CN117436711B - Liquefied gas steel cylinder supervision system and supervision method based on Internet of things - Google Patents
Liquefied gas steel cylinder supervision system and supervision method based on Internet of things Download PDFInfo
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- 239000010959 steel Substances 0.000 title claims abstract description 128
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17C—VESSELS FOR CONTAINING OR STORING COMPRESSED, LIQUEFIED OR SOLIDIFIED GASES; FIXED-CAPACITY GAS-HOLDERS; FILLING VESSELS WITH, OR DISCHARGING FROM VESSELS, COMPRESSED, LIQUEFIED, OR SOLIDIFIED GASES
- F17C2250/00—Accessories; Control means; Indicating, measuring or monitoring of parameters
- F17C2250/04—Indicating or measuring of parameters as input values
- F17C2250/0404—Parameters indicated or measured
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Abstract
The invention relates to the technical field of liquefied gas steel cylinder supervision systems, and particularly discloses an internet-of-things-based liquefied gas steel cylinder supervision system and an internet-of-things-based liquefied gas steel cylinder supervision method.
Description
Technical Field
The invention relates to the technical field of liquefied gas steel cylinder supervision systems, in particular to a liquefied gas steel cylinder supervision system and a supervision method based on the Internet of things.
Background
Liquefied petroleum gas is widely applied to the aspects of resident life, catering service, automobile gas filling, industrial production and the like, and a liquefied petroleum gas steel cylinder is used for storing the liquefied petroleum gas.
As disclosed in patent application No. 201910759043.0, the system for supervising the liquefied gas steel cylinders comprises an intelligent distribution terminal for collecting relevant information, a management platform for receiving information and supervising the information in real time, and an RFID tag on the liquefied gas steel cylinders. The supervision method comprises the following steps: 1. binding the steel bottle, and recording the loading position of the steel bottle by the management platform; 2. the management platform monitors the running track in the steel cylinder distribution; 3. when the vehicle arrives at a delivery place, the steel cylinder is disassembled, and the vehicle is unbundled; 4. the steel cylinder is bound with a user, and the management platform records the use position of the steel cylinder; 5. recovering empty bottles and binding the vehicle bottles; 6. returning to the liquefied gas enterprise or the supply station, unloading the empty bottle, and registering for storage.
According to the scheme, safety monitoring of the liquefied gas steel cylinders in the distribution process is achieved, but in the prior art, safety supervision of the liquefied gas steel cylinders in an operation area is lacked, and the safety monitoring has a large limitation.
Disclosure of Invention
The invention aims to provide a monitoring system and a monitoring method for a liquefied gas steel cylinder based on the Internet of things, wherein the monitoring behavior items of the liquefied gas steel cylinder to be monitored are processed, the monitoring behavior items of which the monitoring data do not meet the preset data requirements are recorded as monitoring evaluation items, the monitoring evaluation item deviation values and the preset deviation coefficients of the monitoring evaluation items are processed to obtain the evaluation risk coefficient of each monitoring evaluation item of the liquefied gas steel cylinder, further the evaluation risk total value of the monitoring evaluation item of the liquefied gas steel cylinder is obtained, and the risk base number of the liquefied gas steel cylinder is obtained based on the evaluation risk total value and the monitoring evaluation ratio of the liquefied gas steel cylinder, namely, the greater the risk base number of the liquefied gas steel cylinder is, the higher the potential risk degree of the liquefied gas steel cylinder is, and the state monitoring of a single liquefied gas steel cylinder is realized.
The aim of the invention can be achieved by the following technical scheme:
the method for supervising the liquefied gas steel cylinders based on the Internet of things comprises the following steps:
step one: acquiring the using state of the liquefied gas steel cylinder, and obtaining the risk base number of the liquefied gas steel cylinder based on the using state of the liquefied gas steel cylinder;
step two: acquiring an operation area corresponding to the liquefied gas steel cylinder, dividing the operation area corresponding to the liquefied gas steel cylinder into a plurality of area subunits, acquiring an area risk total value of each area subunit, and calculating the ratio of the area risk total value to the area value of each area subunit to obtain an area subunit risk coefficient;
step three: obtaining a regional subunit road coefficient of the regional subunit, processing the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifying the regional subunit risk degree based on the regional subunit risk potential value;
step four: and acquiring a target unit maintenance priority value corresponding to the regional subunits with the same risk degree, and maintaining the regional subunits with the same risk degree according to the ordering sequence of the target unit maintenance priority value.
As a further scheme of the invention: in the first step, the acquisition process of the risk base number of the liquefied gas steel cylinder comprises the following steps:
each item to be monitored of the liquefied gas steel cylinder is respectively recorded as a monitoring action item, and monitoring data of the monitoring action item of the liquefied gas steel cylinder in a period are obtained;
acquiring preset data requirements of corresponding supervision behavior items, and recording supervision behavior items, of which the monitoring data do not meet the preset data requirements, in a period as supervision evaluation items;
and calculating the ratio of the number of the supervision evaluation items to the number of the supervision behavior items to obtain a monitoring evaluation ratio.
As a further scheme of the invention: performing difference value calculation on the monitoring data of the supervision evaluation item and the preset data of the supervision behavior item to obtain a supervision evaluation item deviation value;
acquiring a preset deviation coefficient of each supervision evaluation item;
carrying out product operation on the deviation value of each supervision evaluation item of the liquefied gas steel cylinder and the preset deviation coefficient of each supervision evaluation item to obtain the estimated risk coefficient of each supervision evaluation item of the liquefied gas steel cylinder;
summing the estimated risk coefficients of all the supervision and evaluation items of the liquefied gas steel cylinder and taking an average value to obtain an estimated risk total value of the liquefied gas steel cylinder;
and carrying out product operation on the total risk assessment value and the monitoring and evaluation ratio of the liquefied gas steel cylinder to obtain the risk base number of the liquefied gas steel cylinder.
As a further scheme of the invention: in the third step, the obtaining process of the road coefficient of the regional subunit is as follows:
the method comprises the steps of obtaining the number of main roads in a region subunit, obtaining the road value of each main road, adding the road values of all the main roads to obtain a region subunit road total value, and calculating the ratio of the region subunit road total value to the region subunit area value to obtain a region subunit road coefficient.
As a further scheme of the invention: the road value of the main road is obtained by the following steps:
acquiring road data of a main road, wherein the road data comprises the number of lanes of the main road, the number of road intersections and the frequency of road accidents, and processing the road data to obtain road factors of the main road;
acquiring behavior data of a main road, wherein the behavior data comprise the traffic flow of the main road, the traffic flow of the main road and the road surface quality of the main road, and processing the behavior data to obtain a main road behavior factor;
and processing the main road factors and the main road behavior factors to obtain road values of the main road.
As a further scheme of the invention: marking the risk coefficient of the regional subunit as Qf;
marking the road coefficient of the regional subunit as Qd;
by the formula qn=Calculating to obtain a region subunit risk potential value Qn, wherein a1, a2 and a3 are preset proportionality coefficients, and a1, a2 and a3 are larger than zero;
where Qr is the population density value within the regional subunit.
As a further scheme of the invention: presetting a first limit value of a region subunit risk potential value as Qn1 and a first limit value of a region subunit risk potential value as Qn2, wherein the first limit value of the region subunit risk potential value Qn1 < the first limit value of the region subunit risk potential value Qn2;
if Qn is less than Qn1, the potential risk degree of the regional subunit is low, and a low-risk regional signal is obtained;
if Qn1 is less than or equal to Qn < Qn2, the potential risk degree of the regional subunit is indicated to be medium, and a risk regional signal is obtained;
if Qn is more than or equal to Qn2, the potential risk degree of the regional subunit is high, and a high-risk regional signal is obtained.
As a further scheme of the invention: selecting any region subunit in the high risk region based on the high risk region signal, and marking the region subunit as a target unit;
acquiring a region subunit adjacent to the target unit, and marking the region subunit as an adjacent region unit;
acquiring the risk potential values of the regional subunits of the adjacent regional units, summing the risk potential values of the regional subunits of all the adjacent regional units, and taking the average value to acquire the risk potential values of the adjacent regional units;
and obtaining the number value of the adjacent area unit, and carrying out product operation on the number value of the adjacent area unit and the adjacent risk potential value to obtain the maintenance priority value of the target unit.
As a further scheme of the invention: and sequencing all the regional subunits in the high-risk region according to the order of the target unit maintenance priority values from large to small to obtain the regional subunit maintenance order.
As another embodiment of the present invention: a liquefied gas steel cylinder supervision system based on the internet of things, comprising:
the system comprises a single risk acquisition module, a cloud management and control platform and a storage module, wherein the single risk acquisition module is used for acquiring the use state of a liquefied gas steel cylinder, acquiring the risk base number of the liquefied gas steel cylinder based on the use state of the liquefied gas steel cylinder, and transmitting the risk base number of the liquefied gas steel cylinder to the cloud management and control platform;
the regional risk identification module is used for acquiring an operation region corresponding to the liquefied gas steel cylinder, dividing the operation region corresponding to the liquefied gas steel cylinder into a plurality of regional subunits, acquiring a regional risk total value of each regional subunit, calculating the ratio of the regional risk total value to the area value of each regional subunit to obtain a regional subunit risk coefficient, and transmitting the regional subunit risk coefficient to the cloud management and control platform;
the risk area decision module receives the regional subunit risk coefficient transmitted by the cloud management and control platform, acquires the regional subunit road coefficient of the regional subunit, processes the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifies the regional subunit risk degree based on the regional subunit risk potential value;
the maintenance processing module is used for acquiring the maintenance priority values of the target units corresponding to the regional subunits with the same risk degree, and maintaining the regional subunits with the same risk degree according to the ordering sequence of the maintenance priority values of the target units.
The invention has the beneficial effects that:
according to the invention, the monitoring behavior items of the liquefied gas steel cylinders needing to be monitored are processed, the monitoring behavior items of which the monitoring data do not meet the requirements of preset data are recorded as monitoring evaluation items, the monitoring risk coefficient of each monitoring evaluation item of the liquefied gas steel cylinders is obtained by processing the monitoring evaluation item deviation value and the preset deviation coefficient of the monitoring evaluation item, the total risk assessment value of the monitoring evaluation item of the liquefied gas steel cylinders is obtained, the risk base of the liquefied gas steel cylinders is obtained based on the total risk assessment value and the monitoring evaluation ratio of the liquefied gas steel cylinders, namely, the greater the risk base of the liquefied gas steel cylinders is, the higher the potential risk degree of the liquefied gas steel cylinders is, and the state monitoring of single liquefied gas steel cylinders is realized;
the method comprises the steps of dividing an operation area corresponding to a liquefied gas steel cylinder into a plurality of area subunits, obtaining the number of the liquefied gas steel cylinders in each area subunit, and summing risk bases corresponding to all the liquefied gas steel cylinders to obtain an area risk total value; calculating the ratio of the total regional risk value to the area value of the regional subunit to obtain a regional subunit risk coefficient, processing the arterial road in the regional subunit to obtain a regional subunit road coefficient, combining the population density value of the regional subunit to obtain a regional subunit risk potential value, indicating that the arterial road in the regional subunit is crowded and the flow of people is large according to the regional subunit risk potential value, and obviously delaying the rescue time and the rescue degree of the regional subunit, particularly increasing rescue difficulty during rush hours and rush hours when the regional subunit is alert, so as to finish the division of the operation regional risk degree corresponding to the liquefied gas steel cylinders;
the high risk area subunit is marked as a target unit in the invention; acquiring a region subunit adjacent to the target unit, and marking the region subunit as an adjacent region unit; acquiring the risk potential values of the regional subunits of the adjacent regional units, summing the risk potential values of the regional subunits of all the adjacent regional units, and taking the average value to acquire the risk potential values of the adjacent regional units; obtaining the number value of the adjacent area unit, and carrying out product operation on the number value of the adjacent area unit and the adjacent risk potential value to obtain a target unit maintenance priority value; sequencing all the area subunits in the high-risk area according to the target unit maintenance priority value in order from large to small, and maintaining all the area subunits in the high-risk area according to the sequencing order, thereby determining the maintenance sequence of the area subunits with the same risk degree.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for monitoring a liquefied gas steel cylinder based on the Internet of things according to an embodiment;
fig. 2 is a flow diagram of an internet of things-based liquefied gas steel cylinder supervision system according to an embodiment.
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.
Example 1
Referring to fig. 1, the invention discloses a method for supervising a liquefied gas steel cylinder based on internet of things, which comprises the following steps:
step one: acquiring the using state of the liquefied gas steel cylinder, and obtaining the risk base number of the liquefied gas steel cylinder based on the using state of the liquefied gas steel cylinder;
step two: acquiring an operation area corresponding to the liquefied gas steel cylinder, dividing the operation area corresponding to the liquefied gas steel cylinder into a plurality of area subunits, acquiring an area risk total value of each area subunit, and calculating the ratio of the area risk total value to the area value of each area subunit to obtain an area subunit risk coefficient;
step three: obtaining a regional subunit road coefficient of the regional subunit, processing the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifying the regional subunit risk degree based on the regional subunit risk potential value;
step four: and acquiring a target unit maintenance priority value corresponding to the regional subunits with the same risk degree, and maintaining the regional subunits with the same risk degree according to the ordering sequence of the target unit maintenance priority value.
The acquisition process of the risk base number of the liquefied gas steel cylinder comprises the following steps:
each item to be monitored of the liquefied gas steel cylinder is respectively recorded as a monitoring action item, and monitoring data of the monitoring action item of the liquefied gas steel cylinder in a period are obtained;
acquiring preset data requirements of corresponding supervision behavior items, and recording supervision behavior items, of which the monitoring data do not meet the preset data requirements, in a period as supervision evaluation items;
calculating the ratio of the number of the supervision evaluation items to the number of the supervision behavior items to obtain a monitoring evaluation ratio;
wherein, the supervision behavior items include, but are not limited to, the service life value, the air tightness value and the valve state value of the liquefied gas steel cylinder in the period;
wherein, each item of data of the liquefied gas steel cylinder is obtained by monitoring by maintenance personnel in a maintenance period;
the service life value is the difference value between the time when the liquefied gas steel cylinder is put into service and the current time;
acquiring a pressure value detected by a maintainer on a liquefied gas steel cylinder in a maintenance period;
the method comprises the steps of obtaining pressure values of a liquefied gas steel cylinder in a plurality of continuous maintenance periods before a current maintenance period by maintenance personnel, forming a multi-period pressure value group detected by the liquefied gas steel cylinder, and processing the multi-period pressure value group detected by the liquefied gas steel cylinder according to a variance calculation formula to obtain variance values of the multi-period pressure value group detected by the liquefied gas steel cylinder, wherein the variance values are air tightness values;
wherein the number of cycles of the plurality of consecutive maintenance cycles is not less than five cycles;
obtaining abnormal frequency of leakage or blockage of a valve of the liquefied gas steel cylinder from the time when the liquefied gas steel cylinder is put into use to the current time, wherein the abnormal frequency is a valve state value;
performing difference value calculation on the monitoring data of the supervision evaluation item and the preset data of the supervision behavior item to obtain a supervision evaluation item deviation value;
acquiring a preset deviation coefficient of each supervision evaluation item, wherein the larger the data of the preset deviation coefficient is, the higher the supervision risk degree of the corresponding supervision evaluation item is, and the preset deviation coefficient is an experience value and is preset by maintenance personnel according to working experience;
carrying out product operation on the deviation value of each supervision evaluation item of the liquefied gas steel cylinder and the preset deviation coefficient of each supervision evaluation item to obtain the estimated risk coefficient of each supervision evaluation item of the liquefied gas steel cylinder;
summing the estimated risk coefficients of all the supervision and evaluation items of the liquefied gas steel cylinder and taking an average value to obtain an estimated risk total value of the liquefied gas steel cylinder;
and carrying out product operation on the total risk assessment value and the monitoring and evaluation ratio of the liquefied gas steel cylinder to obtain the risk base number of the liquefied gas steel cylinder.
Such periods include, but are not limited to, a worship, a month, or a quarter.
Acquiring an operation area corresponding to the liquefied gas steel cylinder, and dividing the operation area corresponding to the liquefied gas steel cylinder into a plurality of area subunits;
wherein, the principle of dividing the operation area into a plurality of area subunits includes, but is not limited to, grid division or administrative area division (communities);
acquiring the number of the liquefied gas cylinders in each regional subunit, and summing the risk bases corresponding to all the liquefied gas cylinders to obtain a regional risk total value;
calculating the ratio of the total regional risk value to the area value of the regional subunit to obtain a regional subunit risk coefficient;
acquiring the number of main roads in the area subunit, acquiring the road value of each main road, adding the road values of all the main roads to obtain the total road value of the area subunit, and calculating the ratio of the total road value of the area subunit to the area value of the area subunit to obtain the road coefficient of the area subunit;
the road value acquisition process of the main road is as follows:
acquiring road data and behavior data of a main road;
the road data comprises the number of lanes of the main road, the number of road intersections and the frequency of road accidents;
marking the number of lanes of the main road as Z1;
marking the number of road intersections of the main road as Z2;
marking the road accident frequency of a main road as Z3;
by the formulaCalculating to obtain a main road factor Z;
the behavior data comprise the traffic flow of the main road, the traffic flow of the main road and the road surface quality of the main road;
marking the traffic of the arterial road as R1;
marking the traffic flow of a main road as R2;
marking the road surface quality of a main road as R3;
by the formula RCalculated to obtainA main road behavior factor R;
the road surface quality of the main road is obtained through the following steps:
indicators of road surface flatness, damage condition, bearing capacity and anti-skid capacity of a main road;
marking the road surface flatness of the main road as P1;
marking the damage condition of the main road as P2;
marking the bearing capacity of the main road as P3;
marking the anti-skid capability index of the main road as P4;
weighting indexes of road surface evenness, damage condition, bearing capacity and anti-skid capacity of the main road;
that is, the road surface quality of the main road is obtained through a formula lp=p1xd1+p2xd2+p3xd3+p4xd4, wherein d1, d2, d3 and d4 respectively represent weight values occupied by road surface evenness, damage condition, bearing capacity and anti-skid capacity indexes, d1+d2+d3+d4=1;
processing the arterial road factor Z and the arterial road behavior factor R, namely by a formulaAcquiring a road value ZR, < ->Is a preset proportionality coefficient;
acquiring population density values in the regional subunits, and marking the population density values as Qr;
marking the risk coefficient of the regional subunit as Qf;
marking the road coefficient of the regional subunit as Qd;
by the formula qn=And calculating to obtain a region subunit risk potential value Qn, wherein a1, a2 and a3 are preset proportionality coefficients, and a1, a2 and a3 are all larger than zero.
The formula for acquiring the risk potential value of the regional subunit can be known as follows:
the larger the risk coefficient of the regional subunit is, the more the number of the liquefied gas steel cylinders in the regional subunit is, and the larger the risk base number of the liquefied gas steel cylinders in the regional subunit is, the larger the risk potential value of the regional subunit is;
the larger the road coefficient of the regional subunit is, the more crowded the main road in the regional subunit is, the large the traffic flow is, when the regional subunit is warned, the rescue time and the rescue degree of the regional subunit are obviously delayed, especially during rush hours and rush hours, the more difficult the rescue is increased, and the larger the obtained regional subunit risk potential value is.
Presetting a first limit value of a region subunit risk potential value as Qn1 and a first limit value of a region subunit risk potential value as Qn2, wherein the first limit value of the region subunit risk potential value Qn1 < the first limit value of the region subunit risk potential value Qn2;
if Qn is less than Qn1, the potential risk degree of the regional subunit is low, and a low-risk regional signal is obtained;
if Qn1 is less than or equal to Qn < Qn2, the potential risk degree of the regional subunit is indicated to be medium, and a risk regional signal is obtained;
if Qn is more than or equal to Qn2, the potential risk degree of the regional subunit is high, and a high-risk regional signal is obtained.
Based on the identification of the potential risk degree of the regional subunit, the maintainers can conduct targeted processing on the different regional subunits, namely, the processing priority of the maintainers on the region with high potential risk degree of the regional subunit is higher than that of the region with medium potential risk degree of the regional subunit, and the processing priority of the region with medium potential risk degree of the regional subunit is higher than that of the region with low potential risk degree of the regional subunit, so that the maintainers can conveniently conduct visual management on the operation region corresponding to the liquefied gas steel cylinder.
Example 2
On the basis of embodiment 1, the problem of maintenance priority of regional subunits at the same potential risk level is solved:
specifically, in this embodiment, a high risk area signal is obtained, and all the area subunits within a high potential risk level of the area subunits are processed;
selecting any high-risk area subunit, and marking the high-risk area subunit as a target unit;
acquiring a region subunit adjacent to the target unit, and marking the region subunit as an adjacent region unit;
acquiring the risk potential values of the regional subunits of the adjacent regional units, summing the risk potential values of the regional subunits of all the adjacent regional units, and taking the average value to acquire the risk potential values of the adjacent regional units;
obtaining the number value of the adjacent area unit, and carrying out product operation on the number value of the adjacent area unit and the adjacent risk potential value to obtain a target unit maintenance priority value;
and sequencing all the area subunits in the high-risk area according to the order of the target unit maintenance priority values, and carrying out maintenance processing on all the area subunits in the high-risk area according to the sequencing order.
Example 3
Referring to fig. 2, the present invention is a liquefied gas steel cylinder supervision system based on internet of things, comprising:
the system comprises a monomer risk acquisition module, a regional risk identification module, a risk region decision module, a maintenance processing module and a cloud management and control platform;
the monomer risk acquisition module, the regional risk identification module, the risk region decision module and the maintenance processing module are electrically connected with the cloud management and control platform.
The monomer risk acquisition module is used for acquiring the using state of the liquefied gas steel cylinder, acquiring the risk base number of the liquefied gas steel cylinder based on the using state of the liquefied gas steel cylinder, and transmitting the risk base number of the liquefied gas steel cylinder to the cloud management and control platform;
the regional risk identification module is used for acquiring an operation region corresponding to the liquefied gas steel cylinder, dividing the operation region corresponding to the liquefied gas steel cylinder into a plurality of regional subunits, acquiring a regional risk total value of each regional subunit, calculating the ratio of the regional risk total value to the area value of each regional subunit to obtain a regional subunit risk coefficient, and transmitting the regional subunit risk coefficient to the cloud management and control platform;
the risk area decision module receives the regional subunit risk coefficient transmitted by the cloud management and control platform, acquires the regional subunit road coefficient of the regional subunit, processes the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifies the regional subunit risk degree based on the regional subunit risk potential value;
the maintenance processing module is used for acquiring the target unit maintenance priority value corresponding to the regional subunits with the same risk degree, and maintaining the regional subunits with the same risk degree according to the ordering sequence of the target unit maintenance priority value.
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 (8)
1. The method for supervising the liquefied gas steel cylinders based on the Internet of things is characterized by comprising the following steps of:
step one: acquiring the using state of the liquefied gas steel cylinder, and obtaining the risk base number of the liquefied gas steel cylinder based on the using state of the liquefied gas steel cylinder;
step two: acquiring an operation region corresponding to the liquefied gas steel cylinder, dividing the operation region corresponding to the liquefied gas steel cylinder into a plurality of region subunits, acquiring a region risk total value of each region subunit, and calculating the ratio of the region risk total value to the area value of the region subunit to obtain a region subunit risk coefficient;
step three: obtaining a regional subunit road coefficient of the regional subunit, processing the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifying the regional subunit risk degree based on the regional subunit risk potential value;
step four: acquiring a target unit maintenance priority value corresponding to the regional subunits with the same risk degree, and maintaining the regional subunits with the same risk degree according to the ordering sequence of the target unit maintenance priority value;
in the third step, the obtaining process of the road coefficient of the regional subunit is as follows:
acquiring the number of main roads in the area subunit, acquiring the road value of each main road, adding the road values of all the main roads to obtain an area subunit road total value, and calculating the ratio of the area subunit road total value to the area value of the area subunit to obtain an area subunit road coefficient;
the road value of the main road is obtained by the following steps:
acquiring road data of a main road, wherein the road data comprises the number of lanes of the main road, the number of road intersections and the frequency of road accidents, and processing the road data to obtain road factors of the main road;
acquiring behavior data of a main road, wherein the behavior data comprise the traffic flow of the main road, the traffic flow of the main road and the road surface quality of the main road, and processing the behavior data to obtain a main road behavior factor;
and processing the main road factors and the main road behavior factors to obtain road values of the main road.
2. The method for supervising the liquefied gas steel cylinders based on the internet of things according to claim 1, wherein in the first step, the risk base number of the liquefied gas steel cylinders is obtained by:
each item to be monitored of the liquefied gas steel cylinder is respectively recorded as a monitoring action item, and monitoring data of the monitoring action item of the liquefied gas steel cylinder in a period are obtained;
acquiring preset data requirements of corresponding supervision behavior items, and recording supervision behavior items, of which the monitoring data do not meet the preset data requirements, in a period as supervision evaluation items;
and calculating the ratio of the number of the supervision evaluation items to the number of the supervision behavior items to obtain a monitoring evaluation ratio.
3. The method for supervising the liquefied gas steel cylinders based on the Internet of things according to claim 2, wherein difference value calculation is carried out on the monitoring data of the supervision evaluation item and the preset data of the supervision behavior item to obtain a deviation value of the supervision evaluation item;
acquiring a preset deviation coefficient of each supervision evaluation item;
carrying out product operation on the deviation value of each supervision evaluation item of the liquefied gas steel cylinder and the preset deviation coefficient of each supervision evaluation item to obtain the estimated risk coefficient of each supervision evaluation item of the liquefied gas steel cylinder;
summing the estimated risk coefficients of all the supervision and evaluation items of the liquefied gas steel cylinder and taking an average value to obtain an estimated risk total value of the liquefied gas steel cylinder;
and then carrying out product operation on the total risk evaluation value and the monitoring evaluation ratio of the liquefied gas steel cylinder to obtain the risk base number of the liquefied gas steel cylinder.
4. The method for supervising the liquefied gas steel cylinders based on the internet of things according to claim 1, wherein in the third step, the risk coefficient of the regional subunit is marked as Qf;
marking the road coefficient of the regional subunit as Qd;
by the formula qn=Calculating to obtain a region subunit risk potential value Qn, wherein a1, a2 and a3 are preset proportionality coefficients, and a1, a2 and a3 are larger than zero;
where Qr is the regional subunit population density value.
5. The internet of things-based liquefied gas steel cylinder supervision method according to claim 4, wherein a first limit value of a risk potential value of the preset area subunit is Qn1, and a second limit value of the risk potential value of the area subunit is Qn2, wherein the first limit value Qn1 of the risk potential value of the area subunit is less than the second limit value Qn2 of the risk potential value of the area subunit;
if Qn is less than Qn1, the potential risk degree of the regional subunit is low, and a low-risk regional signal is obtained;
if Qn1 is less than or equal to Qn < Qn2, the potential risk degree of the regional subunit is indicated to be medium, and a risk regional signal is obtained;
if Qn is more than or equal to Qn2, the potential risk degree of the regional subunit is high, and a high-risk regional signal is obtained.
6. The method for supervising the liquefied gas steel cylinders based on the internet of things according to claim 5, wherein any regional subunit in a high risk region is selected based on a high risk region signal, and the regional subunit is marked as a target unit;
acquiring a region subunit adjacent to the target unit, and marking the region subunit as an adjacent region unit;
acquiring the risk potential values of the regional subunits of the adjacent regional units, summing the risk potential values of the regional subunits of all the adjacent regional units, and taking the average value to acquire the risk potential values of the adjacent regional units;
and obtaining the number value of the adjacent area unit, and carrying out product operation on the number value of the adjacent area unit and the adjacent risk potential value to obtain the maintenance priority value of the target unit.
7. The method for supervising the liquefied gas steel cylinders based on the internet of things according to claim 6, wherein all the regional subunits in the high risk region are sequenced according to the order of the target unit maintenance priority values from large to small, and the regional subunit maintenance order is obtained.
8. Based on thing networking liquefied gas steel bottle supervisory systems, its characterized in that includes:
the system comprises a single risk acquisition module, a cloud management and control platform and a storage module, wherein the single risk acquisition module is used for acquiring the use state of a liquefied gas steel cylinder, acquiring the risk base number of the liquefied gas steel cylinder based on the use state of the liquefied gas steel cylinder, and transmitting the risk base number of the liquefied gas steel cylinder to the cloud management and control platform;
the regional risk identification module is used for acquiring an operation region corresponding to the liquefied gas steel cylinder, dividing the operation region corresponding to the liquefied gas steel cylinder into a plurality of regional subunits, acquiring a regional risk total value of each regional subunit, calculating the ratio of the regional risk total value to the area value of each regional subunit to obtain a regional subunit risk coefficient, and transmitting the regional subunit risk coefficient to the cloud management and control platform;
the risk area decision module receives the regional subunit risk coefficient transmitted by the cloud management and control platform, acquires the regional subunit road coefficient of the regional subunit, processes the regional subunit road coefficient, the regional subunit risk coefficient and the regional subunit population density value to obtain a regional subunit risk potential value, and identifies the regional subunit risk degree based on the regional subunit risk potential value;
the maintenance processing module is used for acquiring the maintenance priority values of the target units corresponding to the regional subunits with the same risk degree and maintaining the regional subunits with the same risk degree according to the ordering sequence of the maintenance priority values of the target units;
the acquisition process of the road coefficient of the regional subunit comprises the following steps:
acquiring the number of main roads in the area subunit, acquiring the road value of each main road, adding the road values of all the main roads to obtain an area subunit road total value, and calculating the ratio of the area subunit road total value to the area value of the area subunit to obtain an area subunit road coefficient;
the road value of the main road is obtained by the following steps:
acquiring road data of a main road, wherein the road data comprises the number of lanes of the main road, the number of road intersections and the frequency of road accidents, and processing the road data to obtain road factors of the main road;
acquiring behavior data of a main road, wherein the behavior data comprise the traffic flow of the main road, the traffic flow of the main road and the road surface quality of the main road, and processing the behavior data to obtain a main road behavior factor;
and processing the main road factors and the main road behavior factors to obtain road values of the main road.
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