CN218630962U - Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information - Google Patents
Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information Download PDFInfo
- Publication number
- CN218630962U CN218630962U CN202222405395.6U CN202222405395U CN218630962U CN 218630962 U CN218630962 U CN 218630962U CN 202222405395 U CN202222405395 U CN 202222405395U CN 218630962 U CN218630962 U CN 218630962U
- Authority
- CN
- China
- Prior art keywords
- module
- early warning
- characteristic
- electrical cabinet
- acquisition
- 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
Links
Images
Landscapes
- Fire Alarms (AREA)
Abstract
The utility model discloses a regulator cubicle conflagration risk aassessment early warning system based on multisource heterogeneous information, including regional host computer and the collection terminal subassembly that corresponds the setting in a plurality of regulator cubicles, regional host computer and collection terminal subassembly communication connection, the collection terminal subassembly is including the collection module of bleeding, the gaseous collection module of characteristic, thermion collection module, wireless temperature measurement module and the collection module of bleeding install in the regulator cubicle, the gaseous collection module of characteristic and thermion collection module setting of bleeding, the collection module of bleeding, the gaseous collection module of characteristic, thermion collection module and wireless temperature measurement module and regional host computer communication connection. The utility model discloses a heterogeneous conflagration characteristic information signal of a plurality of sources of monitoring electric appliance cabinet from different angles, multidimensional parameter to regulator cubicle conflagration state monitoring analysis, has effectively avoided the not enough of single monitoring sensor monitoring, effectively promotes conflagration early warning rate of accuracy.
Description
Technical Field
The utility model belongs to regulator cubicle conflagration risk assessment early warning field, concretely relates to regulator cubicle conflagration risk assessment early warning system based on multisource heterogeneous information.
Background
The electrical cabinet is used as a device for executing electric energy distribution and line protection, is widely applied to links of power generation, power transmission, power transformation, power distribution and the like of a power system, and the safe operation of the electrical cabinet is directly related to the safe production of electric power. In the use, power cable in the regulator cubicle, the contact point of breaking, cable joint etc. all probably because become flexible, insulating corrosion, there is the fault point then to produce a large amount of heats in electric arc impact etc, because cabinet body overall seal, the easy part of fault point heat in the cabinet body is piled up, thereby can lead to the damage of being heated of internal plant, can also take place the conflagration dangerous situation when serious, traditional regulator cubicle lacks fire prevention early warning device, when the regulator cubicle is inside to catch fire simultaneously, because leakproofness and inside narrow and small space and equipment probably still are electrified, very big difficulty has been caused for conflagration suppression, the large tracts of land power failure accident that arouses easily, cause economic loss, seriously threaten electric wire netting and personnel's safety. Therefore, the fire prevention device has great significance for the safe operation of the electrical cabinet. However, at present, the following disadvantages still exist in fire prevention of electrical cabinets, and are reflected in:
(1) In the regulations of the power sector, it is required to arrange an automatic fire alarm system in an electric cabinet, detect an initial fire and send an alarm by fire detectors of smoke, light, temperature, flame, gas, air suction type, and the like. However, the fire detector detects substances after the fire occurs, so that the loss of the fire can be reduced only to a certain extent, the fire detector belongs to passive fire protection, and early warning and monitoring cannot be realized.
(2) The regulator cubicle conflagration early warning system has been installed to some units, if through at the contact, female junction of arranging, wireless temperature sensor is installed to position such as cable joint, the pyrolysis particle concentration change that cable in the microenvironment was heated in the monitoring regulator cubicle in addition is carried out the early warning, also there is the through temperature, smog, fire light etc. single type sensor monitoring fire information, however, these all exist and acquire that conflagration characteristic kind is single, the principle respectively has self limitation, the coverage is little, receive factors such as environment to influence great grade defect, be difficult to satisfy the demand of the all-round accurate early warning in regulator cubicle practical application place.
Disclosure of Invention
An object of the utility model is to provide a regulator cubicle conflagration risk assessment early warning system based on multisource heterogeneous information, heterogeneous conflagration characteristic information signal through monitoring a plurality of sources of electric appliance cabinet, from different angles, the multidimensional parameter is to regulator cubicle conflagration state monitoring analysis, establish the risk assessment model, fuse a plurality of parameters and synthesize regulator cubicle conflagration risk, give the risk level, and produce hierarchical early warning, state maintenance strategy is provided, the early warning function of conflagration of all-round realization regulator cubicle, the early warning rate of accuracy of early warning has been improved.
In order to achieve the above purpose, the utility model adopts the following technical scheme: the electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information comprises an area host and acquisition terminal assemblies correspondingly arranged in a plurality of electrical cabinets, wherein the area host is in communication connection with the acquisition terminal assemblies.
Further, regional host computer includes first MCU, display module, first loRa communication module, alarm module and the outside cabinet temperature acquisition module, and display module, first loRa communication module, alarm module and the outside cabinet temperature acquisition module are connected with first MCU electricity.
Furthermore, a power module is further arranged in the regional host computer, and the power module is electrically connected with the temperature acquisition module outside the cabinet, the alarm module, the first MCU and the first LoRa communication module respectively.
Furthermore, the collection terminal component comprises an air exhaust collection module, a characteristic gas collection module, a thermionic collection module and a wireless temperature measurement module, the wireless temperature measurement module and the air exhaust collection module are installed in the electrical cabinet, the characteristic gas collection module and the thermionic collection module are arranged in the air exhaust collection module, and the air exhaust collection module, the characteristic gas collection module, the thermionic collection module and the wireless temperature measurement module are in communication connection with the regional host.
Further, the collection module of bleeding includes sampling chamber, adapter, second MCU, micropump, second loRa communication module and sampling pipe, and the sampling pipe is connected through the adapter to the sampling chamber, and micropump and second MCU install in the adapter, and second MCU is connected with micropump and second loRa communication module electricity respectively.
Furthermore, the sampling chamber is internally provided with an installation space for accommodating the characteristic gas acquisition module and the thermion acquisition module.
Further, the characteristic gas collection module comprises CO sensors respectively in communication connection with the regional hostSource wireless sensor, CO 2 Passive wireless sensor, SO 2 Passive wireless sensor, HCL passive wireless sensor, NO X Passive wireless sensor and O 3 A passive wireless sensor.
Furthermore, the pyrolysis ion collection module comprises a PM1.0 passive wireless sensor, a PM2.5 passive wireless sensor, a smoke monitoring sensor, a PM10 passive wireless sensor and a smoke passive wireless sensor which are respectively in communication connection with the regional host.
Furthermore, the alarm module is an alarm lamp.
The electrical cabinet fire risk assessment early warning method based on multi-source heterogeneous information comprises the steps of setting initial values for a plurality of fire characteristic information quantities of an electrical cabinet in a regional host, acquiring a plurality of fire characteristic information quantities of the electrical cabinet by online monitoring of a terminal assembly, and transmitting the fire characteristic information quantities to the regional host;
the regional host machine classifies the fire characteristic information quantities according to the data characteristics thereof to calculate initial value variables and measured value variables of the fire characteristic information quantities;
the regional host calculates one-way risk values corresponding to a plurality of fire characteristic information quantities according to the change rate of the difference between the measured value variable and the initial value variable, wherein the plurality of one-way risk values are multi-source heterogeneous characteristic quantities;
and performing fusion calculation on the multi-source heterogeneous characteristic quantities to obtain an overall risk value, judging fire risk levels of the electrical cabinets according to the risk evaluation model by combining the calculated single risk value and the fused overall risk value, judging whether to give an alarm according to the risk levels by the regional host, and displaying a corresponding maintenance strategy through the display module after giving the alarm.
Furthermore, the fire characteristic information quantities are n electrical cabinet temperature characteristic quantities, m characteristic gas characteristic quantities and l pyrolytic ion characteristic quantities respectively, and when the characteristic gas and the pyrolytic ion are collected, the characteristic gas is firstly pumped for 2 minutes and then collected.
Further, the n electrical cabinet temperature characteristic quantities comprise a contact temperature characteristic quantity of the electrical cabinet, a busbar joint temperature characteristic quantity, a cable joint temperature characteristic quantity and an environment temperature characteristic quantity in the cabinet body;the temperature values of the contact, the busbar and the cable can change along with the change of the size of the running load current flowing, so that the single-phase temperature characteristic quantity change of the contact, the busbar and the cable comprises the common influence of the load current, in order to prevent misjudgment and eliminate the common influence, an aspect ratio analysis method is adopted, firstly, the temperature characteristic quantity of a three-phase measuring point is transversely compared, the common influence generated by the load current is eliminated, the residual quantity is the temperature rise change caused by the fault, then, the change rate is longitudinally compared, the single-phase risk value is calculated, and the transverse comparison calculation formula is as follows:
wherein T is a 、T b 、T c The temperature values measured by the phase A, the phase B and the phase C of any one of the contact connection point, the busbar connection point and the cable connector are respectively, and r is any one of the characteristic quantity of the temperature of the contact connection point, the characteristic quantity of the temperature of the busbar connection point and the characteristic quantity of the temperature of the cable connector; the internal ambient temperature of cabinet adopts temperature value in the cabinet and regional main cabinet external temperature difference to do risk value analysis computational variable, eliminates the internal ambient temperature of cabinet and can be along with the influence that external environment temperature changes and change, and the computational formula is: y = T inter -T out (ii) a Wherein T is inger Is a value of ambient temperature measurement, T, in the cabinet out The temperature value measured outside the regional main cabinet is used, and y is the characteristic quantity of the environment temperature in the cabinet body; when the temperature characteristic quantities of the electrical cabinets are longitudinally compared, the change rate after the difference between the measured value variable and the initial value variable is adopted, the influence caused by different initial environments and different initial values of the electrical cabinets is eliminated, and the calculation formula of the change rate is as follows: r is a radical of hydrogen T ＝(x T -x T0 )/x T0 X is 100%; wherein r is T Is the characteristic change rate of the temperature of the electrical cabinet, x T Calculating a variable, x, for a current measurement of a characteristic quantity of the temperature of the electrical cabinet T0 And the initial value of the calculated variable of the temperature characteristic quantity of the electric cabinet is obtained.
Further, the calculation formula of the single risk value of the n electrical cabinet temperatures is as follows:
wherein h is i Is a single risk value, Y, of the temperature of the electrical cabinet I Early warning threshold value representing first-order risk, Y II Representing a second level risk early warning threshold, Y III Representing a third level risk early warning threshold, V I Represents a first-level early warning risk value V II Representing a secondary early warning risk value, V III Representing a tertiary early warning risk value.
Further, the characteristic gas characteristic quantities of the m electrical cabinets comprise CO and CO of the electrical cabinets 2 、SO 2 、HCL、NO X And O 3 The characteristic gas content of the electrical cabinet; the characteristic gas content of each electrical cabinet is longitudinally compared, the change rate after the difference between the measured value variable and the initial value variable is adopted, the influence caused by different initial environments and different initial values of the electrical cabinets is eliminated, and the calculation formula of the change rate is as follows: r is G ＝(x G -x G0 )/x G0 X is 100%; wherein r is G Characteristic gas characteristic change rate, x, for an electrical cabinet G Calculating a variable, x, for a current measurement of a characteristic gas quantity of an electrical cabinet G0 And the initial value of the calculated variable of the characteristic gas characteristic quantity of the electrical cabinet.
Further, the calculation formula of the single risk value of the characteristic gas characteristic quantities of the m electrical cabinets is as follows:
wherein h is j Is a single risk value, Y, of the characteristic gas of the electrical cabinet I Early warning threshold value representing first-order risk, Y II Representing secondary risk early warning threshold, Y III Representing a third level risk early warning threshold, V I Represents a first-level early warning risk value V II Representing a secondary early warning risk value, V III Representing a tertiary early warning risk value.
Further, the pyrolysis ion characteristic quantities of the l electrical cabinets comprise PM1.0, PM2.5, PM10 and smoke ion content of the electrical cabinets; the content of each pyrolytic ion is longitudinally compared and extractedThe change rate after the difference between the measured value variable and the initial value variable is used for eliminating the influence caused by different initial environments and different initial values of the electrical cabinet, and the calculation formula of the change rate is as follows: (ii) a r is P ＝(x p -x p0 )/x p0 X is 100%; wherein r is p For the rate of change of the pyrolytic ion characteristics of the electrical cabinet, x p Calculating a variable, x, for a current measurement of a feature quantity of a pyrolyzation ion of an electrical cabinet p0 And calculating the initial value of the variable of the characteristic quantity of the pyrolysis ions of the electric cabinet.
Further, the calculation formula of the individual risk value of the pyrolysis ion characteristic quantity of the l electrical cabinets is as follows:
wherein h is k Individual risk value, Y, of the pyrolytic ion characteristic of an electrical cabinet I Early warning threshold value representing first-order risk, Y II Representing secondary risk early warning threshold, Y III Representing a three-level risk early warning threshold, V I Represents a first-level early warning risk value V II Representing a secondary early warning risk value, V III Representing a tertiary early warning risk value.
Further, fusion calculation is carried out on n electrical cabinet temperature characteristic quantities, m characteristic gas characteristic quantities and l pyrolytic ion characteristic quantity risk values, and the calculation formula is as follows:
wherein
For the fused overall risk value, Q i The weight of the temperature characteristic value of each electrical cabinet is defined, and n is the number of the temperature characteristic quantities of the electrical cabinets; q j M is the number of the temperature characteristic quantity of the electrical cabinet, and is the weight of each characteristic gas characteristic value; q k And l is the number of the characteristic quantities of the pyrolysis ions, wherein the weight of each characteristic value of the pyrolysis ions is.
Further, the risk evaluation model divides the fire risk level of the electrical cabinet into a normal level, a attention level B, an abnormal level C and a serious level D, and the total risk value of each risk level is as follows:
further, when a plurality of electrical cabinets are arranged in the area, the last month is taken as a time window, the early warning proportion of the electrical cabinets of the same manufacturer and the same batch in the area is counted according to the early warning grades B, C and D, and when the proportion exceeds 30%, the early warning in the area is considered to be familial fire risk early warning.
Compared with the prior art, the utility model discloses following beneficial effect has: the regional host computer is used for simultaneously monitoring the plurality of electrical cabinets, the centralized monitoring operation of the plurality of electrical cabinets in each region is facilitated, the state of each electrical cabinet is integrated by the regional host computer according to the condition of the plurality of electrical cabinets in a single region, and whether familial fire risks exist in equipment in an intelligent analysis region or not is analyzed. And through monitoring heterogeneous fire characteristic information signals from multiple sources of the electric appliance cabinet, monitoring and analyzing the fire state of the electric cabinet from different angles and multidimensional parameters, the defect of monitoring by a single monitoring sensor is effectively avoided, the early fire early warning function of the electric cabinet is realized in an all-around manner, the occurrence of false alarm and missed alarm conditions is reduced, and the fire early warning accuracy is effectively improved.
Drawings
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic block diagram of the regional host of the present invention;
FIG. 3 is a schematic block diagram of the bleed air collection module of the present invention;
FIG. 4 is a flow chart of the present invention;
Detailed Description
Referring to fig. 1, the electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information comprises an area host and acquisition terminal assemblies correspondingly arranged in a plurality of electrical cabinets, wherein the area host is in communication connection with the acquisition terminal assemblies.
Referring to fig. 2, further, the regional host includes a first MCU, a display module, a first LoRa communication module, an alarm module, and an outside-cabinet temperature acquisition module, and the display module, the first LoRa communication module, the alarm module, and the outside-cabinet temperature acquisition module are electrically connected to the first MCU.
Further, still be provided with power module in the regional host computer, power module is connected with temperature acquisition module, alarm module, first MCU and the first loRa communication module electricity outside the cabinet respectively.
Referring to fig. 3, further, the collection terminal assembly comprises an air exhaust collection module, a characteristic gas collection module, a thermionic collection module and a wireless temperature measurement module, the wireless temperature measurement module and the air exhaust collection module are installed in the electrical cabinet, the characteristic gas collection module and the thermionic collection module are arranged in the air exhaust collection module, and the air exhaust collection module, the characteristic gas collection module, the thermionic collection module and the wireless temperature measurement module are in communication connection with the regional host.
Further, the collection module of bleeding includes sampling chamber, adapter, second MCU, micropump, second loRa communication module and sampling pipe, and the sampling pipe is connected through the adapter to the sampling chamber, and micropump and second MCU install in the adapter, and second MCU is connected with micropump and second loRa communication module electricity respectively.
Furthermore, the sampling chamber is internally provided with an installation space for accommodating the characteristic gas acquisition module and the thermion acquisition module.
Further, the characteristic gas acquisition module comprises a CO passive wireless sensor and a CO, wherein the CO passive wireless sensor and the CO have LoRa communication functions and are respectively in communication connection with the regional host 2 Passive wireless sensor, SO 2 Passive wireless sensor, HCL passive wireless sensor, NO X Passive wireless sensor and O 3 A passive wireless sensor.
Further, the pyrolysis ion collection module comprises a PM1.0 passive wireless sensor, a PM2.5 passive wireless sensor, a smoke monitoring sensor, a PM10 passive wireless sensor and a smoke passive wireless sensor which have LoRa communication functions and are respectively in communication connection with the regional host.
Furthermore, the alarm module is an alarm lamp.
The utility model discloses aassessment early warning method step is as follows:
referring to fig. 4, an electrical cabinet fire risk assessment early warning method based on multi-source heterogeneous information sets initial values for a plurality of fire characteristic information quantities in a regional host, wherein the plurality of fire characteristic information quantities are n electrical cabinet temperature characteristic quantities, m characteristic gas characteristic quantities and l pyrolytic ion characteristic quantities, and when characteristic gas and pyrolytic ion are collected, the characteristic gas and the pyrolytic ion are extracted for 2 minutes and then collected.
Collecting fire characteristic information quantity, pumping air for 2 minutes in the electrical cabinet by the collection terminal assembly, collecting characteristic gas and pyrolysis ions, and sending the characteristic gas and the pyrolysis ions to a regional host; the method comprises the steps of adopting an A, B and C three-phase measuring mode to collect the contact temperature of the electrical cabinet, the busbar contact temperature and the cable joint temperature, collecting the internal environment temperature of the cabinet and the external temperature of the regional host cabinet, and sending the collected temperature to a regional host.
Because the temperature values of the contact, the busbar and the cable can change along with the change of the size of the running load current flowing, the single-phase temperature characteristic quantity change of the contact, the busbar and the cable comprises the common influence of the load current, in order to prevent misjudgment and eliminate the common influence, an aspect ratio analysis method is adopted, firstly, the temperature characteristic quantity of a three-phase measuring point is transversely compared, the common influence generated by the load current is eliminated, the residual quantity is the temperature rise change caused by faults, and the contact temperature characteristic quantity, the busbar joint temperature characteristic quantity and the cable joint temperature characteristic quantity are calculated; the transverse comparison calculation formula is as follows:
wherein T is a 、T b 、T c The temperature values measured by the phase A, the phase B and the phase C of any one of the contact connection point, the busbar connection point and the cable connector are respectively, and r is any one of the characteristic quantity of the temperature of the contact connection point, the characteristic quantity of the temperature of the busbar connection point and the characteristic quantity of the temperature of the cable connector;
in order to eliminate the influence that the environment temperature in the cabinet body changes along with the change of the external environment temperature, the environment temperature in the cabinet body adopts the difference value between the temperature value in the cabinet and the temperature value outside the main cabinet of the areaDoing the risk value analysis computational variable, eliminating the influence that the internal environment temperature of cabinet can change along with external environment temperature change, calculating the internal environment temperature characteristic quantity of cabinet, the computational formula is: y = T inter -T out (ii) a Wherein T is inger Is a value of ambient temperature measurement, T, in the cabinet out The temperature value measured outside the main cabinet is a region, and y is the characteristic quantity of the environment temperature in the cabinet body.
The formula is then calculated according to the rate of change as: r is a radical of hydrogen T ＝(x T -x T0 )/x T0 X is 100%; calculated as the characteristic rate of change of the temperature of the electrical cabinet, wherein r T Is the characteristic rate of change, x, of the temperature of the electrical cabinet T Calculating a variable, x, for a current measurement of a characteristic quantity of the temperature of the electrical cabinet T0 And the initial value of the calculated variable of the temperature characteristic quantity of the electric cabinet is obtained.
Then, calculating the single risk values of the temperatures of the n electrical cabinets according to a single risk value calculation formula;
Then calculating the characteristic gas characteristic change rate of the electrical cabinet, wherein the characteristic gas characteristic quantities of the m electrical cabinets comprise CO and CO of the electrical cabinet 2 、SO 2 、HCL、NO X And O 3 The characteristic gas content of the electrical cabinet; the characteristic gas content of each electrical cabinet is longitudinally compared, the change rate after the difference between the measured value variable and the initial value variable is adopted, the influence caused by different initial environments and different initial values of the electrical cabinets is eliminated, and the calculation formula of the change rate is as follows: (ii) a r is G ＝(x G -x G0 )/x G0 ×100％；r G Characteristic gas characteristic rate of change for the electrical cabinet, where x G Characterizing gas characteristics for an electrical cabinetCurrent measurement of quantity calculating variable, x G0 And the initial value of the calculated variable of the characteristic gas characteristic quantity of the electrical cabinet.
Then calculating the single risk value of the characteristic gas characteristic quantity of the m electrical cabinets according to a single risk value calculation formula,
h j is a single risk value, Y, of the characteristic gas of the electrical cabinet I Early warning threshold value representing first-order risk, Y II Representing a second level risk early warning threshold, Y III Representing a three-level risk early warning threshold, V I Represents a first-level early warning risk value V II Representing the secondary early warning risk value V III Representing a tertiary early warning risk value.
Then calculating the characteristic change rate of the pyrolyzation ions of the electrical cabinets, wherein the characteristic quantities of the pyrolyzation ions of the electrical cabinets comprise PM1.0, PM2.5, PM10 and smoke ion content of the electrical cabinets; the content of each pyrolytic ion is longitudinally compared, the change rate after the difference between the measured value variable and the initial value variable is adopted, the influence caused by different initial environments and different initial values of the electrical cabinet is eliminated, and the calculation formula of the change rate is as follows: r is a radical of hydrogen P ＝(x-x 0 )/x 0 ×100％；r P ＝(x p -x p0 )/x p0 X 100%; wherein r is p For the rate of change of the pyrolytic ion characteristics, x, of the electrical cabinet p Calculating a variable, x, for a current measurement of a characteristic quantity of pyrolized ions of an electrical cabinet p0 And calculating the initial value of the variable of the characteristic quantity of the pyrolysis ions of the electric cabinet.
Then calculating the single risk value of the pyrolysis ion characteristic quantity of 1 electric cabinet according to a single risk value calculation formula,
h k individual risk value, Y, of pyrolyzation ion characteristic of electrical cabinet I Early warning threshold value representing first-order risk, Y II Representing a second level risk early warning threshold, Y III Representing a third level risk early warning threshold, V I Represents a first-level early warning risk value V II Representing a secondary early warning risk value, V III Representing a tertiary early warning risk value.
Performing fusion calculation on the calculated plurality of unidirectional risk values to obtain an overall risk value, and combining the calculated single risk value and the fused overall risk value, wherein the overall risk value calculation formula is as follows:
wherein
For the fused overall risk value, Q i The weight of the temperature characteristic value of each electrical cabinet is defined, and n is the number of the temperature characteristic quantities of the electrical cabinets; q j M is the number of the temperature characteristic quantities of the electrical cabinet as the weight of each characteristic gas characteristic value; q k And l is the number of the characteristic quantities of the pyrolysis ions, wherein the weight of each characteristic value of the pyrolysis ions is. And judging the fire risk level of each electric cabinet according to the risk evaluation model, judging whether to give an alarm or not according to the risk level by the regional host computer, displaying a corresponding maintenance strategy through the display module after giving the alarm, counting the early warning proportion of the electric cabinets of the same manufacturer and the same batch in the region according to the early warning levels B, C and D by taking the latest month as a time window when the electric cabinets in the region are multiple, and considering that the early warning in the region is familial fire risk early warning when the proportion exceeds 30 percent.
Calculation parameter for fire characteristic information quantity risk value of electric cabinet
Table 2 Electrical cabinet risk assessment model
Table 3 electric cabinet fire risk maintenance strategy
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing embodiments, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. Regulator cubicle conflagration risk assessment early warning system based on multisource heterogeneous information, characterized by: the system comprises an area host and acquisition terminal assemblies correspondingly arranged in a plurality of electrical cabinets, wherein the area host is in communication connection with the acquisition terminal assemblies, each acquisition terminal assembly comprises an air exhaust acquisition module, a characteristic gas acquisition module, a thermionic acquisition module and a wireless temperature measurement module, the wireless temperature measurement modules and the air exhaust acquisition modules are installed in the electrical cabinets, the characteristic gas acquisition modules and the thermionic acquisition modules are arranged in the air exhaust acquisition modules, and the air exhaust acquisition modules, the characteristic gas acquisition modules, the thermionic acquisition modules and the wireless temperature measurement modules are in communication connection with the area host.
2. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 1, wherein: the air exhaust collection module comprises a sampling chamber, an adapter, a second MCU, a micropump, a second LoRa communication module and a sampling pipe, wherein the sampling chamber is connected with the sampling pipe through the adapter, the micropump and the second MCU are installed in the adapter, and the second MCU is respectively electrically connected with the micropump and the second LoRa communication module.
3. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 1, wherein: and the sampling chamber is internally provided with an installation space for accommodating the characteristic gas acquisition module and the thermion acquisition module.
4. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 1, wherein: regional host computer includes first MCU, display module, first loRa communication module, alarm module and the outside cabinet temperature acquisition module, and display module, first loRa communication module, alarm module and the outside cabinet temperature acquisition module are connected with first MCU electricity.
5. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 4, wherein: still be provided with power module in the regional host computer, power module is connected with temperature acquisition module, alarm module, first MCU and a loRa communication module electricity outside the cabinet respectively.
6. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 1, wherein: the characteristic gas acquisition module comprises a CO passive wireless sensor and a CO which are respectively in communication connection with the regional host 2 Passive wireless sensor, SO2 passive wireless sensor, HCL passive wireless sensor, NO X Passive wireless sensor and O 3 A passive wireless sensor.
7. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 1, wherein: the pyrolysis ion acquisition module comprises a PM1.0 passive wireless sensor, a PM2.5 passive wireless sensor, a smoke monitoring sensor, a PM10 passive wireless sensor and a smoke passive wireless sensor which are respectively in communication connection with the regional host.
8. The electrical cabinet fire risk assessment and early warning system based on multi-source heterogeneous information as claimed in claim 5, wherein: the alarm module is an alarm lamp.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202222405395.6U CN218630962U (en) | 2022-09-08 | 2022-09-08 | Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202222405395.6U CN218630962U (en) | 2022-09-08 | 2022-09-08 | Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN218630962U true CN218630962U (en) | 2023-03-14 |
Family
ID=85465992
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202222405395.6U Active CN218630962U (en) | 2022-09-08 | 2022-09-08 | Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN218630962U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116107265A (en) * | 2023-04-13 | 2023-05-12 | 温康纳(常州)机械制造有限公司 | Remote control system and method for artificial board processing equipment |
| CN117975699A (en) * | 2024-03-29 | 2024-05-03 | 烟台信谊电器有限公司 | Intelligent regulator cubicle control governing system based on thing networking |
-
2022
- 2022-09-08 CN CN202222405395.6U patent/CN218630962U/en active Active
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116107265A (en) * | 2023-04-13 | 2023-05-12 | 温康纳(常州)机械制造有限公司 | Remote control system and method for artificial board processing equipment |
| CN117975699A (en) * | 2024-03-29 | 2024-05-03 | 烟台信谊电器有限公司 | Intelligent regulator cubicle control governing system based on thing networking |
| CN117975699B (en) * | 2024-03-29 | 2024-06-04 | 烟台信谊电器有限公司 | Intelligent regulator cubicle control governing system based on thing networking |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN218630962U (en) | Electrical cabinet fire risk assessment early warning system based on multi-source heterogeneous information | |
| CN106093720B (en) | High-voltage cable state monitoring system and its implementation based on protective grounding case | |
| CN112116776B (en) | System and method for predicting and monitoring cable fire in transformer substation | |
| CN101893672B (en) | Mine high-voltage cable state monitoring and fault diagnosis prewarning device | |
| CN116295595A (en) | Electrical cabinet fire risk assessment and early warning method based on multi-source heterogeneous information | |
| CN107219453B (en) | A kind of substation relay protection hidden failure diagnostic method based on Multidimensional and Hybrid amount | |
| CN111854855B (en) | Multi-scene cable fire characteristic quantity online monitoring method and device | |
| CN113013988A (en) | Intelligent power distribution cabinet based on double networks | |
| CN110474424A (en) | A kind of intelligent monitoring system used in distributing substation | |
| CN117055446A (en) | Electrical signal equipment monitoring system and method for analog signals | |
| CN106054763A (en) | Intelligent switch cabinet online measurement and control device | |
| CN112462176A (en) | Device and method for supporting detection of photovoltaic system direct current arc fault | |
| CN104698261B (en) | Power distribution station monitoring data exception discriminating method based on waveform pass zero point rate of change | |
| CN111024261A (en) | Method and system for monitoring cable joint by NB-IOT technology | |
| CN110412226A (en) | A kind of high-precision gas density monitor and system based on edge calculations | |
| CN112468086B (en) | Arc monitoring system and method applied to photovoltaic energy | |
| CN111711414B (en) | Photovoltaic power station fault detection device with maximum power | |
| CN110411894B (en) | Gas density monitoring system | |
| CN107807583A (en) | The internal environment detection method of electric power cabinet | |
| GU et al. | Research on intelligent early warning algorithm for distribution network considering extreme climate conditions | |
| CN212181599U (en) | Electric line fire early warning terminal | |
| EP3982087A1 (en) | An electricity metering device | |
| CN114594408A (en) | Non-electric quantity protection instant monitoring system for transformer | |
| CN111711415A (en) | Photovoltaic power station fault detection device with maximum power point tracking function | |
| CN212845848U (en) | Alternating current insulation monitoring device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |