CN116105802B - Underground facility safety monitoring and early warning method based on Internet of things - Google Patents

Underground facility safety monitoring and early warning method based on Internet of things Download PDF

Info

Publication number
CN116105802B
CN116105802B CN202310382003.5A CN202310382003A CN116105802B CN 116105802 B CN116105802 B CN 116105802B CN 202310382003 A CN202310382003 A CN 202310382003A CN 116105802 B CN116105802 B CN 116105802B
Authority
CN
China
Prior art keywords
equipment
monitoring
environmental
environment
underground
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202310382003.5A
Other languages
Chinese (zh)
Other versions
CN116105802A (en
Inventor
谢永强
刘甲红
华小红
王程
谭嘉辉
马志宏
焦永水
卜青营
范琳琳
李忠兴
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangdong Pulan Geographic Information Service Co ltd
Original Assignee
Guangdong Pulan Geographic Information Service Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangdong Pulan Geographic Information Service Co ltd filed Critical Guangdong Pulan Geographic Information Service Co ltd
Priority to CN202310382003.5A priority Critical patent/CN116105802B/en
Publication of CN116105802A publication Critical patent/CN116105802A/en
Application granted granted Critical
Publication of CN116105802B publication Critical patent/CN116105802B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention relates to the technical field of monitoring, and discloses an underground facility safety monitoring and early warning method based on the Internet of things, which comprises the following steps: step S10, acquiring real-time environment data in an underground infrastructure space; step S20, acquiring equipment key parameters of environment adjusting equipment in the underground infrastructure space; step S30, detecting and judging according to the real-time environment data and the key parameters of the equipment to obtain a real-time judging result; step S40, early warning is carried out according to the judging result; by monitoring the real-time environment data of each position point of the underground infrastructure space, comprehensive analysis and judgment are carried out by comprehensively considering the key parameters of equipment responsible for the environment regulating equipment in the corresponding underground infrastructure space, so that the environmental change in the underground infrastructure space can be more comprehensively pre-warned, the accuracy of detecting the potential safety hazards of the underground infrastructure is improved, and meanwhile, the operation health of related equipment can be monitored and judged, so that the function is comprehensive.

Description

Underground facility safety monitoring and early warning method based on Internet of things
Technical Field
The invention relates to the technical field of monitoring, in particular to an underground facility safety monitoring and early warning method based on the Internet of things.
Background
The underground infrastructure comprises underground civil air defense engineering, a power substation built underground, a water pump room, an underground garage, an underground passage and the like, and compared with the ground building, the underground infrastructure has more potential safety hazards and has more complex treatment process, so that the state of the underground infrastructure needs to be monitored.
However, only a few professionals perform operations in the daily operation of the underground municipal facilities, so that the monitoring system inside the underground municipal facilities can accurately and timely and safely identify the underground environment when accidents occur and when the underground municipal facilities are inspected daily.
The existing early warning method for potential safety hazards of underground municipal facilities mainly comprises the steps of inspection, lack of an intelligent underground municipal facility management platform, difficulty in effectively collecting relevant information, difficulty in finding problems existing in underground municipal facilities in time, and insufficient direct and convenient information reporting ways in the process of finding problems.
Disclosure of Invention
The invention aims to provide an underground facility safety monitoring and early warning method based on the Internet of things, which solves the following technical problems:
how to provide a method for comprehensively and accurately carrying out safety monitoring and early warning on underground infrastructure.
The aim of the invention can be achieved by the following technical scheme:
an underground facility safety monitoring and early warning method based on the Internet of things comprises the following steps:
step S10, acquiring real-time environment data in an underground infrastructure space;
step S20, acquiring equipment key parameters of environment adjusting equipment in the underground infrastructure space;
step S30, detecting and judging according to the real-time environment data and the key parameters of the equipment to obtain a real-time judging result;
and S40, early warning is carried out according to the judging result.
According to the technical scheme, the real-time environment data of each position point of the underground infrastructure space is monitored, the equipment key parameters of the environment adjusting equipment in the corresponding underground infrastructure space are comprehensively considered for comprehensive analysis and judgment, so that the environmental change in the underground infrastructure space can be comprehensively early warned, the accuracy of detecting the potential safety hazards of the underground infrastructure is improved, meanwhile, the operation health of related equipment can be monitored and judged, and the function is comprehensive.
As a further scheme of the invention: before step S10, the method further includes:
step S01, dividing a monitoring area according to the responsible area of the environment adjusting device;
step S02, M groups of environment monitoring sensors are distributed in each monitoring area, and each group of environment monitoring sensors is responsible for N environmental data parameters;
step S03, setting B groups of monitors for monitoring environment-regulating equipment in the underground infrastructure space, wherein each group of monitors is in charge of H equipment key parameters corresponding to the environment-regulating equipment;
wherein M is greater than or equal to 1, N is greater than or equal to 1, B is greater than or equal to 1, and H is greater than or equal to 1.
As a further scheme of the invention: the step S30 includes:
step S301, recording and storing each environmental data parameter X obtained by M groups of the environmental monitoring sensors ij And B group of each device key parameter Y obtained by the monitor ij ；
Step S302, according to each of the environmental data parameters X ij And each of said device key parameters Y ij Calculate the corresponding environmental degradation degree E (X ij ) And device anomaly degree D (Y ij )；
Step S303, according to the environmental degradation E (X ij ) And the device anomaly degree D (Y ij ) Acquiring facility risk assessment value P t ；
The degree of environmental deterioration E (X ij ) The calculation formula of (2) is as follows:
Figure GDA0004247055250000031
the device anomaly degree D (Y ij ) The calculation formula of (2) is as follows:
Figure GDA0004247055250000032
wherein i is E [1, N]，j∈[1，M]，[X ith1 ，X ith2 ]The normal threshold interval corresponding to the ith environmental data parameter item; alpha i Fixed coefficient of the i-th environmental data parameter item, alpha i >1, a step of; k is a power coefficient, and the value of k is related to the category of the corresponding key parameter item of the equipment;
y 0 corresponding i item of equipment key parameter Y representing corresponding environment regulating equipment ij Normal value of y min And y max And respectively corresponding to the upper limit and the lower limit of the key parameters of the equipment when the environment-adjusting equipment is required to be shut down.
As a further scheme of the invention: the step S303 includes:
step S3031, obtaining an average degradation degree of the environmental item corresponding to the environmental data parameter of the ith item
Figure GDA0004247055250000033
Step S3032, obtaining the average anomaly degree of the equipment items corresponding to the key parameters of the equipment in the ith item
Figure GDA0004247055250000034
Step S3033, calculating the facility risk assessment value P according to a preset calculation rule t ；
Average degree of deterioration of the environmental item
Figure GDA0004247055250000035
The calculation formula of (2) is as follows:
Figure GDA0004247055250000041
average anomaly degree of the equipment items
Figure GDA0004247055250000044
The calculation formula of (2) is as follows:
Figure GDA0004247055250000042
the preset calculation rule comprises the following steps:
Figure GDA0004247055250000043
wherein sigma i Dimensionality reduction coefficient corresponding to the ith environmental parameter monitoring item, tau i And (5) the dimensionality removing coefficient corresponding to the key parameter item of the ith equipment.
As a further scheme of the invention: the step S30 further includes:
step S304, according to the obtained facility risk evaluation value P t Early warning judgment is carried out;
the early warning judgment comprises the following steps:
the facility risk assessment value P t Comparing with a preset threshold value:
if P t ＞P bo And judging that the safety risk exists in the underground infrastructure space.
As a further scheme of the invention: the step S30 further includes:
step S305, if it is determined that there is a security risk, determining a risk location point according to the sensing parameters of each group of the environmental monitoring sensors and the monitors and the corresponding spatial locations.
As a further scheme of the invention: the method for acquiring the risk location point comprises the following steps:
step S3051, for the monitoring area, obtaining an environmental degradation degree E (X) corresponding to the environmental monitoring sensor and the monitor ij ) And device anomaly degree D (Y ij )；
Step S3052, dividing the environmental degradation E (X) ij ) And device anomaly degree D (Y ij ) Respectively descending order to obtain E c (X ij ) And D c (Y ij ) C is descending order;
step S3053, judge E 1 (X ij ) And D 1 (Y ij ) If the association is corresponding, the step S3054 is entered if the association is corresponding, otherwise the step S3055 is entered;
step S3054, judging E 1 (X ij ) And E is connected with 2 (X ij ) If the corresponding monitoring areas are adjacent, E is determined to be the same 1 (X ij ) The corresponding monitoring area is defined as the risk position point, otherwise, the step S3055 is carried out;
step S3055, E 1 (X ij ) And D 1 (Y ij ) And respectively comparing the detected areas with the historical normal environment degradation degree and the historical normal equipment anomaly degree of the corresponding detected areas, and determining the detected area corresponding to the item with the larger comparison difference as the risk position point.
As a further scheme of the invention: further comprises:
and step S50, the early warning result is sent to the manager terminal.
The invention has the beneficial effects that: according to the invention, through monitoring the real-time environment data of each position point of the underground infrastructure space, comprehensive analysis and judgment are performed by comprehensively considering the equipment key parameters of the environment adjusting equipment in the corresponding underground infrastructure space, so that the environmental change in the underground infrastructure space can be more comprehensively pre-warned, the accuracy of detecting the potential safety hazards of the underground infrastructure is improved, and meanwhile, the operation health of related equipment can be monitored and judged, so that the function is comprehensive.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a schematic diagram of a basic flow of the method for monitoring and early warning of underground facilities safety.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention discloses an underground facility safety monitoring and early warning method based on the internet of things, which comprises the following steps:
step S10, acquiring real-time environment data in an underground infrastructure space;
step S20, acquiring equipment key parameters of environment adjusting equipment in the underground infrastructure space;
step S30, detecting and judging according to the real-time environment data and the key parameters of the equipment to obtain a real-time judging result;
and S40, early warning is carried out according to the judging result.
Through the technical scheme, the real-time environment data of each position point of the underground infrastructure space is monitored, the equipment key parameters of the environment adjusting equipment in the corresponding underground infrastructure space are comprehensively considered for comprehensive analysis and judgment, and then the environmental change in the underground infrastructure space can be comprehensively early-warned, the accuracy of detecting the potential safety hazards of the underground infrastructure is improved, meanwhile, the operation health of related equipment can be monitored and judged, and the function is comprehensive.
As a further scheme of the invention: before step S10, the method further includes:
step S01, dividing a monitoring area according to the responsible area of the environment adjusting device;
step S02, M groups of environment monitoring sensors are distributed in each monitoring area, and each group of environment monitoring sensors is responsible for N environmental data parameters;
step S03, setting B groups of monitors for monitoring environment-regulating equipment in the underground infrastructure space, wherein each group of monitors is in charge of H equipment key parameters corresponding to the environment-regulating equipment;
wherein M is greater than or equal to 1, N is greater than or equal to 1, B is greater than or equal to 1, and H is greater than or equal to 1.
According to the technical scheme, at least one group of environment monitoring sensors can be arranged in each monitoring area according to the division of the monitoring areas, and each group of environment monitoring sensors can comprise sensors for monitoring environment data parameters of projects such as smoke, temperature, air pressure, pollutants and the like; in addition, at least one group of monitors can be arranged at each environment-adjusting device according to the specific condition of the environment-adjusting device, and each group of monitors can comprise a sensor for monitoring key parameters of the device such as vibration, local temperature and the like of the device.
As a further scheme of the invention: the step S30 includes:
step S301, recording and storing each environmental data parameter X obtained by M groups of the environmental monitoring sensors ij And B group of each device key parameter Y obtained by the monitor ij ；
Step S302, according to each of the environmental data parameters X ij And each of said device key parameters Y ij Calculate the corresponding environmental degradation degree E (X ij ) And device anomaly degree D (Y ij )；
Step S303, according to the environmental degradation E (X ij ) And the device anomaly degree D (Y ij ) Acquiring facility risk assessment value P t ；
The degree of environmental deterioration E (X ij ) The calculation formula of (2) is as follows:
Figure GDA0004247055250000071
the device anomaly degree D (Y ij ) The calculation formula of (2) is as follows:
Figure GDA0004247055250000072
wherein i is E [1, N]，j∈[1，M]，[X ith1 ，X ith2 ]The normal threshold interval corresponding to the ith environmental data parameter item; alpha i Fixed coefficient of the i-th environmental data parameter item, alpha i >1；
y 0 Corresponding i item of equipment key parameter Y representing corresponding environment regulating equipment ij Normal value of y min And y max And respectively corresponding to the upper limit and the lower limit of the key parameters of the equipment when the environment-adjusting equipment is required to be shut down. It can be seen that in the present embodiment of the present invention, the environmental degradation degree E (X ij ) The higher the description environment condition is, the worse the device abnormality degree D (Y ij ) The higher the probability of a device failure is, the greater.
The value of k is related to the category of the key parameter item of the corresponding equipment, for example, at least two abnormal models exist at present when the equipment is abnormal, one is an acceleration abnormal model, k is greater than 1, the other is a deceleration abnormal model, and k is less than 1.
As a further scheme of the invention: the step S303 includes:
step S3031, obtaining an average degradation degree of the environmental item corresponding to the environmental data parameter of the ith item
Figure GDA0004247055250000081
Step S3032, obtaining the average anomaly degree of the equipment items corresponding to the key parameters of the equipment in the ith item
Figure GDA0004247055250000082
Step S3033, calculating the facility risk assessment value P according to a preset calculation rule t ；
Average degree of deterioration of the environmental item
Figure GDA0004247055250000083
The calculation formula of (2) is as follows:
Figure GDA0004247055250000084
average anomaly degree of the equipment items
Figure GDA0004247055250000087
The calculation formula of (2) is as follows:
Figure GDA0004247055250000085
the preset calculation rule comprises the following steps:
Figure GDA0004247055250000086
wherein sigma i Dimensionality reduction coefficient corresponding to the ith environmental parameter monitoring item, tau i The dimensionality coefficient corresponding to the key parameter item of the ith equipment can be obtained through P t Reflecting the overall environment and equipment operation conditions in the facility.
As a further scheme of the invention: the step S30 further includes:
step S304, according to the obtained facility risk evaluation value P t Early warning judgment is carried out;
the early warning judgment comprises the following steps:
the facility risk assessment value P t Comparing with a preset threshold value:
if P t ＞P bo And judging that the safety risk exists in the underground infrastructure space.
Wherein P is bo The risk threshold is preset in advance.
As a further scheme of the invention: the step S30 further includes:
step S305, if it is determined that there is a security risk, determining a risk location point according to the sensing parameters of each group of the environmental monitoring sensors and the monitors and the corresponding spatial locations.
As a further scheme of the invention: the method for acquiring the risk location point comprises the following steps:
step S3051, for the monitoring area, obtaining an environmental degradation degree E (X) corresponding to the environmental monitoring sensor and the monitor ij ) And device anomaly degree D (Y ij )；
Step S3052, dividing the monitoring area to be inferior to the environmentDegree of conversion E (X) ij ) And device anomaly degree D (Y ij ) Respectively descending order to obtain E c (X ij ) And D c (Y ij ) C is descending order;
step S3053, judge E 1 (X ij ) And D 1 (Y ij ) If the association is corresponding, the step S3054 is entered if the association is corresponding, otherwise the step S3055 is entered;
step S3054, judging E 1 (X ij ) And E is connected with 2 (X ij ) If the corresponding monitoring areas are adjacent, E is determined to be the same 1 (X ij ) The corresponding monitoring area is defined as the risk position point, otherwise, the step S3055 is carried out;
step S3055, E 1 (X ij ) And D 1 (Y ij ) And respectively comparing the detected areas with the historical normal environment degradation degree and the historical normal equipment anomaly degree of the corresponding detected areas, and determining the detected area corresponding to the item with the larger comparison difference as the risk position point.
Through the technical scheme, the accuracy of risk judgment can be improved by judging whether the monitoring area with the largest environmental degradation degree is responsible for the largest equipment abnormality degree, and E is judged 1 (X ij ) And E is connected with 2 (X ij ) Whether the corresponding monitoring areas are adjacent or not can judge whether the environmental degradation degree is concentrated or not, because the general environmental detection items have problems, the problems can spread nearby, and the more concentrated the position points with larger deviation amount, the larger the safety risk is, and the more accurate the monitoring result is.
As a further scheme of the invention: further comprises:
and step S50, the early warning result is sent to the manager terminal.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.

Claims (5)

1. The underground facility safety monitoring and early warning method based on the Internet of things is characterized by comprising the following steps of:
step S10, acquiring real-time environment data in an underground infrastructure space;
step S20, acquiring equipment key parameters of environment adjusting equipment in the underground infrastructure space;
step S30, detecting and judging according to the real-time environment data and the key parameters of the equipment to obtain a real-time judging result;
step S40, early warning is carried out according to the judging result;
before step S10, the method further includes:
step S01, dividing a monitoring area according to the responsible area of the environment adjusting device;
step S02, M groups of environment monitoring sensors are distributed in each monitoring area, and each group of environment monitoring sensors is responsible for N environmental data parameters;
step S03, setting B groups of monitors for monitoring environment-regulating equipment in the underground infrastructure space, wherein each group of monitors is in charge of H equipment key parameters corresponding to the environment-regulating equipment;
wherein M is more than or equal to 1, N is more than or equal to 1, B is more than or equal to 1, and H is more than or equal to 1;
the step S30 includes:
step S301, recording and storing each environmental data parameter X obtained by M groups of the environmental monitoring sensors ij And B group of each device key parameter Y obtained by the monitor ij ；
Step S302, according to each of the environmental data parameters X ij And each of said device key parameters Y ij Calculate the corresponding environmental degradation degree E (X ij ) And device anomaly degree D (Y ij )；
Step S303, according to the environmental degradation E (X ij ) And the device anomaly degree D (Y ij ) Acquiring facility risk assessment value P t ；
The degree of environmental deterioration E (X ij ) The calculation formula of (2) is as follows:
Figure FDA0004247055240000021
the device anomaly degree D (Y ij ) The calculation formula of (2) is as follows:
Figure FDA0004247055240000022
wherein i is E [1, N]，j∈[1，M]，[X ith1 ，X ith2 ]The normal threshold interval corresponding to the ith environmental data parameter item; alpha i Fixed coefficient of the i-th environmental data parameter item, alpha i > 1; k is a power coefficient, and the value of k is related to the category of the corresponding key parameter item of the equipment;
y 0 corresponding i item of equipment key parameter Y representing corresponding environment regulating equipment ij Normal value of y min And y max The upper limit and the lower limit of the key parameters of the equipment when the environment-adjusting equipment is required to be shut down are respectively corresponding to the upper limit and the lower limit of the key parameters of the equipment when the environment-adjusting equipment is required to be shut down;
the step S303 includes:
step S3031, obtaining an average degradation degree of the environmental item corresponding to the environmental data parameter of the ith item
Figure FDA0004247055240000023
Step S3032, obtaining the average anomaly degree of the equipment items corresponding to the key parameters of the equipment in the ith item
Figure FDA0004247055240000024
Step S3033, calculating the facility risk assessment value P according to a preset calculation rule t ；
Average degree of deterioration of the environmental item
Figure FDA0004247055240000025
The calculation formula of (2) is as follows:
Figure FDA0004247055240000026
average anomaly degree of the equipment items
Figure FDA0004247055240000027
The calculation formula of (2) is as follows:
Figure FDA0004247055240000031
the preset calculation rule comprises the following steps:
Figure FDA0004247055240000032
wherein sigma i Dimensionality reduction coefficient corresponding to the ith environmental parameter monitoring item, tau i And (5) the dimensionality removing coefficient corresponding to the key parameter item of the ith equipment.
2. The method for monitoring and pre-warning safety of underground facilities based on the internet of things according to claim 1, wherein the step S30 further comprises:
step S304, according to the obtained facility risk evaluation value P t Early warning judgment is carried out;
the early warning judgment comprises the following steps:
the facility risk assessment value P t Comparing with a preset threshold value:
if P t ＞P bo Judging that the safety risk exists in the underground infrastructure space;
wherein P is bo The risk threshold is preset in advance.
3. The method for monitoring and pre-warning safety of underground facilities based on the internet of things according to claim 2, wherein the step S30 further comprises:
step S305, if it is determined that there is a security risk, determining a risk location point according to the sensing parameters of each group of the environmental monitoring sensors and the monitors and the corresponding spatial locations.
4. The method for monitoring and early warning of underground facility safety based on the internet of things according to claim 3, wherein the method for acquiring the risk location point comprises the following steps:
step S3051, for the monitoring area, obtaining an environmental degradation degree E (X) corresponding to the environmental monitoring sensor and the monitor ij ) And device anomaly degree D (Y ij )；
Step S3052, dividing the environmental degradation E (X) ij ) And device anomaly degree D (Y ij ) Respectively descending order to obtain E c (X ij ) And D c (Y ij ) C is descending order;
step S3053, judge E 1 (X ij ) And D 1 (Y ij ) If the association is corresponding, the step S3054 is entered if the association is corresponding, otherwise the step S3055 is entered;
step S3054, judging E 1 (X ij ) And E is connected with 2 (X ij ) If the corresponding monitoring areas are adjacent, E is determined to be the same 1 (X ij ) The corresponding monitoring area is defined as the risk position point, otherwise, the step S3055 is carried out;
step S3055, E 1 (X ij ) And D 1 (Y ij ) And respectively comparing the detected areas with the historical normal environment degradation degree and the historical normal equipment anomaly degree of the corresponding detected areas, and determining the detected area corresponding to the item with the larger comparison difference as the risk position point.
5. The internet of things-based underground facility safety monitoring and early warning method according to claim 1, further comprising:
and step S50, the early warning result is sent to the manager terminal.
CN202310382003.5A 2023-04-12 2023-04-12 Underground facility safety monitoring and early warning method based on Internet of things Active CN116105802B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310382003.5A CN116105802B (en) 2023-04-12 2023-04-12 Underground facility safety monitoring and early warning method based on Internet of things

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310382003.5A CN116105802B (en) 2023-04-12 2023-04-12 Underground facility safety monitoring and early warning method based on Internet of things

Publications (2)

Publication Number Publication Date
CN116105802A CN116105802A (en) 2023-05-12
CN116105802B true CN116105802B (en) 2023-06-23

Family

ID=86256504

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310382003.5A Active CN116105802B (en) 2023-04-12 2023-04-12 Underground facility safety monitoring and early warning method based on Internet of things

Country Status (1)

Country Link
CN (1) CN116105802B (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116952654B (en) * 2023-07-11 2024-04-09 广州众拓计算机科技有限公司 Environment monitoring and early warning system for administrative supervision
CN117073753A (en) * 2023-08-09 2023-11-17 北京城建设计发展集团股份有限公司 Underground space environment monitoring system and method based on Internet of Things
CN117129041B (en) * 2023-10-25 2024-01-02 广东省农业科学院动物科学研究所 Agricultural product processing environment anomaly monitoring system based on Internet of things

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
IN2015CH04425A (en) * 2015-08-24 2015-09-04 Wipro Ltd
KR102005138B1 (en) * 2016-08-29 2019-07-29 한국수력원자력 주식회사 Device abnormality presensing method and system using thereof
CN110097748A (en) * 2019-04-04 2019-08-06 国电南瑞科技股份有限公司 A kind of environmental monitoring of Urban Underground power grid pipeline and method for early warning
KR102065435B1 (en) * 2019-08-14 2020-01-13 주식회사 심플비트 Infrastructure health monitoring system and method
CN114970083A (en) * 2022-04-02 2022-08-30 国电联合动力技术有限公司 Degradation degree determination method and device and electronic equipment
CN115329812B (en) * 2022-08-10 2023-07-21 贵州桥梁建设集团有限责任公司 Bridge infrastructure anomaly monitoring method based on artificial intelligence
CN115497271A (en) * 2022-11-16 2022-12-20 广东普蓝地理信息服务有限公司 Early warning method for potential safety hazards of underground municipal facilities

Also Published As

Publication number Publication date
CN116105802A (en) 2023-05-12

Similar Documents

Publication Publication Date Title
CN116105802B (en) Underground facility safety monitoring and early warning method based on Internet of things
CN112348237B (en) Abnormal trend detection method for dynamic drilling data
CN112378445A (en) Building construction environment intelligence real-time monitoring system based on big data analysis
CN107291991B (en) Early defect early warning method for wind turbine generator based on dynamic network sign
CN116246407A (en) Agriculture and forestry area fire early warning supervisory systems based on artificial intelligence
CN114997682B (en) Construction site safety monitoring system and method based on big data
CN114894411B (en) Bridge health monitoring method and system based on wireless sensor network
CN112541430B (en) Fault diagnosis method for fusion of temperature signal and noise signal
CN114429308A (en) Enterprise security risk assessment method and system based on big data
CN116432989B (en) Intelligent construction-based construction site safety control system
CN112380599A (en) Bridge intelligent online monitoring and early warning system based on big data analysis
CN115165725A (en) Data-driven marine equipment corrosion monitoring and safety early warning system
CN106081958A (en) A kind of derrick crane on-line monitoring system
US20200156680A1 (en) Railway vehicle major component and system diagnosis apparatus
CN116909235A (en) Intelligent factory monitoring method, intelligent factory monitoring system and electronic equipment
CN115650006B (en) Elevator safety monitoring and early warning method and system based on big data
CN116661399A (en) Chemical workshop safety monitoring method and system
CN114582083A (en) Tunnel monitoring multi-sensor data fusion fire early warning method
CN114997759B (en) Heat supply pipeline support and hanger stability early warning method and system
CN113137983B (en) Self-learning well lid posture monitoring method and monitoring system
CN117007247A (en) Chemical gas leakage safety feedback system and method based on data analysis
CN116703037B (en) Monitoring method and device based on road construction
CN112911004B (en) Method and device for ensuring safe operation of Internet of things system and computing equipment
CN214652927U (en) Monitoring system based on temperature signal and noise signal
CN117893010A (en) Intelligent construction site safety risk evaluation method based on self-adaptive weighted fusion

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
PE01 Entry into force of the registration of the contract for pledge of patent right
PE01 Entry into force of the registration of the contract for pledge of patent right

Denomination of invention: A Safety Monitoring and Early Warning Method for Underground Facilities Based on the Internet of Things

Effective date of registration: 20230824

Granted publication date: 20230623

Pledgee: Bank of China Limited by Share Ltd. Guangzhou Tianhe branch

Pledgor: Guangdong Pulan Geographic Information Service Co.,Ltd.

Registration number: Y2023980053617