CN115054212A - Equipment and method for monitoring risks of underground operators of municipal drainage pipe network - Google Patents

Abstract

The invention discloses a risk monitoring device and a monitoring method for underground operators of an urban drainage pipe network, belonging to the technical field of monitoring devices. The present invention directly feeds back timely signals that can be fed back immediately, such as harmful gas concentration and aperiodic fluctuation biometric indicators, to the operators, so that the operators can take corresponding risk avoidance measures in time without transmitting the signals to the main control platform on the ground. , to avoid the signal transmission delay and attenuation between the pipeline and the ground; for the periodically fluctuating biometric indicators, motion state data and image data of the operating environment, the edge computing module is uploaded to the main control The main control platform analyzes the trend of these data in a period of time, and issues the corresponding trend information to the operator, so that the operator can take corresponding risk avoidance measures. The invention improves the underground operation of the urban drainage pipe network. Accuracy of risk monitoring for personnel.

Description

Equipment and monitoring method for risk monitoring of underground workers in urban drainage network

technical field

The invention belongs to the technical field of monitoring equipment, and more particularly, relates to a wearable device and a monitoring method for risk monitoring of underground workers in an urban drainage pipe network.

Background technique

The drainage pipe network is an important urban infrastructure. At present, the operation and maintenance of the pipe network, whether it is testing, dredging or repairing, is mainly based on manual downhole operations. Problems such as narrow space and poor gas circulation have brought great challenges to the safety risks of operators. Monitoring the concentration of harmful gases in the pipeline and the physiological characteristics of operators can effectively prevent harmful gases from causing damage to workers' health, and it can also facilitate ground operators to carry out rescue in emergencies.

However, the current gas monitoring equipment on the market is bulky and has poor mobility. It cannot follow the real-time movement of workers, and it is impossible to perform individual and accurate safety and physiological monitoring of each individual.

With the continuous development of sensor technology, Internet of Things technology, and edge computing technology, smart wearable devices are developing rapidly. Wearable devices can monitor the gas concentration in the environment and the physiological indicators of the human body by embedding various biosensors, motion sensors, and gas detection sensors. monitoring requirements.

However, since the signal strength in the drainage pipeline is relatively weak, and the signal of obstacles such as silt in the pipeline will also attenuate the signal, which further weakens the signal strength. Wearable devices in the prior art often use Bluetooth, ZigBee and other transmission methods to directly transmit the information collected by the front-end to the back-end platform for data processing, and then give corresponding instructions to the operator, whether the information collected by the front-end is transmitted to the operator. There is a large signal delay in the back-end platform or the corresponding instructions issued by the back-end platform to the operators, and the risk monitoring of the underground operators in the urban drainage network is not accurate enough.

SUMMARY OF THE INVENTION

Aiming at the defects and improvement needs of the prior art, the present invention provides a device and a monitoring method for risk monitoring of underground operators in urban drainage network, the purpose of which is to improve the accuracy of risk monitoring of underground operators in urban drainage network.

In order to achieve the above object, according to an aspect of the present invention, a device for monitoring the risk of underground workers in an urban drainage pipe network is provided, including: a signal acquisition module, an edge computing module, a network communication module and a main control platform, the signal The acquisition module is connected with the edge computing module through the network communication module, and the edge computing module is also connected with the main control platform through the network communication module;

The signal acquisition module is used to collect harmful gas concentration data and image data in the working environment, and also used to collect the periodic fluctuation biometric index, aperiodic fluctuation biometric index and motion state data of the operator;

The edge computing module is used to compare the harmful gas concentration data and the non-periodic fluctuation biometric index with the set safety threshold, and determine whether it is within the set safety threshold range, and if it is not within the set safety threshold Within the range, issue early warning information to the operator; upload the image data, periodic fluctuation biometric index and motion status data to the main control platform;

The main control platform is used to analyze the trend of the image data, the periodic fluctuation biometric index and the motion state data over a period of time, predict the working environment and the safety state of the operator, and issue instructions to the operator according to the prediction result. .

Further, the signal acquisition module includes a harmful gas monitoring unit, a physiological feature monitoring unit, an attitude monitoring unit, and an image acquisition unit;

The harmful gas monitoring unit is used to collect harmful gas concentration data in the working environment;

The physiological characteristic monitoring unit is used to collect the periodic fluctuation biometric index and the non-periodic fluctuation biometric index of the operator;

The attitude monitoring unit is used to collect the movement state data of the operator;

The image acquisition unit is used for acquiring image data in the working environment.

Further, the harmful gas monitoring unit includes a methane sensor, an ammonia gas sensor, a hydrogen sulfide sensor and an oxygen sensor.

Further, the non-periodic fluctuation biometric index includes the body temperature data index and blood oxygen data index of the operator;

The periodically fluctuating biometric indicators include the ECG data indicators and blood pressure data indicators of the operator.

Further, the attitude monitoring unit includes a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetic sensor.

Further, the network communication module includes NB-IoT and 5G networks, the signal acquisition module is connected to the edge computing module through the NB-IoT, and the edge computing module is also connected to the host through the 5G network. Control platform connection.

Further, the signal acquisition module further includes one or more of a positioning unit, a voice interaction unit, an alarm and an illuminator.

Further, the edge computing module is also used to upload the harmful gas concentration data and aperiodic fluctuation biometric indicators to the main control platform, and the main control platform is also used to analyze the harmful gas concentration data and The trend of aperiodically fluctuating biometric indicators over a period of time can predict the working environment and the safety status of workers.

Further, the harmful gas monitoring unit is located outside the left arm of the operator, the posture monitoring unit is located at the waist, the image acquisition unit, the voice interaction unit, the positioning unit, the alarm and the illuminator are integrated into the helmet, and the physiological feature monitoring unit is integrated. Located on the operator's wrist.

According to another aspect of the present invention, a method for risk monitoring of underground operators in an urban drainage network is provided, comprising:

Collect harmful gas concentration data and image data in the working environment, collect periodic fluctuation biometric indicators, non-periodic fluctuation biometric indicators and motion state data of operators;

In the working environment, compare the harmful gas concentration data and the aperiodic fluctuation biometric index with the set safety threshold, and judge whether the harmful gas concentration data and the aperiodic fluctuation biometric index are within the set safety threshold. Within the safety threshold range, if it is not within the set safety threshold range, a warning message will be sent to the operator;

Upload the image data, periodic fluctuation biometric index and motion state data to the outside of the drainage pipe network, analyze the trend of the image data, periodic fluctuation biometric index and motion state data over a period of time, and predict the operating environment and the safety status of the operators, and issue instructions to the operators according to the prediction results.

In general, through the above technical solutions conceived by the present invention, the following beneficial effects can be achieved:

(1) The present invention directly enters the edge computing module with timely signals that can be fed back immediately, such as harmful gas concentration data and non-periodic fluctuation biometric indicators. If the signal strength is not within the set safety threshold range, it directly alarms the operator in real time. , so that the operator can take corresponding risk avoidance measures in time, without the need to transmit the signal to the main control platform on the ground, to avoid the signal delay caused by transmitting the signal to the main control platform outside the pipeline, and the main control platform will send the signal after signal processing The signal delay generated from the command to the pipeline and the attenuation of the round-trip signal by the obstacles in the pipeline; the biometric indicators, motion state data and image data of the working environment for the periodic fluctuation of the operator are uploaded to the main control through the edge computing module. Platform, the main control platform analyzes the trend of these data over a period of time, and sends the corresponding trend information to the operator, so that the operator can take corresponding risk avoidance measures, because the upload to the main control platform is within a period of time The main control platform sends trend information, which is insensitive to signal delay and attenuation, thus improving the accuracy of risk monitoring for underground operators in the urban drainage network.

Description of drawings

1 is a schematic structural diagram of a wearable device for risk monitoring of underground workers in an urban drainage network according to an embodiment of the present invention;

2 is a functional schematic diagram of a wearable device for risk monitoring of underground workers in an urban drainage network according to an embodiment of the present invention;

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

As shown in FIG. 1 , the wearable device provided by the present invention for risk monitoring of underground operators in urban drainage network mainly includes: a signal acquisition module, an edge computing module, a network communication module and a main control platform, and the signal acquisition module passes through the network The communication module is connected with the edge computing module, and the edge computing module is connected with the main control platform through the network communication module.

Among them, the signal acquisition module is used to collect the data of the operator and the working environment, and specifically includes: a harmful gas monitoring unit, a physiological feature monitoring unit, an attitude monitoring unit, an image acquisition unit and a positioning unit;

Harmful gas monitoring unit, used to collect data on the concentration of harmful gases in the operating environment;

The physiological characteristic monitoring unit is used to collect the periodic fluctuation biometric index and aperiodic fluctuation biometric index of the operator;

The attitude monitoring unit is used to collect the movement state data of the operators in the underground well of the urban drainage pipe network;

The image acquisition unit is used to collect image data in the working environment;

The positioning unit is used to collect the position information of the operators in the underground of the urban drainage pipe network;

The edge computing module, which is installed on the tooling of the operator, is used to control the data acquisition and storage of the signal acquisition module, and upload the stored data to the main control platform on the ground; specifically, the harmful gas concentration data collected by the harmful gas monitoring unit is collected. 、Compare the non-periodic fluctuation biometric indicators collected by the physiological characteristic monitoring unit with the set safety threshold range to determine whether the harmful gas concentration data and the non-periodic fluctuation biometric indicators are within the set safety threshold range, if not Within the range of the set safety threshold, an early warning message will be issued to the operator; in addition, the periodic fluctuation biometric index collected by the physiological feature monitoring unit, the motion state data collected by the attitude monitoring unit, and the image data collected by the image collection unit and positioning The positioning data collected by the unit is uploaded to the main control platform. The main control platform predicts the health state of the workers and the safety state of the working environment by analyzing the periodic fluctuation of biometric indicators, motion state data and image data within a period of time. The prediction result judges whether the operator can continue the operation, and sends the corresponding instruction to the operator;

The network communication module is used to realize the communication and data transmission between the harmful gas monitoring unit, the physiological characteristic monitoring unit, the attitude monitoring unit, the image acquisition unit and the positioning unit and the edge computing module, as well as the communication between the edge computing module and the main control platform. communication and data transmission;

The main control platform is set outside the drainage pipe network well, that is, on the ground, and is used for unified management and issuing instructions for the data returned by the edge computing module. Specifically, the main control platform periodically fluctuates over a period of time by analyzing Biometric indicators, motion status data and image data, predict the health status of the workers and the safety status of the working environment, determine whether the workers can continue to work according to the prediction results, and issue corresponding instructions to the workers; for example, through Analyze the movement state data of the workers over a period of time to determine the movement trend of the workers, and judge whether the physiological characteristics of the workers are normal by analyzing the periodic fluctuation data of the workers over a period of time. The image data is collected to judge whether the working environment is safe, such as whether there is a danger source, and then give corresponding instructions and send them to the operators, so that the operators can avoid the corresponding risks. In addition, the data processed and stored by the edge computing module can be uploaded to the main control platform. The main control platform uses different algorithms to analyze different data, classify the corresponding data, and provide data reference for the next operation.

Preferably, the working environment gases collected by the harmful gas monitoring unit include but are not limited to CH ₄ , NH ₄ , H ₂ S, O ₂ , etc., and the sensors used include methane sensors, ammonia sensors, hydrogen sulfide sensors, and oxygen sensors.

The periodic fluctuation biometric indicators in the physiological characteristic monitoring unit include the electrocardiogram data indicators, blood pressure data indicators, etc. of the operator; the non-periodic fluctuation biometric indicators include the operator's body temperature data indicators, blood oxygen data indicators, etc.; specifically, Corresponding biometric indicators are collected by sensors such as ECG sensors, blood pressure sensors, body temperature sensors, and blood oxygen sensors; as an option, in this embodiment, an infrared body temperature sensor and an optical ECG sensor are integrated, and photoplethysmography (PPG) is used. to measure ECG, blood pressure, blood oxygen, and other biometrics.

The attitude monitoring unit collects the movement state data of the operator in the underground of the urban drainage pipe network, including the acceleration, angular velocity and angle of the operator during the movement, and collects the corresponding data through the nine-axis motion sensor. The three-axis gyroscope and three-axis magnetic sensor collect the corresponding acceleration, angular velocity, and angle data.

The image acquisition unit includes a camera for real-time acquisition of image information in the operating environment; preferably, a illuminator; preferably, an alarm, and the edge computing module determines the harmful gas concentration data and aperiodic fluctuation biometric indicators When the set safety threshold is exceeded, warning information is sent to the operator through the alarm device. In this embodiment, the alarm device adopts sound and light alarm device. A wireless communication device may also be included for voice interaction.

The positioning unit adopts GPS positioning; the communication module mainly includes NB-IoT and 5G networks; each unit in the signal acquisition module and the edge computing module are connected through NB-IoT; the edge computing module and the main control platform are electrically connected through 5G network for data transmission.

Specifically, the sensors in each unit of the signal acquisition module are embedded in the work clothes of the operator, wherein the harmful gas monitoring unit is located outside the operator's left forearm, the attitude monitoring unit is located at the waist, and the image acquisition unit, alarm, The wireless communication device, the lighting device and the positioning unit are integrated into the helmet, and the physiological feature monitoring unit is located at the operator's wrist.

Based on the above-mentioned wearable device for risk monitoring of underground workers in urban drainage network, the method for monitoring through the wearable device includes:

The edge computing module is connected with the harmful gas monitoring unit, attitude monitoring unit, image and sound acquisition module, physiological feature monitoring unit and positioning unit through NB-IoT, and the edge computing module and the main control platform are connected through 5G network;

The edge computing module controls the corresponding sensors for data collection and storage. The harmful gas monitoring unit collects the harmful gas concentration in the working environment. After the collected gas concentration signal undergoes a chemical reaction inside the sensor, a weak current that has a linear relationship with the gas concentration is generated. Signal, the corresponding signal is processed and converted into a corresponding voltage value and transmitted to the edge computing module through NB-IoT. The edge computing module compares the corresponding voltage value with the set safety threshold. If the signal strength is not within the set safety threshold If the signal strength is not within the set safety threshold range, it will activate the alarm The alarm will alarm in real time; abnormal concentration information or aperiodically fluctuating biometric index information will be sent to the alarm in the helmet through NB-IoT for alarming;

For the periodic fluctuation biometric index collected by the physiological feature monitoring unit, the motion state data collected by the posture monitoring unit, the image data collected by the image collection unit, and the positioning data collected by the positioning unit, the edge computing module uploads the corresponding data through the network communication module To the main control platform, the main control platform analyzes the periodic fluctuation biometric index, motion state data and image data through the corresponding algorithm, and obtains the trend of the corresponding data indicators of the operator and the working environment, and divides the trend into Different security levels, when the security level indicated by this trend shows that the movement state of the operator is abnormal, the periodic fluctuation of biometric indicators is abnormal, or the work environment is abnormal, the main control platform sends the corresponding command to the operator, and the command information can indicate The operator stops the operation, continues the operation, can continue the operation time or other instructions that can avoid risks, etc.;

In this process, the real-time location information of the operator is obtained through the positioning unit;

Among them, the data collected by the signal acquisition module are all stored in the edge computing module;

It also includes uploading the harmful gas concentration data and aperiodic fluctuation biometric indicators stored in the edge computing module to the main control platform, and the main control platform analyzes the harmful gas concentration, aperiodic Fluctuate biometric indicators, classify the corresponding data, and provide data reference for the next operation.

Also included, the operator makes emergency calls through voice interaction.

As shown in FIG. 2 , according to different equipment and applications, the equipment in the present invention can be divided into an object layer, a perception layer, a network communication layer, an information processing layer, and a decision control layer. Among them, the object layer is the object monitored by the wearable device, including the environment of the pipeline operators and the drainage network; the perception layer is divided into the sensor's perception of the situation of the pipeline workers and the internal environment of the pipeline where they are located, and the workers' perception of the subsequent feedback. Voice interaction and perception of sound and light alarm information; network communication layer refers to data transmission and instruction issuance based on wireless network and 5G signals; information processing layer includes intelligent data analysis and image analysis based on edge computing; decision control layer includes main control Platforms, data monitoring systems and large screens for collaborative command, etc., record, archive, analyze and predict the data information transmitted by the information processing layer, and issue instructions to pipeline operators according to the results of analysis and prediction. In addition, the main control platform can also transmit the analyzed data information to mobile terminals such as mobile phones, and the ground assistance personnel can classify the danger level according to the information received by the mobile terminal, and provide corresponding information instructions to the ground staff, thereby reducing the drainage pipeline. The internal staff will be irreversibly damaged due to the influence of harmful gases and abnormal physical conditions, which is convenient to prevent the safety risks of pipeline operations and to quickly provide rescue decisions in emergency situations.

Among them, in the information processing layer, timely signals that can be fed back immediately (such as the concentration of harmful gases in the operating environment collected by the harmful gas monitoring unit, and the aperiodic fluctuation biometric indicators collected by the physiological feature monitoring unit) will directly enter the edge computing through the sensor. Module, if the signal strength is not within the set safety threshold range, the alarm will be activated directly to give real-time alarm, so that the operator can take corresponding risk avoidance measures in time, without the need to transmit the corresponding signal to the main control platform on the ground to avoid In order to transmit the signal to the main control platform outside the pipeline, the signal delay, the main control platform after signal processing and then send the command to the pipeline, the signal delay and the obstacles in the pipeline to the attenuation of the back and forth signal; for the periodic fluctuation of biometric indicators, The motion state data collected by the attitude monitoring unit and the image data collected by the image collection unit are uploaded to the main control platform through the edge computing module. The main control platform analyzes the trend of these data over a period of time, and issues the corresponding trend information. To the operator, so that the operator can take corresponding risk avoidance measures. Since the data information uploaded to the main control platform is within a period of time, and the main control platform sends trend information, it is not sensitive to signal delay and attenuation. The device and the method improve the accuracy of risk monitoring for underground workers in an urban drainage pipe network.

Those skilled in the art can easily understand that the above are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention, etc., All should be included within the protection scope of the present invention.

Claims (10)

1. The utility model provides an equipment to municipal drainage pipe network borehole operation personnel risk monitoring which characterized in that includes: the edge computing system comprises a signal acquisition module, an edge computing module, a network communication module and a main control platform, wherein the signal acquisition module is connected with the edge computing module through the network communication module, and the edge computing module is also connected with the main control platform through the network communication module;

the signal acquisition module is used for acquiring harmful gas concentration data and image data in a working environment and is also used for acquiring a periodically fluctuating biometric index, an aperiodic fluctuating biometric index and motion state data of an operator;

the edge calculation module is used for comparing the harmful gas concentration data and the aperiodic fluctuating biometric index with a set safety threshold value, judging whether the harmful gas concentration data and the aperiodic fluctuating biometric index are within the range of the set safety threshold value, and if the harmful gas concentration data and the aperiodic fluctuating biometric index are not within the range of the set safety threshold value, sending early warning information to an operator; uploading the image data, the periodic fluctuation biometric index and the motion state data to the main control platform;

the main control platform is used for analyzing the trends of the image data, the periodic fluctuation biometric index and the motion state data in a period of time, predicting the safety state of the operating environment and the operating personnel, and issuing an instruction to the operating personnel according to the prediction result.

2. The apparatus of claim 1, wherein the signal acquisition module comprises a harmful gas monitoring unit, a physiological characteristic monitoring unit, an attitude monitoring unit, an image acquisition unit;

the harmful gas monitoring unit is used for acquiring harmful gas concentration data in the operating environment;

the physiological characteristic monitoring unit is used for acquiring a periodically fluctuating biometric index and an aperiodic fluctuating biometric index of an operator;

the attitude monitoring unit is used for acquiring motion state data of the operating personnel;

the image acquisition unit is used for acquiring image data in the working environment.

3. The apparatus of claim 2, wherein the harmful gas monitoring unit includes a methane sensor, an ammonia sensor, a hydrogen sulfide sensor, and an oxygen sensor.

4. The device of claim 2, wherein the aperiodic, fluctuating biometric marker includes a temperature data marker, a blood oxygen data marker of the practitioner;

the periodic fluctuation biometric index comprises an electrocardiogram data index and a blood pressure data index of an operator.

5. The device of claim 4, wherein the attitude monitoring unit comprises a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetic sensor.

6. The device of claim 1, wherein the network communication module comprises NB-IoT and 5G network, the signal acquisition module is connected to the edge computing module through the NB-IoT, and the edge computing module is further connected to the main control platform through the 5G network.

7. The apparatus of claim 2, wherein the signal acquisition module further comprises one or more of a positioning unit, a voice interaction unit, an alarm, and a luminaire.

8. The apparatus of claim 1, wherein the edge computing module is further configured to upload the harmful gas concentration data and the aperiodic corrugated biometric indicator to the main control platform, and the main control platform is further configured to analyze trends of the harmful gas concentration data and the aperiodic corrugated biometric indicator over a period of time to predict the safety status of the working environment and the working personnel.

9. The device of claim 7, wherein the harmful gas monitoring unit is located outside the left upper arm of the worker, the posture monitoring unit is located at the waist, the image acquisition unit, the voice interaction unit, the positioning unit, the alarm and the illuminator are integrated in the safety helmet, and the physiological characteristic monitoring unit is located at the wrist of the worker.

10. A method for monitoring risks of underground operators of a municipal drainage pipe network is characterized by comprising the following steps:

collecting harmful gas concentration data and image data in a working environment, and collecting a periodic fluctuation biometric index, an aperiodic fluctuation biometric index and motion state data of an operator;

in the working environment, comparing the harmful gas concentration data and the aperiodic fluctuation biometric index with a set safety threshold, judging whether the harmful gas concentration data and the aperiodic fluctuation biometric index are in the set safety threshold range, and if not, sending early warning information to an operator;

uploading the image data, the periodic fluctuation biometric index and the motion state data to the outside of a drainage pipe network well, analyzing the trends of the image data, the periodic fluctuation biometric index and the motion state data in a period of time, predicting the safety state of the operating environment and the operating personnel, and issuing an instruction to the operating personnel according to the prediction result.

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