004364 calculation method Methods 0.000 claims abstract description 14
- 238000007405 data analysis Methods 0.000 claims abstract description 14
- 238000004458 analytical method Methods 0.000 claims abstract description 13
- 230000002159 abnormal effect Effects 0.000 claims abstract description 11
- 230000005856 abnormality Effects 0.000 claims abstract description 5
- 230000035772 mutation Effects 0.000 claims abstract description 4
- 238000006073 displacement reaction Methods 0.000 claims description 39
- 238000007781 pre-processing Methods 0.000 claims description 13
- 239000011148 porous material Substances 0.000 claims description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 6
- 230000001133 acceleration Effects 0.000 claims description 4
- 238000013480 data collection Methods 0.000 claims description 4
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- 238000013528 artificial neural network Methods 0.000 description 2
- 238000009412 basement excavation Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 239000011435 rock Substances 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005422 blasting Methods 0.000 description 1
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- 230000005484 gravity Effects 0.000 description 1
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- 238000012706 support-vector machine Methods 0.000 description 1
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The invention relates to the technical field of geological disaster early warning, and discloses a data acquisition method of slope monitoring internet of things equipment, which comprises the following steps of: s10: setting initial data acquisition frequency parameters; s20: internet of things equipment f 0 Collecting slope monitoring data at fixed time; s30: the slope monitoring data are transmitted to a data acquisition system to perform edge calculation and analysis, and a preliminary data analysis result is obtained; s40: judging whether the current slope monitoring data has abnormality or mutation according to the data analysis result; s50: if so, continuing to execute the steps S20-S50; if abnormal, automatically adjusting the data acquisition frequency parameter to f 1 Collecting slope monitoring data at fixed time, wherein f 1 >f 0 And proceeds to steps S30-S50. The methodBy monitoring and analyzing the slope state in real time, the data acquisition frequency is automatically adjusted, the accuracy and the instantaneity of slope monitoring are improved, and the method has the advantages of being high in accuracy, good in reliability, high in flexibility and the like.
Description
Technical Field
The invention relates to the technical field of geological disaster early warning, in particular to a data acquisition method of slope monitoring internet of things equipment.
Background
The mountain highway is built with great relief, and high-steep cut slopes are usually formed at two sides of the road. Unstable rock high-steep side slope blasting excavation or after excavation causes a certain threat to the personal safety of vehicles and site constructors.
The slope monitoring has important significance for guaranteeing engineering construction and production safety. The traditional slope monitoring equipment generally adopts fixed data acquisition frequency, is difficult to adjust in real time according to the actual condition of the slope, and can cause interruption of key data acquisition, overhigh or overlow frequency, excessive equipment resources are easily occupied due to overhigh data acquisition frequency, and the performance and the service life of the equipment are affected; too low data acquisition frequency can affect data quality, and accurate and timely early warning information is difficult to provide.
Disclosure of Invention
The invention aims to provide a data acquisition method of slope monitoring Internet of things equipment, and aims to solve the problem that in the prior art, the data acquisition frequency of slope monitoring is difficult to determine.
The invention realizes the data acquisition method of the equipment of the internet of things for monitoring the side slope, monitors the side slope by adopting the equipment of the internet of things, controls the equipment of the internet of things to acquire data by a data acquisition system, and comprises the following steps:
s10: setting initial data acquisition frequency parameters for the data acquisition system;
s20: the Internet of things equipment collects frequency f at initial data 0 Collecting slope monitoring data at fixed time;
s30: the slope monitoring data are transmitted to the data acquisition system, and the data acquisition system performs edge calculation and analysis on the slope monitoring data to obtain a preliminary data analysis result;
s40: judging whether the current slope monitoring data has abnormality or mutation according to the data analysis result;
s50: if the judgment result shows that the operation is normal, continuing to execute the steps S20-S50;
if the judgment result shows that the data acquisition frequency is abnormal, automatically adjusting the data acquisition frequency parameter to enable the Internet of things equipment to acquire the frequency f at the adjusted data acquisition frequency 1 Collecting slope monitoring data at fixed time, wherein f 1 >f 0 And proceeds to steps S30-S50.
Optionally, the slope monitoring data collected by the internet of things device at regular time is transmitted to a remote server.
Optionally, the internet of things device comprises one or more of a rainfall sensor, a camera, an earth surface displacement sensor, a stress sensor, a deep displacement sensor, an acceleration sensor, an inclination sensor and a pore water pressure meter.
Optionally, the data collection frequencies of the plurality of internet of things devices are the same or different.
Optionally, in step S30, the side slope monitoring data is subjected to a preprocessing operation, and then the preprocessed side slope monitoring data is subjected to edge calculation and analysis.
Optionally, the preprocessing operation includes, but is not limited to, one or more of data smoothing, data filtering, data deduplication.
Optionally, after the preprocessing operation, feature extraction is performed on the preprocessed slope monitoring data, and feature information which has influence on the target variable is extracted for edge calculation.
Optionally, the mathematical model employed for edge computation includes, but is not limited to, one or more of an SVM model, an RBF model, and a BP model.
Optionally, the internet of things device collects displacement time sequence data of the slope, and the analysis method according to the displacement time sequence data includes:
acquiring displacement time sequence data of the slope within a certain time range;
accumulating displacement time sequence data of the side slope based on the gray prediction model to generate pretreatment, so as to obtain a new sequence;
and carrying out displacement prediction of the side slope based on the SVM model.
Optionally, in step S40, when the preliminary data analysis result exceeds the set threshold, the determination result is expressed as abnormal; and when the preliminary data analysis result does not exceed the set threshold value, the judgment result indicates normal.
Compared with the prior art, the data acquisition method of the slope monitoring internet of things equipment provided by the invention automatically adjusts the data acquisition frequency by monitoring and analyzing the slope state in real time, performs slope data acquisition at a lower data acquisition frequency at ordinary times, reduces the occupation of the internet of things equipment resources, reduces the operation load of the internet of things equipment, and is beneficial to prolonging the service life of the internet of things equipment; when abnormal conditions occur, slope data acquisition is automatically carried out at a higher data acquisition frequency, the accuracy and the instantaneity of slope monitoring are improved, the method has the advantages of being high in accuracy, good in reliability, strong in flexibility and the like, the quality of slope monitoring data can be effectively improved, and powerful support is provided for slope safety early warning and protection.
Drawings
Fig. 1 is a flow chart of a data acquisition method of slope monitoring internet of things equipment provided by the invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The implementation of the present invention will be described in detail below with reference to specific embodiments.
The same or similar reference numerals in the drawings of the present embodiment correspond to the same or similar components; in the description of the present invention, it should be understood that, if there is an azimuth or positional relationship indicated by terms such as "upper", "lower", "left", "right", etc., based on the azimuth or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not indicated or implied that the apparatus or element referred to must have a specific azimuth, be constructed and operated in a specific azimuth, and thus terms describing the positional relationship in the drawings are merely illustrative and should not be construed as limiting the present invention, and specific meanings of the terms described above may be understood by those of ordinary skill in the art according to specific circumstances.
Referring to FIG. 1, a preferred embodiment of the present invention is shown.
The data acquisition method of the slope monitoring internet of things equipment monitors the slope by adopting the internet of things equipment and controls the internet of things equipment to acquire data through a data acquisition system, and the method comprises the following steps:
s10: setting initial data acquisition frequency parameters for a data acquisition system; the data acquisition system can be embedded into the Internet of things equipment or arranged outside the Internet of things equipment and in communication connection with the Internet of things equipment, so that the Internet of things equipment can be conveniently controlled and acquired data can be conveniently processed;
s20: the Internet of things equipment collects frequency f at initial data 0 Collecting slope monitoring data at fixed time;
s30: the slope monitoring data are transmitted to a data acquisition system, and the data acquisition system performs edge calculation and analysis on the slope monitoring data to obtain a preliminary data analysis result;
s40: judging whether the current slope monitoring data has abnormality or mutation according to the data analysis result;
s50: if the judgment result shows that the operation is normal, continuing to execute the steps S20-S50;
if the judgment result shows that the data acquisition frequency is abnormal, automatically adjusting the data acquisition frequency parameter to enable the Internet of things equipment to acquire the frequency f of the adjusted data 1 Collecting slope monitoring data at fixed time, wherein f 1 >f 0 And proceeds to steps S30-S50.
According to the data acquisition method for the slope monitoring internet of things equipment, the slope state is monitored and analyzed in real time, the data acquisition frequency is automatically adjusted, slope data acquisition is carried out at a lower data acquisition frequency at ordinary times, occupation of internet of things equipment resources is reduced, operation load of the internet of things equipment is reduced, and service life of the internet of things equipment is prolonged; when abnormal conditions occur, slope data acquisition is automatically carried out at a higher data acquisition frequency, the accuracy and the instantaneity of slope monitoring are improved, the method has the advantages of being high in accuracy, good in reliability, strong in flexibility and the like, the quality of slope monitoring data can be effectively improved, and powerful support is provided for slope safety early warning and protection.
In step S50, after the collected data returns to the normal trend, i.e. after the judgment result indicates that the collected data is normal, the internet of things equipment is restored at the initial data collection frequency f 0 And (5) collecting slope data so as to reduce equipment power consumption.
In step S50, when the judgment result indicates that the slope is abnormal, the internet of things device sends out an early warning signal or transmits the early warning signal to the remote server, and early warning is performed at the remote end, so that the early warning signal is sent out to the user at the remote end in time, countermeasures are taken in time, and the hazard caused by the slope abnormality is reduced.
Optionally, the slope monitoring data collected by the internet of things device at regular time is transmitted to a remote server. The slope monitoring data collected by the internet of things equipment at regular time can be transmitted to a remote server through GPRS data transmission, a 4G network, a wireless network and the like, so that a user can conveniently and directly call the slope monitoring data at a remote end.
Specifically, the internet of things equipment comprises one or more of a rainfall sensor, a camera, an earth surface displacement sensor, a stress sensor, a deep displacement sensor, an acceleration sensor, an inclination angle sensor and a pore water pressure meter. The rainfall sensor can be used for monitoring rainfall; the camera can be used for video monitoring; the acceleration sensor measures the inclination condition of the slope according to the gravity principle; the inclination sensor can monitor the inclination and deformation of the slope surface. The displacement sensor is used for monitoring the horizontal displacement and the vertical displacement of the slope. The deep displacement sensor is used for monitoring the displacement condition of the slope. The pore water pressure meter is used for measuring pore water pressure in the side slope so as to monitor the influence of rainfall on the pore water pressure in the side slope, and is generally suitable for the condition that the porosity of the side slope rock is large. The earth surface displacement sensor is mainly used for measuring the earth surface displacement on the slope surface by installing the displacement sensor. Common earth displacement sensors include total stations, rangefinders, GNSS positioners, and the like. The earth surface displacement monitoring method can accurately measure the displacement condition of the side slope in real time and evaluate the stability of the side slope. In the monitoring of the displacement of the earth surface, a series of measuring points are required to be arranged, and the change condition of the position of the measuring points is measured periodically. By analyzing the measurement data, the displacement speed and trend of the side slope can be judged, and corresponding protection measures can be taken in time.
Optionally, the data collection frequencies of the plurality of internet of things devices are the same or different. When more than 2 pieces of Internet of things equipment are adopted, the data acquisition frequency of each piece of Internet of things equipment can be the same or different, and the influence of the data detected by each piece of Internet of things equipment on slope monitoring is determined.
Specifically, in step S30, the side slope monitoring data is subjected to a preprocessing operation, and then the preprocessed side slope monitoring data is subjected to an edge calculation and analysis. Optionally, the preprocessing operations include, but are not limited to, one or more of data smoothing, data filtering, data deduplication. In the data preprocessing stage, preprocessing operation is carried out, so that data quality and data consistency are ensured, and the influence of data noise is reduced, thereby facilitating subsequent data processing and analysis.
After the preprocessing operation, feature extraction is carried out on the preprocessed slope monitoring data, and feature information which has influence on the target variable is extracted and used for edge calculation.
Optionally, the mathematical model used for edge calculation includes, but is not limited to, one or more of an SVM model (support vector machine model), an RBF model (Radical Basis Function, radial basis function neural network), and a BP model (back propagation, inverse neural network).
Optionally, the internet of things device collects displacement time sequence data of the slope, and the analysis method according to the displacement time sequence data includes:
acquiring displacement time sequence data of the slope within a certain time range;
accumulating displacement time sequence data of the side slope based on the gray prediction model to generate pretreatment, so as to obtain a new sequence;
and carrying out displacement prediction of the side slope based on the SVM model.
For example, in the following edge calculation method, the displacement time-series data in a certain time range of the slope isWherein n is the deformation monitoring period number of the side slope; the slope displacement time sequence is preprocessed by accumulation generation in a gray prediction method GM (1, 1) to obtain a new sequence +.>And establishing a slope displacement prediction model by adopting an SVM model. Let the prediction set of the sample be { (xi, yi) |i=1, 2,. & gt, m }, where xi e Rn is the input vector, yi e Rn is the output vector, and the nonlinear mapping is used to map the sample input original space to the high-dimensional feature space, and construct the regression function of the SVM modelWherein->In order to satisfy the kernel function of the Mercer condition, ω is a weight vector of the hyperplane, and b is a bias term.
Obtaining the estimated parameters of SVM asCalculating the predictive value y of the accumulated sequence m+j (j=1, 2,., n-m) and performing reducing reduction to obtain a slope monitoring positionPrediction model of the move sequence->
Optionally, in step S40, when the preliminary data analysis result exceeds the set threshold, the determination result is expressed as abnormal; and when the preliminary data analysis result does not exceed the set threshold value, the judgment result indicates normal.
In a specific embodiment, the initial data acquisition frequency parameter may be set to acquire data once every 30 minutes. The equipment end of the Internet of things regularly collects monitoring data such as displacement, inclination, rainfall and the like of the slope through various sensors, and an edge calculation module of the equipment performs preprocessing and analysis on the data. And judging whether the data exceeds a threshold value according to the preprocessing and analysis results, if so, automatically adjusting the data acquisition frequency parameter, and improving the data acquisition frequency to five times per second so as to acquire more detailed and accurate monitoring data. If the data normally fluctuates, the current data acquisition frequency is kept unchanged, and the monitoring data is continuously acquired. For example: when the monitoring data show that the slope displacement is abnormal, the data acquisition frequency can be automatically improved, and the monitoring of the slope is enhanced; when the monitoring data display slope tends to be stable, the data acquisition frequency can be reduced, invalid data acquisition and transmission are reduced, equipment resources and network bandwidth are saved, and power consumption is reduced. In the embodiment, the data acquisition frequency is automatically adjusted by monitoring and analyzing the slope state in real time, so that the accuracy and the instantaneity of slope monitoring are improved, and powerful support is provided for slope safety pre-warning and protection. Meanwhile, the intelligent self-adaptive slope monitoring system has the characteristics of intelligence and self adaptation, reduces the manual intervention and operation cost, improves the efficiency and reliability of slope monitoring, and improves the safety management level of the slope.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. The data acquisition method of the slope monitoring internet of things equipment monitors the slope by adopting the internet of things equipment and controls the internet of things equipment to acquire data through a data acquisition system, and is characterized by comprising the following steps:
s10: setting initial data acquisition frequency parameters for the data acquisition system;
s20: the Internet of things equipment collects frequency f at initial data 0 Collecting slope monitoring data at fixed time;
s30: the slope monitoring data are transmitted to the data acquisition system, and the data acquisition system performs edge calculation and analysis on the slope monitoring data to obtain a preliminary data analysis result;
s40: judging whether the current slope monitoring data has abnormality or mutation according to the data analysis result;
s50: if the judgment result shows that the operation is normal, continuing to execute the steps S20-S50;
if the judgment result shows that the data acquisition frequency is abnormal, automatically adjusting the data acquisition frequency parameter to enable the Internet of things equipment to acquire the frequency f at the adjusted data acquisition frequency 1 Collecting slope monitoring data at fixed time, wherein f 1 >f 0 And proceeds to steps S30-S50.
2. The data acquisition method of the slope monitoring internet of things device according to claim 1, wherein slope monitoring data acquired by the internet of things device at regular time are transmitted to a remote server.
3. The data acquisition method of the slope monitoring internet of things device according to claim 1, wherein the internet of things device comprises one or more of a rainfall sensor, a camera, a ground surface displacement sensor, a stress sensor, a deep displacement sensor, an acceleration sensor, an inclination angle sensor and a pore water pressure meter.
4. The data acquisition method of the slope monitoring internet of things equipment is characterized in that the data acquisition frequencies of the plurality of internet of things equipment are the same or different.
5. The data acquisition method of the slope monitoring internet of things device according to claim 1, wherein in step S30, the slope monitoring data is subjected to a preprocessing operation, and then the preprocessed slope monitoring data is subjected to edge calculation and analysis.
6. The data collection method of the slope monitoring internet of things device according to claim 5, wherein the preprocessing operation comprises one or more of data smoothing, data filtering and data deduplication.
7. The data acquisition method of the slope monitoring internet of things device according to claim 6, wherein after the preprocessing operation, feature extraction is performed on the preprocessed slope monitoring data, and feature information having an influence on a target variable is extracted for edge calculation.
8. The data acquisition method of the slope monitoring internet of things equipment according to claim 7, wherein the mathematical model adopted by the edge calculation comprises one or more of an SVM model, an RBF model and a BP model.
9. The data acquisition method of the slope monitoring internet of things device according to claim 8, wherein the internet of things device acquires displacement time series data of the slope, and the analysis method according to the displacement time series data comprises the following steps:
acquiring displacement time sequence data of the slope within a certain time range;
accumulating displacement time sequence data of the side slope based on the gray prediction model to generate pretreatment, so as to obtain a new sequence;
and carrying out displacement prediction of the side slope based on the SVM model.
10. The data acquisition method of the slope monitoring internet of things device according to any one of claims 1 to 9, wherein in step S40, when the preliminary data analysis result exceeds the set threshold, the judgment result is expressed as abnormal; and when the preliminary data analysis result does not exceed the set threshold value, the judgment result indicates normal.
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| CN117874435A (en) * | 2024-03-11 | 2024-04-12 | 中国电子科技集团公司第十五研究所 | Distributed edge data acquisition method and device, electronic equipment and storage medium |
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| CN117874435A (en) * | 2024-03-11 | 2024-04-12 | 中国电子科技集团公司第十五研究所 | Distributed edge data acquisition method and device, electronic equipment and storage medium |
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