CN-116226962-B - Deodorization pipeline system generation method based on BIM and improved ant colony algorithm

Abstract

The invention discloses a deodorizing pipeline generation method based on BIM technology and an improved ant colony algorithm, which comprises the steps of 1, generating a space analysis chart under a beam through BIM forward or semi-forward design after collecting project requirements, 2, gridding the space analysis chart under the beam, cutting the space analysis chart into fine grid units for facilitating subsequent calculation, 3, arranging the positions of odor collecting points and odor treatment equipment, 4, executing calculation commands through the improved ant colony algorithm, accelerating calculation through positive and negative feedback double regulation, and finally obtaining a pipeline path planning chart, 5, automatically arranging pipelines, valve accessories and equipment connecting pipes by combining the pipeline path planning chart, and 6, rechecking an air pipe according to the hydraulic power requirements of the air port and the air pipe wind speed, and determining a final deodorizing pipeline system. The invention executes the calculation command through the improved ant colony algorithm to generate the deodorizing pipeline system.

Inventors

• ZHOU YANZHAO
• LIN XIAO
• YU WENJUN
• HU SHUAI
• SHEN ZHENG
• MU LEI
• DAI MINGHUA
• LI ZHENCHUAN
• WANG HAILONG

Assignees

• 北京市市政工程设计研究总院有限公司

Dates

Publication Date

20260508

Application Date

20221220

Claims (1)

1. 1. A deodorizing pipeline generating method based on BIM technology and improved ant colony algorithm is characterized by comprising the following steps: (1) Step one, after collecting project requirements, carrying out difference calculation on the space under the beam and the net height requirements through BIM forward or semi-forward design, and generating an available two-dimensional space analysis chart under the beam so as to reduce the calculation amount of solving the three-dimensional problem, wherein the available space analysis chart under the beam has the following characteristics: (1-1) the particles in the space analysis chart should meet, under a rectangular coordinate system, on one hand, the coordinates of the particles in the Z direction meet the available space calculation formula of the beam bottom and the point set formula meeting the requirements of the net height under the beam, and on the other hand, the direction X, Y is not coincident with the component in the BIM model of the existing project, namely the position of the obstacle, namely the point set formula meeting the area beyond the obstacle; (1-2) formula for calculating available space at bottom of beam H under-bridge ＝H n -H clear-height -H beam-structures -H pipe+mac Wherein H under-bridge is the available net height of the beam bottom, H n is the layer height of each room, H clear-height is the net height of each room, H beam-structures is the structural beam height, and H pipe+mac is the height occupied by the vertical pipeline and equipment after the beam height and the net height are subtracted from the layer height; (1-3) a point set formula meeting the underbeam clearance requirement: P={Pi,j=P(x,y,z)} Hn-z-Hbeam-structures-Hpipe-mac≤Hunder-bridge Pi, j should satisfy the above formula, wherein P is the set of all points Pi, j satisfying the requirement of the clearance height under the beam, and Z is the coordinate of the point in the Z-axis direction of the rectangular coordinate system; (1-4) satisfying a point set formula in a region other than the obstacle: P=U-P{Pi,j=P(x 0 ,y 0 )} P is the set of points that meet the requirement of the area outside the obstacle, U is the complete set of all particles in the investigation region, P (x 0 ,y 0 ) is the point set of the barrier, namely the available space particles under the beam, which should be the complement of the barrier point set in the whole set of the research area; (2) Step two, gridding the available space analysis chart under the beam, and dividing the available space analysis chart into tiny grid units for facilitating subsequent calculation, wherein the grid dividing units have the following characteristics: (2-1) in the plan view, dividing the grid scale into tiny units of 1mmx1mm, and adjusting the grid scale in a computer according to engineering fineness degree and calculation speed; (2-2) dividing the two-dimensional space analysis map into small cells, and accommodating a set of points satisfying the net height requirement into the divided grid cells; (3) arranging an odor collecting point and an odor treatment device in the space analysis diagram below the beams after grid splitting, wherein the position of a pipeline interface of the odor treatment device is used as a starting point, the odor collecting point at the farthest end from the deodorizing device is used as an ending point, and the odor collecting point at the middle position is used as a middle point; (4) Inputting boundary conditions including odor collection point positions, odor treatment equipment positions, building barrier positions and pipeline curvature radiuses at a boundary parameter interface of a deodorization pipeline system according to an available space analysis chart under a beam, executing calculation commands through an improved ant colony algorithm, accelerating calculation through positive and negative feedback dual regulation, judging and adjusting boundary parameters when design conditions are changed, and carrying out calculation again, and circularly calculating until a final pipeline path planning chart is generated, wherein the steps comprise the following steps: (4-1) defining ant crawling speed, transfer probability, pheromone distribution, odor pheromone calculation formulas and related parameter meanings in the improved ant colony algorithm; (4-2) prescribing an implementation flow of the deodorization pipeline path generation method, and defining a solution sequence of the flow as that a trunk path is solved and then a branch path is calculated; (4-3) defining 2 solution judgments of the implementation flow, namely whether to fall into a local optimal solution judgment and whether to change the individual professional conditions, and judging whether the algorithm can end calculation; (4-4) preliminary trial calculation and rechecking calculation, wherein when the external parameters are adjusted and changed, the boundary parameters are modified and calculated according to design requirements, and the recalculation is performed; (4-5) a positive and negative feedback regulation mechanism, wherein when the crawling speed of ants is influenced by the distribution of pheromones, the following 3 calculation problems under the regulation mechanism can be solved, the mechanism 1 increases the accumulation of the pheromones in the branch by increasing the positive feedback factor G stren in the pheromone distribution formula when the crawling speed is slow, and increases the crawling speed of ants, namely the iterative calculation speed v τ , the mechanism 2 calculates the problem that the stagnation falls into a local optimal solution, particularly shows that the crawling speed v τ -0 of ants, for the situation that the solution is completed or the problem that the local optimal solution falls into, by releasing the odor pheromones S bad , reducing the accumulation of the pheromones through negative feedback regulation, reminding other ant groups to avoid the repeated calculation of the branch, completing the convergence judgment of the branch as soon as possible, the odor pheromones bad gradually withdraws along with the ants in the unfavorable branch, and when the ants completely withdraw from the unfavorable path and recover the normal crawling speed, the mechanism 3 respectively changing the condition problems that logic judgment is carried out, if the situation is unconditional, the optimal main pipe and the branch path are output, if the situation is changed, the algorithm is updated again in the initial adjustment of the corresponding main beam, and the calculation of the main beam space condition is updated according to the specific adjustment, and the calculation of the main beam has been completed; (4-6) core function 1 of improved ant colony algorithm, namely ant crawling speed: Wherein v τ is defined as the instant speed of ant crawling, and is the ratio of the crawling displacement DeltaL of an ant at a certain position and the time Deltaτ used in infinitesimal time; (4-7) core function 2. Transition probability formula of improved ant colony algorithm: Wherein G stren is a positive feedback strengthening factor, S bad is an odor pheromone, namely a negative feedback factor, and other parameters are the same as a traditional ant colony algorithm transition probability formula; (4-8) core function 3. Pheromone assignment formula of improved ant colony algorithm: Wherein, G stren is a positive feedback factor, G stren =1 when G stren ∈[1,2];① climbs normally, the accumulation of pheromone is rapidly increased through the positive feedback factor when the calculation speed needs to be increased, and the crawling speed vτ -0 when ② ants creep and stagnate into a local optimal solution is regulated through the negative feedback of the odor pheromone of S bad ; (4-9) core function 4. The calculation formula of the malodor information element is: S bad is an odor information element, wherein S bad is less than or equal to 0, the odor information element, namely a negative feedback factor, is used for fine adjustment algorithm progress by adopting an addition strategy, 3 states of the odor information element are ① initial state, the odor information element is 0, ants creep normally, ② is in a local optimal solution state, the odor information element reaches the maximum in a short time and then is continuously reduced until the state is recovered, ③ is recovered, and when ants completely exit unfavorable branches and recover normal crawling speed, the odor information element is reduced to 0; (5) Step five, combining the pipeline path planning diagram to automatically arrange the pipeline, attaching the valve, and connecting the equipment with the pipe and the air port with the pipe, wherein the core characteristics of the step are as follows: (5-1) converting a single line diagram of a pipeline path into a double line diagram with actual pipeline wall thickness, pipe diameter and material according to a designed pipe diameter after the pipeline path is formed by using a BIM technology, so as to realize automatic pipe distribution; (5-2) manually adding a valve accessory and a tail end air port to complete the arrangement of a pipeline system; (6) Step six, checking the waterpower of the air pipe according to the wind speed requirements of the air port and the air pipe, and determining a final deodorizing pipeline system; (7) And combining the variation range of design parameters in the specification, and carrying out check calculation on the requirement contract of resistance loss, and adjusting the length, the width size or the pipe diameter of the circular air pipe to realize the optimization of the deodorizing pipeline system.

Description

Deodorization pipeline system generation method based on BIM and improved ant colony algorithm Technical Field The invention relates to a pipeline design technology of a deodorizing pipeline system. Background With the improvement of urban level, municipal infrastructure such as urban sewage treatment plants, garbage disposal stations, sludge incineration and the like is gradually increased, and a deodorizing system is an important ring in the design of such municipal projects, and plays a vital role in improving the internal and peripheral environments of workshops. In the traditional deodorizing system design, after the process scheme is determined, the position of a deodorizing tower or core treatment equipment is generally determined, then local sealing treatment is carried out according to the area where odor is located, then an air port and a pipeline route are arranged through CAD software two-dimensional drawing, then the air port and the pipeline are connected, and finally the pipe diameter is adjusted according to the hydraulic balance of the pipeline and other professional drawings. However, the traditional deodorization system design has obvious defects that firstly, the visualization effect is poor, the identification of each professional space position is difficult, the node position needs to be repeatedly discussed, secondly, the accuracy is low, because the pipeline routing arrangement is generally manually determined, the control on the net height and the grasping accuracy of the space under the beam are lower, particularly, the collision with a structural beam or other professional pipelines is easy to cause under the conditions of narrow space under the beam and high requirement on the net height, thirdly, the optimality is poor, the continuous alternation of drawings is deepened along with the continuous updating of the scheme, the pipeline space arrangement is tension, and the route needs to be continuously optimized, and at the moment, the defects of the traditional design are more and more obvious. Fourthly, the time consumption is long and the efficiency is low. The method has the advantages that manual calculation, analysis and meeting negotiation are continuously carried out by a designer on the plane route overlapping of the multi-specialty drawing, the time consumption is low, the automation degree of pipeline calculation and arrangement is low, and the change cost is high easily. When the path planning is unreasonable due to the problems of local clear height, incomplete updating of drawings and the like of the manually determined path, local civil engineering or electromechanical solution can be adjusted only through the form of a contact list and the like, so that the cost is increased. The core of the pipeline system design is path planning, and the main flow algorithm of the current path planning comprises an ant colony algorithm, an A-x algorithm, a neural network algorithm and the like, wherein the ant colony algorithm has extremely high research heat. The ant colony algorithm is a bionic algorithm discovered by Italian scholars M.dorigo in 1991, the algorithm is that ant colony is used for searching food, the principle is that 'pheromone' (feromone chemical substance) transmitted between ants is utilized to realize that a walking path is perceived by other ants, the closer to the real food, the higher the concentration of the pheromone is left by the ants, the higher the probability that the subsequent ants select the path is, and the optimal path is finally found through continuous iterative calculation. The ant colony algorithm is used in the fields of path planning, business trip, power distribution, communication routing and the like. The method has the main advantages that 1) the ants have information sharing and cooperation mechanisms, so that the optimal solution of searching can be realized, 2) the positive feedback mechanism of the ant colony can strengthen the optimizing capability, and 3) the ant colony is easy to combine with other algorithms. The method has the main defects of 1) low path optimizing speed in a large space and a large range and long time consumption, and 2) easy sinking into a local optimal solution. The improvement of the ant colony algorithm is mainly focused on the following aspects, 1) the cross fusion of the ant colony algorithm and other algorithms, and the complementary advantages and disadvantages improve the calculation speed. The method for planning the flight path of the express unmanned aerial vehicle by introducing the A-and-ant colony hybrid algorithm of the black area is disclosed in the Chinese patent document CN 108932876A, integrates the advantages of the ant colony and the A-algorithm, realizes route obstacle avoidance and quick optimization, and 2) improves the selection probability of the next node, reduces the blindness of search and improves the calculation efficiency. For example, a path planning method of a warehouse m