CN114971224A - Irrigation area intelligent inspection system based on smart phone and inspection method thereof - Google Patents
Irrigation area intelligent inspection system based on smart phone and inspection method thereof Download PDFInfo
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Abstract
The invention discloses an irrigation area intelligent inspection system based on a smart phone. The system comprises a background management system and a mobile terminal inspection App system; the mobile terminal inspection App system is in data communication with the background management system through a 4G/5G wireless network or a VPN private line; the data communication content comprises that the background management system pushes the inspection task and the data information to the mobile terminal, and the mobile terminal submits the inspection information to the background management system; the background management system realizes the functions of formulating an inspection task, planning an inspection path and the like; the mobile terminal inspection App system realizes the functions of mobile positioning, inspection trajectory diagram generation and the like. The invention has the advantages of saving the inspection cost, reducing the risk of missed inspection of the inspection object, preventing the inspection personnel from cheating, improving the inspection efficiency, enhancing the judgment and prediction analysis of the working condition risk of the inspection object, synchronizing the mobile terminal and the background automatic data and the like. The invention also discloses a polling method of the intelligent polling system for the irrigated area based on the smart phone.
Description
Technical Field
The invention relates to the field of safe operation management of an irrigation area, in particular to an intelligent inspection system of the irrigation area based on a smart phone. The invention also relates to a polling method of the intelligent polling system for the irrigated area based on the smart phone.
Background
The irrigation area is an important infrastructure for agricultural and rural economic development and an important production base of agricultural products in China. With the continuous promotion of the continuous construction matching and the reconstruction engineering of the irrigated area in China, the information construction of the irrigated area is an important construction content for the engineering reconstruction of the irrigated area as an important measure for improving the management level and efficiency of the irrigated area and realizing the modernization of the irrigated area.
The irrigation area has the characteristics of large irrigation area, long channel line, wide engineering distribution range, multiple types, large quantity and the like. As the foundation of the informatization of the irrigation areas, the construction of the perception system of the irrigation areas is more and more emphasized, and the automatic acquisition of the perception systems of the water and rain condition, the water quality, the soil moisture content, the engineering safety and the like is basically realized in the process of the engineering transformation of the irrigation areas. The inspection of the irrigation area engineering is an important supplement for the construction of an irrigation area sensing system, potential risks can be found in time through the inspection of the irrigation area engineering, and the inspection is an indispensable important means for the safe operation management of the irrigation area engineering. Because the inspection objects of the irrigation area project are of a plurality of types, a large number and are distributed dispersedly, manual inspection is still the main mode of inspection of the irrigation area project at present. Because the polling tasks of a plurality of polling objects need to be completed in the process of polling once, polling personnel often arrange polling routes and polling sequences according to personal habits, scientific path planning is lacked, a curved path is easy to walk in the polling process, the polling cost is increased, and the risk of missing the polling is also existed.
The patrolling and examining personnel patrols and examines the in-process in the field, looks up data, analysis calculation, comparison and judgment data processing and analysis work, and work load is big and make mistakes easily, if according to actual measurement operating mode data, combines the parameter threshold value of the normal operating mode of each item characteristic element of this object of patrolling and examining, through patrolling and examining the risk of analytic system quick judgement existence and generating alarm information, can alleviate the work load of patrolling and examining personnel risk analysis greatly. In addition, with the continuous development and wide application of the big data technology, how to utilize the big data technology to carry out the risk prediction analysis of the inspection object according to the historical monitoring data and catch the trend of risk development as soon as possible is worthy of further deep research.
The auxiliary inspection by means of the mobile intelligent equipment is an effective means for improving the inspection efficiency and efficiency of the irrigation area. If the inspection trace graph is generated through mobile positioning and inspection card punching, an important technical measure for preventing inspection missing of an inspection worker is provided; the mobile terminal system is used for reading monitoring data, filling in inspection information on site, uploading data such as videos and pictures and the like, and is an important means for improving inspection efficiency. The smart phone is used as the most widely applied smart mobile terminal, and the inspection terminal system based on the smart phone has the advantages of high popularization degree, small use difficulty, convenience in carrying and the like. The dependence of common apps with positioning functions in the smart phone on a wireless network is strong, inspection points of an irrigation area are distributed in remote areas, wireless network signals are weak or even no signals, therefore, a mobile positioning function module needs to be researched and developed, the problem that mobile positioning depends on the wireless network signals is solved, the positioning function in an offline state is realized, a transmission scheme of inspection data of a mobile terminal is provided, and the problem that the inspection data of the mobile terminal and a background management system are synchronous in the offline state is solved.
Disclosure of Invention
The first purpose of the invention is to provide an irrigation area intelligent inspection system based on a smart phone, which greatly reduces the workload of inspection personnel, improves the inspection efficiency, enhances the risk judgment and prediction analysis of inspection objects and has good application value; meanwhile, a mobile phone positioning function module is researched and developed by utilizing GNSS (Global Navigation Satellite System) data of the mobile phone, so that the positioning function in an off-line state is realized, and meanwhile, the mobile terminal polling data and a background management System are synchronized in the off-line state, so that the mobile terminal polling System is convenient to use; the problem that mobile positioning depends on wireless network signals is solved, and the defect that a trace graph generated by routing inspection and card punching is limited by the wireless network signals is overcome.
The second purpose of the invention is to provide the inspection method of the intelligent inspection system for the irrigation area based on the smart phone.
In order to achieve the first object of the present invention, the technical solution of the present invention is: the utility model provides an irrigated area intelligence system of patrolling and examining based on smart mobile phone which characterized in that: the system comprises a background management system and a mobile terminal inspection App system;
the mobile terminal inspection App system is in data communication with the background management system through a 4G/5G wireless network or a VPN private line; the data communication content comprises that the background management system pushes a polling task and data information to the mobile terminal polling App system, and the mobile terminal submits polling information to the background management system;
the background management system realizes the functions of routing inspection task making, routing inspection path planning, routing inspection data prediction analysis and early warning, data receiving and management, information inquiry, data synchronization and the like;
the mobile terminal inspection App system realizes the functions of mobile positioning, inspection track map generation, on-site inspection information filling, data uploading, inspection alarm, information query and display and the like.
In order to achieve the second object of the present invention, the technical solution of the present invention is: the inspection method of the intelligent inspection system for the irrigated area based on the smart phone is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
the method comprises the following steps: constructing an irrigation area inspection comprehensive database;
constructing an irrigation area inspection comprehensive database, and providing support for irrigation area inspection task formulation, inspection data management, inspection object working condition risk analysis and early warning, and inspection information query;
step two: constructing an inspection map of an irrigation area;
constructing an irrigation area inspection map based on a GIS platform for visually displaying irrigation area inspection data;
step three: constructing a patrol object working condition risk analysis model base;
constructing an inspection object working condition risk analysis model base by taking an inspection object as a unit, setting inspection object basic information, presetting parameter threshold value ranges under normal working conditions (safe operation) of various characteristic elements of the inspection object in standard specifications and judgment conditions and rules of different working condition risk levels, and providing services for on-site inspection object working condition risk judgment, prediction analysis and alarm early warning;
step four: making a routing inspection task and planning a routing inspection path;
the inspection personnel sends an inspection task request to a background management system through a mobile terminal inspection App system according to the irrigation area piece, the background management system automatically extracts all inspection points in the irrigation area piece according to the irrigation area piece information, carries out path planning, determines the inspection sequence of each inspection point, generates an inspection route, formulates an inspection task and pushes the inspection task to the mobile terminal inspection App system, and all inspection points and the inspection route contained in the inspection task are visually displayed on an inspection map of the irrigation area;
step five: polling and checking a card to generate a polling trace diagram;
when an inspection person arrives at an inspection point, the two-dimensional code of the inspection object needs to be scanned first to obtain basic information of the inspection object, wherein the basic information of the inspection object comprises inspection object operation condition risk analysis model data, inspection point geographical coordinate information and the like; when an inspector scans a two-dimensional code, the position (namely a scanning position point) of a scanning point is automatically positioned through a positioning function module of an App system of a mobile terminal, geographical coordinate information of the scanning position point is obtained, a linear distance L1 between the scanning position point and an inspection object position point is calculated, a distance threshold value delta L is set and the sizes of L1 and delta L are compared, if L1 is less than or equal to delta L, inspection and card punching are successful, inspection and card punching related information is recorded, and inspection track points are generated, wherein the inspection and card punching comprises the time of a card punching person, coordinate information and inspection object information, and if L1 is greater than delta L, inspection and card punching are failed, and the inspection and inspection track points cannot be generated; comparing the coordinate information of the routing inspection point with the coordinate information of the routing inspection point, when the distance between the two coordinates is smaller than a given threshold value, the routing inspection and the card punching are successful, and routing inspection and card punching related information is recorded to generate routing inspection track points, wherein the routing inspection track points comprise card punching personnel, card punching time, coordinate information, routing inspection object information and the like;
step six: filling in inspection information on site;
the inspection personnel fill in inspection information on site through the inspection App system through the mobile terminal, wherein the inspection information comprises inspection records, inspection object characteristic element observed values, pictures and videos shot on site and the like;
step seven: the risk of the working condition of the inspection object is alarmed;
according to the inspection object working condition model data and the on-site inspection object characteristic element observation data, the mobile terminal inspection App system obtains the parameter information of the inspection object working condition risk analysis model base, and analyzes and compares the parameter information, if the characteristic element F is detected i Is observed value S i Working condition risk analysis model parameter P corresponding to the element i The difference Delt _ i between them is greater than or equal to a given threshold Delt i Namely: delt _ i ≧ Δ T i Generating alarm information by an intelligent inspection system of an irrigation area based on a smart phone, and visually displaying the alarm information in a picture in the modes of colors, symbols and the like; if Delt _ i<ΔT i If so, the item is considered to have no risk and no alarm information is generated;
step eight: predicting, analyzing and early warning the working condition risk of the inspection object;
constructing a patrol object working condition risk prediction analysis model, carrying out patrol object safe operation working condition risk development trend prediction analysis according to historical patrol data of the patrol object by using a big data analysis method to obtain a risk development trend predicted value in a given time period in the future, and if the predicted value exceeds a set threshold value, generating early warning information and carrying out visual display in a picture; and if the predicted value does not exceed the set threshold value, no early warning information is generated, and the current working condition of the inspection object is indicated to be normal.
In the above technical solution, in the step one, the patrol checking integrated database mainly includes the following data:
1) basic data of an irrigation area; the method mainly comprises basic information data of an irrigation area, basic data of irrigation area hydraulic engineering, canal system data, basic data of a routing inspection point (routing inspection object) and the like;
2) data are patrolled; the irrigation area inspection comprises visual inspection and instrument exploration; the data which are filed and collected by the inspection personnel at each inspection point comprise data detected by an instrument, records of the inspection personnel, pictures or videos shot at the site and the like;
3) polling task data; the polling task is generated by a background, and polling task data comprises a polling point list, polling personnel information, polling path data and the like;
4) model data; constructing a risk analysis model of the operation condition of the inspection object, mainly comprising basic information of the inspection object, thresholds of normal conditions of various characteristic elements under different conditions in standard specifications, and judgment conditions and rules of risk grades of different conditions, and mainly used for warning and early warning analysis of the operation condition of the inspection object;
5) spatial data; the system mainly comprises irrigation area hydraulic engineering spatial distribution data, road network structure data, canal system data, inspection object spatial distribution data, administrative district, remote sensing image and other geographic spatial data.
In the above technical solution, in the second step, the irrigation area patrol data mainly includes the following map layers: 1) irrigation area range and irrigation area partition (surface layer); 2) irrigation area channel system (line pattern layer); 3) a water gate (comprising a check gate, a water diversion gate, a water outlet gate and a dot pattern layer); 4) a pump station (comprising a water lifting pump station, a waterlogging drainage pump station and a dot map layer); 5) culverts (line pattern layers); 6) inverted siphon (line pattern layer); 7) aqueduct (line pattern layer); 8) irrigation area dangerous work dangerous sections (point layers and line layers); 9) water system (line pattern layer); 10) lakes (surface layer); 11) road networks (graph layers); 12) town (dot map layer); 13) administrative divisions (surface layers); 14) high-definition remote sensing image data of the irrigation area; 15) routing inspection; 16) a routing inspection track graph; 17) a routing inspection alarm early warning information distribution map; the spatial data are organized according to layers, the display state of each layer can be controlled, unique codes are set for spatial elements of each hydraulic structure/inspection object, association with inspection data is established, relevant data of each inspection object can be inquired in one image, and the relevant data of the inspection object comprises inspection object basic data, theoretical threshold values, data acquired by inspection personnel on site, inspection alarm early warning information and the like.
In the above technical solution, in the fourth step, the method for routing inspection includes the following steps:
s41: setting the location (namely the starting position, also called office place) of a patrol personnel working unit;
s42: setting the number of inspection groups and inspection irrigation area pieces;
s43: initializing data;
s44: searching a path;
s45: a path planning scheme;
s46: judging whether the path planning scheme meets constraint conditions or not;
the constraint conditions are: (1) each inspection point can only finish the inspection task by one inspection group; (2) one inspection group can execute inspection tasks on a plurality of inspection points; (3) the starting point and the end point of each inspection group are required to be the same office;
when the constraint condition is satisfied, jumping to step S49;
when the constraint condition is not satisfied, go to step S47:
s47: comparing with the original route;
s48: judging whether the new route is more optimal;
when the new route is more optimal, jumping to step S49;
when the new route is not more optimal, jumping to step S46;
s49: judging whether the path planning scheme obtained by the S45 is an optimal scheme;
when the optimal solution is obtained, jumping to step S50;
when the optimal solution is not obtained, jumping to step S44;
s50: outputting the scheme;
s51: and finishing routing inspection path planning.
The invention has the following advantages:
according to the invention, according to the inspection object list, the trip position and the trip time of an inspector are combined, and a path planning algorithm is applied to carry out scientific and reasonable path planning on the inspector, so that the trip cost is saved, and the risk of missed inspection of an inspection point is avoided; the method is an effective means for preventing the inspection omission of the inspection personnel, and the inspection and the card punching need to acquire the geographic position coordinate information of the card punching point of the inspection personnel, but in the field area where the wireless network signal is weak or even no signal, the positioning function of the smart phone depending on the network signal cannot be normally used, and the card punching is difficult, so that the method utilizes the GNSS (Global Navigation Satellite System) data of the smart phone to research and develop the positioning function module independent of the network signal, and overcomes the defect that the trace map generated by the inspection and the card punching is limited by the wireless network signal; the invention constructs a working condition risk analysis model for each inspection object, inputs parameter threshold values under normal working conditions of various characteristic elements of the inspection object in standard specifications, can quickly judge whether the inspection object has working condition risks or not through a system when inspection information is input on site by an inspector, generates alarm information if the inspection object has the working condition risks, visually displays the alarm information in a GIS scene of a picture in the forms of characters, colors, symbols and the like, further utilizes a big data analysis technology at the background, combines historical inspection data to predict and analyze the working condition risk development trend of the inspection object, and discovers potential risks as soon as possible.
The intelligent inspection method and the intelligent inspection system for the smart phone, which are disclosed by the invention, greatly reduce the workload of inspection personnel, improve the inspection efficiency, enhance the judgment and prediction analysis of the working condition risk of the inspection object and have good application value.
Drawings
Fig. 1 is a general structure diagram of an intelligent inspection system for an irrigation area.
Fig. 2 is a flowchart of a routing inspection path planning algorithm (ant colony algorithm) in the present invention.
Fig. 3 is a flowchart of a mobile phone precise single-point positioning calculation in the present invention.
Fig. 4 is a schematic diagram of a data synchronization process of the mobile terminal polling App system and the background system in the invention.
Fig. 5 is a flow chart for analyzing and predicting the inspection object working condition risk in the invention.
Detailed Description
The embodiments of the present invention will be described in detail with reference to the accompanying drawings, which are not intended to limit the present invention, but are merely exemplary. While the advantages of the invention will be clear and readily understood by the description.
With reference to the accompanying drawings: an irrigation area intelligent inspection system based on a smart phone comprises a background management system and a mobile terminal inspection App system;
the mobile terminal inspection App system is in data communication with the background management system through a 4G/5G wireless network or a VPN private line; the data communication content comprises that the background management system pushes the inspection task and the data information to the mobile terminal, and the mobile terminal submits the inspection information to the background management system;
the background management system realizes the functions of routing inspection task formulation, routing inspection path planning, routing inspection data prediction analysis and early warning, data receiving and management, information inquiry, data synchronization and the like;
the mobile terminal inspection App system realizes the functions of mobile positioning, inspection track map generation, on-site inspection information filling, data uploading, inspection alarm, information inquiry and display and the like (as shown in figure 1).
With reference to the accompanying drawings: the inspection method of the intelligent inspection system for the irrigated area based on the smart phone comprises the following steps,
step 1, constructing an irrigation area inspection comprehensive database
The method comprises the following steps of constructing a comprehensive irrigation area inspection database for storing and managing data, finishing data sorting, inputting and updating maintenance work, and mainly comprising the following steps: irrigation area basic information, irrigation area hydraulic engineering data, inspection object basic data, irrigation area road network data, inspection data, irrigation area basic geographic space data and the like. The system comprises basic data of an irrigation area, basic geographic space data and basic data of an inspection object, wherein the working condition model data of the inspection object belongs to static data, the change frequency is low, the change content is less, the data are sorted and stored according to requirements, the inspection data belong to dynamic data, and the dynamic increment is updated.
Step 2, constructing an inspection map of the irrigation area
And constructing a graph visualization scene based on the GIS platform. The inspection space data of the irrigation area is organized according to layers, and comprises 1) an irrigation area range and an irrigation area partition (a surface layer); 2) irrigation area channel system (line pattern layer); 3) a water gate (comprising a check gate, a water diversion gate, a water outlet gate and a dot pattern layer); 4) pump stations (including water lifting pump stations, drainage pump stations and point map layers); 5) culverts (line pattern layers); 6) inverted siphon (line pattern layer); 7) aqueduct (line pattern layer); 8) irrigation area dangerous work dangerous sections (point layers and line layers); 9) water system (line pattern layer); 10) lakes (surface layer); 11) road networks (graph layers); 12) town (dot map layer); 13) administrative divisions (surface layers); 14) irrigation area high-definition remote sensing image data; 15) routing inspection; 16) a routing inspection track graph; 17) and (5) routing inspection alarm early warning information distribution map. Each layer can control the display state of the layer. A set of coding system is established for the inspection objects in the irrigation area, each water engineering building and the inspection object have unique codes, and the codes are associated with inspection data, operation conditions, early warning information and the like, so that corresponding basic information and inspection data can be inquired in a layer by selecting space element objects.
Step 3, constructing a patrol object working condition risk analysis model base
Establishing an inspection object working condition risk analysis model base, inputting safe operation parameter thresholds of various characteristic elements of the inspection object under normal working conditions in standard specifications according to related standard specification requirements for each inspection object, setting judgment conditions and rules of different working condition risk levels, and providing services for inspection object working condition risk judgment, prediction analysis and alarm early warning;
the construction of the inspection object working condition risk analysis model base is the premise of working condition risk analysis. Assume that a floodgate includes the following information: (1) basic information such as the name, the code, the construction time, the grade and the like of the sluice; (2) basic design parameters of the sluice; (3) various required data and threshold data for ensuring safe operation of the project, such as the maximum overflowing capacity and the maximum water level required in relevant specifications and regulations; (4) the method comprises the steps of (1) judging the risk level of engineering operation and judging conditions of different risk levels; (5) historical/real-time monitoring data of each characteristic element; the information data are effectively organized, risk judgment rules are set, a working condition risk analysis model is formed, actual monitoring data serve as input, and working condition risk grades serve as output.
Step 4, routing planning of inspection task
And automatically extracting all the inspection objects in the inspected irrigation area according to the inspection area determined by the inspection task, and constructing an inspection point list. According to the initial position of the polling task executed by the polling personnel, path planning is carried out by using a path planning algorithm, and a scientific and reasonable polling sequence and a polling path are provided for the polling personnel through the routing planning of the polling task, so that the polling time and the cost are saved;
routing inspection path planning is a typical VRP Problem (Vehicle path Problem), an inspection group (one or more groups) starts from a starting position (the starting position is generally set as a regular office location of an inspector), inspects a plurality of inspection points in a specified irrigation area, and finally returns to the starting position, and the core of the path planning is to obtain an optimal planning scheme according to input under the condition that given constraint conditions are met. For routing inspection path planning, the minimum total routing inspection cost is taken as an optimal planning scheme, and the path distance is taken as a routing inspection cost measurement index in the invention, namely the shortest routing inspection path is taken as a target.
The known conditions are as follows:
(1) the number of the inspection points is n, each point is numbered as i, and i is 0 and represents the initial position of an inspector;
(2) the number of the routing inspection subgroups set in the irrigation area management processing is m, and the number of each routing inspection subgroup is k;
(3) the distance from the starting position to each inspection point and the distance between each inspection point are c ij (i＝0，1，2，…,n-1；j＝1,2,…,n；i<j; i-0 denotes the patrol inspector starting position).
Constraint conditions are as follows:
(1) each inspection point can only finish the inspection task by one inspection group;
(2) one inspection group can execute inspection tasks on a plurality of inspection points;
(3) the start and end points of each routing team must be the same location, i.e., the start location.
The path planning function aims at minimizing the total cost of routing inspection travel, namely, the shortest total travel path is taken as a target function, and a mathematical model is established:
in the formula: c. C ij Indicating the distance from the office to each inspection point and the distance between inspection points (i-0, 1, …, n-1; j-1, 2, …, n; i ═ 1<j) i-0 represents the starting position; x is the number of ijk And indicating that the inspection group k drives from the inspection point i to the inspection point j, and taking the value of 1 when the event occurs, or taking the value of 0.
The constraints are as follows:
in the formula, y jk The freight task representing the inspection point i is completed by an inspection team k, and 1 is taken when the event occurs, otherwise 0 is taken
(formula 1) is an objective function; (formula 2) each inspection point executes the inspection task by and only one inspection group; (equation 3) shows that if the inspection point j is performed by the inspection team k, the inspection team k must reach the inspection point j from the inspection point i. (equation 4) indicates that if the inspection point i is executed by the inspection team k, the inspection team k must arrive at another inspection point j after the inspection task of the inspection point i is executed.
The VRP path planning has a plurality of mature algorithms, the routing inspection path planning is carried out by adopting an ant colony search algorithm in a heuristic algorithm, and the algorithm flow is shown in figure 2.
Step 5, polling and checking a card by a positioning function module based on the GNSS data of the smart phone to generate a polling trajectory diagram;
the invention develops a mobile positioning function module based on mobile GNSS data, and realizes the positioning function of a mobile phone independent of a mobile network. The method comprises the steps of acquiring GNSS observation data carried by a mobile phone by adopting an open data interface, and researching and developing a Positioning function module independent of wireless network signals by using a PPP Positioning algorithm (precision Point Positioning), so as to realize mobile Positioning in a network signal-free state.
Because the spatial distribution of the routing inspection points is relatively dispersed, the requirement of the mobile phone positioning for routing inspection and card punching on the positioning precision is not high, and the positioning precision of the decimeter level or even the meter level can meet the requirement of the routing inspection and card punching positioning.
PPP positioning is to use the GPS observation data of a plurality of global ground tracking stations to calculate the precise satellite orbit and satellite clock error, and to perform positioning calculation to the phase and pseudo range observation value collected by a single GPS receiver.
The PPP positioning is an absolute positioning technology, and the PPP technology can complete high-precision positioning of a single receiver by using a high-precision carrier phase observation value, a high-precision pseudo-range observation value and a series of precision products. The precise single-point positioning uses precise products such as a precise orbit, a clock error and earth rotation provided by an igs (International GNSS service) or iGMAS (International GNSS Monitoring association System), and mobile-end carrier waves and pseudo-range observation data to obtain a high-precision positioning result.
In GNSS measurements, the observation equation of pseudorange to carrier phase is as follows:
in the formula, P is a pseudo range observed value;
is a carrier observation; c is the speed of light in vacuum;
is the receiver clock error;
is the satellite clock error; v ion Is ionospheric delay; v rtop Is tropospheric delay; λ is the wavelength; n is the integer ambiguity; δ ρ is the influence of the satellite ephemeris error on the ranging; δ ρ mul Is a multipath error; epsilon p Observing noise for the pseudo range;
observing noise for the carrier; ρ is the distance between the satellite and the receiver.
(x, y, z) are receiver position coordinates; (x) s ，y s ，z s ) Are the satellite coordinates.
The precise three-dimensional coordinates and the clock errors of the satellites in (equation 5) and (equation 6) can be obtained by processing and calculating the related data of the precise ephemeris product issued by the IGS. Errors such as earth rotation, polar motion, relativistic effects, etc. can be corrected by respective error models. Ionospheric delay can be eliminated by eliminating a first-order ionospheric combination observation value, and a Kalman filtering model is adopted in the parameter estimation method. The error model is prior art.
The flow of polling card punching and generating polling trace diagram is shown in fig. 3. As shown in fig. 3, the method for implementing mobile positioning in a no-network-signal state by using PPP positioning algorithm of the present invention includes data input, data preprocessing and parameter estimation, and finally generates PPP positioning result by data input, data preprocessing and parameter estimation; the data input comprises the steps of acquiring GNSS data from a mobile phone chip by using an API (application programming interface) interface and downloading precise ephemeris product data from an IGS (integrated navigation system); the data preprocessing comprises error processing, gross error elimination, phase epoch difference and cycle slip detection; the parameter estimation comprises a constant velocity model, Kalman filtering, state prediction and measurement update.
When an inspection person arrives at an inspection point, scanning the two-dimensional code of the inspection object to obtain basic information of the inspection object, wherein the basic information of the inspection object comprises inspection object operation condition risk analysis model data and inspection point geographical coordinate information; when an inspector scans a two-dimensional code, the position (scanning position point) of a scanning point is automatically positioned through a mobile terminal positioning function, geographical coordinate information of the scanning position point is obtained, a linear distance L1 between the scanning position point and an inspection object position point is calculated, a distance threshold value delta L is set and the sizes of L1 and the delta L are compared, if L1 is less than or equal to the delta L, inspection and card punching are successful, inspection and card punching related information is recorded, inspection and card punching track points are generated, including card punching personnel, card punching time, coordinate information and inspection object information, and if L1 is greater than the delta L, inspection and card punching are failed, and the inspection and card punching track points cannot be generated;
step 6, polling information filling and alarming
The personnel of patrolling and examining need fill in on-the-spot and patrol and examine information, upload and examine data, specifically include: (1) the inspection object condition description and the recorded information; (2) pictures and videos shot on site; (3) and (5) observing the value of the patrol instrument. Because the inspection object working condition risk analysis model is created, the relevant parameters of the model are preset in the two-dimensional code, and when inspection data are filled, the working condition risk analysis can be carried out immediately. The risk of the working condition of the inspection object is divided into 3 grades: and (3) normally, early warning and alarming, wherein the current monitoring value is set as S _ c, the theoretical value under the normal working condition is S _ t, the given increment threshold value is delta q, and the working condition risk level is determined according to the following table 1.
TABLE 1 inspection object work condition risk level determination
| Serial number | State determination | The judgment result |
| 1 | S_c≤S_t | Normal state |
| 2 | S_t<S_c≤S_c+Δq | Early warning state |
| 3 | S_c>S_t+Δq | Alert state |
If one or more observation values of the characteristic elements of the inspection object exceed a parameter threshold value preset by the model, the system generates alarm information and displays the alarm information in a picture in the modes of characters, symbols, colors and the like; if the observed value does not exceed the preset parameter threshold value of the model, no alarm information is generated, so that the problem that the informatization and automation of routing inspection data field processing are difficult to realize due to the fact that manual routing inspection is adopted in the irrigation area routing inspection project in the prior art is solved.
Step 7, predicting, analyzing and early warning the working condition risk of the inspection object
And (3) selecting an autoregressive Moving Average model (ARMA model) to construct a working condition risk prediction analysis model of the inspection object. The ARMA (p, q) model comprises p autoregressive terms and q moving average terms, and can be expressed as:
where p and q are the autoregressive order and the moving average order of the model,
and θ is a pending coefficient, ε, of other than 0 t Is an independent error term, X t Is a smooth, normal, zero mean time series.
And calculating the predicted value of the characteristic element in a given time interval delta t in the future according to the historical monitoring data of the inspection object as the input data of the model. And (3) setting the current measured value as S _ c, the predicted value obtained through model calculation as S _ f, the theoretical threshold value of the characteristic element of the inspection object under the normal working condition as S _ t, and the increment threshold value of the observed value of the characteristic element as delta q, and then judging the working condition risk of the inspection object according to the following table 2.
Table 2 shows that the working condition risk judgment is carried out according to the monitoring value and the predicted value of the inspection object
Visually displaying the inspection object working condition analysis result in a picture by adopting the modes of characters, symbols, colors, thematic maps and the like; the characteristic element values are predicted by adopting the inspection object working condition risk prediction model, and the defects that inspection data prediction analysis cannot be performed, development trend prediction analysis of inspection object safe operation risks is lacked, and potential risk hidden dangers cannot be found in time in the prior art are overcome. The inspection object working condition risk analysis and prediction flow chart is shown in figure 5.
In the inspection object working condition risk prediction analysis, comprehensive analysis is carried out by combining real-time monitoring data with historical monitoring data, and after the alarm information in the step 6 is generated and the relevant requirements of the technical rules are digitalized and modeled, the observed value is compared with the threshold value specified in the technical rules, and when the threshold value is exceeded, the alarm is given, so that the inspection object working condition risk prediction analysis method is simple, direct and efficient, and the workload of inspection personnel for looking up the technical rules, and simple calculation and conversion is reduced.
Step 8, the mobile terminal polling data and the background management system realize data synchronization
The invention researches and develops data synchronization service between a mobile terminal and a background management system. And (3) creating a routing inspection database table structure which is the same as the background service in the mobile terminal routing inspection App system. The polling personnel fills in polling data records on the spot at the polling points, and directly transmits the polling data records to the background management system through the VPN network under the condition of good wireless network signals to realize data synchronization; if no wireless network signal exists, the wireless network signal is firstly stored in the local inspection App system, and when a network signal exists, the wireless network signal is automatically synchronized to the background management system; the problem that polling data cannot be synchronized in a field no-signal state of the smart phone in the prior art and the defect that field polling data cannot be transmitted to a background server in an off-line state are overcome; the data synchronization flow chart of the patrol App system and the background management system is shown in figure 4.
Other parts not described belong to the prior art.
Claims (5)
1. The utility model provides an irrigated area intelligence system of patrolling and examining based on smart mobile phone which characterized in that: the system comprises a background management system and a mobile terminal inspection App system;
the mobile terminal inspection App system is in data communication with the background management system through a 4G/5G wireless network or a VPN private line; the data communication content comprises that the background management system pushes a polling task and data information to the mobile terminal polling App system, and the mobile terminal submits polling information to the background management system;
the background management system realizes the functions of setting inspection tasks, planning inspection paths, predicting, analyzing and early warning inspection data, receiving and managing data, inquiring information and synchronizing data;
the mobile terminal inspection App system realizes the functions of mobile positioning, inspection trace map generation, on-site inspection information filling, data uploading, inspection alarm, information inquiry and display.
2. The inspection method of the intelligent inspection system for the irrigated area based on the smart phone according to claim 1, wherein: comprises the following steps of (a) carrying out,
the method comprises the following steps: constructing an irrigation area inspection comprehensive database;
constructing an irrigation area patrol comprehensive database, and providing support for irrigation area patrol task formulation, patrol data management, patrol risk analysis and early warning, and patrol information query;
step two: constructing an inspection map of an irrigation area;
constructing an irrigation area inspection map based on a GIS platform for visually displaying irrigation area inspection data;
step three: constructing a risk analysis model base of the operation condition of the inspection object;
constructing an inspection object operation condition risk analysis model base by taking an inspection object as a unit, setting inspection object basic information, parameter value ranges under the condition of safe operation of each characteristic element, risk grades of different conditions and judgment rules, and providing services for inspection object condition risk judgment, prediction analysis and alarm early warning;
step four: making a routing inspection task and planning a routing inspection path;
the inspection personnel sends an inspection task request to a background management system through an inspection App system of the mobile terminal according to the irrigation area slice, the background management system automatically extracts all inspection points in the irrigation area slice according to the information of the irrigation area slice, carries out path planning, determines the inspection sequence of each inspection point, generates an inspection route, formulates an inspection task and pushes the inspection task to the inspection App system of the mobile terminal, and all the inspection points and the inspection route contained in the inspection task are visually displayed on an inspection map of the irrigation area;
step five: polling and checking a card to generate a polling trace diagram;
when an inspection person arrives at an inspection point, scanning the two-dimensional code of the inspection object to obtain basic information of the inspection object, wherein the basic information of the inspection object comprises inspection object operation condition risk analysis model data and inspection point geographical coordinate information; when an inspector scans a two-dimensional code, the position of a scanning point is automatically positioned through the positioning function of an App system of a mobile terminal, geographical coordinate information of the scanning position point is obtained, the linear distance L1 between the scanning position point and an inspection object position point is calculated, a distance threshold value delta L is set and the sizes of L1 and the delta L are compared, if L1 is less than or equal to the delta L, inspection and card punching are successful, inspection and card punching related information is recorded, inspection and card punching track points are generated, including card punching personnel, card punching time, coordinate information and inspection object information, and if L1 is greater than the delta L, inspection and card punching are failed, and the inspection and card punching track points cannot be generated;
step six: filling in inspection information on site;
the inspection personnel fill in inspection information on site through the inspection App system through the mobile terminal, wherein the inspection information comprises inspection records, inspection object characteristic element observed values, pictures and videos shot on site;
step seven: the risk of the working condition of the inspection object is alarmed;
according to the inspection object working condition model data and the on-site inspection object characteristic element observation data, the mobile terminal inspection App system obtains the parameter information of the inspection object working condition risk analysis model base, and analyzes and compares the parameter information, if the characteristic element F is detected i Is observed value S i Working condition risk analysis model parameter P corresponding to the element i The difference Delt _ i between them is greater than or equal to a given threshold Delt i Namely: delt _ i ≧ Δ T i Generating alarm information by an intelligent inspection system of the irrigation area based on the smart phone, and visually displaying the alarm information in a picture in a color and symbol mode; if Delt _ i<ΔT i If so, the item is considered to have no risk and no alarm information is generated;
step eight: predicting, analyzing and early warning the working condition risk of the inspection object;
constructing a patrol object working condition risk prediction analysis model, carrying out patrol object safe operation working condition risk development trend prediction analysis according to historical patrol data of the patrol object by using a big data analysis method to obtain a risk development trend predicted value in a given time period in the future, and if the predicted value exceeds a set threshold value, generating early warning information and carrying out visual display in a picture; and if the predicted value does not exceed the set threshold value, no early warning information is generated, and the current working condition of the inspection object is indicated to be normal.
3. The inspection method of the intelligent inspection system for the irrigated area based on the smart phone according to claim 2, wherein the inspection method comprises the following steps: in step one, the inspection comprehensive database comprises the following data:
1) basic data of an irrigation area; the method comprises irrigation area basic information data, irrigation area hydraulic engineering basic data, canal system data and inspection point basic data;
2) data are patrolled; the irrigation area inspection comprises visual inspection and instrument exploration; the data which are filed and collected by the inspection personnel at each inspection point comprise data detected by an instrument, inspection records and picture or video data shot on site;
3) polling task data; the polling task is generated by a background, and polling task data comprises a polling point list, polling personnel information and polling path data;
4) model data; constructing a safe operation condition model of the inspection object for each inspection object, wherein the safe operation condition model comprises theoretical threshold data of the operation condition of each inspection object and is used for alarming, early warning and analyzing the operation condition of the inspection object;
5) spatial data; the method comprises water conservancy project spatial distribution data, road network structure data, channel system data, inspection object spatial distribution data, administrative region data and remote sensing image geographic spatial data.
4. The inspection method of the intelligent inspection system for the irrigated area based on the smart phone according to claim 2 or 3, wherein: in the second step, the irrigation area patrol data comprises the following map layers: the method comprises the following steps of (1) dividing an irrigation area range and an irrigation area; irrigation canal system; a sluice; a pump station; a culvert; inverted siphon; aqueduct; a dangerous section of the irrigation area; a water system; a lake; a road network; town; performing administrative division; irrigation area high-definition remote sensing image data; routing inspection; a routing inspection track graph; a routing inspection alarm early warning information distribution map; the spatial data are organized according to layers, and the display state of each layer is controlled; setting a unique code for the space element object, establishing association with the inspection data, and inquiring related data of each inspection object in a graph, wherein the related data of the inspection objects comprise basic data of the inspection objects, a theoretical threshold, data acquired by inspection personnel on site and inspection alarm early warning information.
5. The inspection method of the intelligent inspection system for the irrigated area based on the smart phone according to claim 4, wherein: in the fourth step, the method for routing inspection comprises the following steps:
s41: setting the location of a patrol worker working unit;
s42: setting the number of inspection groups and inspection irrigation area pieces;
s43: initializing data;
s44: searching a path;
s45: a path planning scheme;
s46: judging whether the path planning scheme meets constraint conditions or not;
when the constraint condition is satisfied, jumping to step S49;
when the constraint condition is not satisfied, go to step S47:
s47: comparing with the original route;
s48: judging whether the new route is more optimal;
when the new route is more optimal, jumping to step S49;
when the new route is not more optimal, jumping to step S46;
s49: judging whether the path planning scheme obtained by the S45 is an optimal scheme;
when the optimal solution is obtained, jumping to step S50;
when the optimal solution is not obtained, jumping to step S44;
s50: outputting the scheme;
s51: and finishing routing inspection path planning.
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| CN116485065A (en) * | 2023-06-21 | 2023-07-25 | 成都秦川物联网科技股份有限公司 | Pipe network inspection management method based on intelligent gas GIS and Internet of things system |
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| CN116485065A (en) * | 2023-06-21 | 2023-07-25 | 成都秦川物联网科技股份有限公司 | Pipe network inspection management method based on intelligent gas GIS and Internet of things system |
| CN116485065B (en) * | 2023-06-21 | 2023-09-08 | 成都秦川物联网科技股份有限公司 | Pipe network inspection management method based on intelligent gas GIS and Internet of things system |
| US11977827B2 (en) | 2023-06-21 | 2024-05-07 | Chengdu Qinchuan Iot Technology Co., Ltd. | Methods, internet of things systems, and storage mediums for management of pipeline network inspection based on smart gas geographic information systems |
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