CN115097842A - Safety inspection robot path planning method based on fire risk level of chemical industry park - Google Patents
Safety inspection robot path planning method based on fire risk level of chemical industry park Download PDFInfo
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Abstract
The invention discloses a safety inspection robot path planning method based on fire risk levels of a chemical industry park, which comprises the steps of firstly designing an inspection path of the chemical industry park of a robot by utilizing an improved discrete electrostatic discharge algorithm; adopting an ESDA-NPSVM evaluation model to obtain the fire risk level of each position to be patrolled and examined in the chemical industry park; and (3) optimizing the inspection path of the robot chemical industry park obtained in the step (1) according to the fire risk grade of the position to be inspected, so that the inspection robot can efficiently finish the inspection task with a side focus. According to the method, the fire risk level of the inspection position and the path optimization of the safety inspection robot are combined, so that the inspection robot can efficiently finish the inspection task with a side focus, and the purpose of reducing the accident occurrence probability is achieved.
Description
Technical Field
The invention relates to the technical field of robot path planning, in particular to a method for planning a path of a safety inspection robot based on fire risk levels of a chemical industry park.
Background
In recent years, fire and explosion accidents in chemical industrial parks frequently occur, and a great amount of property loss is caused. If the potential safety hazard is eliminated before the fire and explosion accident happens, the accident can be prevented, the safety inspection is an effective means for inspecting the potential safety hazard, and the accident loss can be effectively reduced, even the accident can be prevented. At present, the mode of safety inspection is mainly divided into manual inspection and robot inspection, because the area of a chemical industry park is large, hidden dangers are more and more dispersed, the requirement on the quality of inspection personnel is higher in the manual inspection, wrong judgment is easily made when people are in a fatigue state, the problem inspection is not in place or omitted, the robot inspection can make up the problem of manual inspection, and the working efficiency of the robot is not limited by the workload and the working time.
The route optimization is very important when the inspection robot automatically inspects the route, the establishment of the optimal route can find hidden dangers appearing in the detection points in time, meanwhile, the shortest distance of the inspection route is ensured, and the optimal route has more obvious advantages when the number of points to be detected is large and the danger degree is different. In the prior art, a robot inspection mode mostly adopts a fixed inspection path, when the production process, the raw material type, the storage amount and the like of a detection point are changed to cause the fire risk level to be dynamically changed, an optimal inspection path cannot be planned in time, and the object with the highest risk cannot be inspected preferentially.
Disclosure of Invention
The invention aims to provide a safety inspection robot path planning method based on fire risk levels of chemical industrial parks.
The purpose of the invention is realized by the following technical scheme:
a safety inspection robot path planning method based on fire risk levels of chemical industrial parks comprises the following steps:
and 3, optimizing the routing inspection path of the robot chemical industry park obtained in the step 1 according to the fire risk grade of the position to be inspected, so that the routing inspection robot can efficiently complete routing inspection tasks with a side focus.
According to the technical scheme provided by the invention, the method combines the fire risk level of the inspection position with the path optimization of the safety inspection robot, so that the inspection robot can efficiently finish the inspection task with a side focus, and the purpose of reducing the accident occurrence probability is achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for planning a path of a safety inspection robot based on a fire risk level of a chemical industry park according to an embodiment of the present invention;
FIG. 2 is a simulation map of an exemplary chemical industry park according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a simulation path optimization result of the safety inspection robot according to the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention are 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 only a part of the embodiments of the present invention, not all embodiments, and this does not limit the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for planning a path of a safety inspection robot based on a fire risk level of a chemical industrial park according to an embodiment of the present invention, where the method includes:
in the step, a heuristic crossover operator is adopted by a DESDA (discrete electrostatic discharge) algorithm for generating new individuals, and in order to keep population diversity, inversion, insertion and exchange operators are adopted for individual variation to replace individual components in the original algorithm;
the improved discrete electrostatic discharge algorithm IDESDA adopts a greedy algorithm initial population, and when the algorithm falls into local optimum and cannot jump out, a 2-opt algorithm is adopted to generate a new solution and add the new solution into an elite set so as to provide an optimum segment for jumping out of the local optimum;
the improved discrete electrostatic discharge algorithm IDESDA has better global search capability and higher precision and stability in path planning application, and the process of designing the routing inspection path of the robot industrial park by using the improved discrete electrostatic discharge algorithm specifically comprises the following steps:
firstly, initializing all electronic equipment by adopting a greedy algorithm, wherein the position of each electronic equipment is defined as a path plan which possibly exists in a chemical industry park;
and then, the electronic equipment with the lowest fitness in the space is moved to the electronic equipment with high fitness to change the position of the electronic equipment by utilizing the phenomenon of indirect or direct electrostatic discharge of the electronic equipment individuals, the optimal position is finally obtained, and the shortest path for the chemical industrial park robot to patrol is continuously and iteratively found.
in the step, the inspection points in the chemical industry park are divided into three types of positions to be inspected according to the functions, namely a type A dangerous chemical storehouse (called type A storehouse for short), a production workshop and a public area (an office building and a dining hall). Since class a libraries have the highest risk and the most stringent requirements for fire prevention, class a libraries are used as an example to illustrate the fire risk level evaluation process. Part of samples of the class A library sample set are shown in the following table, and inventory quantity, temperature increment, humidity, ratio increment of combustible gas concentration and Lower Explosion Limit (LEL) are selected as research indexes (the four research indexes are obtained by comprehensively considering relevant specifications and actual installation conditions of sensors in a certain Beijing chemical industry park);
sample set part sample of class A library in chemical industry park
Acquiring the current safety state data of the class A library by using an enterprise safety management platform, wherein the method comprises the following steps: inventory quantity, temperature increment, humidity, combustible gas concentration, and Lower Explosion Limit (LEL) ratio increment;
inputting the acquired current safety state data into an ESDA-NPSVM evaluation model, and evaluating the fire risk level of the chemical industry park by the ESDA-NPSVM evaluation model according to the safety state data;
the construction process of the ESDA-NPSVM evaluation model comprises the following steps:
firstly, NPSVM is linearly combined by NRBF and Poly, and its mathematical form is as follows:
K(x,y)＝(1-α)K NRBF +αK Ploy
in the formula, x is any point in space; y is a specified center point in space; alpha is a weight coefficient; k NRBF Represents a modified gaussian kernel function; kcloy represents a polynomial kernel; c is the minimum external sphere center of the training sample in the original space; q represents the dimension of the function; sigma is a width parameter of the function and is used for controlling the radial action range of the function;
then, further optimizing the NPSVM model parameters by utilizing the ESDA, and finally forming an ESDA-NPSVM evaluation model; the optimized parameters comprise a penalty factor C, a kernel function parameter g and a mononuclear weight factor alpha in a mixed kernel;
then judging whether the fire risk level of the chemical industry park is increased, and if the fire risk level is not increased, continuing to perform the next round of evaluation and detection; and if the risk level is increased, the safety management personnel checks the chemical industry park and judges whether the evaluation result is correct or not, if the evaluation result is correct, the sample data is added into the sample set of the first-class dangerous chemical storehouse, and if the evaluation result is incorrect, the wrong sample data is added into the sample set of the first-class dangerous chemical storehouse after the correct result is given to the wrong sample data.
And 3, optimizing the inspection path of the robot chemical industry park obtained in the step 1 according to the fire risk grade of the position to be inspected, so that the inspection robot can efficiently finish the inspection task with a side focus.
In the step, firstly, the fire risk grade of the position to be inspected is used for guiding the planning of an inspection path, and the shortest inspection path is planned on the premise of preferentially inspecting the position with high fire risk grade; it is important to note that the fire risk level is a fire risk early warning level in a safe state, i.e., a fire occurrence probability.
Specifically, firstly, finding the optimal path of each position to be inspected according to the fire risk level of the position to be inspected;
then calculating the distance from all the high-risk inspection point positions to the middle-risk inspection point positions and the distance from all the middle-risk inspection point positions to the low-risk inspection point positions;
then selecting the shortest distance to connect the high-risk and medium-risk paths end to end, and connecting the medium-risk and low-risk paths end to finally form an optimized optimal path;
the inspection robot starts to sequentially inspect from the position to be inspected with the highest risk until the position to be inspected with the lowest risk is reached, so that high-risk inspection and shortest path are guaranteed.
Wherein a high fire risk level indicates a high probability of a fire at the location; whether hidden dangers exist or not needs to be checked in time in comparison with the position with a low risk level, and therefore high-level priority routing inspection is necessary. In addition, the optimal routing inspection path can be quickly planned through path planning, the routing inspection efficiency is effectively guaranteed, and the routing inspection time is saved.
When the production process, the raw material type, the storage amount, the temperature and the combustible gas concentration of the position to be inspected are changed, so that the fire risk grade of the position to be inspected is changed, the optimal inspection path is re-planned, and the position with the highest risk is preferentially inspected. Therefore, the requirements of high-risk inspection, low-risk inspection, short path and high efficiency are met, and the safety of the park is guaranteed to the maximum extent.
It is noted that those skilled in the art will recognize that embodiments of the present invention are not described in detail herein.
In the embodiment, all the inspection positions are divided into three types according to the actual conditions of the chemical industry park enterprises to be inspected, namely a storehouse, a production workshop and an office area; and then setting the coordinates of the inspection positions by referring to the actual conditions of the chemical industry park, and finally determining the fire risk level of each inspection position.
Fig. 2 is a simulation map of a chemical industry park according to an example of the embodiment of the present invention, in which: the circle, the triangle and the rhombus represent coordinate positions of inspection points with different fire risk levels, namely the fire risk levels are high risk, medium risk and low risk in sequence, and the serial number of each inspection point is randomly arranged.
The inspection robot executes an inspection task according to the principle of preferentially inspecting high risk levels and simultaneously ensuring the shortest path, in order to obtain the optimal path according with the principle, the inspection robot firstly utilizes IDESDA to find the respective optimal path respectively aiming at the inspection positions of three different risk levels, then calculates the distance from all the inspection positions of high risk to all the inspection positions of medium risk through the algorithm, and the distance from all the inspection positions of medium risk to all the inspection positions of low risk, and then selects the shortest distance to connect the high risk and medium risk paths end to end, and the medium risk and low risk paths end to end, so as to finally form a complete optimal path; at the moment, the inspection robot starts to inspect in sequence from the position with the highest risk, so that high-risk inspection and shortest path are guaranteed.
It should be noted that, during path optimization, barrier of the enclosing wall between enterprises and the condition that two points cannot be connected are not considered, as shown in fig. 3, a schematic diagram of the simulation path optimization result of the safety inspection robot according to the embodiment of the present invention is shown, and as can be seen from fig. 3: the points with the highest risk levels are 21, 13 and 27, 21 is set as a patrol starting point, and the optimal sub-paths after IDESDA optimization are (21, 13, 27), (8, 24, 1, 28, 6, 9, 5, 26, 29, 2, 20, 10, 4, 15, 18, 14, 17, 22, 11, 25, 19, 16) and (7, 23, 12, 3); after IDESDA calculation, connecting 27 with 8 and connecting 16 with 7, namely connecting the three sub-paths to complete path establishment, and obtaining the optimal routing inspection path as follows: (21, 13, 27, 8, 24, 1, 28, 6, 9, 5, 26, 29, 2, 20, 10, 4, 15, 18, 14, 17, 22, 11, 25, 19, 16, 7, 23, 12, 3).
The IDESDA can quickly and accurately calculate the optimal path through the simulation experiment, so that the method disclosed by the embodiment of the invention can be effectively applied to the global path planning of the safety inspection robot, and the technical scheme has the following advantages:
1. the IDESDA algorithm in the application has better global search capability, higher precision and better stability in path planning application;
2. this application patrols and examines the conflagration risk level result of position and patrol and examine robot path optimization with chemical industry garden respectively and combine together with safety for patrol and examine the robot and can high-efficiently and have the completion of the key point of side and patrol and examine the task, guaranteed "high risk, patrol and examine earlier, low risk, time patrol and examine", thereby can reduce the conflagration emergence of chemical industry garden, have important practical meaning.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Claims (6)
1. A safety inspection robot path planning method based on fire risk levels of a chemical industry park is characterized by comprising the following steps:
step 1, designing a routing inspection path of a robot industrial park by using an improved discrete electrostatic discharge algorithm;
step 2, adopting an ESDA-NPSVM evaluation model to obtain fire risk levels of positions to be patrolled and examined in the chemical industry park;
and 3, optimizing the inspection path of the robot chemical industry park obtained in the step 1 according to the fire risk grade of the position to be inspected, so that the inspection robot can efficiently finish the inspection task with a side focus.
2. The safety inspection robot path planning method based on the fire risk level of the chemical industry park according to claim 1, wherein the process of the step 1 is specifically as follows:
firstly, initializing all electronic equipment by adopting a greedy algorithm, wherein the position of each electronic equipment is defined as a path plan which possibly exists in a chemical industry park;
and then, the electronic equipment with the lowest fitness in the space is moved to the electronic equipment with high fitness to change the position of the electronic equipment by utilizing the phenomenon of indirect or direct electrostatic discharge of the electronic equipment individuals, the optimal position is finally obtained, and the shortest path for the chemical industrial park robot to patrol is continuously and iteratively found.
3. The safety inspection robot path planning method based on the fire risk level of the chemical industry park according to claim 1, wherein the process of the step 2 specifically comprises the following steps:
firstly, dividing the inspection points of a chemical industry park into three types of positions to be inspected according to the functions, namely a first-type dangerous chemical storehouse, a production workshop and a public area;
acquiring the current safety state data of the first-class dangerous chemical storehouse by using an enterprise safety management platform, wherein the data comprises the following steps: inventory quantity, temperature increment, humidity, combustible gas concentration and ratio increment of explosion lower limit;
inputting the acquired current safety state data into an ESDA-NPSVM evaluation model, and evaluating the fire risk level of the chemical industry park by the ESDA-NPSVM evaluation model according to the safety state data;
then judging whether the fire risk level of the chemical industry park is increased, and if the fire risk level is not increased, continuing to perform the next round of evaluation and detection; and if the risk level is increased, the safety management personnel checks the chemical industry park and judges whether the evaluation result is correct or not, if the evaluation result is correct, the sample data is added into the sample set of the first-class dangerous chemical storehouse, and if the evaluation result is incorrect, the wrong sample data is added into the sample set of the first-class dangerous chemical storehouse after the correct result is assigned to the wrong sample data.
4. The method for planning the path of the safety inspection robot based on the fire risk level of the chemical industry park according to claim 1, wherein in the step 2, the construction process of the ESDA-NPSVM evaluation model is as follows:
firstly, NPSVM is linearly combined by NRBF and Poly, and its mathematical form is as follows:
K(x,y)＝(1-α)K NRBF +αK Ploy
in the formula, x is any point in space; y is a specified central point in space; alpha is a weight coefficient; k NRBF Represents a modified gaussian kernel function; kcloy represents a polynomial kernel; c is the minimum external sphere center of the training sample in the original space; q represents the dimension of the function; sigma is a width parameter of the function and is used for controlling the radial action range of the function;
then, further optimizing the NPSVM model parameters by utilizing the ESDA, and finally forming an ESDA-NPSVM evaluation model; the optimized parameters include a penalty factor C, a kernel function parameter g, and a mononuclear weight factor α in the mixed kernel.
5. The method for planning the route of the robot for safety inspection according to claim 1, wherein in step 3, the route of the robot for chemical industry park inspection obtained in step 1 is optimized according to the fire risk level of the location to be inspected, and specifically comprises:
guiding the planning of the routing inspection path by using the fire risk level of the position to be inspected, and planning the shortest routing inspection path on the premise of preferentially inspecting the position with high fire risk level; wherein a high fire risk level indicates a high probability of a fire at the location;
when the production process, the raw material type, the storage amount, the temperature and the combustible gas concentration of the position to be inspected are changed, so that the fire risk grade of the position to be inspected is changed, the optimal inspection path is planned again, and the position with the highest risk is inspected preferentially.
6. The method for planning the path of the safety inspection robot based on the fire risk level of the chemical industry park according to claim 5, wherein the process of planning the shortest inspection path on the premise of preferentially inspecting the position with the high fire risk level is specifically as follows:
firstly, finding the optimal path of each position to be inspected according to the fire risk level of the position to be inspected;
then calculating the distance from all the high-risk inspection point positions to the middle-risk inspection point positions and the distance from all the middle-risk inspection point positions to the low-risk inspection point positions;
then selecting the shortest distance to connect the high-risk and medium-risk paths end to end, and connecting the medium-risk and low-risk paths end to finally form an optimized optimal path;
the inspection robot starts to sequentially inspect from the position to be inspected with the highest risk until the position to be inspected with the lowest risk is reached, so that high-risk inspection and shortest path are guaranteed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114412A (en) * | 2023-09-12 | 2023-11-24 | 瑞丰宝丽(北京)科技有限公司 | Safety pre-control method and device for dangerous chemical production enterprises |
| CN117319452A (en) * | 2023-11-28 | 2023-12-29 | 平利县安得利新材料有限公司 | Safety inspection method and system applied to barium sulfate preparation |
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2022
- 2022-07-13 CN CN202210819157.1A patent/CN115097842A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117114412A (en) * | 2023-09-12 | 2023-11-24 | 瑞丰宝丽(北京)科技有限公司 | Safety pre-control method and device for dangerous chemical production enterprises |
| CN117319452A (en) * | 2023-11-28 | 2023-12-29 | 平利县安得利新材料有限公司 | Safety inspection method and system applied to barium sulfate preparation |
| CN117319452B (en) * | 2023-11-28 | 2024-03-08 | 平利县安得利新材料有限公司 | Safety inspection method and system applied to barium sulfate preparation |
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