CN110956409B - Community gas equipment risk control method and device - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for controlling risks of community gas equipment, wherein the method comprises the following steps: acquiring the current states of all community gas equipment and corresponding state variables on a risk path with a disaster causing risk; the state variable corresponding to each community gas device is at least one; and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the empirical values of the state variables, and controlling the state variables corresponding to the abnormal community gas equipment. According to the risk control method and device for the community gas equipment, provided by the embodiment of the invention, the state variables corresponding to the abnormal community gas equipment are controlled by acquiring the community gas equipment on the risk path with the disaster causing risk and acquiring the current state and the abnormal state of the state variables corresponding to the community gas equipment, so that the automatic control of the abnormal risk source is realized, and the automatic hidden danger elimination after the hidden danger of the gas is found can be realized.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to a risk control method and device for community gas equipment.
Background
At present, gas is an indispensable living energy source in families, and the use safety of the gas becomes a problem worthy of vigilance more and more. The gas equipment in the community is complex to deploy and comprises various pipelines, valves and the like, and faults can occur in any place, so that potential risks such as gas leakage are brought.
At present, for a possible fault such as gas leakage, a resident generally installs a gas alarm or the like at home. However, these devices can only prompt that risks such as gas leakage occur, but cannot automatically eliminate hidden dangers, and people are required to search for other methods to find and eliminate hidden dangers.
Disclosure of Invention
In order to solve the problems in the prior art, embodiments of the present invention provide a method and an apparatus for risk control of a community gas appliance.
In a first aspect, an embodiment of the present invention provides a risk control method for a community gas appliance, including: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one; and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
Further, after the controlling the state variables corresponding to the abnormal gas devices in each community, the method further includes: acquiring the current state of the state variable after control according to a preset time period, and judging whether the state variable is recovered to be normal or not according to the current state of the state variable after control; and if the state variable which is not recovered to be normal is judged and known, further controlling the corresponding state variable.
Further, the state variable has a preset danger level; wherein a higher risk level indicates a greater degree of risk; the control of the state variable corresponding to each abnormal community gas device comprises: and acquiring the danger level of the state variable corresponding to the abnormal community gas equipment, and sequentially controlling the state variable corresponding to the abnormal community gas equipment according to the danger level.
Further, the obtaining the current state of the state variable corresponding to each community gas device includes: acquiring the current state of the state variable corresponding to each community gas device through a preset sensor; the control of the state variable corresponding to each abnormal community gas device comprises: and controlling the state variables corresponding to the abnormal community gas equipment through a preset actuator and a preset controller.
Further, the method further comprises: and performing machine learning training through the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value.
Further, before the acquiring the individual community gas appliances on the risk path with the disaster causing risk, the method further includes: and determining the risk path with the disaster causing risk through a conditional random field CRF model.
Further, the determining the risk path with the disaster-causing risk through the conditional random field CRF model includes: inputting each community gas device corresponding to the risk path and a label value corresponding to each community gas device into the conditional random field CRF model; determining that the risk path has disaster-causing risk according to a comparison result that the output value of the conditional random field CRF model is larger than a corresponding preset threshold value; and the labeled value represents the possibility of the fault of the community gas equipment.
In a second aspect, an embodiment of the present invention provides a risk control device for a community gas appliance, including: a state variable state acquisition module configured to: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one; a state variable control module to: and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method provided in the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method as provided in the first aspect.
According to the risk control method and device for the community gas equipment, provided by the embodiment of the invention, the automatic control on the abnormal risk source is realized by acquiring each community gas equipment on the risk path with the disaster causing risk, acquiring the current state and the abnormal state of the state variable corresponding to each community gas equipment and controlling the state variable corresponding to each abnormal community gas equipment, and the automatic hidden danger elimination after the hidden danger of the gas is found can be realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a risk control method for community gas appliances according to an embodiment of the present invention;
FIG. 2 is a schematic view of a risk control structure of a community gas appliance according to an embodiment of the present invention;
fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a risk control method for a community gas appliance according to an embodiment of the present invention. As shown in fig. 1, the method includes:
After a risk path with a disaster risk is obtained, a risk control device of the community gas equipment acquires each community gas equipment on the risk path, wherein each community gas equipment on the risk path is also called a risk source, and acquires the current state of a state variable corresponding to each community gas equipment. And each community gas device corresponds to which state variable can be preset.
As shown in table 1, it is a comparison table of the faults related to the community gas equipment, the industrial control language and the state variables.
TABLE 1
Table 1 shows that any node on the gas passage can be regarded as a community gas device, and the specific division of the community gas device can be defined by itself. And obtaining the state variable corresponding to the community gas equipment according to the fault form and the parameter corresponding to the fault of the community gas equipment. If a plurality of parameters are changed corresponding to the possible faults of a certain community gas equipment, a plurality of state variables are corresponding to the community gas equipment.
And 102, judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
And after the current state of the state variable corresponding to each community gas device is obtained, judging whether the state variable corresponding to each community gas device is abnormal or not according to the experience value of the state variable corresponding to each community gas device. If the current state of the state variable corresponding to each community gas device is consistent with the experience value or the difference value is within a preset range, the corresponding state variable is normal, and otherwise, the corresponding state variable is abnormal. And controlling the state variables corresponding to the abnormal gas equipment in each community so as to restore the abnormal gas equipment to be normal.
The risk path with the disaster risk can be acquired through a risk analysis process. According to the embodiment of the invention, a risk analysis process is combined with an automatic control process, a control theory is brought into risk analysis, a state variable replaces a risk term, the control of a risk event is quantized into the control of a controlled variable, and the risk is accurately controlled through single-loop feedback control. Through quantifying the risk path nodes into the change of state variables, the problems can be visually presented, and quantitative standards can be provided for preventing and treating risks.
According to the embodiment of the invention, by acquiring each community gas device on the risk path with the disaster causing risk, acquiring the current state and the abnormal state of the state variable corresponding to each community gas device, and controlling the state variable corresponding to each abnormal community gas device, the automatic control of the abnormal risk source is realized, and the automatic hidden danger elimination after the gas hidden danger is found can be realized.
Further, based on the above embodiment, after the controlling the state variable corresponding to each abnormal gas device in the community, the method further includes: acquiring the current state of the state variable after control according to a preset time period, and judging whether the state variable is recovered to be normal or not according to the current state of the state variable after control; and if the state variable which is not recovered to be normal is judged and known, further controlling the corresponding state variable.
And after the state variable parameters are improved through risk control, whether the running state of each device is improved or not is continuously observed, if the running state of each device is not improved, feedback information can be sent out in time, and a further control flow is triggered. Therefore, after the state variables corresponding to the abnormal community gas devices are controlled, the current states of the controlled state variables are obtained according to a preset time period, and whether the state variables are normal or not is judged according to the current states of the controlled state variables; and if the state variable which is not recovered to be normal is judged and known, further controlling the corresponding state variable.
On the basis of the above embodiment, the embodiment of the present invention further controls the state variable that has not been restored to normal after the control, thereby improving the reliability of risk control.
Further, based on the above embodiment, the state variable has a preset risk level; wherein a higher risk level indicates a greater degree of risk; the control of the state variable corresponding to each abnormal community gas device comprises: and acquiring the danger level of the state variable corresponding to the abnormal community gas equipment, and sequentially controlling the state variable corresponding to the abnormal community gas equipment according to the danger level.
The state variable has a preset danger level; wherein a higher level indicates a greater degree of risk. For example, the severity level classification of the state variables required for risk assessment is as follows:
the first state variable: the concentration and the numerical value of the fuel gas are abnormal, so that the fire disaster explosion is directly caused, and the danger coefficient is the largest;
the second state variable: variables such as gas flow rate, air pressure and the like which easily cause damage to gas equipment can directly cause the abnormality of the first state variable, and have the characteristics of burstiness and larger danger coefficient;
the third state variable: the variables such as temperature and humidity which indirectly cause the abnormity of the first state variable have an accumulative effect, are in positive correlation with time, are easy to predict and have general danger coefficients.
Therefore, in order to realize preferential elimination of a fault with a large hidden danger, when the state variables corresponding to the abnormal community gas devices are controlled, the danger levels of the state variables corresponding to the abnormal community gas devices are obtained, and the state variables corresponding to the abnormal community gas devices are sequentially controlled according to the danger levels. That is, the state variable having a high risk level is preferentially controlled.
On the basis of the above embodiment, the embodiment of the invention further improves the reliability of risk control by sequentially controlling the state variables corresponding to the abnormal gas appliances in each community according to the level of the risk level.
Further, based on the above embodiment, the obtaining the current state of the state variable corresponding to each community gas device includes: acquiring the current state of the state variable corresponding to each community gas device through a preset sensor; the control of the state variable corresponding to each abnormal community gas device comprises: and controlling the state variables corresponding to the abnormal community gas equipment through a preset actuator and a preset controller.
The method comprises the steps of focusing risk disaster-causing factor attention points causing risk events on community gas equipment state quantities, converting fuzzy risk terms into state variables convenient for sensing and identifying by sensors, extracting the equipment state variables related to the risk terms, sensing the change of corresponding state variables of a gas system through the sensors such as temperature, humidity and concentration, taking out risk source state quantities which cause the risk events probabilistically, and defining a numerical warning line.
And when the current state of the state variable corresponding to each community gas device is obtained, obtaining the current state of the state variable corresponding to each community gas device through a preset sensor according to the parameter type corresponding to the state variable. For example, the current state of the valve port outlet pressure is obtained by a pressure sensor, the gas temperature is obtained by a temperature sensor, and the like. And when the state variables corresponding to the abnormal community gas equipment are controlled, the state variables corresponding to the abnormal community gas equipment are automatically controlled through a preset actuator and a preset controller. And similarly, determining corresponding actuators and controllers according to the parameter types corresponding to the state variables. For example, the temperature state variables of the fuel gas are controlled by a PLC and a heating/cooling device.
On the basis of the above embodiment, in the embodiment of the invention, the current state of the state variable corresponding to each community gas device is acquired through the preset sensor, and the state variable corresponding to each abnormal community gas device is controlled through the preset actuator and the controller, so that the reliability of risk control is further improved.
Further, based on the above embodiment, the method further includes: and performing machine learning training through the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value.
And when judging whether the state variables corresponding to the community gas equipment are abnormal or not, comparing the current values of the state variables corresponding to the community gas equipment with the empirical values to judge. And the empirical value of the state variable is obtained by performing machine learning training on the state variable corresponding to the equipment gas equipment in a normal running state of a preset number of communities. When an empirical value corresponding to a certain state variable is obtained, a large number of corresponding state variables corresponding to the community gas equipment in the normal operation state of the community form a training sample, and the empirical value is obtained through machine learning training.
On the basis of the above embodiment, the embodiment of the invention performs machine learning training by using the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value for judging whether the state variables are abnormal, so that the accuracy of abnormal judgment is improved, and the reliability of risk control is further improved.
Further, based on the above embodiment, before the acquiring the individual community gas appliances on the risk path where the disaster risk exists, the method further includes: and determining the risk path with the disaster causing risk through a conditional random field CRF model.
Since disaster-causing factors are necessarily correlated with each other, the CRF can effectively use the characteristic to distinguish whether a series of risk sources form a risk path. The identification of the disaster-causing risk source is carried out through the classification prediction function of the CRF conditional random field, whether the risk source sequence needs to be prevented or not is judged through the given sequence risk source and the existing fault tree risk path, the risk source which can possibly cause the risk event is taken out, and the risk assessment of the next step can be carried out.
On the basis of the embodiment, the risk path with the disaster causing risk is determined through the conditional random field CRF model, so that the accuracy of determining the risk path is improved, the accuracy of determining the risk source and the accuracy of determining the state variable to be controlled are improved, and the reliability of risk control is further improved.
Further, based on the above embodiment, the determining, by a conditional random field CRF model, the risk path with the risk of disaster includes: inputting each community gas device corresponding to the risk path and a label value corresponding to each community gas device into the conditional random field CRF model; determining that the risk path has disaster-causing risk according to a comparison result that the output value of the conditional random field CRF model is larger than a corresponding preset threshold value; and the labeled value represents the possibility of the fault of the community gas equipment.
The embodiment of the invention determines various risk paths causing a certain risk event by using the fault tree diagram of the community gas equipment. Because various community gas systems are similar to each other, after various risk paths in fault tree diagrams of a large number of community gas equipment are trained through modeling, fault derivation of the community gas system to be evaluated can be inferred and predicted on the basis of the trained model.
In particular, this feature can be exploited by the CRF to efficiently determine the disaster-causing risk of the risk path:
let O be (O)1,O2,…,Oi) Defining a random field, I ═ I (I)1,I2,…,Ii) A random field is also defined.
Wherein O represents a series of risk sources in the risk path, OiRepresenting the source of the risk at the ith location. E.g. OiA preset number of the risk source may be indicated, such as a number of a gas delivery pipe section, a number of a gas valve, etc.
And I represents a labeled value corresponding to the risk source and represents the possibility of the failure of the risk source. For example, I3Can be the 3 rd section O of the gas transmission pipe3And the degree of corrosion (or damage) of the gas line section can be classified as severe, relatively severe, normal, light, and no corrosion (or damage), the corresponding values are labeled as 5, 4, 3, 2, and 1.
As another example, I2Can indicate the No. 2 gas valve O in a certain risk path2And the degree of sealing of the gas valve can be classified into sealing, slight leakage and severe leakage corrosion, the corresponding labeled values are 3, 2 and 1.
For a CRF, two kinds of feature functions may be defined for it: transition feature & status feature.
Here the general formula for modeling is expanded:
wherein Z (O) is a normalization factor, and:
combining the two formulas:
wherein:
(1)tjis a feature function defined on the edge, called the transfer feature, depending on the current and previous positions;
(2)slis a feature function defined on the node, called state feature, dependent on the current position;
(3)λj，μlis tj，slThe corresponding weight value;
(4) characteristic function tj，slValues of 1 or 0: when the characteristic condition is met, the value is 1, otherwise, the value is 0;
(5)fk(O,Ii-1,Ii ,i)is a characteristic function; according to the embodiment of the invention, the weights of various characteristic functions can be determined through the training of the CRF according to the risk paths of various community gas equipment and corresponding risk sources, and finally the output values of various risk paths are determined through the CRF collected by various characteristic functions.
In one embodiment, each feature function may be entered with labeled values for the current position i, position i +1, and i-1 of the risk source sequence O when training the CRF model. Then, each characteristic function is given a weight, and all the characteristic functions are weighted and summed to obtain a corresponding output value.
The conditional random field CRF training and predicting steps are as follows:
(1) performing data training on the CRF, and extracting a characteristic function: firstly, an observation sequence is determined, wherein the observation sequence is composed of various types of risk sources of a community gas system, such as valves, pipelines, pressure regulators and the like, the corresponding risk sources can generate corresponding risk faults, such as damage of the valves, breakage of the pipelines, overpressure of the pressure regulators and the like, the different risk sources and the different risk faults are respectively used as input and output of the CRF to be trained, and a plurality of characteristic functions f1 and f2 … fn are extracted.
(2) The risk sources causing the risk events are necessarily correlated with each other according to the fault tree model, the relevance and the coupling among the risk faults can be effectively ensured through the found transfer characteristics, and the state characteristics ensure that the related equipment cannot generate faults with low relevance. The value ranges of the determined labeling sequences are faults such as overpressure, overtemperature, damage and rupture and the like.
(3) And finally, forecasting, giving a group of risk sources needing to be observed and several existing risk fault paths through a trained CRF model, determining the magnitude of the risk probability, regarding an observation sequence corresponding to the risk probability larger than a certain limit as a risk source easily causing a risk event, and further taking early warning measures (when the risk probability is larger than a certain degree, the risk source is a hidden risk source corresponding to the risk fault path with different severity causing different risk events, so that risk grade classification can be performed on a series of risk sources possibly causing the risk event).
It should be noted that, the CRF training is performed through a large amount of historical data, so that the output values of the CRF in case of disaster of various risk paths can be obtained. Therefore, these output values can be used as corresponding preset threshold values, that is, when a trained CRF model is used to determine a certain risk path, if the output value of the CRF is greater than the output value corresponding to the risk path, it can be determined that the risk path has a disaster risk.
On the basis of the above embodiment, in the embodiment of the present invention, because the input of the model is based on each risk source in the risk path, the position of the risk source can be determined, the evaluation and control targets can be refined, and the accurate disaster risk evaluation and control can be realized.
Fig. 2 is a schematic view of a risk control structure of a community gas appliance according to an embodiment of the present invention. As shown in fig. 2, the apparatus includes: a state variable state obtaining module 10 and a state variable control module 20, wherein: the state variable state acquisition module 10 is configured to: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one; the state variable control module 20 is configured to: and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
According to the embodiment of the invention, by acquiring each community gas device on the risk path with the disaster causing risk, acquiring the current state and the abnormal state of the state variable corresponding to each community gas device, and controlling the state variable corresponding to each abnormal community gas device, the automatic control of the abnormal risk source is realized, and the automatic hidden danger elimination after the gas hidden danger is found can be realized.
Further, based on the above embodiment, the state variable control module 20 is further configured to: acquiring the current state of the state variable after control according to a preset time period, and judging whether the state variable is recovered to be normal or not according to the current state of the state variable after control; and if the state variable which is not recovered to be normal is judged and known, further controlling the corresponding state variable.
On the basis of the above embodiment, the embodiment of the present invention further controls the state variable that has not been restored to normal after the control, thereby improving the reliability of risk control.
Further, based on the above embodiment, the state variable has a preset risk level; wherein a higher risk level indicates a greater degree of risk; when the state variable control module 20 is configured to control the state variables corresponding to the abnormal gas appliances in each community, the state variable control module is specifically configured to: and acquiring the danger level of the state variable corresponding to the abnormal community gas equipment, and sequentially controlling the state variable corresponding to the abnormal community gas equipment according to the danger level.
On the basis of the above embodiment, the embodiment of the invention further improves the reliability of risk control by sequentially controlling the state variables corresponding to the abnormal gas appliances in each community according to the level of the risk level.
Further, based on the above embodiment, when the state variable state obtaining module 10 is configured to obtain the current state of the state variable corresponding to each community gas device, the current state of the state variable corresponding to each community gas device is obtained through a preset sensor; when the state variable control module 20 is used for controlling the state variables corresponding to the abnormal community gas appliances, the state variables corresponding to the abnormal community gas appliances are controlled through a preset actuator and a preset controller.
On the basis of the above embodiment, in the embodiment of the invention, the current state of the state variable corresponding to each community gas device is acquired through the preset sensor, and the state variable corresponding to each abnormal community gas device is controlled through the preset actuator and the controller, so that the reliability of risk control is further improved.
Further, based on the above embodiment, the apparatus further includes an empirical value obtaining module, where the empirical value obtaining module is configured to: and performing machine learning training through the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value.
On the basis of the above embodiment, the embodiment of the invention performs machine learning training by using the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value for judging whether the state variables are abnormal, so that the accuracy of abnormal judgment is improved, and the reliability of risk control is further improved.
Further, based on the above embodiment, the apparatus further includes a risk assessment module, configured to: and determining the risk path with the disaster causing risk through a conditional random field CRF model.
On the basis of the embodiment, the risk path with the disaster causing risk is determined through the conditional random field CRF model, so that the accuracy of determining the risk path is improved, the accuracy of determining the risk source and the accuracy of the state variable to be controlled are improved, and the reliability of risk control is further improved.
Further, based on the above embodiment, the risk assessment module is specifically configured to: inputting each community gas device corresponding to the risk path and a label value corresponding to each community gas device into the conditional random field CRF model; determining that the risk path has disaster-causing risk according to a comparison result that the output value of the conditional random field CRF model is larger than a corresponding preset threshold value; and the labeled value represents the possibility of the fault of the community gas equipment.
On the basis of the above embodiment, in the embodiment of the present invention, because the input of the model is based on each risk source in the risk path, the position of the risk source can be determined, the evaluation and control targets can be refined, and the accurate disaster risk evaluation and control can be realized.
The apparatus provided in the embodiment of the present invention is used for the method, and specific functions may refer to the method flow described above, which is not described herein again.
Fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 3, the electronic device may include: a processor (processor)310, a communication Interface (communication Interface)320, a memory (memory)330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform the following method: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one; and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to perform the method provided by the foregoing embodiments, for example, including: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one; and judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, and controlling the abnormal state variables corresponding to the community gas equipment.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (7)
1. A risk control method of community gas equipment is characterized by comprising the following steps:
determining a risk path with a disaster causing risk through a conditional random field CRF model, and inputting each community gas device corresponding to the risk path and a label value corresponding to each community gas device into the conditional random field CRF model; determining that the risk path has disaster-causing risk according to a comparison result that the output value of the conditional random field CRF model is larger than a corresponding preset threshold value; the labeled value represents the possibility of the failure of the community gas equipment;
acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one and each state variable has a preset danger level, wherein the higher the danger level is, the greater the danger degree is;
judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, acquiring the danger levels of the state variables corresponding to the community gas equipment with the abnormal state, sequentially controlling the state variables corresponding to the community gas equipment with the abnormal state through a preset actuator and a preset controller according to the height of the danger levels, and determining the specific corresponding actuator and controller according to the parameter types corresponding to the state variables.
2. The method for controlling the risk of the community gas equipment according to claim 1, wherein after the controlling the state variable corresponding to each abnormal community gas equipment, the method further comprises:
acquiring the current state of the state variable after control according to a preset time period, and judging whether the state variable is recovered to be normal or not according to the current state of the state variable after control; and if the state variable which is not recovered to be normal is judged and known, further controlling the corresponding state variable.
3. The method for controlling the risk of the community gas equipment according to claim 1, wherein the obtaining the current state of the state variable corresponding to each community gas equipment comprises: and acquiring the current state of the state variable corresponding to each community gas device through a preset sensor.
4. The risk control method of community gas appliances of claim 1, characterized in that the method further comprises:
and performing machine learning training through the state variables corresponding to the equipment gas equipment in the normal operation state of the preset number of communities to obtain the empirical value.
5. A risk control device of community gas equipment, characterized by comprising:
a risk assessment module to: determining a risk path with a disaster causing risk through a conditional random field CRF model, and inputting each community gas device corresponding to the risk path and a label value corresponding to each community gas device into the conditional random field CRF model; determining that the risk path has disaster-causing risk according to a comparison result that the output value of the conditional random field CRF model is larger than a corresponding preset threshold value; the labeled value represents the possibility of the failure of the community gas equipment;
a state variable state acquisition module configured to: acquiring each community gas device on a risk path with a disaster risk, and acquiring the current state of a state variable corresponding to each community gas device; the state variable corresponding to each community gas device is at least one and each state variable has a preset danger level, wherein the higher the danger level is, the greater the danger degree is;
a state variable control module to: judging whether the state variables corresponding to the community gas equipment are abnormal or not according to the experience values of the state variables corresponding to the community gas equipment, acquiring the danger levels of the state variables corresponding to the community gas equipment with the abnormal state, sequentially controlling the state variables corresponding to the community gas equipment with the abnormal state through a preset actuator and a preset controller according to the height of the danger levels, and determining the specific corresponding actuator and controller according to the parameter types corresponding to the state variables.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements the steps of the risk control method of the community gas appliances of any one of claims 1 to 4.
7. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the risk control method of a community gas appliance according to any one of claims 1 to 4.
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