CN116794726A - Geological seepage early warning method, system and medium - Google Patents

Abstract

The application aims to provide a geological seepage early warning method, a geological seepage early warning system and a geological seepage early warning medium, wherein the node of the Internet of things where a sensor is located is initialized at the end of the sensor based on the energy storage voltage of the sensor; monitoring a pre-warning signal of geological seepage at the position of the sensor; after the early warning signal is detected, the early warning signal and the identity information of the node of the Internet of things are sent to a data processing end in a broadcast mode, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information. Therefore, the geological seepage early warning function can be realized based on environmental change, the operation process is simple, the required equipment is few, and the energy is saved and the efficiency is high.

Description

Geological seepage early warning method, system and medium

Technical Field

The application relates to the field of computers, in particular to a geological seepage early warning method, a geological seepage early warning system and a geological seepage early warning medium.

Background

For geological disaster hidden trouble points, the geological disaster hidden trouble points are limited by expenses, most underground conditions are not surveyed, and the property, scale and development change of the geological disaster hidden trouble points are difficult to accurately grasp. The situation of preventing and controlling the geological disasters is still severe. The natural resource department has developed geological disaster monitoring and early warning experiments for 3 years continuously, and by improving the integrated and intelligent level and the risk early warning capability of geological disaster monitoring technical equipment, the special group combined monitoring and early warning coverage of geological disasters is enlarged, so that the control of geological disasters in China is promoted to accelerate the realization of ' civil air defense + ' technical defense '. The geological disaster monitoring equipment has the characteristics of proper precision, simple function, lower power consumption, convenient installation and the like, and the standardized equipment can realize industrialized mass production. However, because the standards of all places are different, the specifications of instruments and equipment of all manufacturers are different, so that the equipment cannot be mixed and cannot be produced in large scale.

Over 80% of geological disasters worldwide are directly or intermittently affected by geological seepage, such as mountain collapse, landslide, debris flow, ground collapse, ground cracks, ground subsidence, and the like. The common property and the cost performance are two elements which are particularly emphasized by the monitoring and early warning equipment. In the aspect of high cost performance, although a plurality of high-precision ground disaster monitoring and early warning devices exist nationwide, some ground disaster monitoring and early warning devices reach the world level, in fact, for the disaster prevention and reduction of wide villages, the aim of avoiding danger can be achieved by only finding out that the hidden trouble points have obvious topography change and evacuating the masses in time. Thus, early warning should be focused on sudden changes in the amount of water in the geological formation, especially monitoring for water penetration.

Disclosure of Invention

The application aims to provide a geological seepage early warning method, a geological seepage early warning system and a geological seepage early warning medium, which solve the problems that ground disaster monitoring early warning equipment is high in cost, high in maintenance cost, inadaptable to complex environments and low in early warning efficiency in the prior art.

According to one aspect of the present application, there is provided a method for geological seepage early warning, applied to a sensor end, the method comprising:

initializing an Internet of things node where a sensor is located based on energy storage voltage of the sensor;

monitoring a pre-warning signal of geological seepage at the position of the sensor;

after the early warning signal is detected, the early warning signal and the identity information of the node of the Internet of things are sent to a data processing end in a broadcast mode, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information.

Optionally, the method comprises:

and serially connecting a plurality of batteries for sensing the ambient humidity to generate sensing signals, and buffering the serially connected voltage energy into a capacitor.

Optionally, before initializing the node of the internet of things where the sensor is located, the energy storage voltage based on the sensor includes:

the capacitor is managed by using a self-powered power management circuit and is connected with the sensor to provide electric energy for the sensor, wherein the self-powered power management circuit comprises an energy sensing unit, a voltage stabilizing unit and a switching unit.

Optionally, initializing an internet of things node where the sensor is located based on an energy storage voltage of the sensor includes:

and judging whether the voltage of the capacitor is larger than a starting threshold value through the energy sensing unit, if so, initializing the node of the Internet of things where the sensor is located after receiving a conduction signal sent by the switch unit, and receiving the power supply voltage of the voltage stabilizing unit.

Optionally, the method for monitoring the early warning signal of geological seepage at the position of the sensor comprises the following steps:

determining a reduced voltage signal of the sensor based on a change in the ambient humidity in which the sensor is located;

and generating an early warning signal of geological seepage at the position based on the reduced voltage signal, and activating the node of the Internet of things when a signal interception gateway in the sensor detects the early warning signal.

Optionally, determining the reduced voltage signal of the sensor based on the change in the ambient humidity in which the sensor is located includes:

outputting a varying electrical signal based on a variation in ambient humidity when the sensor is immersed in water, wherein the sensor comprises a plurality of batteries connected in series to sense ambient humidity to generate a sensing signal;

and comparing the changed electric signal with a voltage comparison reference value, and determining a falling voltage signal of the sensor according to a comparison result.

Optionally, the method comprises:

and packaging the early warning signals into data packets and then sending the data packets to an application program of the mobile terminal, so that the application program can carry out identity authentication and verification on the data packets, and displaying the early warning signals in the data packets after the verification is successful.

According to another aspect of the present application, there is also provided a method for geological seepage early warning, applied to a data processing end, the method comprising:

receiving broadcast data detected by a sensor, wherein the broadcast data comprises an early warning signal of geological seepage determined by the sensor and identity information of an Internet of things node where the sensor is located;

and carrying out identity recognition on the broadcast data, determining the position of the sensor when the identification is passed, and generating alarm information for issuing.

According to another aspect of the application, there is also provided a system for geological seepage early warning, the system comprising a sensor end and a data processing end; wherein,,

the sensor end is used for initializing an Internet of things node where the sensor is located based on the energy storage voltage of the sensor, monitoring an early warning signal of geological seepage at the position where the sensor is located, and sending the early warning signal and identity information of the Internet of things node to the data processing end in a broadcasting mode after the early warning signal is monitored;

the data processing end is used for receiving the broadcast data detected by the sensor end, carrying out identity recognition on the broadcast data, determining the position of the sensor when the identification is passed, and generating alarm information for issuing.

According to yet another aspect of the present application there is also provided a computer readable medium having stored thereon computer readable instructions executable by a processor to implement a method as described above.

Compared with the prior art, the method and the device initialize the node of the Internet of things where the sensor is located based on the energy storage voltage of the sensor at the sensor end; monitoring a pre-warning signal of geological seepage at the position of the sensor; after the early warning signal is detected, the early warning signal and the identity information of the node of the Internet of things are sent to a data processing end in a broadcast mode, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information. Therefore, the geological seepage early warning function can be realized based on environmental change, the operation process is simple, the required equipment is few, and the energy is saved and the efficiency is high.

Drawings

Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:

FIG. 1 is a flow chart of a method for providing a geological seepage warning according to an aspect of the present application;

FIG. 2 is a schematic diagram of a self-powered power management circuit according to an embodiment of the application;

FIG. 3 is a flow chart of a method for geological seepage early warning according to another aspect of the present application;

FIG. 4 is a schematic diagram of a system for geological seepage early warning according to yet another aspect of the present application;

FIG. 5 is a schematic flow chart of a method for geological seepage early warning at a sensor end according to an embodiment of the application;

FIG. 6 is a schematic flow chart of a method for geological seepage early warning by a data processing end according to an embodiment of the application;

FIG. 7 is a schematic diagram of using a geological early warning method in a real scene in an embodiment of the application.

The same or similar reference numbers in the drawings refer to the same or similar parts.

Detailed Description

The application is described in further detail below with reference to the accompanying drawings.

In one exemplary configuration of the application, the terminal, the device of the service network, and the trusted party each include one or more processors (e.g., central processing units (Central Processing Unit, CPU)), input/output interfaces, network interfaces, and memory.

The Memory may include non-volatile Memory in a computer readable medium, random access Memory (Random Access Memory, RAM) and/or non-volatile Memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase-Change RAM (PRAM), static random access Memory (Static Random Access Memory, SRAM), dynamic random access Memory (Dynamic Random Access Memory, DRAM), other types of Random Access Memory (RAM), read-Only Memory (ROM), electrically erasable programmable read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), flash Memory or other Memory technology, read-Only optical disk read-Only Memory (Compact Disc Read-Only Memory, CD-ROM), digital versatile disks (Digital Versatile Disk, DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by the computing device. Computer readable media, as defined herein, does not include non-transitory computer readable media (transmission media), such as modulated data signals and carrier waves.

Fig. 1 is a schematic flow chart of a geological seepage early warning method provided according to an aspect of the present application, applied to a sensor end, the method includes: step S11 to step S13, wherein step S11 is performed, and the node of the Internet of things where the sensor is located is initialized based on the energy storage voltage of the sensor; step S12, monitoring a geological seepage early warning signal at the position of the sensor; and step S13, after the early warning signal is detected, the early warning signal and the identity information of the node of the Internet of things are sent to a data processing end in a broadcast mode, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information. Therefore, the geological seepage early warning function can be realized based on environmental change, the operation process is simple, the required equipment is few, and the energy is saved and the efficiency is high.

Specifically, in step S11, initializing an internet of things node where a sensor is located based on an energy storage voltage of the sensor; here, adopt the sensor to gather environmental change, the electric energy of this sensor adopts the storage voltage mode, designs the power with the front end of sensor, for this sensor self-power, can reach the requirement of long-term use in the field. The sensor is connected into the Internet of things, an early warning system is built through the Internet of things, when the environment where each sensor is collected is changed, whether the energy storage voltage of the sensor can be subjected to subsequent signal collection or not is judged, if the energy storage voltage of the sensor cannot be subjected to subsequent signal collection, the sensor is self-powered, if the energy storage voltage of the sensor cannot be subjected to subsequent signal collection, the node of the Internet of things where the sensor is located is initialized, the node of the Internet of things is used after being activated subsequently, and geological seepage conditions at the node are analyzed conveniently.

Specifically, in step S12, an early warning signal of geological seepage at the position where the sensor is located is monitored; the sensor is used for collecting environmental changes, and when the environmental changes cause the values of the sensor to change, an early warning signal is generated, and the early warning signal is timely detected and is processed and analyzed by the data processing end. Next, in step S13, after the early warning signal is detected, the early warning signal and the identity information of the node of the internet of things are sent to the data processing end in a broadcast manner, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information. The data processing end comprises an edge node end, a cloud server and other equipment ends with data processing functions, after an early warning signal is detected in a sensor network, the identity information of the node of the Internet of things where the sensor is located and the early warning signal are packaged according to a preset flow and a wireless data packet carrying the early warning information is sent, the data packet is sent in a broadcasting mode, broadcasting data of the data packet are obtained, and accordingly the broadcasting data are analyzed after the data processing end receives the data packet, the early warning signal and the position of the node are analyzed, and early warning is carried out in time.

In this embodiment of the application, the data processing end uses a cloud computing platform as an example, and may construct a sensor network for a sensor, and may be divided into three layers: self-powered sensing equipment, a signal interception gateway and a cloud computing platform; the self-powered sensing equipment can be deployed in a scene with frequent geological seepage, and the equipment of the Internet of things is quickly awakened to send an early warning signal when the seepage occurs; the signal interception gateway is used for intercepting an early warning signal in a larger area and comprehensively forwarding the early warning signal, the identity information of the sensor node and the like to the cloud computing platform; and after receiving the data forwarding of the interception gateway of each area, the cloud computing platform can comprehensively analyze by means of big data, machine learning and the like, so that corresponding environment changes are obtained, and the geological seepage early warning function is realized.

In one embodiment of the application, the method comprises the following steps: and serially connecting a plurality of batteries for sensing the ambient humidity to generate sensing signals, and buffering the serially connected voltage energy into a capacitor. Here, in order to meet the requirement of long-term use in the field, a certain amount of electric energy needs to be provided inside to maintain normal working consumption while the geological seepage early warning function is realized, including use for sensing, anomaly identification, wireless transmission and the like. For this purpose, the system is powered in a self-powered manner in the present application, which includes a battery made of a suitable electrode material that is capable of sensing a change in voltage in ambient humidity, and the absorption of the ambient liquid by the electrode material generates a sensing signal based on which self-powering in a self-powered power management circuit is achieved. In a preferred embodiment of the present application, the battery is a bacterial cellulose composite silk fibroin ion gel zinc air battery, which can absorb the liquid in the environment to generate the induction signal, and is integrated with a programmable internet of things (IoT) platform to obtain a geological seepage early warning system, in the portable system, a plurality of bacterial cellulose composite silk fibroin ion gel zinc air batteries are connected in series as a front-end circuit to provide energy, such as ten batteries are connected in series; the energy of the power supply is buffered into a capacitor. Whenever the capacitor accumulates a lot of energy, i.e. the voltage of the capacitor reaches a certain threshold, the subsequent circuit is turned on to be ready to perform a predetermined IoT task. The system has extremely low static power consumption, and the design ensures the long-term use requirement in remote areas. In the specific battery manufacturing process, bacterial cellulose aerogel is placed in a beaker, the filtered silk fibroin ion conductor solution is added into the beaker and sealed, so that the solution gradually permeates into a bacterial cellulose aerogel network to obtain bacterial cellulose composite silk fibroin ion conductor precursor gel, the conductor precursor gel is treated to obtain bacterial cellulose composite silk fibroin ion conductor gel, and the bacterial cellulose composite silk fibroin ion conductor gel is used as electrolyte to manufacture the battery. The battery has environmental sensitivity, and the voltage of the battery can be reduced along with the rise of relative humidity; the response accuracy of the battery to humidity reaches 5% RH. The voltage of the bacterial cellulose composite silk protein ion gel zinc-air battery prepared by the embodiment of the application is 1.2V to 1.5V, and the bacterial cellulose composite silk protein ion gel zinc-air battery can stably work for more than 1 month. Compared with lithium batteries and the like, the energy-saving and flame-retardant lithium battery has the characteristics of biological safety, high flexibility, flame retardance and long-term stability, so that a plurality of batteries can be connected in series to serve as a power supply to supply energy for the whole early warning system.

In an embodiment of the present application, before the sensor-based energy storage voltage initializes the node of the internet of things where the sensor is located, a self-powered power management circuit is used to manage the capacitor, andthe self-powered power management circuit is connected with the sensor and provides electric energy for the sensor, wherein the self-powered power management circuit comprises an energy sensing unit, a voltage stabilizing unit and a switching unit. The application designs a self-powered power management circuit, which mainly comprises an energy sensing unit, a voltage stabilizing unit and a switching unit, wherein the energy sensing unit is used for monitoring the electric energy level in the current system in real time. The specific means for monitoring the power level is to monitor the voltage across the capacitor. According to the formula It can be known that: when the capacitance value of the capacitor is kept unchanged, the available energy of the Internet of things system in one switching cycle can be controlled by adjusting the starting voltage threshold and the closing voltage threshold of the energy sensing unit.

Fig. 2 shows a schematic diagram of a self-powered power management circuit in an embodiment of the present application, wherein a graph a is that an open-circuit voltage of a bacterial cellulose composite silk protein ion gel zinc-air battery at different temperatures is kept stable, and the voltage stability of the battery can be known from the graph a; and the graph B shows that the open-circuit voltage change of the same battery placed at room temperature is basically stable and unchanged, and the battery can be placed for a long time. Panel C shows excellent discharge performance for discharge plateau at different current densities, which is to illustrate that the battery can be stably discharged as a power source. The graph D shows the response of the open circuit voltage to the ambient humidity in five rapid cycles, the battery voltage has a certain response to the ambient humidity, and the battery is also subjected to voltage change when immersed in water, so that the sensor can be used for sensing, and meanwhile, the battery response to the ambient humidity is indicated. The response of the open circuit voltage to humidity during two long cycles is shown in the graph E, which shows that the battery voltage is responsive to ambient humidity and the voltage change is the same and decreases with increasing humidity. The open circuit voltage and weight response changes with ambient humidity, humidity increases, battery weight increases, voltage decreases, indicating that the response to the environment is primarily related to the moisture in the environment.

In the above embodiment, the energy sensing unit is configured to determine whether the capacitor voltage is greater than a starting threshold, if yes, initialize an internet of things node where the sensor is located after receiving a conducting signal sent by the switch unit, and receive a supply voltage of the voltage stabilizing unit. When enough energy is accumulated in the energy storage capacitor, after a preset starting threshold is reached, an energy sensing unit sends a conducting signal to the switch unit, the node of the internet of things is initialized and then connected into the system, the voltage stabilizing unit provides stable power supply voltage for the node of the internet of things until the energy in the energy storage capacitor is consumed, the voltage is reduced to a closing threshold, and the energy sensing unit disconnects the system of the internet of things through the switch unit and stops providing electric energy for the system of the internet of things. The starting threshold value can be designed selectively according to different chips, for example, a singlechip chip produced by company A has a power supply voltage of 1.7-3.6V, a singlechip chip produced by company B has a power supply voltage of 5V, and different starting threshold values of different chips are designed.

In one embodiment of the present application, in step S12, a reduced voltage signal of the sensor is determined based on a change in the ambient humidity in which the sensor is located; and generating an early warning signal of geological seepage at the position based on the reduced voltage signal, and activating the node of the Internet of things when a signal interception gateway in the sensor detects the early warning signal. The sensor is an environment sensor, when the environment humidity changes, the sensor can acquire corresponding changes, when the environment humidity changes obviously, for example, the humidity increases more, the voltage at the sensor end can drop, a drop voltage signal is output, if the output voltage of the sensor at a certain position drops, the drop voltage signal is obtained, the existence of seepage is considered, an early warning signal is generated, and therefore, the Internet of things node can be activated rapidly after the signal interception gateway in the sensor detects the early warning signal.

With the above embodiment, when the sensor is immersed in water, a changing electric signal is output based on the change of the ambient humidity, wherein the sensor comprises a plurality of batteries connected in series to sense the ambient humidity and generate a sensing signal; and comparing the changed electric signal with a voltage comparison reference value, and determining a falling voltage signal of the sensor according to a comparison result. In the embodiment of the application, the sensor is an environmental sensor for sensing environmental changes, in the portable wireless system, several (such as three) batteries are used for environmental sensing in series and are simultaneously connected with the front-end circuit in series, and a plurality of (such as ten) batteries for sensing environmental humidity to generate sensing signals are connected in series in the front-end circuit, wherein the batteries for sensing the environmental humidity to generate sensing signals can be made of bacterial cellulose composite silk fibroin ion gel zinc air; in the front-end circuit, ten bacterial cellulose composite silk protein ion gel zinc air batteries are used as power sources in series to provide energy for the whole system. The bacterial cellulose composite silk protein ion gel zinc air battery has the characteristic of environmental sensitivity, and when the environmental humidity changes, the electric signal output attribute of the material can change correspondingly. Connected to it is a low power comparator unit and provided with a voltage comparison reference value by the microcontroller. When the sensor is in a normal state, the output voltage level of the sensor is higher than the threshold value of the comparator, and the system does not react to the sensor; when the sensor is in a flooded condition, its output voltage level drops suddenly, crossing the comparator threshold. The voltage change of the bacterial cellulose composite silk protein ion gel zinc air battery as the sensor is captured by the comparator and then sent into the microcontroller for further processing. The sensing of the external environment is realized by sensing of three batteries in series and an internally integrated low-power comparator. An environmental sensor is integrated in the unit to sense different environmental information. Through the optimal design, the system can provide remote water seepage alarm in unattended field environment or underground mine, and can identify and display the position coordinates of water seepage alarm in real time in mobile phone application program.

In some embodiments of the present application, the early warning signal is packaged into a data packet and then sent to an application program of the mobile terminal, so that the application program performs identity authentication and verification on the data packet, and displays the early warning signal in the data packet after the verification is successful. In this case, at the signal interception gateway layer, the wireless data packets emitted by the self-powered sensor device can be intercepted by means of an application program (APP) or a hosting application (e.g. applet) of the mobile terminal. The APP or the applet can perform the functions of data packet identity authentication, information verification, original data display and the like, and can be used for deploying and maintaining debugging terminals of personnel; related data can also be directly presented as a user interface in a small-scale deployment scenario. And the cloud platform performs data visualization after uniformly receiving the data forwarded by the signal interception gateway layer, and visually displays the normal/early warning state. According to the embodiment of the application, the design of the interactive interface can be carried out according to the user requirements on the basis of information transmission, so that the user can reasonably set parameters and open programs of the equipment according to the local environment and requirements, and the application scene of the application is greatly expanded.

Fig. 3 is a schematic flow chart of a method for geological seepage early warning according to another aspect of the present application, which is applied to a data processing end, and the method includes: step S21 and step S22, wherein in step S21, broadcast data detected by a sensor end are received, wherein the broadcast data comprise early warning signals of geological seepage determined by the sensor end and identity information of an Internet of things node where the sensor is located; and S22, carrying out identity recognition on the broadcast data, determining the position of the sensor when the identification is passed, and generating alarm information for issuing. The data processing end can be an edge node, a cloud server, a computing platform and the like, after receiving broadcast data, the broadcast data is analyzed, the broadcast data is an early warning signal of geological seepage at a position determined by the sensor end and identity information of the node, and further the position of the sensor, namely the position of a seepage event, is obtained by identifying the broadcast data, early warning is issued at the moment, and related personnel are informed of the processing.

FIG. 4 is a schematic structural diagram of a system for geological seepage early warning according to still another aspect of the present application, which includes a sensor end 100 and a data processing end 200; the sensor end 100 is configured to initialize an internet of things node where the sensor is located based on an energy storage voltage of the sensor, perform an early warning signal of geological seepage where the sensor is located, and send the early warning signal and identity information of the internet of things node to a data processing end in a broadcast manner after the early warning signal is detected; the data processing end 200 is configured to receive the broadcast data detected by the sensor end, identify the broadcast data, determine the location of the sensor when the identification is passed, and generate alarm information for issuing. In the geological seepage early warning method of the application, as shown in fig. 5, the sensor end firstly checks the energy storage voltage, when the energy storage voltage is larger than the starting threshold value, the initialization of the node of the internet of things is carried out, the initialized node of the internet of things enters dormancy to wait for the triggering of the sensor event, namely, the sensor detects the early warning signal, the node of the internet of things is triggered to activate, and the early warning signal and the identity information are transmitted in a broadcasting mode. As shown in fig. 6, at the edge node end or the cloud service end, whether new broadcast data exist is monitored, identity recognition is performed after the new broadcast data are monitored, if yes, the broadcast data are uploaded to the cloud end, and therefore the position where the early warning signal is located is analyzed and confirmed, and alarm information is issued. And discarding the received broadcast data when the identification fails. The method is based on an advanced ultra-low power consumption energy sensing and management system, and is used for collecting energy from a self-powered power supply and enabling a low-power consumption signal transmitter to transmit a wireless data packet with a specific identity mark; after being intercepted by an edge computing node deployed in a nearby environment, the data packet can analyze the functions of identity identification of a transmitter, position confirmation, event analysis and the like. Finally, a plurality of (such as three) batteries are connected in series to serve as sensing of the seepage early warning system, a plurality of (such as ten) batteries are connected in series to serve as self-powered power supply of the seepage early warning system, after sensing is immersed in water, the electric signal of the sensing device can be rapidly reduced, and the signal is visualized to a user terminal in a forecast mode through a plurality of or single transmission modes such as a wired network, a 5.8G wireless network, a 4/5G network, an operator network and the like, so that the early warning effect is achieved at the early stage of seepage.

As shown in FIG. 7, A represents the real-time positioning and water seepage monitoring provided by the mobile terminal application program by displaying the real-time photos of four geological seepage early warning systems distributed at different positions; b represents that the geological seepage early warning system is in a normal state; c represents that the geological seepage early warning system is immersed in water and is in an alarm state.

In addition, in one embodiment of the application, a preparation method of the bacterial cellulose composite silk fibroin ion gel zinc air battery is provided, which can be composed of an electrolyte base layer composed of silk fibroin gel, anode plates, cathode plates and the like arranged on two opposite sides of the electrolyte base layer. Wherein the anode plate is made of graphite; the cathode plate is made of zinc foil. The electrolyte base layer is used for sensing the external humidity and generating a voltage signal reaction.

Among them, silk protein gel can be prepared by bacterial cellulose aerogel and silk protein solution with electric conductivity, and the preparation method is briefly described by the following examples:

step one: soaking the bacterial cellulose sheet in a NaOH aqueous solution with the concentration of 2wt% at 95 ℃ for 2 hours to remove acetobacter xylinum and other impurities, and repeatedly washing the bacterial cellulose sheet with deionized water for a plurality of times to be neutral (the pH is approximately equal to 7) to obtain a bacterial cellulose expansion sheet;

step two: and (3) putting the bacterial cellulose expansion sheet into liquid nitrogen for freezing, and then putting the bacterial cellulose expansion sheet into a freeze dryer for three days to obtain the bacterial cellulose aerogel.

Step three: to be soluble financial salts, e.g. CaCl ₂ Dissolving in solvent such as formic acid solvent according to preset mass ratio to obtain salt solution, adding degummed silk fiber into the salt solution to obtain silk fibroin salt solution, and filtering with gauze to remove impurities, wherein degummed silk fiber can be placed in a regular stack or an irregular stack or dispersed bulk; the mass ratio of the solvent to the soluble metal salt is 20:1-50:1. The mass ratio of the degummed silk fiber to the soluble metal salt is 2:1-5:1.

Step four: the silk protein gel is placed in a container.

Step five: adding the silk fibroin solution into the container, immersing the silk fibroin gel, and sealing the silk fibroin gel, so that the silk fibroin solution is immersed in the silk fibroin gel for 24 hours;

step six: the silk fibroin ion conductor precursor gel is laid in a mould according to a preset volume to form volatile liquid, wherein the size of the mould can be preferably 20cm by 30cm by 1.5cm (length by width by height).

Step seven: and (3) placing the volatile liquid in a ventilation environment with the relative humidity of 60-90% RH for self-crosslinking for 48 hours to remove the formic acid solvent, so as to obtain the silk fibroin gel, and taking the silk fibroin gel as the silk fibroin gel.

It should be noted that the above steps are only illustrative, and in practical application, other parameters or other substances may be adopted, so that the prepared silk protein gel can be used for sensing humidity in an external environment and generating a voltage signal reaction after being used as an electrolyte layer to manufacture a bacterial cellulose composite silk protein ion gel zinc-air battery, and specific details or limitations are not described herein.

In addition, the embodiment of the application also provides a computer readable medium, wherein computer readable instructions are stored on the computer readable medium, and the computer readable instructions can be executed by a processor to realize the geological seepage early warning method.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

It should be noted that the present application may be implemented in software and/or a combination of software and hardware, e.g., using Application Specific Integrated Circuits (ASIC), a general purpose computer or any other similar hardware device. In one embodiment, the software program of the present application may be executed by a processor to perform the steps or functions described above. Likewise, the software programs of the present application (including associated data structures) may be stored on a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. In addition, some steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.

Furthermore, portions of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application by way of operation of the computer. Program instructions for invoking the inventive methods may be stored in fixed or removable recording media and/or transmitted via a data stream in a broadcast or other signal bearing medium and/or stored within a working memory of a computer device operating according to the program instructions. An embodiment according to the application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to operate a method and/or a solution according to the embodiments of the application as described above.

It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. The terms first, second, etc. are used to denote a name, but not any particular order.

Claims (10)

1. A method for geological seepage early warning, which is applied to a sensor end, and is characterized in that the method comprises the following steps:

initializing an Internet of things node where a sensor is located based on energy storage voltage of the sensor;

monitoring a pre-warning signal of geological seepage at the position of the sensor;

after the early warning signal is detected, the early warning signal and the identity information of the node of the Internet of things are sent to a data processing end in a broadcast mode, so that the data processing end confirms the alarm information of geological seepage based on the received broadcast data and issues the alarm information.

2. The method according to claim 1, characterized in that the method comprises:

and serially connecting a plurality of batteries for sensing the ambient humidity to generate sensing signals, and buffering the serially connected voltage energy into a capacitor.

3. The method of claim 1, wherein before initializing the internet of things node at which the sensor is located based on the sensor stored energy voltage, comprising:

the capacitor is managed by using a self-powered power management circuit and is connected with the sensor to provide electric energy for the sensor, wherein the self-powered power management circuit comprises an energy sensing unit, a voltage stabilizing unit and a switching unit.

4. The method of claim 3, wherein initializing the internet of things node at which the sensor is located based on the stored energy voltage of the sensor comprises:

and judging whether the voltage of the capacitor is larger than a starting threshold value through the energy sensing unit, if so, initializing the node of the Internet of things where the sensor is located after receiving a conduction signal sent by the switch unit, and receiving the power supply voltage of the voltage stabilizing unit.

5. The method of claim 1, wherein the act of monitoring the pre-warning signal for geological seepage at the location of the sensor comprises:

determining a reduced voltage signal of the sensor based on a change in the ambient humidity in which the sensor is located;

and generating an early warning signal of geological seepage at the position based on the reduced voltage signal, and activating the node of the Internet of things when a signal interception gateway in the sensor detects the early warning signal.

6. The method of claim 5, wherein determining the sensor's reduced voltage signal based on the change in ambient humidity in which the sensor is located comprises:

outputting a varying electrical signal based on a variation in ambient humidity when the sensor is immersed in water, wherein the sensor comprises a plurality of batteries connected in series to sense ambient humidity to generate a sensing signal;

and comparing the changed electric signal with a voltage comparison reference value, and determining a falling voltage signal of the sensor according to a comparison result.

7. The method according to claim 1, characterized in that the method comprises:

and packaging the early warning signals into data packets and then sending the data packets to an application program of the mobile terminal, so that the application program can carry out identity authentication and verification on the data packets, and displaying the early warning signals in the data packets after the verification is successful.

8. A method for geological seepage early warning, which is applied to a data processing end, and is characterized in that the method comprises the following steps:

receiving broadcast data detected by a sensor, wherein the broadcast data comprises an early warning signal of geological seepage determined by the sensor and identity information of an Internet of things node where the sensor is located;

and carrying out identity recognition on the broadcast data, determining the position of the sensor when the identification is passed, and generating alarm information for issuing.

9. The geological seepage early warning system is characterized by comprising a sensor end and a data processing end; wherein,,

the sensor end is used for initializing an Internet of things node where the sensor is located based on the energy storage voltage of the sensor, monitoring an early warning signal of geological seepage at the position where the sensor is located, and sending the early warning signal and identity information of the Internet of things node to the data processing end in a broadcasting mode after the early warning signal is monitored;

the data processing end is used for receiving the broadcast data detected by the sensor end, carrying out identity recognition on the broadcast data, determining the position of the sensor when the identification is passed, and generating alarm information for issuing.

10. A computer readable medium having stored thereon computer readable instructions executable by a processor to implement the method of any of claims 1 to 8.