CN116708495A - A hydrological telemetry method and system capable of intelligent maintenance - Google Patents

Abstract

The application discloses a method and a system capable of intelligently maintaining hydrological telemetering, which are characterized in that a measuring point module is used for collecting measuring point position water area data according to a first collecting strategy, the water area data is sent to a cloud platform, whether the first collecting strategy is matched with the current measuring point collecting requirement is judged according to the water area data, if not, a second collecting strategy is generated according to a preset strategy generating rule and the water area data, the second collecting strategy is sent to the measuring point module, and the measuring point module is used for collecting the measuring point position water area data according to the second collecting rule. The remote control and remote parameter adjustment of the hydrologic telemetering equipment, the communication state and the key operation information are realized without parameter adjustment by operation staff of hydrologic telemetering under the condition of no equipment fault, the remote control, the operation and maintenance efficiency and the intellectualization of the hydrologic telemetering equipment are improved, the labor and time cost of hydrologic adjustment parameters and operation and maintenance is reduced to the greatest extent, and the effectiveness and the data quality of telemetering data are improved.

Description

A hydrological telemetry method and system capable of intelligent maintenance

technical field

The present application relates to the technical field of hydrological telemetry capable of intelligent maintenance, in particular to a method and system of hydrological telemetry capable of intelligent maintenance.

Background technique

Hydrological telemetry technology is an important basis for water conservancy informatization. The remote transmission channel between the central program of the early telemetry system and the telemetry equipment generally adopts ultrashort wave, satellite, PSTN (Public Switched Telephone Network), etc., which is basically a point-to-point transmission. From the perspective of the topology model, the current monitoring of water conservancy data has been from Traditional methods such as manual meter reading and local area network statistics have entered the cloud collection mode. However, there are two prominent problems at this stage. One is that manual intervention is required for parameter adjustment at measurement points, and the other is that the telemetry strategy cannot be self-adapted after solidification.

Usually, various sensors such as flow rate, water level, rainfall, etc. have corresponding mature sensors to collect their status, and access the collection controller through different local communication protocols. These sensors have different parameters to control their collection behavior; which hydrological elements to collect, when to collect, and the frequency of collection, etc., also need to be controlled by the collection controller through software parameters. Nowadays, the Internet of Things is mostly used for remote acquisition and communication, but the setting of various parameters related to the acquisition strategy needs to be set at the factory. Once adjustments are required, on-site construction or maintenance personnel are required to go to the site. For hydrological telemetry, each measuring point is often distributed far away, and it takes a lot of manpower, material resources and time to complete a parameter adjustment. However, due to factors such as equipment upgrades, changes in the surrounding environment of the measuring point, and adjustment of measurement content, the adjustment of parameters cannot be avoided. The existing technology is time-consuming and labor-intensive to manually adjust the parameters of the measuring point on site, and it is even impossible to adjust the measuring point in time during the flood season. parameter.

Contents of the invention

Based on this, in view of the above technical problems, a method and system for intelligent maintenance of hydrological telemetry is provided to solve the problem of time-consuming and labor-consuming manual on-site adjustment of measuring point parameters in the prior art, and it is impossible to adjust the measuring point parameters in time during the flood season.

In the first aspect, a method for intelligently maintaining hydrological telemetry, the method includes:

The measuring point module collects the water area data of the measuring point position according to the first acquisition strategy, and sends the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller According to the first acquisition strategy, a plurality of sensors are controlled to collect multiple sets of data of the water area of the measuring point position to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; the acquisition controller converts the Sending the water area data to the cloud platform includes that the transceiver establishes an https connection to the cloud platform through a mobile communication network, and sends the water area data to the cloud platform;

Judging whether the first collection strategy matches the current survey point collection according to the water area data, if not, generating a second collection strategy according to the preset strategy generation rules and the water area data;

The second collection strategy is sent to the measuring point module, and the measuring point module collects the water area data of the measuring point according to the second collection rule.

In the above scheme, optionally, the measuring point module collects the water area data of the measuring point position according to the first collection strategy, and sends the water area data to the cloud platform, including:

The transceiver uses 4G mobile communication to access the Internet, adopts multi-mode communication equipment, and ensures the reliability of network communication by simultaneously accessing multiple operators;

The acquisition controller is used to drive the transceiver and the plurality of sensors, and is used to deploy the first acquisition strategy and the second acquisition strategy; the acquisition controller is equipped with a flash memory chip for storing software parameter;

The multiple sensors are used to collect different indicator data through the sensor protocol and API, wherein the multiple types of sensors include water temperature sensors, water level sensors, water quality sensors, water pressure sensors, and water flow sensors.

In the above solution, further optionally, the cloud platform includes a policy generation rule module, an adaptive telemetry policy pool module, and a telemetry adaptation module; the policy generation rule module includes preset policy generation rules, and the adaptive telemetry pool The latest telemetry strategy of each measurement point is recorded, and the telemetry adaptation module is used to calculate and generate a new strategy.

In the above solution, further optionally, the strategy generation rule module includes: enumerating and sorting the water area factors of each measuring point, and forming a preset strategy generation rule for each target measuring point through normalization processing;

The preset strategy generation rules for forming each target measuring point through normalization processing are specifically: quantitatively describe the degree of each water area factor, the degree is from 1 to 10, 1 means the minimum matching degree, and 10 means matching The degree is the largest, and the matching degree of each water area factor is scored; and the decision weight of each telemetry index is calculated to obtain the weight of each index;

According to the weight of the indicators, the importance of the indicators is classified into three categories: general, important and very important; the weights below 30% are general, those above 30% and below 60% are important, and those above 60% The behavior is very important, and then match the alarm frequency to obtain the second acquisition strategy of the measuring point.

In the above solution, further optionally, the strategy telemetry pool is used to store the collection strategy of each measuring point, and the dedicated collection strategy of each measuring point is recorded and stored in the strategy pool, and the strategy pool includes the Point number, current strategy, decision frequency.

In the above solution, further optionally, the telemetry adaptation module obtains the policy generation rules through the console, and when the cloud platform receives new measurement point collection data, it immediately stores the measurement point collection data in the data warehouse, The telemetry adaptation module obtains new data from the data warehouse, generates exclusive policies corresponding to the measurement points according to the current policy generation rules and calculation rules, and stores them in the policy pool.

In the above solution, further optionally, the sending the second collection strategy to the point-measurement module includes: the cloud platform establishes an https connection with the point-measurement module, and sends the second collection strategy Send to the measuring point module.

In the second aspect, a hydrological telemetry system capable of intelligent maintenance, the system includes:

Measuring point module: used to collect water area data at the location of the measuring point according to the first acquisition strategy, and send the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the The acquisition controller controls a plurality of sensors to collect multiple sets of data of the water area of the measuring point position according to the first acquisition strategy to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; Sending the water area data to the cloud platform includes that the transceiver establishes https to connect to the cloud platform through the mobile communication network, and sends the water area data to the cloud platform; cloud platform module: used to receive the data sent by the measuring point module water area data and judge whether the first acquisition strategy matches the current measuring point acquisition according to the water area data, if not, generate a second acquisition strategy according to the preset policy generation rules and the water area data; The collection strategy is sent to the measuring point module, and the measuring point module collects the water area data of the measuring point according to the second collection rule.

In a third aspect, a computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

The measuring point module collects the water area data of the measuring point position according to the first acquisition strategy, and sends the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller According to the first collection strategy, multiple sensors are controlled to collect multiple sets of data of the water area of the measuring point position to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; the sending of the water area data To the cloud platform includes the transceiver establishing an https connection to the cloud platform through a mobile communication network, and sending the water data to the cloud platform;

Judging whether the first collection strategy matches the current survey point collection according to the water area data, if not, generating a second collection strategy according to the preset strategy generation rules and the water area data;

The callback of the second acquisition strategy is sent to the measuring point module, and the measuring point module collects the water area data of the measuring point according to the second acquisition rule.

In a fourth aspect, a computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the following steps are implemented:

The measuring point module collects the water area data of the measuring point position according to the first acquisition strategy, and sends the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller According to the first collection strategy, multiple sensors are controlled to collect multiple sets of data of the water area of the measuring point position to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; the sending of the water area data To the cloud platform includes the transceiver establishing an https connection to the cloud platform through a mobile communication network, and sending the water area data to the cloud platform; judging whether the first collection strategy matches the current measurement according to the water area data point collection, if not, then generate the second collection strategy according to the preset strategy generation rule and the water area data;

The second collection strategy is sent to the measuring point module, and the measuring point module collects the water area data of the measuring point according to the second collection rule.

The present invention has at least the following beneficial effects:

Based on further analysis and research on the problems in the prior art, the present invention realizes that in the prior art, it is time-consuming and labor-intensive to manually adjust the parameters of the measuring points on site, and it is impossible to adjust the parameters of the measuring points in time during the flood season. The present invention collects the water area data of the position of the measuring point through the measuring point module according to the first acquisition strategy, and sends the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; The acquisition controller controls a plurality of sensors to collect multiple sets of data of the water area of the measuring point position according to the first acquisition strategy to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; Sending the water area data to the cloud platform includes that the transceiver establishes an https connection to the cloud platform through a mobile communication network, and sends the water area data to the cloud platform; judging whether the first acquisition strategy is based on the water area data Match the current measuring point collection, if not, generate a second collection strategy according to the preset strategy generation rule and the water area data; send the second collection strategy to the measuring point module, and the measuring point module according to the The second collection rule collects the water area data at the location of the measuring point.

Through the solution of the present invention, the operation and maintenance personnel of hydrological telemetry do not have to go to each site for parameter adjustment without equipment failure, and realize remote control and remote parameter adjustment of hydrological telemetry equipment, communication status, and key operating information, which significantly improves hydrological The remote control, operation and maintenance efficiency and intelligence of telemetry equipment minimize the manpower and time costs of hydrological adjustment parameters and operation and maintenance. Reverse intervention of real-time hydrological telemetry data to achieve the purpose of real-time optimization of telemetry strategy, so that telemetry can not only collect remote measurement point data, but also automatically adjust the telemetry plan for reasonable control, so as to achieve more efficient monitoring purposes and make telemetry data More instant, effective, and more valuable.

Description of drawings

Fig. 1 is a schematic flow chart of an intelligently maintained hydrological telemetry method provided by an embodiment of the present invention;

Fig. 2 is a traditional hydrological telemetry center control system topology diagram provided by an embodiment of the present invention;

Fig. 3 is a topological diagram of the hydrological telemetry center control system provided by an embodiment of the present invention;

Fig. 4 is a sequence diagram of data interaction of a traditional hydrological telemetry system provided by an embodiment of the present invention;

Fig. 5 is a sequence diagram of data interaction of the hydrological telemetry system provided by an embodiment of the present invention;

Fig. 6 is the http direction control communication model provided by one embodiment of the present invention;

Figure 7 is an internal block diagram of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

The intelligent maintenance hydrological telemetry method provided by this application, as shown in Figure 1, includes the following steps:

The measuring point module collects the water area data of the measuring point position according to the first acquisition strategy, and sends the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller According to the first collection strategy, multiple sensors are controlled to collect multiple sets of data of the water area of the measuring point position to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; the sending of the water area data To the cloud platform includes the transceiver establishing an HTTPS connection to the cloud platform through a mobile communication network, and sending the water data to the cloud platform;

Judging whether the first collection strategy matches the current survey point collection according to the waters data and cloud platform policy rules, if not, then generating a second collection strategy according to the preset strategy generation rules and the waters data; wherein, the first collection The strategy and the second acquisition strategy are the original strategy and the optimized new strategy, and the replacement of the strategy is a continuous iterative process.

The second collection strategy is sent to the measuring point module, and the measuring point module collects the water area data of the measuring point according to the second collection rule.

In one embodiment, the measuring point module collects the water area data of the measuring point position according to the first acquisition strategy, and sends the water area data to the cloud platform, including:

The transceiver uses 4G mobile communication to access the Internet, adopts multi-mode communication equipment, and ensures the reliability of network communication by simultaneously accessing multiple operators;

The acquisition controller is used to drive the transceiver and the plurality of sensors, and is used to deploy the first acquisition strategy and the second acquisition strategy; the acquisition controller is equipped with a flash memory chip for storing software parameter;

The multiple sensors are used to collect different indicator data through the sensor protocol and API, wherein the multiple sensors include a water temperature sensor, a water level sensor, a water quality sensor, a water pressure sensor and a water flow sensor.

In one embodiment, the cloud platform includes a policy generation rule module, an adaptive telemetry policy pool module, and a telemetry adaptation module; the policy generation rule module includes preset policy generation rules, and the adaptive telemetry pool records each measurement The telemetry policy of the point, the telemetry adaptation module is used to calculate and generate a new policy.

In one embodiment, the strategy generating rule module includes: enumerating and sorting the water area factors of each measuring point, and forming a preset strategy generating rule for each target measuring point through normalization processing;

The preset strategy generation rules for forming each target measuring point through normalization processing are specifically: quantitatively describe the degree of each water area factor, the degree is from 1 to 10, 1 means the minimum matching degree, and 10 means matching The degree is the largest, and the matching degree of each water area factor is scored; and the decision weight of each telemetry index is calculated to obtain the weight of each index;

According to the weight of the indicators, the importance of the indicators is classified into three categories: general, important and very important; the weights below 30% are general, those above 30% and below 60% are important, and those above 60% The behavior is very important, and then match the alarm frequency to obtain the second acquisition strategy of the measuring point. Wherein, the weight is adjustable, and the importance of indicators can be classified according to user requirements, and the user is an operation and maintenance personnel of hydrological telemetry.

In one embodiment, the strategy telemetry pool is used to store the acquisition strategy of each measuring point, and the exclusive acquisition strategy of each measuring point is recorded and stored in the strategy pool respectively, and the strategy pool includes the number of each measuring point, Current strategy, decision frequency.

In one embodiment, the telemetry adaptation module acquires policy generation rules through the console, and when the cloud platform receives new measurement point collection data, the telemetry adaptation module acquires new data from the database, according to the current The strategy generation rules and calculation rules generate exclusive strategies corresponding to the measurement points and store them in the strategy pool.

In one embodiment, the sending the second collection strategy to the point measurement module includes: the cloud platform establishes an https connection with the point measurement module, and sends the second collection strategy to the point measurement module. The measurement point module.

In one embodiment, it includes: several aspects of hardware model, communication protocol and cloud platform. The intelligent maintenance of the hydrological telemetry system is realized by deploying measuring points with two-way communication capabilities on the hardware model, deploying two-way communication protocols on the communication side, and deploying conventional response capabilities and adaptive decision-making capabilities on the cloud platform.

In one embodiment, in the telemetry network topology, the measurement points are composed of transceiver modules, collection controllers and various sensors. Each component includes at least but not limited to the following functions:

Transceiver module: use 4G mobile communication to access the Internet, use multi-mode communication equipment, and ensure the reliability of network communication through simultaneous access to multi-operator solutions, such as simultaneous access to China Unicom and China Mobile networks, when establishing communication , according to the strength of the signal, select a stronger mobile network access.

Acquisition controller: It is the core control device of the measurement point, capable of driving transceiver modules and sensors, and capable of strategy deployment. On the acquisition controller, it is equipped with a flash memory chip with a certain capacity, which is used to store various software parameters. The acquisition controller can not only write the policy into the flash memory chip, but also read the telemetry policy issued by the cloud platform from the flash memory chip, control the sensor to sample indicators at the right time, and control the transceiver module to send data to the cloud at the right time platform.

Various types of sensors: through the sensor protocol and API, deploy relevant secondary development software on the acquisition controller to perform various simultaneous access, thereby realizing the acquisition function of various indicators.

In one embodiment, the hardware model includes: introducing a flash memory chip on the acquisition controller for storing and reading and writing various parameters. Furthermore, using SLC particles, that is, Single-Level Cell, that is, a single-layer storage unit, a unit space (cell) can store 1 bit of data, that is, 1 bit/cell, and the theoretical erasing and writing times of a single particle are more than 100,000 times. For low-frequency water conservancy collection scenarios, the use of this particle does not need to consider the problem of functional failure caused by too many reads and writes.

Further, on the realization of acquisition controller, hardware of the present invention adopts ARM single-chip microcomputer to realize, and ARM single-chip microcomputer adopts novel 32-bit ARM core processor, makes it all exceed in order system, bus structure, debugging technology, power consumption and cost performance etc. The traditional 51 series single-chip microcomputer is replaced, and at the same time, the ARM single-chip microcomputer integrates a large number of on-chip and external devices inside the chip, so the function and reliability are greatly improved. It can be conveniently programmed through the single-chip microcomputer to realize functions such as collection control, sending and receiving control, strategy reading and writing deployment of the collection controller.

In one embodiment, in terms of communication protocol: https protocol+domain name is adopted, https is a secure version of http protocol, the transmission process is encrypted by SSL mode, and data security is guaranteed; domain name is used instead of IP, converted through DNS To achieve the purpose of directing the server IP, so that when the server needs to be relocated or the IP address is changed, as long as the corresponding relationship between the domain name and the new server IP is registered on the DNS server, as long as the domain name remains unchanged, the measuring point can still correctly transfer the data Delivered to the server, and instant messaging with the server.

In one embodiment, on the protocol model, a reverse control parameter adjustment mechanism is applied to realize the function of remote measurement point control parameter adjustment. When it is necessary to adjust the parameters of the measurement points, it is only necessary to reversely issue the telemetry strategy to achieve remote parameter adjustment.

In one embodiment, the model of the http protocol implements reverse control in the following manner: the http protocol is generally called a connectionless protocol, but it is not that there is no connection, but that the client and the server do not maintain a long connection, and the server can only Passively waiting to be connected, only the client can actively initiate a connection to the server, and the server cannot actively connect to the client. When the client needs to report data, the client will initiate an http request. When the server receives the request, it has established a connection with the client at this time, and then the server will respond to the connection request, and then disconnect the connection.

In one embodiment, further, when the http response is made, the telemetry strategy is brought back to the measuring point as ancillary data, and the hardware on the measuring point has been developed through programming to realize the parsing function of the telemetry strategy, so that when the measuring point receives When reporting the telemetry policy carried by the http response of the request, the policy is parsed and deployed, thereby achieving the purpose of reverse control.

In one embodiment, the present invention applies telemetry strategy to real-time decision-making, and provides an implementation method, so that the measurement point strategy is no longer static, but is adjusted in real time according to the actual measurement point environment, so as to achieve the purpose of self-adaptation, so that the measurement point strategy The monitoring behavior is more targeted and the reported data is more effective.

In one embodiment, the method for implementing real-time decision-making of telemetry policies is to deploy policy generation rules, adaptive telemetry policy pools, and telemetry AI adaptation modules on the basis of traditional functional modules. The strategy generation rules are responsible for describing the principles of strategy generation, the adaptive telemetry pool is used to record the personalized telemetry strategy of each measurement point, and the telemetry AI adaptation module is used to calculate and generate new strategies.

In one embodiment, policy generation rules: responsible for describing the principles of policy generation and performing quantitative descriptions. The steps for policy generation rules are as follows:

Furthermore, in order to quantify the strategy, weights are introduced, and the factors to be considered for each measuring point are listed and sorted, and given according to the importance of each pair, and the generation rules of the measuring points are formed through normalization processing;

Further, through normalization processing, the measurement point telemetry strategy generation rule table is obtained;

Further, quantify the degree of each factor, from 1 to 10, 1 means the smallest degree of matching, and 10 means the highest degree of matching. In this way, the degree of matching of each factor is scored.

Further, calculate the decision weight of each telemetry indicator;

Further, the normalization process is performed again to obtain the weight of each index;

Further, under the current rules, the importance ranking of several telemetry indicators;

Furthermore, the importance of indicators is classified according to the weight, which is divided into three categories: general, important and very important. Less than 30% is general, more than 30% and less than 60% is important, and more than 60% is very important, and then matched with the alarm frequency to form a telemetry strategy for the measurement point.

In one embodiment, the strategy telemetry pool is used to store the telemetry strategy of each measurement point, based on the individual characteristics of each measurement point factor, the exclusive telemetry strategy of each measurement point is recorded and stored in the strategy pool, The strategy pool includes at least but not limited to the number of measurement points, the current strategy, and the frequency of decision-making.

In one embodiment, for the telemetry adaptation module, the system administrator enters the telemetry generation rules through the console, and when the cloud platform receives new point telemetry data, the cloud platform will notify the telemetry adaptation module to receive the new data, and the telemetry The adaptation module will obtain new data from the database. According to the above-mentioned strategy, no matter whether the data triggers an over-limit alarm, the module will generate a dedicated strategy for the corresponding measurement point according to the current strategy generation rules and the above calculation rules, and Stored in the policy pool, the cloud platform will bring it back to the measuring point when replying the http response to the reported http connection, and the measuring point will deploy and execute the new telemetry strategy.

In one embodiment, collection and reporting functions are separated. The collected data can be intensively sampled through the application of the telemetry strategy. First, the sampled data is uniformly cached on the flash memory card. When a certain amount is accumulated, the data is compressed and reported uniformly.

In one embodiment, as shown in Figure 2 and Figure 3, under the guidance of the previous fixed strategy, each measuring point collects and reports data according to the set method and frequency, as long as there is no manual intervention, the data will always be maintained. How and how often to measure. For example, if a measuring point monitors the water level, the system presets an alarm threshold. When there are frequent alarms and limit violations at this measuring point, it may indicate the occurrence of abnormal conditions in the surrounding area. Usually, the collection frequency of water level telemetry is collected with a low-frequency strategy unless there are special circumstances. If it is in the flood season, it may be within a day. If the water level rises, it may exceed the warning value, so this low-frequency reporting mechanism is no longer applicable due to the high delay. Only by increasing the sampling frequency of the measuring point can it adapt to the rapid change of the water level. At this time, when there are a large number of measurement points that require different strategies to deal with various situations, the strategy of manual remote intervention is also insufficient. Therefore, intelligent maintenance and self-adaptation of strategies are even more important.

In one embodiment, the problem that the adjustment parameters of the measurement point must be manually operated on site and the problem that the telemetry scheme cannot be automatically optimized are solved.

In order to achieve the above purpose, the technical solution adopted in this embodiment: build a telemetry network topology model, deploy measuring points with two-way communication capabilities through hardware, deploy two-way communication protocols in communication, and deploy conventional response capabilities and adaptive decision-making capabilities in cloud platforms network topology model.

The traditional telemetry network topology model, as shown in Figure 2, consists of measurement points, the Internet, firewalls, cloud servers, and data warehouses. Each measuring point is responsible for the collection and reporting of various on-site indicators, and the Internet is used as the carrier of remote communication; the firewall is used for communication security; the cloud server is used to respond to the reporting request of the measuring point and handle various telemetry services; the data warehouse is responsible for storing telemetry reports data.

In the present invention, a method for deploying two-way communication measuring points is given. The network topology is shown in Figure 2. In the present invention, the measuring points are composed of transceiver modules, acquisition controllers and various sensors. The functions of each component include but are not limited to the following:

Transceiver module: use 4G mobile communication to connect to the Internet. Generally, it is enough to connect to a mobile operator. In some important measurement points, in order to ensure the reliability of communication, as shown in the figure, it is recommended to use multi-mode communication equipment. The reliability of network communication is ensured through simultaneous redundant access to multiple operators, such as simultaneous access to China Unicom and China Mobile networks. When establishing communication, select a stronger mobile network access according to the strength of the signal.

Acquisition controller: It is the core control device of the measurement point, capable of driving transceiver modules and sensors, and capable of strategy deployment. On the acquisition controller, it is equipped with a flash memory chip with a certain capacity, which is used to store various software parameters. The acquisition controller can not only write the policy into the flash memory chip, but also read the telemetry policy issued by the cloud platform from the flash memory chip, control the sensor to sample indicators at the right time, and control the transceiver module to send data to the cloud at the right time platform.

The traditional telemetry reporting module mostly adopts the single reporting mode, collects according to fixed frequency and parameters, and collects and reports immediately. When encountering network failures, reporting failures often result in data loss. In the present invention, the collection and reporting functions can be separated through policy control.

The collected data can be intensively sampled through the application of the telemetry strategy. First, the sampled data is uniformly cached on the flash memory card. When a certain amount is accumulated, the data is compressed and reported uniformly. In this way, the sampling rate can be increased and the bandwidth can be largely saved.

Various sensors: With the development of sensor technology, there are many types of water conservancy-related sensors to choose from on the market, not only can collect conventional indicators such as water temperature, water level, flow rate, but also new sensors that can measure water quality, such as Measure the hardness of water, the content of Ca, measure whether heavy metals exceed the standard, such as measuring the molar concentration of Hg, etc. These sensors have been developed relatively mature, and they all have mature protocols and APIs. By deploying relevant secondary development software on the acquisition controller, they can be connected at the same time conveniently, so that the acquisition functions of various indicators can be realized.

Further, hardware model optimization:

In terms of hardware, the traditional acquisition module solidifies the control program and response parameters on the EEPROM. Since the EEPROM is a programmable read-only memory, it is impossible to write data in the running process. In the present invention, a flash memory chip is introduced into the acquisition controller for storing and reading and writing various parameters. The core component of flash memory is flash memory particles. The present invention adopts SLC particles, Single-Level Cell single-layer storage unit, a unit space (cell) can store 1bit data, that is, 1bit/cell, and the number of erasing and writing of a single particle is more than 100,000 times theoretically. In the collection scene, using this particle does not need to consider the problem of functional failure caused by too many reads and writes.

In the realization of acquisition controller, the traditional acquisition hardware mostly adopts 51 series single-chip microcomputers to realize, and the hardware of the present invention adopts ARM single-chip microcomputers to realize, and ARM single-chip microcomputer has adopted novel 32-bit ARM core processors, so that it can be used in command system, bus structure, debugging technology , Power consumption and cost performance have surpassed the traditional 51 series single-chip microcomputer, and at the same time, the ARM single-chip microcomputer integrates a large number of on-chip and external devices inside the chip, so the function and reliability are greatly improved. It can be conveniently programmed through the single-chip microcomputer to realize functions such as collection control, sending and receiving control, strategy reading and writing deployment of the collection controller.

In terms of communication protocol, traditional telemetry is mostly realized by http protocol + server IP, so there are two problems. If http protocol is used directly, the data is not encrypted in the transmission link, which is prone to data security problems; directly using IP address, When the server is relocated or the IP is adjusted, all measurement points will not be able to report data. In the present invention, the mode of https protocol+domain name is adopted, https is a safe version of http protocol, the transmission process adopts SSL mode to encrypt, and data security is guaranteed; domain name is used instead of IP, and DNS conversion is used to achieve directional server IP Purpose, so that when the server needs to be relocated or the IP address needs to be changed, as long as the corresponding relationship between the domain name and the new server IP is registered on the DNS server, as long as the domain name remains unchanged, the measuring point can still correctly deliver the data to the server, and the server to communicate.

In terms of the protocol model, traditional telemetry mostly adopts a single reporting mode, which means that data is reported to the server in one direction, and the server completes an interaction when it receives the data. Although this method realizes the basic function of telemetry data reporting, it has great limitations. In the present invention, the reporting communication protocol is improved, a reverse control parameter adjustment mechanism is introduced, and the function of remote measuring point control parameter adjustment is realized. When it is necessary to adjust the parameters of the measurement points, it is only necessary to reversely issue the telemetry strategy to achieve remote parameter adjustment.

In the reverse control sequence diagram, the traditional telemetry method mainly implements the data reporting function, and does not further process whether the reporting is successful. The present invention adopts the reverse control mode, as shown in Fig. 6, the present invention cleverly utilizes the model of the http protocol to realize the reverse control.

Further, the reverse control method of the https protocol model is as follows: the https protocol is usually called a connectionless protocol, but it is not that there is no connection, but that the client and the server do not maintain a long connection, and the server can only passively wait to be connected , only the client can actively initiate a connection to the server, and the server cannot actively connect to the client. When the client needs to report data, the client will initiate an HTTPS request. When the server receives the request, it has established a connection with the client at this time, and then the server will respond to the connection request and then disconnect the connection. In general, the https response is mostly used to indicate the status of the connection. In fact, more data can be carried in the https response. Therefore, the present invention takes advantage of this feature to bring back the telemetry policy as auxiliary data to the https response. Measuring point, the hardware on the measuring point has realized the parsing function of the telemetry strategy through programming development, so that when the measuring point receives the telemetry strategy carried by the report request https response, it will analyze and deploy the strategy, thereby achieving reverse control the goal of.

In terms of cloud platforms, traditional cloud platforms generally mainly complete data collection, with the purpose of data collection, storage, monitoring and basic query. On this basis, the present invention introduces the concept of real-time decision-making of telemetry strategy, and provides an implementation method, so that the measurement point strategy is no longer static, but adjusted in real time according to the actual measurement point environment, so as to achieve the purpose of self-adaptation, so that the measurement point The monitoring behavior of the point is more targeted, and the reported data is more effective. The implemented solution is to deploy policy generation rules, adaptive telemetry policy pool and telemetry adaptation module on the basis of traditional functional modules. The strategy generation rules are responsible for describing the principles of strategy generation, the adaptive telemetry pool is used to record the personalized telemetry strategy of each measurement point, and the telemetry adaptation module is used to calculate and generate new strategies.

The strategy generation steps of the present invention:

Strategy generation rules: Responsible for describing the principles of strategy generation and making quantitative descriptions. In different periods and environments, the focus of telemetry indicators is different. For example, more attention is paid to changes in water levels during rainy or flood seasons, and changes in water quality are more concerned when there are many factories around.

Furthermore, in order to quantify the strategy, the concept of weight is introduced, the factors to be considered for each measurement point are listed and sorted, and given according to the importance of each pair, and the generation rules of the measurement points are formed through normalization processing.

Further, through normalization processing, the measuring point telemetry strategy schedule rule table is obtained.

In the present invention, the degree of each factor is quantified and described, the degree is from 1 to 10, 1 means the minimum matching degree, 10 means the largest matching degree, for example, during the non-flood season, the degree of "in the flood season" is 1, and the degree is close to the flood season It can be 5, and the degree is 10 when the flood season arrives. In this way, the matching degree of each factor is scored. For example: the score of a measuring point is as follows: in flood season = 10; river width = 5; surrounding factories = 1; at this time, the decision weight of each telemetry index is calculated: water level = 10*10/16+5*5/16+1* 3/16=9.000; flow rate=10*5/16+5*10/16+1*3/16=6.437; water quality=10*1/16+5*1/16+1*10/16=1.6625;

Further, the normalization process is performed again to obtain the weight of each index: water level=9/(9+6.3475+1.6625)*100%=0.526*100%=52.6%; flow rate=6.375/(9+6.3475+1.6625)*100 %=0.375*100%=37.4%; water quality=1.6625/(9+6.3475+1.6625)*100%=0.09*100%=9%.

Furthermore, under the current rules, the order of importance of several telemetry indicators is water level > flow rate > water quality. Further, the present invention classifies the index importance according to the weight, and divides them into three categories: general, important and very important. Less than 30% is general, more than 30% and less than 60% is important, and more than 60% is very important, and then matched with the alarm frequency, the telemetry strategy for the measurement point can be formed.

Policy telemetry pool, used to store the telemetry policy for each point. In traditional telemetry, the reporting frequency of the telemetry equipment and the parameters of the sensors are set at the factory. If adjustments are required, the on-site maintenance personnel generally complete the parameter adjustment work on site. The policy will not be stored on the cloud platform. In the present invention, a telemetry strategy pool is introduced. Based on the individual characteristics of each measurement point factor, the exclusive telemetry strategy of each measurement point is recorded and stored in the strategy pool.

In the telemetry adaptation module, the system administrator enters the telemetry generation rules through the console, as shown in the above table. When the cloud platform receives new point telemetry data, the cloud platform will notify the telemetry AI adaptation module to receive the new data, and the telemetry AI adaptation module will obtain new data from the database. When a threshold violation alarm is triggered, the module will generate a dedicated policy corresponding to the measurement point according to the current policy generation rules and the above calculation rules, and store it in the policy pool, and the cloud platform will bring it back to the measurement point when it replies to the http response to the reported http connection. Point, by which the new telemetry policy is deployed and enforced.

In one embodiment, the following preparatory work needs to be performed before the measurement point collection:

With reverse deployed https communication protocol, policy generation rules, adaptive telemetry policy pool and telemetry AI adaptation module, the description is as follows:

(1) HTTPS communication protocol with reverse deployment

HTTPS is essentially a secure version of HTTP, so the HTTP protocol is used for description. It is enough to establish an HTTPS connection when establishing communication. In this way, the data is encrypted based on the SSL connection during the communication process, ensuring data security.

In the http protocol, there are two methods of reporting parameters: get and post. On the one hand, the amount of data that post can carry is higher than that of get. On the other hand, binary transmission is used, which strengthens the security of data transmission to a certain extent. Therefore, using post mode. In terms of data encapsulation, the text-based JSON format is adopted, which is simple in structure, strong in maintainability, and easy to read.

(2) The interface is as follows:

https://cloud platform domain name:port/interface/getTelemetryData.php

(3) Reporting method: POST

Input parameters: {"measuring point name": "", "measuring point location": "", "measuring point type": "", "reported data": "", "current strategy": "", .. .}

Return data: {"measurement point name": "", "whether to update the strategy": "", "new strategy": "", ...}

(4) Policy generation rules

Investigate and list the consideration factors of each measuring point, and calibrate according to the method of 1 to 10 points of importance from low to high, for example:

weight\factor in flood season channel width Peripheral factories water level 10 5 3 flow rate 5 10 3 water quality 1 1 10

(5) Adaptive telemetry policy pool

Organize all the measurement points, register in the strategy pool, and deploy the default strategy, as shown in the table:

(6) Generate acquisition strategy

(7) The order of importance of several telemetry indicators is water level > flow velocity > water quality.

(8) Form a new strategy.

(9) With the progress of the telemetry business, the AI module performs adaptive and intelligent management on the strategy of each measuring point, and automatically adjusts and updates the strategy. Decision-making frequency refers to the telemetry frequency of the highest frequency item in the telemetry strategy of the same measuring point. In actual use, different sensors of each measuring point can be controlled to report time-sharing according to the strategy, or they can be reported uniformly according to the decision-making frequency. The data obtained according to the time-sharing report is more effective, and the implementation logic requirements for the cloud platform software and the measurement point acquisition controller are higher; according to the unified reporting method of decision-making frequency, the implementation logic requirements for the cloud platform software and the measurement point acquisition controller are higher. Low, easier to implement, but there will be redundant data reporting based on policy solutions, and the specific method needs to be adopted according to the actual situation.

The timing steps for implementation are as follows:

According to the currently deployed telemetry strategy, the acquisition controller records the time, and when the data acquisition time is reached, the acquisition controller controls to send data acquisition instructions to the sensor;

The sensor receives the collection instruction, collects and obtains the corresponding data;

(3) The IP and port of the acquisition controller calibration data are sent to the cloud platform;

(4) Utilize the transceiver module to establish an https connection and report data through the mobile communication network, and wait for a reply;

(5) The cloud platform receives the reported data;

(6) The cloud platform notifies the policy AI module that there is new data to report;

(7) The strategic AI module acquires real-time data;

(8) The strategy AI module analyzes and calculates the real-time data according to the strategy generation rules to generate a new telemetry strategy, or when the collection strategy is manually intervened, the telemetry strategy can be manually set or modified on the cloud platform, such as setting the collection of a certain sensor frequency and give reasons for manual intervention;

(9) The strategy AI module pushes the new telemetry strategy to the adaptive telemetry strategy pool to cover the corresponding old strategy;

(10) The policy AI module notifies the cloud platform that the policy is ready;

(11) The cloud platform obtains the new telemetry strategy of the measuring point from the adaptive telemetry strategy pool;

(12) The HTTPS connection established by the corresponding measuring point on the cloud platform, and carries a new telemetry strategy;

(13) The measuring point transceiver module receives the feedback from the cloud platform and obtains a new telemetry strategy for the measuring point;

(14) The measuring point transceiver module stores the strategy in its own flash memory card and notifies the acquisition control module;

(15) the acquisition control module reads the new strategy in the flash memory card and executes the new strategy;

From the overall framework, the present invention adopts an intelligent maintenance telemetry system based on the Internet of Things, which mainly includes sensors, acquisition controllers, transceiver modules, cloud platforms, data warehouses, telemetry strategy pools, strategy AI, and consoles to form a telemetry system to realize software Hardware two-way data interaction has achieved the purpose of remote control acquisition strategy or intelligent modification of acquisition strategy.

The realization of the present invention enables the operation and maintenance personnel of hydrological telemetry to realize the remote control and remote parameter adjustment of hydrological telemetry equipment, communication status, and key operating information without having to go to each site for parameter adjustment without equipment failure, which significantly improves hydrological telemetry The remote control, operation and maintenance efficiency and intelligence of the equipment minimize the manpower and time costs of hydrological adjustment parameters and operation and maintenance. Reverse intervention of real-time hydrological telemetry data to achieve the purpose of real-time optimization of telemetry strategy, so that telemetry can not only collect remote measurement point data, but also automatically adjust the telemetry plan for reasonable control, so as to achieve more efficient monitoring purposes and make telemetry data More instant, effective, and more valuable.

But the function of the present invention is not limited thereto. On the one hand, with the development of single-chip microcomputer technology, the sampling data can be preprocessed on the hydrological acquisition controller, such as denoising, simple statistics, etc., to reduce the computing pressure of the cloud platform; On the one hand, the present invention adopts the instant communication method, so that the sensor can be turned on when it needs to collect data, send and receive data, and then be in a standby state in the waiting state, which is a low-power communication strategy. Point usage has more obvious advantages.

It should be understood that although the various steps in the flow chart of FIG. 1 are displayed sequentially as indicated by the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in FIG. 1 may include multiple steps or stages, these steps or stages are not necessarily executed at the same moment, but may be executed at different moments, and the execution sequence of these steps or stages is also It is not necessarily performed sequentially, but may be performed alternately or alternately with other steps or at least a part of steps or stages in other steps.

In one embodiment, an intelligently maintainable hydrological telemetry system is provided, comprising the following program modules: wherein:

Measuring point module: used to collect water area data at the location of the measuring point according to the first acquisition strategy, and send the water area data to the cloud platform; wherein, the measuring point module includes a transceiver, an acquisition controller and a plurality of sensors; the The acquisition controller controls a plurality of sensors to collect multiple sets of data of the water area of the measuring point position according to the first acquisition strategy to generate the water area data of the measuring point position; wherein, the water area data includes multiple sets of data collected by a plurality of sensors; Sending the water area data to the cloud platform includes that the transceiver establishes https to connect to the cloud platform through the mobile communication network, and sends the water area data to the cloud platform;

Cloud platform module: used to receive the water area data sent by the measuring point module and judge whether the first acquisition strategy matches the current measuring point acquisition according to the water area data, if not, generate rules and the water area according to the preset strategy The data generates a second collection strategy; used to send the second collection strategy to the measuring point module, and the measuring point module collects water area data at the location of the measuring point according to the second collection rule.

For specific limitations on the intelligently maintainable hydrological telemetry system, please refer to the above-mentioned limitations on the intelligently maintainable hydrological telemetry method, which will not be repeated here. Each module in the above-mentioned intelligently maintainable hydrological telemetering system can be fully or partially realized by software, hardware and combinations thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, and can also be stored in the memory of the computer device in the form of software, so that the processor can invoke and execute the corresponding operations of the above-mentioned modules.

In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure may be as shown in FIG. 7 . The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected by a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, an operator network, NFC (Near Field Communication) or other technologies. When the computer program is executed by the processor, a method for intelligently maintaining hydrological telemetry is realized. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device may be a touch layer covered on the display screen, or a button, a trackball or a touch pad provided on the computer device shell , and can also be an external keyboard, touchpad, or mouse.

Those skilled in the art can understand that the structure shown in Figure 7 is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation to the computer equipment on which the solution of this application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, and a computer program is stored in the memory, which relates to all or part of the processes in the methods of the above embodiments.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, relating to all or part of the procedures in the methods of the above-mentioned embodiments.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above-mentioned embodiments can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any references to memory, storage, database or other media used in the various embodiments provided in the present application may include at least one of non-volatile memory and volatile memory. The non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory or optical memory, and the like. Volatile memory may include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above-mentioned embodiments only represent several implementation modes of the present application, and the description thereof is relatively specific and detailed, but it should not be construed as limiting the scope of the patent for the invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the scope of protection of the patent application should be based on the appended claims.

Claims (10)

1. An intelligent maintainable hydrological telemetry method, the method comprising:

the measuring point module collects measuring point position water area data according to a first collecting strategy and sends the water area data to the cloud platform; the measuring point module comprises a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller controls the plurality of sensors to acquire a plurality of groups of data of the measuring point position water area according to a first acquisition strategy to generate measuring point position water area data; wherein the water area data comprises a plurality of groups of data acquired by a plurality of sensors; the step of sending the water area data to a cloud platform comprises the steps that the transceiver establishes https connection with the cloud platform through a mobile communication network, and sends the water area data to the cloud platform;

Judging whether the first acquisition strategy is matched with current measuring point acquisition according to the water area data, and if not, generating a second acquisition strategy according to a preset strategy generation rule and the water area data;

and the second acquisition strategy is sent to the measuring point module, and the measuring point module acquires the measuring point position water area data according to the second acquisition rule.

2. The method of claim 1, wherein the survey point module collects survey point location water data according to a first collection strategy and transmits the water data to a cloud platform, comprising:

the transceiver is accessed to the Internet in a 4G mobile communication mode, multimode communication equipment is adopted, and the reliability of network communication is ensured by simultaneously accessing to a scheme of multiple operators;

the acquisition controller is used for driving the transceiver and the plurality of sensors and deploying the first acquisition strategy and the second acquisition strategy; the acquisition controller is provided with a flash memory chip for storing software parameters;

the plurality of sensors are used for acquiring different index data through protocols and APIs of the sensors, wherein the plurality of sensors comprise a water temperature sensor, a water level sensor, a water quality sensor, a water pressure sensor and a water flow sensor.

3. The method of claim 1, wherein the cloud platform comprises a policy generation rules module, an adaptive telemetry policy pool module, and a telemetry adaptation module; the strategy generation rule module comprises preset strategy generation rules, the self-adaptive telemetry pool records telemetry strategies of all measuring points, and the telemetry adaptation module is used for calculating and generating new strategies.

4. The method of claim 3, wherein the policy generation rule module comprises: enumerating and sequencing the water area factors of each measuring point, and forming a preset strategy generation rule of each target measuring point through normalization processing;

the preset strategy generation rule of each target measuring point is formed through normalization processing, specifically: quantitatively describing the degree reached by each water area factor, wherein the degree is 1 to 10,1 represents the minimum matching degree, 10 represents the maximum matching degree, and scoring the matching degree of each water area factor; the decision weight of each telemetry index is calculated, and each index weight is obtained;

classifying the index importance according to the index weight into three categories of general importance and very important importance; the weight lower than 30% is general, the weight higher than 30% and lower than 60% is important and the weight higher than 60% is very important, and the alarm frequency is matched, so that a second acquisition strategy of the measuring point is obtained.

5. The method of claim 4, wherein the policy telemetry pool is used for storing the acquisition policy of each measuring point, and the dedicated acquisition policy of each measuring point is respectively recorded and stored in the policy pool, and the policy pool comprises the number of each measuring point, the current policy and the decision frequency.

6. The method of claim 5, wherein the telemetry adaptation module obtains policy generation rules through a console, and when the cloud platform receives new measurement point acquisition data, the telemetry adaptation module obtains new data from a database, generates a dedicated policy corresponding to the measurement point according to the current policy generation rules and calculation rules, and stores the dedicated policy into a policy pool.

7. The method of claim 1, wherein the sending the second acquisition strategy to the station module comprises: and the cloud platform establishes https connection with the measuring point module and sends the second acquisition strategy to the measuring point module.

8. An intelligent maintainable hydrological telemetry system, the system comprising:

and a measuring point module: the cloud platform is used for acquiring the water area data of the measuring point position according to the first acquisition strategy and transmitting the water area data to the cloud platform; the measuring point module comprises a transceiver, an acquisition controller and a plurality of sensors; the acquisition controller controls the plurality of sensors to acquire a plurality of groups of data of the measuring point position water area according to a first acquisition strategy to generate measuring point position water area data; wherein the water area data comprises a plurality of groups of data acquired by a plurality of sensors; the step of sending the water area data to a cloud platform comprises the step of establishing https connection with the cloud platform through a mobile communication network by the transceiver and sending the water area data to the cloud platform; cloud platform module: the water area data acquisition module is used for receiving the water area data sent by the measuring point module, judging whether the first acquisition strategy is matched with the current measuring point acquisition according to the water area data, and if not, generating a second acquisition strategy according to a preset strategy generation rule and the water area data; and the measuring point module is used for acquiring the measuring point position water area data according to the second acquisition rule.

9. A computer device comprising a memory and a processor, the memory storing a computer program and site cache data, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium having stored thereon a computer program and site cache data, characterized in that the computer program when executed by a processor implements the steps of the method of any of claims 1 to 7.