CN113759219A - Active environmental safety monitoring and early warning device, method and installation scheme - Google Patents
Active environmental safety monitoring and early warning device, method and installation scheme Download PDFInfo
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- 230000007613 environmental effect Effects 0.000 title claims abstract description 40
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- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
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- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
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Abstract
The invention discloses an active environmental safety monitoring and early warning device, a method and an installation scheme, which aim to solve the problems that the monitoring and early warning cannot be carried out on the thermal degradation of materials in electrical equipment and an operating environment thereof, and the monitoring of the insulation defect discharge of the equipment is realized at the same time, and comprise an omnibearing monitoring module, an overheating hidden danger early warning module, a defect discharge monitoring and early warning module, an environmental safety module and a diagnosis module which are sequentially connected; the method comprises the following steps: s1: collecting or detecting parameter information of electrical equipment and an operating environment; s2: randomly arranging specific data uploading moments in each preset time period, and homogenizing the data uploading amount; s3: analyzing the data of the detection early warning module to generate an early warning event; s4: and the diagnosis module sends early warning information and an equipment operation safety report according to the early warning event. The invention has the beneficial effects that: the monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment thereof are realized, and the monitoring of the insulation defect discharge of the equipment is realized at the same time.
Description
Technical Field
The invention relates to the technical field of monitoring, in particular to an active environmental safety monitoring and early warning device, method and installation scheme.
Background
The power distribution station room is a direct power supply node of a distribution network, and the operation reliability of the power distribution station room is directly related to the power supply reliability. The method has the advantages of accelerating the construction of digital transformation of the distribution network, developing intelligent monitoring of the power distribution station room, improving the intelligent level of the power distribution station room and having important significance for ensuring the power supply reliability of the distribution network.
Along with the construction of a cloud, pipe, side and end power distribution internet of things, the intelligent level of a power distribution station room is greatly improved, but the monitoring means for equipment and environmental safety of the power distribution station room are more traditional, such as oxygen content, temperature and humidity, video images, audible and visual alarms, temperature sensing probes and the like, on one hand, the monitoring range is more dispersed, and the monitoring range is smaller; on the other hand, passive sensing and after-treatment are mostly adopted, the safety early warning function is lacked, and a closed loop cannot be formed.
Along with the implementation of an unattended and integrated monitoring system, the demand of the power transformation equipment on an online monitoring technology is higher and higher. Although the pressure of operation and maintenance personnel is greatly reduced by the inspection robot, the monitoring range of the inspection robot is limited, the indoor equipment in a station cannot be supervised, the indoor equipment is usually only provided with temperature and humidity monitoring, monitoring blind areas exist in partial areas, and manual inspection is still relied on. Thus, existing safety monitoring techniques still have deficiencies and deadlines.
Most of electrical equipment runs in a strong electromagnetic environment, a discharge fault is easily formed when an insulating material is degraded, the equipment is locally overheated due to discharge, the temperature is higher after an arc is formed, and the equipment is easily burnt; on the other hand, the through-flow device is easy to overheat after long-term operation due to the thermal effect of the current. Therefore, monitoring of the electrical discharge and overheating of electrical equipment is an important point in ensuring its safe operation.
The invention discloses an electrical equipment joint temperature early warning and monitoring system which is disclosed in Chinese patent document, and the publication number CN111323147A comprises an equipment joint temperature early warning system host, a wireless temperature measurement receiver and a wireless temperature measurement module, wherein the inside of the equipment joint temperature early warning system host is provided with electrical equipment joint temperature early warning system software, the invention introduces the load current and the environment temperature of electrical equipment into the electrical equipment joint temperature early warning system, thereby leading the utilization of mutation quantity temperature early warning, three-phase inconsistent temperature early warning and trend analysis temperature early warning to be possible, greatly reducing the threshold value of temperature early warning, eliminating the false alarm possibility of temperature early warning, finding abnormality at the early stage of temperature abnormality, winning precious time for abnormality treatment, avoiding the occurrence of insulation accidents and fire accidents due to continuous temperature rise, the safe and stable operation of the electrical equipment is ensured. The disadvantages are as follows: aiming at the overheat monitoring of electrical equipment, active early warning cannot be achieved, the application scene is limited, and technical short boards of a distribution station room and a transformer substation on safety monitoring cannot be complemented; the monitoring and early warning can not be carried out aiming at the thermal degradation of the electrical equipment and the material in the operating environment, and the monitoring of the insulation defect discharge of the equipment can be realized.
Disclosure of Invention
The invention mainly aims to solve the problems that the monitoring and early warning cannot be carried out on the thermal degradation of materials in electrical equipment and an operating environment thereof, and the monitoring of the insulation defect discharge of the equipment is realized, and provides an active environmental safety monitoring and early warning device, method and installation scheme, which can carry out the monitoring and early warning on the thermal degradation of materials in the electrical equipment and the operating environment thereof, and realize the monitoring of the insulation defect discharge of the equipment.
In order to achieve the purpose, the invention adopts the following technical scheme:
active environmental safety monitoring early warning device, including the shell, be equipped with in the shell:
the omnibearing monitoring module is used for actively detecting the electrical equipment and the operating environment;
the overheating hidden danger early warning module is used for detecting the concentration change of the micro-particles and realizing early warning of overheating hidden dangers;
the defect discharge monitoring and early warning module is used for monitoring and early warning equipment defect discharge and determining hidden danger equipment;
the environment safety module is used for monitoring environment parameters and providing operation and maintenance suggestions;
and the diagnosis module is used for analyzing the data and sending early warning information and an equipment operation safety report.
The device adopts a leading nano particle detection technology, can detect nano-scale thermal degradation products, can perform active early warning when electrical equipment discharges or has overheating hidden danger, ensures the safety of the electrical equipment and the operating environment thereof, realizes the monitoring and early warning of the thermal degradation of materials in the electrical equipment and the operating environment thereof, and simultaneously realizes the monitoring of the insulation defect discharge of the equipment.
The device has strong environmental adaptability and anti-electromagnetic interference capability, and can make up the defects of the current safety monitoring means of the distribution station room and the transformer substation.
The omnibearing monitoring module adopts an active detection mode to carry out omnibearing monitoring on the electrical equipment and the operating environment thereof.
The overheating hidden danger early warning module can detect the concentration change of microparticles of 0.002-20 microns, and early warning is achieved in the stage of the germination of the overheating hidden danger of the electrical equipment, and the advance time is 5 minutes-12 hours.
The defect discharge monitoring and early warning module can monitor and early warn the defects of arc discharge, surface flashover and the like of the equipment; and can be accurately positioned to specific hidden danger equipment through a special installation mode.
The environment safety module can monitor the temperature, the humidity, the carbon monoxide and the like in the running environment of the equipment in real time, can configure a gas sensor (such as SF 6) aiming at a special scene, and can provide a reasonable operation and maintenance suggestion according to the monitoring parameters.
The diagnosis module provides mass data preprocessing, analysis and model training for the intelligent monitoring system, can quickly establish and deploy a model for field application, sends early warning information, and sends an equipment operation safety report at regular time, so that operation and maintenance personnel can master the equipment operation state at the first time.
Preferably, the omnibearing monitoring module, the overheating hidden danger early warning module, the defect discharge monitoring early warning module, the environmental safety module and the diagnosis module are sequentially connected.
The all-round monitoring module, the overheating hidden danger early warning module, the defect discharge monitoring early warning module, the environmental safety module and the diagnosis module are connected in an electrical connection mode such as a wire, and communication and information interaction between the modules are facilitated.
Preferably, the environment safety module comprises a plurality of gas sensors, a plurality of temperature sensors and a plurality of humidity sensors which are connected in sequence.
The gas sensor is a toxic and harmful gas sensor, comprises a carbon monoxide gas sensor, a hydrogen sulfide gas sensor, a methane gas sensor and the like, and is used for detecting toxic and harmful gases in the operating environment.
The environment safety module can be used for detecting different working environments by additionally arranging a dust detection sensor and the like according to the requirements of a user.
Preferably, the front surface of the shell is provided with a display screen, an indicator light and a key, and the display screen and the indicator light are connected with the diagnosis module.
The display screen is used for displaying data parameters detected by a sensor and the like, the indicating lamp is used for indicating the working state of equipment, and the key is used for adjusting the working mode of the equipment and the like.
The active environmental safety monitoring and early warning method comprises the following steps:
s1: collecting or detecting parameter information of electrical equipment and an operating environment;
s2: randomly arranging specific data uploading moments in each preset time period, and homogenizing the data uploading amount;
s3: analyzing the data of the detection early warning module based on a time sequence prediction algorithm to generate an early warning event;
s4: and the diagnosis module sends early warning information and an equipment operation safety report according to the early warning event.
The method can effectively realize the monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment thereof, and simultaneously realize the monitoring of the insulation defect discharge of the equipment.
In step S1, the parameter information is collected by the omnidirectional monitoring module, the overheating hidden danger warning module, the defect discharge monitoring and warning module, and the environmental safety module.
The method provides mass data preprocessing, analysis and model training for the intelligent monitoring system, can quickly create and deploy models for field application, sends early warning information and regularly sends equipment operation safety reports, and enables operation and maintenance personnel to master the equipment operation condition at the first time.
Preferably, in step S1, the parameter information of the electrical device and the operating environment includes electrical device and operating environment information, device defect discharge information, and device overheating hidden danger information, and the collecting or detecting module includes an omnidirectional monitoring module, an overheating hidden danger warning module, a defect discharge monitoring and warning module, and an environmental safety module.
By collecting different parameter information of the electrical equipment and the operating environment, the real-time state of the operating environment can be accurately displayed, the monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment are facilitated, and meanwhile, the monitoring of the insulation defect discharge of the equipment is realized.
Preferably, step S2 includes the steps of:
s21: carrying out real-time statistical operation on the sampling result while sampling;
s22: calculating a group of characteristic parameters of the time period every other preset time period;
s23: randomly arranging specific data uploading moments in each preset time period;
s24: and uniformly uploading the data volume to the cloud server at each moment.
And carrying out real-time statistical operation on the sampling result while sampling, calculating a group of characteristic parameters of the time period every other preset time period, transmitting the characteristic parameters to a cloud server through a communication module every other preset time period, and carrying out further diagnosis and predictive analysis after gathering.
The instantaneous impact of large-scale concurrent connection on the cloud server is considered, the specific time of data uploading in each preset time period is randomly arranged, and the data volume uploaded to the cloud server at each moment is uniformized as much as possible.
Preferably, step S3 includes the steps of:
s31: the data received by the cloud server form a first time sequence, and a predicted value time sequence is obtained through processing of a time sequence prediction algorithm;
s32: continuously monitoring to obtain an actual time sequence of the predicted value, and adding the actual time sequence of the predicted value to the end of the first time sequence to obtain a second time sequence;
s33: correcting parameters of the time sequence prediction algorithm based on the difference between the predicted value time sequence and the actual time sequence of the predicted value, and processing the second time sequence by the corrected time sequence prediction algorithm to obtain a new predicted value time sequence;
s34: iterating the steps S31-S33 to obtain a time sequence prediction algorithm with continuously and automatically adjusted parameters, a continuously updated second time sequence and a new predicted value time sequence;
s35: and setting an event rule base to process the second time sequence and the new predicted value time sequence to obtain an early warning event and early warn the early warning event.
In step S31, the data received by the cloud server are collectively referred to as measured values, the time sequence formed by the measured values is recorded as Xi, that is, the first time sequence, the duration of the predicted time period is set to be T, the nth time period end time is used for processing the Xi of the previous N time periods by using the time sequence prediction algorithm, and the predicted value time sequence Xi' of the N +1 th time period, that is, the predicted value time sequence, is obtained.
In step S32, the end time of the N +1 time interval is continuously monitored, so as to obtain the time series Xi 'formed by the data measured value of the N +1 time interval, i.e. the actual time series of the predicted value, and Xi' is added to the end of Xi of the previous N time intervals, so as to obtain Xi of the previous N +1 time intervals, i.e. the second time series.
In step S33, the parameters of the time sequence prediction algorithm are modified based on the difference between the (N + 1) th time period Xi ″ and Xi ', and the modified time sequence prediction algorithm is used to process the Xi of the previous (N + 1) th time periods, i.e., the second time sequence, to obtain the predicted value time sequence Xi' of the (N + 2) th time period, i.e., the new predicted value time sequence.
In step S34, steps S31-S33 are iterated to obtain a time sequence prediction algorithm L with continuously and automatically adjusted parameters and continuously updated time sequences Xi and Xi', that is, a second time sequence and a new predicted value time sequence.
Setting an event rule base P in the step S35 to process the time sequences Xi and Xi', calling an early warning event based on the event generated by Xi, and early warning the early warning event; events generated based on Xi and Xi' are called predicted events, and a time series formed by predicting the number of events every prediction time period is set as Mi.
And processing the Mi by using an Xi processing method to obtain a time sequence prediction algorithm with continuously and automatically adjusted parameters and continuously updated time sequences Mi and Mi ', setting an event rule base Q in a manner similar to setting P to process the Mi and Mi', obtaining a second-order early warning event, and early warning the second-order early warning event.
Preferably, the event rule base in step S35 includes the following steps:
s351: generating an early warning event when the interval of the industry standard required value is exceeded;
s352: and early warning is carried out on the early warning event.
An installation scheme of an active environmental safety monitoring and early warning device comprises an all-dimensional monitoring installation scheme, an accurate positioning installation scheme and a key part installation scheme.
The accurate positioning installation scheme extends the capillary sampling tube to the interior of the box body through a special accurate positioning box body installation mode, and the function of accurately positioning hidden dangers is achieved through an intelligent algorithm.
The key part installation scheme aims at narrow spaces such as cable tunnels and cable interlayers, equipment can be installed at key parts such as cable joints, and sampling pipes extend along the wall.
Through the different installation schemes, the installation schemes can be adopted according to different application scenes, and a better monitoring effect is achieved.
The invention has the beneficial effects that:
(1) the device realizes monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment thereof, and simultaneously realizes monitoring of the insulation defect discharge of the equipment.
(2) The method realizes monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment thereof, and simultaneously realizes monitoring of the insulation defect discharge of the equipment.
(3) The step S2 is used to homogenize the data volume uploaded, thereby avoiding the transient impact of the large-scale concurrent connection on the cloud server.
(4) Through different installation schemes, the installation scheme can be adopted in a targeted manner aiming at different application scenes, and a better monitoring effect is achieved.
Drawings
Fig. 1 is a schematic structural view of the present apparatus.
Fig. 2 is a schematic diagram of the module structure of the present invention.
FIG. 3 is a schematic flow diagram of the present invention.
Illustration of the drawings: the system comprises a shell 1, an omnibearing monitoring module 2, an overheating hidden danger early warning module 3, a defect discharge monitoring early warning module 4, an environmental safety module 5, a diagnosis module 6, a display screen 7, an indicator light 8, a key 9, a gas sensor 51, a temperature sensor 52 and a humidity sensor 53.
Detailed Description
The invention is further described with reference to the following figures and detailed description.
As shown in fig. 1 and fig. 2, the active environmental safety monitoring and early warning device includes a housing 1, and is provided with:
the omnibearing monitoring module 2 is used for actively detecting electrical equipment and an operating environment;
the overheating hidden danger early warning module 3 is used for detecting the concentration change of the microparticles and realizing early warning of overheating hidden dangers;
the defect discharge monitoring and early warning module 4 is used for monitoring and early warning equipment defect discharge and determining hidden danger equipment;
the environment safety module 5 is used for monitoring environment parameters and providing operation and maintenance suggestions;
and the diagnosis module 6 is used for analyzing the data and sending early warning information and equipment operation safety reports.
The device adopts a leading nano particle detection technology, can detect nano-scale thermal degradation products, can perform active early warning when electrical equipment discharges or has overheating hidden danger, ensures the safety of the electrical equipment and the operating environment thereof, realizes the monitoring and early warning of the thermal degradation of materials in the electrical equipment and the operating environment thereof, and simultaneously realizes the monitoring of the insulation defect discharge of the equipment.
The device has strong environmental adaptability and anti-electromagnetic interference capability, and can make up the defects of the current safety monitoring means of the distribution station room and the transformer substation.
The omnibearing monitoring module adopts an active detection mode to carry out omnibearing monitoring on the electrical equipment and the operating environment thereof.
The overheating hidden danger early warning module can detect the concentration change of microparticles of 0.002-20 microns, and early warning is achieved in the stage of the germination of the overheating hidden danger of the electrical equipment, and the advance time is 5 minutes-12 hours.
The defect discharge monitoring and early warning module can monitor and early warn the defects of arc discharge, surface flashover and the like of the equipment; and can be accurately positioned to specific hidden danger equipment through a special installation mode.
The environment safety module can monitor the temperature, humidity, carbon monoxide and the like in the operating environment of the equipment in real time, can configure a gas sensor (such as SF 6) aiming at a special scene, and can provide reasonable operation and maintenance suggestions according to the monitoring parameters.
The diagnosis module provides mass data preprocessing, analysis and model training for the intelligent monitoring system, can quickly establish and deploy a model for field application, sends early warning information and sends an equipment operation safety report at regular time, so that operation and maintenance personnel can master the equipment operation condition at the first time.
The all-dimensional monitoring module, the overheating hidden danger early warning module, the defect discharge monitoring early warning module, the environmental safety module and the diagnosis module are connected in sequence.
The omnibearing monitoring module, the overheating hidden danger early warning module, the defect discharge monitoring early warning module, the environmental safety module and the diagnosis module are connected in an electrical connection mode such as a wire, and communication and information interaction among the modules are facilitated.
The environmental safety module comprises a plurality of gas sensors 51, a plurality of temperature sensors 52 and a plurality of humidity sensors 53 which are connected in sequence.
The gas sensor is a toxic and harmful gas sensor, comprises a carbon monoxide gas sensor, a hydrogen sulfide gas sensor, a methane gas sensor and the like, and is used for detecting toxic and harmful gases in the operating environment.
The environment safety module can be used for detecting different working environments by additionally arranging a dust detection sensor and the like according to the requirements of a user.
The positive surface of shell is equipped with display screen 7, pilot lamp 8 and button 9, and display screen and pilot lamp all are connected with diagnostic module.
The display screen is used for displaying data parameters detected by the sensor and the like, the indicating lamp is used for indicating the working state of the equipment, and the key is used for adjusting the working mode of the equipment and the like.
As shown in fig. 3, the active environmental safety monitoring and early warning method includes the following steps:
s1: collecting or detecting parameter information of electrical equipment and an operating environment;
s2: randomly arranging specific data uploading moments in each preset time period, and homogenizing the data uploading amount;
s3: analyzing the data of the detection early warning module based on a time sequence prediction algorithm to generate an early warning event;
s4: and the diagnosis module sends early warning information and an equipment operation safety report according to the early warning event.
The method can effectively realize the monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment thereof, and simultaneously realize the monitoring of the insulation defect discharge of the equipment.
In step S1, parameter information is collected by the omnidirectional monitoring module, the overheating hidden danger warning module, the defect discharge monitoring warning module, and the environmental safety module.
The method provides mass data preprocessing, analysis and model training for the intelligent monitoring system, can quickly create and deploy models for field application, sends early warning information and regularly sends equipment operation safety reports, and enables operation and maintenance personnel to master the equipment operation condition at the first time.
In the step S1, the parameter information of the electrical equipment and the operating environment includes information of the electrical equipment and the operating environment, defect discharge information of the equipment, and overheat hidden danger information of the equipment, and the acquisition or detection module includes an omnidirectional monitoring module, an overheat hidden danger early warning module, a defect discharge monitoring early warning module, and an environmental safety module.
By collecting different parameter information of the electrical equipment and the operating environment, the real-time state of the operating environment can be accurately displayed, the monitoring and early warning of the thermal degradation of the material in the electrical equipment and the operating environment are facilitated, and meanwhile, the monitoring of the insulation defect discharge of the equipment is realized.
Step S2 includes the following steps:
s21: carrying out real-time statistical operation on the sampling result while sampling;
s22: calculating a group of characteristic parameters of the time period every other preset time period;
s23: randomly arranging specific data uploading moments in each preset time period;
s24: and uniformly uploading the data volume to the cloud server at each moment.
And carrying out real-time statistical operation on the sampling result while sampling, calculating a group of characteristic parameters of the time period every other preset time period, transmitting the characteristic parameters to a cloud server through a communication module every other preset time period, and carrying out further diagnosis and predictive analysis after gathering.
The instantaneous impact of large-scale concurrent connection on the cloud server is considered, the specific time of data uploading in each preset time period is randomly arranged, and the data volume uploaded to the cloud server at each moment is uniformized as much as possible.
Step S3 includes the following steps:
s31: the data received by the cloud server form a first time sequence, and a predicted value time sequence is obtained through processing of a time sequence prediction algorithm;
s32: continuously monitoring to obtain an actual time sequence of the predicted value, and adding the actual time sequence of the predicted value to the end of the first time sequence to obtain a second time sequence;
s33: correcting parameters of the time sequence prediction algorithm based on the difference between the predicted value time sequence and the actual time sequence of the predicted value, and processing the second time sequence by the corrected time sequence prediction algorithm to obtain a new predicted value time sequence;
s34: iterating the steps S31-S33 to obtain a time sequence prediction algorithm with continuously and automatically adjusted parameters, a continuously updated second time sequence and a new predicted value time sequence;
s35: and setting an event rule base to process the second time sequence and the new predicted value time sequence to obtain an early warning event and early warn the early warning event.
In step S31, the data received by the cloud server are collectively referred to as measured values, the time sequence formed by the measured values is recorded as Xi, that is, the first time sequence, the duration of the predicted time period is set to be T, the nth time period end time is used for processing the Xi of the previous N time periods by using the time sequence prediction algorithm, and the predicted value time sequence Xi' of the N +1 th time period, that is, the predicted value time sequence, is obtained.
In step S32, the end time of the N +1 time interval is continuously monitored, so as to obtain the time series Xi 'formed by the data measured value of the N +1 time interval, i.e. the actual time series of the predicted value, and Xi' is added to the end of Xi of the previous N time intervals, so as to obtain Xi of the previous N +1 time intervals, i.e. the second time series.
In step S33, the parameters of the time sequence prediction algorithm are modified based on the difference between the (N + 1) th time period Xi ″ and Xi ', and the modified time sequence prediction algorithm is used to process the Xi of the previous (N + 1) th time periods, i.e., the second time sequence, to obtain the predicted value time sequence Xi' of the (N + 2) th time period, i.e., the new predicted value time sequence.
In step S34, steps S31-S33 are iterated to obtain a time sequence prediction algorithm L with continuously and automatically adjusted parameters and continuously updated time sequences Xi and Xi', that is, a second time sequence and a new predicted value time sequence.
Setting an event rule base P in the step S35 to process the time sequences Xi and Xi', calling an early warning event based on the event generated by Xi, and early warning the early warning event; events generated based on Xi and Xi' are called predicted events, and a time series formed by predicting the number of events every prediction time period is set as Mi.
And processing the Mi by using an Xi processing method to obtain a time sequence prediction algorithm with continuously and automatically adjusted parameters and continuously updated time sequences Mi and Mi ', setting an event rule base Q in a manner similar to setting P to process the Mi and Mi', obtaining a second-order early warning event, and early warning the second-order early warning event.
The event rule base in step S35 includes the following steps:
s351: generating an early warning event when the interval of the industry standard required value is exceeded;
s352: and early warning is carried out on the early warning event.
An installation scheme of an active environmental safety monitoring and early warning device comprises an all-dimensional monitoring installation scheme, an accurate positioning installation scheme and a key part installation scheme.
The accurate positioning installation scheme extends the capillary sampling tube to the interior of the box body through a special accurate positioning box body installation mode, and the function of accurately positioning hidden dangers is achieved through an intelligent algorithm.
The key part installation scheme aims at narrow spaces such as cable tunnels and cable interlayers, equipment can be installed at key parts such as cable joints, and sampling pipes extend along the wall.
It should be understood that this example is only for illustrating the present invention and is not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
Claims (10)
1. Active environmental safety monitoring early warning device, its characterized in that, including shell (1), be equipped with in shell (1):
the omnibearing monitoring module (2) is used for actively detecting electrical equipment and an operating environment;
the overheating hidden danger early warning module (3) is used for detecting the concentration change of the microparticles and realizing early warning of overheating hidden dangers;
the defect discharge monitoring and early warning module (4) is used for monitoring and early warning equipment defect discharge and determining hidden danger equipment;
the environment safety module (5) is used for monitoring environment parameters and proposing operation and maintenance suggestions;
and the diagnosis module (6) is used for analyzing the data and sending early warning information and a device operation safety report.
2. The active environmental safety monitoring and early warning device according to claim 1, wherein the omnibearing monitoring module (2), the overheating hidden danger early warning module (3), the defect discharge monitoring and early warning module (4), the environmental safety module (5) and the diagnosis module (6) are sequentially connected.
3. The active environmental safety monitoring and early warning device according to claim 1 or 2, wherein the environmental safety module (5) comprises a plurality of gas sensors (51), a plurality of temperature sensors (52) and a plurality of humidity sensors (53) which are connected in sequence.
4. The active environmental safety monitoring and early warning device according to claim 3, wherein a display screen (7), an indicator light (8) and a key (9) are arranged on the front surface of the housing (1), and the display screen (7) and the indicator light (8) are connected with the diagnosis module (6).
5. An active environmental safety monitoring and early warning method, which is suitable for any one of the active environmental safety monitoring and early warning devices in claims 1 to 4, is characterized by comprising the following steps:
s1: collecting or detecting parameter information of electrical equipment and an operating environment;
s2: randomly arranging specific data uploading moments in each preset time period, and homogenizing the data uploading amount;
s3: analyzing the data of the detection early warning module based on a time sequence prediction algorithm to generate an early warning event;
s4: and the diagnosis module sends early warning information and an equipment operation safety report according to the early warning event.
6. The active environmental safety monitoring and early warning method according to claim 5, wherein the parameter information of the electrical equipment and the operating environment in step S1 includes electrical equipment and operating environment information, equipment defect discharge information, and equipment overheating hidden danger information, and the collecting or detecting module includes an omnidirectional monitoring module, an overheating hidden danger early warning module, a defect discharge monitoring and early warning module, and an environmental safety module.
7. The active environmental safety monitoring and early warning method according to claim 5, wherein the step S2 comprises the following steps:
s21: carrying out real-time statistical operation on the sampling result while sampling;
s22: calculating a group of characteristic parameters of the time period every other preset time period;
s23: randomly arranging specific data uploading moments in each preset time period;
s24: and uniformly uploading the data volume to the cloud server at each moment.
8. The active environmental safety monitoring and early warning method according to claim 5, wherein the step S3 comprises the following steps:
s31: the data received by the cloud server form a first time sequence, and a predicted value time sequence is obtained through processing of a time sequence prediction algorithm;
s32: continuously monitoring to obtain an actual time sequence of the predicted value, and adding the actual time sequence of the predicted value to the end of the first time sequence to obtain a second time sequence;
s33: correcting parameters of the time sequence prediction algorithm based on the difference between the predicted value time sequence and the actual time sequence of the predicted value, and processing the second time sequence by the corrected time sequence prediction algorithm to obtain a new predicted value time sequence;
s34: iterating the steps S31-S33 to obtain a time sequence prediction algorithm with continuously and automatically adjusted parameters, a continuously updated second time sequence and a new predicted value time sequence;
s35: and setting an event rule base to process the second time sequence and the new predicted value time sequence to obtain an early warning event and early warn the early warning event.
9. The active environmental security monitoring and early warning method of claim 8, wherein the event rule base in step S35 includes the following steps:
s351: generating an early warning event when the interval of the industry standard required value is exceeded;
s352: and early warning is carried out on the early warning event.
10. An active environmental safety monitoring and early warning device installation scheme is suitable for any one of the active environmental safety monitoring and early warning devices in claims 1 to 4, and is characterized by comprising an all-dimensional monitoring installation scheme, an accurate positioning installation scheme and a key part installation scheme.
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