CN117969521A - Intelligent visual detection method for asphalt stirring equipment - Google Patents
Intelligent visual detection method for asphalt stirring equipment Download PDFInfo
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- CN117969521A CN117969521A CN202410390647.3A CN202410390647A CN117969521A CN 117969521 A CN117969521 A CN 117969521A CN 202410390647 A CN202410390647 A CN 202410390647A CN 117969521 A CN117969521 A CN 117969521A
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- 239000010426 asphalt Substances 0.000 title claims abstract description 327
- 238000003756 stirring Methods 0.000 title claims abstract description 326
- 238000001514 detection method Methods 0.000 title claims abstract description 23
- 230000000007 visual effect Effects 0.000 title claims abstract description 14
- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000002156 mixing Methods 0.000 claims description 119
- 238000012544 monitoring process Methods 0.000 claims description 100
- 230000002159 abnormal effect Effects 0.000 claims description 88
- 230000005856 abnormality Effects 0.000 claims description 40
- 238000000034 method Methods 0.000 claims description 38
- 238000011282 treatment Methods 0.000 claims description 12
- 238000011179 visual inspection Methods 0.000 claims description 8
- 238000011418 maintenance treatment Methods 0.000 claims description 6
- 238000007689 inspection Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000003068 static effect Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000007580 dry-mixing Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
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Abstract
The invention discloses an intelligent visual detection method for asphalt stirring equipment, which relates to the technical field of visual detection and comprises the following steps: step 1, detecting the tail gas area of equipment, step 2, detecting and processing the tail gas temperature of equipment, step 3, detecting and processing the temperature of an equipment stirring cylinder and step 4, detecting and processing the shaking of the equipment stirring cylinder.
Description
Technical Field
The invention relates to the technical field of visual detection, in particular to an intelligent visual detection method for asphalt stirring equipment.
Background
The smooth expansion of various pavement construction projects is independent of the operation of the asphalt stirring equipment, the asphalt stirring equipment is key equipment for ensuring the construction quality and improving the benefit, the efficiency of the asphalt stirring equipment and the quality of the stirred finished product are greatly related to whether the asphalt stirring equipment has faults or not and the type of the faults, and the images of all parts of the asphalt stirring equipment are acquired through machine vision, so that the health state of the asphalt stirring equipment can be effectively judged, and therefore, the research of an intelligent vision detection method for the asphalt stirring equipment is very necessary.
The existing intelligent visual detection method of the asphalt stirring equipment can basically meet the current requirements, but has certain defects, and the special performance of the intelligent visual detection method is as follows: (1) The existing intelligent visual detection method of the asphalt stirring equipment is lack of a certain attention to the tail gas exhausted by the asphalt stirring equipment, the state of the asphalt stirring equipment is reflected to a certain extent, the tail gas exhausted by the asphalt stirring equipment is mostly analyzed to judge whether harmful substances in the tail gas exceed standard, the intelligent visual detection is performed on the size and the temperature of the exhaust amount of the tail gas, so that faults of the asphalt stirring equipment can only be found manually by experience, the fault rate of the asphalt stirring equipment is improved, the efficiency of the asphalt stirring equipment is reduced, and the engineering speed is influenced.
(2) The existing intelligent visual detection method of the asphalt mixing equipment lacks a certain importance on whether the mixing drum breaks down, the mixing drum is a position which is important in relation to the asphalt generation quality, and whether the mixing drum breaks down is judged by manual experience at present, so that judgment is too dependent on subjective feeling, when the mixing drum breaks down, the problem is difficult to find in time, when the mixing drum breaks down, the problem is good to maintain and not easy to influence production, if the problem is not maintained in time, the problem is caused, the problem that the asphalt mixing equipment cannot be maintained easily occurs, so that the progress of engineering is seriously influenced, the rejection rate of the asphalt mixing equipment is improved, and engineering property is damaged.
Disclosure of Invention
The invention aims to provide an intelligent visual detection method for asphalt stirring equipment, which solves the problems in the background technology.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention provides an intelligent visual detection method for asphalt stirring equipment, which comprises the following steps: step 1, detecting an equipment tail gas area: before the asphalt stirring equipment is started, an exhaust-free image corresponding to the asphalt stirring equipment is obtained through a camera, after the asphalt stirring equipment is started, exhaust images corresponding to each monitoring time point of the asphalt stirring equipment are obtained through the camera, the tail gas area ratio coefficient of the asphalt stirring equipment is analyzed, and the asphalt stirring equipment is marked as normal asphalt stirring equipment or abnormal tail gas asphalt stirring equipment.
Step 2, detecting and treating the tail gas temperature of the equipment: and acquiring a temperature value corresponding to each pixel point of an infrared image of an exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs by a camera, and calculating a temperature abnormality threat coefficient of the exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs, so that the tail gas abnormal asphalt stirring equipment is marked as temperature abnormal asphalt stirring equipment or temperature normal asphalt stirring equipment, and carrying out exhaust inspection treatment on the temperature normal asphalt stirring equipment.
Step 3, detecting and treating the temperature of the stirring cylinder of the equipment: and acquiring a temperature value corresponding to each pixel point of an infrared image of a stirring cylinder to which the temperature-abnormal asphalt stirring equipment belongs by a camera, and calculating a stirring cylinder temperature abnormality threat coefficient of the temperature-abnormal asphalt stirring equipment, so that the temperature-abnormal asphalt stirring equipment is marked as stirring cylinder temperature-abnormal asphalt stirring equipment or to-be-dithered detection asphalt stirring equipment, and stirring cylinder temperature abnormality processing is performed.
Step 4, equipment mixing drum shake detection and treatment: the method comprises the steps of obtaining corresponding mixing drum images of each monitoring time point of the asphalt mixing equipment to be detected through a camera, obtaining the distance between the mixing drum of the asphalt mixing equipment to be detected and the camera at each monitoring time point through a laser ranging sensor on the camera, analyzing the average gray level difference value of the mixing drum images of each monitoring time point of the asphalt mixing equipment to be detected, calculating the shaking coefficient of the asphalt mixing equipment to be detected, judging whether serious shaking occurs to the asphalt mixing equipment to be detected, and carrying out shaking maintenance treatment.
Preferably, the specific analysis method for analyzing the ratio coefficient of the tail gas area of the asphalt stirring equipment comprises the following steps: extracting each pixel point of the exhaust image corresponding to each monitoring time point from the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment, and carrying out gray scale processing on each pixel point of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment so as to obtain each pixel point corresponding gray scale value of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipmentWherein x is represented as the number of each monitoring time point,/>Y is a positive integer greater than 2, n is the number of each pixel point, and is expressed by/>M is a positive integer greater than 2.
Extracting each pixel point of the non-exhaust image corresponding to the non-exhaust image from the asphalt stirring equipment, and obtaining the gray value corresponding to each pixel point of the non-exhaust image corresponding to the asphalt stirring equipment。
Calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhanced。
Analyzing gray level difference value of each pixel point of each monitoring time point of asphalt stirring equipment。
The method comprises the steps of obtaining a pre-defined gray difference value threshold value from a local database, comparing gray difference values of pixel points of each monitoring time point of asphalt stirring equipment with the pre-defined gray difference value threshold value, and if the gray difference value of a pixel point of a certain monitoring time point of the asphalt stirring equipment is larger than the pre-defined gray difference value threshold value, marking the pixel point as the tail gas pixel point, so that each tail gas pixel point of the monitoring time point is obtained, and each tail gas pixel point of each monitoring time point of the asphalt stirring equipment is obtained.
Counting the number of tail gas pixel points of each monitoring time point of asphalt stirring equipmentAnalyzing the ratio coefficient/>, of the tail gas area of the asphalt stirring equipmentWhere m is the number of pixels and y is the number of monitoring time points.
Preferably, each monitoring time point of the asphalt mixing equipment corresponds to each pixel point corresponding to the gray value after the contrast of the exhaust image is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhancedThe specific calculation method comprises the following steps: extracting a maximum value/>, corresponding to the gray scale, corresponding to the pixel point, of the exhaust image corresponding to each monitoring time point from the gray scale value, corresponding to each pixel point, of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipmentAnd gray minimum/>。
And extracting a pixel point corresponding gray maximum value j and a gray minimum value k of the non-exhaust image from the pixel point corresponding gray values of the non-exhaust image corresponding to the asphalt stirring equipment.
Calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhanced。
Calculating the gray value corresponding to each pixel point after the contrast of the non-exhaust image corresponding to the asphalt stirring equipment is enhanced。
Preferably, the method for calculating the temperature abnormality threat coefficient of the exhaust pipeline of the tail gas abnormality asphalt mixing equipment specifically comprises the following steps: and acquiring a tail gas temperature safety threshold of the asphalt stirring equipment from a local database.
Comparing the corresponding temperature value of each pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment with the exhaust gas temperature safety threshold, if the corresponding temperature value of a certain pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment is larger than the exhaust gas temperature safety threshold, marking the pixel point as the temperature abnormal pixel point, thereby obtaining each temperature abnormal pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number p of the temperature abnormal pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number q of the pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment。
Preferably, the calculating method of the temperature abnormality threat coefficient of the stirring cylinder of the temperature abnormality asphalt stirring device comprises the following steps: and acquiring a safe temperature threshold of a stirring cylinder of the asphalt stirring equipment from a local database.
Comparing the corresponding temperature value of each pixel point of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment with the safety threshold value of the temperature of the stirring barrel, counting the number r of the temperature abnormal pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment according to a method for calculating the temperature abnormal threat coefficient of the exhaust pipeline of the tail gas abnormal asphalt stirring equipment, counting the number s of the pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the stirring barrel of the temperature abnormal asphalt stirring equipment。
Preferably, the analyzing method is that the average gray level difference value of the mixing drum image of each monitoring time point of the asphalt mixing equipment to be detected in a shaking way is as follows: a still image of the mixing drum of the asphalt mixing apparatus is obtained from a local database.
Extracting each pixel point of each monitoring time point corresponding to the mixing drum image from each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, and carrying out gray scale processing on each pixel point of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, thereby obtaining each pixel point corresponding to gray scale value of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected。
Extracting each pixel point of the stirring cylinder still image from the stirring cylinder still image of the asphalt stirring device, and obtaining the corresponding gray value of each pixel point of the stirring cylinder still image of the asphalt stirring device。
Analyzing average gray level difference value of mixing drum images of each monitoring time point of asphalt mixing equipment to be detected in shaking modeWhere m is the number of pixels and y is the number of monitoring time points.
Preferably, the calculating method for calculating the shake coefficient of the asphalt mixing equipment to be shake-detected comprises the following specific steps: and obtaining the distance B between the asphalt stirring equipment and the camera in a static state from a local database.
Detecting the distance between a stirring cylinder and a camera of asphalt stirring equipment at each monitoring time point according to-be-shakenCalculating shaking coefficient/>, of to-be-shaken detection asphalt stirring equipmentWhere y is the number of monitoring time points.
Preferably, the method for judging whether the asphalt stirring equipment to be detected to be dithered is severely dithered and performing dithering maintenance treatment comprises the following steps: and acquiring a predefined shaking coefficient threshold value from a local database, comparing the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment with the predefined shaking coefficient threshold value, if the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment is larger than the predefined shaking coefficient threshold value, severely shaking the to-be-shaken detecting asphalt mixing equipment, and notifying a maintenance engineer to inspect and maintain the bearings, the chains and the connecting screws.
The invention has the beneficial effects that: (1) According to the invention, the tail gas area ratio coefficient of the asphalt stirring equipment is analyzed, so that the tail gas abnormal asphalt stirring equipment is obtained, the temperature abnormal threat coefficient of the exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs is calculated, the tail gas abnormal asphalt stirring equipment is marked as the temperature abnormal asphalt stirring equipment or the temperature normal asphalt stirring equipment, corresponding treatment is carried out, the tail gas discharged by the asphalt stirring equipment is detected visually, the fault of the asphalt stirring equipment is detected effectively, and accordingly, corresponding personnel can be informed to check or maintain in time, the fault rate of the asphalt stirring equipment is reduced, the efficiency of the asphalt stirring equipment is improved, and the engineering speed is ensured.
(2) According to the invention, the temperature anomaly threat coefficient of the stirring cylinder of the temperature anomaly asphalt stirring equipment is calculated, so that the temperature anomaly asphalt stirring equipment is marked as stirring cylinder temperature anomaly asphalt stirring equipment or stirring cylinder image average gray level difference values of all monitoring time points of the stirring cylinder temperature anomaly asphalt stirring equipment to be detected, the shaking coefficient of the stirring cylinder image average gray level difference values of all monitoring time points of the stirring cylinder temperature anomaly asphalt stirring equipment to be detected is calculated, so that whether the stirring cylinder image of the stirring cylinder image to be detected is severely shaken or not is judged, corresponding processing is carried out, the situation that the stirring cylinder fails but is not maintained in time is avoided, dependence on artificial subjective feeling is reduced, so that the engineering progress is ensured, the rejection rate of the stirring cylinder image to be detected is reduced, and damage to engineering property is avoided.
(3) According to the invention, the contrast ratio of the exhaust images corresponding to the monitoring time points of the asphalt stirring equipment is increased, the exhaust images corresponding to the monitoring time points with similar images are distinguished, and the difference value of the gray values of the pixel points between the exhaust images corresponding to the monitoring time points is increased, so that the subsequent analysis is convenient.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of the method of the present invention.
Fig. 2 is a schematic view of the positions of the stirring barrel, the camera and the laser ranging sensor.
Reference numerals: 1. mixing drum 2, camera, 3, laser rangefinder sensor.
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.
Referring to fig. 1, the present invention provides an intelligent visual inspection method for asphalt mixing equipment, comprising: step 1, detecting an equipment tail gas area: before the asphalt stirring equipment is started, an exhaust-free image corresponding to the asphalt stirring equipment is obtained through a camera, after the asphalt stirring equipment is started, exhaust images corresponding to each monitoring time point of the asphalt stirring equipment are obtained through the camera, the tail gas area ratio coefficient of the asphalt stirring equipment is analyzed, and the asphalt stirring equipment is marked as normal asphalt stirring equipment or abnormal tail gas asphalt stirring equipment.
It should be noted that, the cameras are high-speed infrared cameras, and the cameras in the embodiment of the invention are all high-speed infrared cameras.
In one specific embodiment, the method for analyzing the ratio coefficient of the tail gas area of the asphalt stirring equipment comprises the following steps: extracting each pixel point of the exhaust image corresponding to each monitoring time point from the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment, and carrying out gray scale processing on each pixel point of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment so as to obtain each pixel point corresponding gray scale value of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipmentWherein x is represented as the number of each monitoring time point,/>Y is a positive integer greater than 2, n is the number of each pixel point,M is a positive integer greater than 2.
Extracting each pixel point of the non-exhaust image corresponding to the non-exhaust image from the asphalt stirring equipment, and obtaining the gray value corresponding to each pixel point of the non-exhaust image corresponding to the asphalt stirring equipment。
Calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhanced。
Analyzing gray level difference value of each pixel point of each monitoring time point of asphalt stirring equipment。
The method comprises the steps of obtaining a pre-defined gray difference value threshold value from a local database, comparing gray difference values of pixel points of each monitoring time point of asphalt stirring equipment with the pre-defined gray difference value threshold value, and if the gray difference value of a pixel point of a certain monitoring time point of the asphalt stirring equipment is larger than the pre-defined gray difference value threshold value, marking the pixel point as the tail gas pixel point, so that each tail gas pixel point of the monitoring time point is obtained, and each tail gas pixel point of each monitoring time point of the asphalt stirring equipment is obtained.
Counting the number of tail gas pixel points of each monitoring time point of asphalt stirring equipmentAnalyzing the ratio coefficient/>, of the tail gas area of the asphalt stirring equipmentWhere m is the number of pixels and y is the number of monitoring time points.
The positions of the pixels of the asphalt mixing plant corresponding to the exhaust image and the pixels of the asphalt mixing plant corresponding to the non-exhaust image are identical.
In a specific embodiment, each monitoring time point of the asphalt mixing device corresponds to each pixel point corresponding to a gray value after the contrast of the exhaust image is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhancedThe specific calculation method comprises the following steps: extracting a maximum value/>, corresponding to the gray scale, corresponding to the pixel point, of the exhaust image corresponding to each monitoring time point from the gray scale value, corresponding to each pixel point, of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipmentAnd gray minimum/>。
And extracting a pixel point corresponding gray maximum value j and a gray minimum value k of the non-exhaust image from the pixel point corresponding gray values of the non-exhaust image corresponding to the asphalt stirring equipment.
Calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhanced。
Calculating the gray value corresponding to each pixel point after the contrast of the non-exhaust image corresponding to the asphalt stirring equipment is enhanced。
According to the invention, the contrast ratio of the exhaust images corresponding to the monitoring time points of the asphalt stirring equipment is increased, the exhaust images corresponding to the monitoring time points with similar images are distinguished, and the difference value of the gray values of the pixel points between the exhaust images corresponding to the monitoring time points is increased, so that the subsequent analysis is convenient.
In a specific embodiment of the invention, the asphalt stirring equipment is marked as normal asphalt stirring equipment or tail gas abnormal asphalt stirring equipment, and the specific marking method comprises the following steps: and acquiring a predefined tail gas area ratio coefficient threshold value from a local database, comparing the tail gas area ratio coefficient of the asphalt stirring equipment with the predefined tail gas area ratio coefficient threshold value, and if the tail gas area ratio coefficient of the asphalt stirring equipment is larger than the predefined tail gas area ratio coefficient threshold value, marking the asphalt stirring equipment as abnormal tail gas asphalt stirring equipment, otherwise, marking the asphalt stirring equipment as normal asphalt stirring equipment.
Step 2, detecting and treating the tail gas temperature of the equipment: and acquiring a temperature value corresponding to each pixel point of an infrared image of an exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs by a camera, and calculating a temperature abnormality threat coefficient of the exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs, so that the tail gas abnormal asphalt stirring equipment is marked as temperature abnormal asphalt stirring equipment or temperature normal asphalt stirring equipment, and carrying out exhaust inspection treatment on the temperature normal asphalt stirring equipment.
In a specific embodiment, the method for calculating the temperature abnormality threat coefficient of the exhaust pipeline of the tail gas abnormality asphalt mixing equipment comprises the following steps: and acquiring a tail gas temperature safety threshold of the asphalt stirring equipment from a local database.
Comparing the corresponding temperature value of each pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment with the exhaust gas temperature safety threshold, if the corresponding temperature value of a certain pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment is larger than the exhaust gas temperature safety threshold, marking the pixel point as the temperature abnormal pixel point, thereby obtaining each temperature abnormal pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number p of the temperature abnormal pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number q of the pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment。
In a specific embodiment of the invention, the tail gas abnormal asphalt stirring equipment is marked as abnormal temperature asphalt stirring equipment or normal temperature asphalt stirring equipment, and the specific marking method comprises the following steps: the method comprises the steps of obtaining a predefined temperature abnormality threat coefficient threshold value from a local database, comparing a temperature abnormality threat coefficient of an exhaust pipeline of the tail gas abnormality asphalt mixing equipment with the predefined temperature abnormality threat coefficient threshold value, if the temperature abnormality threat coefficient of the exhaust pipeline of the tail gas abnormality asphalt mixing equipment is larger than the predefined temperature abnormality threat coefficient threshold value, marking the tail gas abnormality asphalt mixing equipment as temperature abnormality asphalt mixing equipment, otherwise, marking the tail gas abnormality asphalt mixing equipment as temperature abnormality asphalt mixing equipment.
In a specific embodiment of the invention, the exhaust gas inspection treatment is performed on the normal-temperature asphalt stirring equipment, and the specific treatment method comprises the following steps: and when the asphalt stirring equipment is suspended, notifying a maintenance engineer to check the dust removing cloth bag of the asphalt stirring equipment with normal temperature.
According to the invention, the tail gas area ratio coefficient of the asphalt stirring equipment is analyzed, so that the tail gas abnormal asphalt stirring equipment is obtained, the temperature abnormal threat coefficient of the exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs is calculated, the tail gas abnormal asphalt stirring equipment is marked as the temperature abnormal asphalt stirring equipment or the temperature normal asphalt stirring equipment, corresponding treatment is carried out, the tail gas discharged by the asphalt stirring equipment is detected visually, the fault of the asphalt stirring equipment is detected effectively, and accordingly, corresponding personnel can be informed to check or maintain in time, the fault rate of the asphalt stirring equipment is reduced, the efficiency of the asphalt stirring equipment is improved, and the engineering speed is ensured.
Step 3, detecting and treating the temperature of the stirring cylinder of the equipment: and acquiring a temperature value corresponding to each pixel point of an infrared image of a stirring cylinder to which the temperature-abnormal asphalt stirring equipment belongs by a camera, and calculating a stirring cylinder temperature abnormality threat coefficient of the temperature-abnormal asphalt stirring equipment, so that the temperature-abnormal asphalt stirring equipment is marked as stirring cylinder temperature-abnormal asphalt stirring equipment or to-be-dithered detection asphalt stirring equipment, and stirring cylinder temperature abnormality processing is performed.
In a specific embodiment, the calculating method of the temperature abnormality threat coefficient of the stirring cylinder of the temperature abnormality asphalt stirring device comprises the following steps: and acquiring a safe temperature threshold of a stirring cylinder of the asphalt stirring equipment from a local database.
Comparing the corresponding temperature value of each pixel point of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment with the safety threshold value of the temperature of the stirring barrel, counting the number r of the temperature abnormal pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment according to a method for calculating the temperature abnormal threat coefficient of the exhaust pipeline of the tail gas abnormal asphalt stirring equipment, counting the number s of the pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the stirring barrel of the temperature abnormal asphalt stirring equipment。
In a specific embodiment of the invention, the temperature abnormal asphalt stirring equipment is marked as stirring cylinder temperature abnormal asphalt stirring equipment or asphalt stirring equipment to be detected in a shaking way, and the specific marking method comprises the following steps: acquiring a predefined stirring cylinder temperature abnormality threat coefficient threshold value from a local database, comparing the stirring cylinder temperature abnormality threat coefficient of the temperature abnormality asphalt stirring equipment with the predefined stirring cylinder temperature abnormality threat coefficient threshold value, if the stirring cylinder temperature abnormality threat coefficient of the temperature abnormality asphalt stirring equipment is larger than the predefined stirring cylinder temperature abnormality threat coefficient threshold value, marking the temperature abnormality asphalt stirring equipment as stirring cylinder temperature abnormality asphalt stirring equipment, otherwise, marking the temperature abnormality asphalt stirring equipment as asphalt stirring equipment to be detected in a shaking mode.
In the specific embodiment of the invention, the temperature abnormality treatment of the stirring cylinder is carried out, and the specific treatment method comprises the following steps: the operating equipment engineer is notified, and for the setting parameters of the asphalt mixing equipment, such as dry mixing time setting, wet mixing time setting, and mixing heating temperature setting, etc., it is checked whether the setting parameters are properly set according to the specifications of the equipment.
Step 4, equipment mixing drum shake detection and treatment: the method comprises the steps of obtaining corresponding mixing drum images of all monitoring time points of the asphalt mixing equipment to be detected through a camera 2, obtaining the distance between a mixing drum 1 of the asphalt mixing equipment to be detected and the camera 2 at all monitoring time points through a laser ranging sensor 3 on the camera 2, analyzing the average gray level difference value of the mixing drum images of all monitoring time points of the asphalt mixing equipment to be detected, calculating the shaking coefficient of the asphalt mixing equipment to be detected, judging whether serious shaking occurs to the asphalt mixing equipment to be detected, and carrying out shaking maintenance treatment.
The relative positions of the stirring cylinder 1, the camera 2, and the laser distance measuring sensor 3 are shown in fig. 2.
In a specific embodiment, the analyzing method for analyzing the average gray level difference value of the mixing drum image of each monitoring time point of the asphalt mixing equipment to be detected in a shaking manner comprises the following steps: a still image of the mixing drum of the asphalt mixing apparatus is obtained from a local database.
Extracting each pixel point of each monitoring time point corresponding to the mixing drum image from each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, and carrying out gray scale processing on each pixel point of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, thereby obtaining each pixel point corresponding to gray scale value of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected。
Extracting each pixel point of the stirring cylinder still image from the stirring cylinder still image of the asphalt stirring device, and obtaining the corresponding gray value of each pixel point of the stirring cylinder still image of the asphalt stirring device。
Analyzing average gray level difference value of mixing drum images of each monitoring time point of asphalt mixing equipment to be detected in shaking modeWhere m is the number of pixels and y is the number of monitoring time points.
In a specific embodiment, the calculating method of the shake coefficient of the asphalt mixing equipment to be shake-detected comprises the following steps: and obtaining the distance B between the asphalt stirring equipment and the camera in a static state from a local database.
Detecting the distance between a stirring cylinder and a camera of asphalt stirring equipment at each monitoring time point according to-be-shakenCalculating shaking coefficient/>, of to-be-shaken detection asphalt stirring equipmentWhere y is the number of monitoring time points.
In a specific embodiment, the method for judging whether the asphalt mixing equipment to be detected to be dithered is severely dithered and performing dithering maintenance treatment comprises the following steps: and acquiring a predefined shaking coefficient threshold value from a local database, comparing the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment with the predefined shaking coefficient threshold value, if the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment is larger than the predefined shaking coefficient threshold value, severely shaking the to-be-shaken detecting asphalt mixing equipment, and notifying a maintenance engineer to inspect and maintain the bearings, the chains and the connecting screws.
If serious shaking does not occur, the purchasing engineer is notified to perform quality inspection on the remaining asphalt raw material used by the asphalt mixing apparatus to be detected for shaking, and pay attention to the same batch of asphalt raw material.
According to the invention, the temperature anomaly threat coefficient of the stirring cylinder of the temperature anomaly asphalt stirring equipment is calculated, so that the temperature anomaly asphalt stirring equipment is marked as stirring cylinder temperature anomaly asphalt stirring equipment or stirring cylinder image average gray level difference values of all monitoring time points of the stirring cylinder temperature anomaly asphalt stirring equipment to be detected, the shaking coefficient of the stirring cylinder image average gray level difference values of all monitoring time points of the stirring cylinder temperature anomaly asphalt stirring equipment to be detected is calculated, so that whether the stirring cylinder image of the stirring cylinder image to be detected is severely shaken or not is judged, corresponding processing is carried out, the situation that the stirring cylinder fails but is not maintained in time is avoided, dependence on artificial subjective feeling is reduced, so that the engineering progress is ensured, the rejection rate of the stirring cylinder image to be detected is reduced, and damage to engineering property is avoided.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (8)
1. An intelligent visual inspection method for asphalt mixing equipment, comprising the steps of:
step 1, detecting an equipment tail gas area: before the asphalt stirring equipment is started, acquiring an exhaust-free image corresponding to the asphalt stirring equipment through a camera, acquiring exhaust images corresponding to each monitoring time point of the asphalt stirring equipment through the camera after the asphalt stirring equipment is started, analyzing the tail gas area ratio coefficient of the asphalt stirring equipment, and marking the asphalt stirring equipment as normal asphalt stirring equipment or tail gas abnormal asphalt stirring equipment;
Step 2, detecting and treating the tail gas temperature of the equipment: acquiring a temperature value corresponding to each pixel point of an infrared image of an exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs by a camera, and calculating a temperature abnormality threat coefficient of the exhaust pipeline to which the tail gas abnormal asphalt stirring equipment belongs, so that the tail gas abnormal asphalt stirring equipment is marked as temperature abnormal asphalt stirring equipment or temperature normal asphalt stirring equipment, and carrying out exhaust inspection treatment on the temperature normal asphalt stirring equipment;
Step 3, detecting and treating the temperature of the stirring cylinder of the equipment: acquiring a temperature value corresponding to each pixel point of an infrared image of a stirring cylinder to which the temperature-abnormal asphalt stirring equipment belongs by a camera, and calculating a stirring cylinder temperature abnormality threat coefficient of the temperature-abnormal asphalt stirring equipment, so that the temperature-abnormal asphalt stirring equipment is marked as stirring cylinder temperature-abnormal asphalt stirring equipment or to-be-dithered asphalt stirring equipment to be detected, and stirring cylinder temperature abnormality processing is carried out;
Step 4, equipment mixing drum shake detection and treatment: the method comprises the steps of obtaining corresponding mixing drum images of each monitoring time point of the asphalt mixing equipment to be detected through a camera, obtaining the distance between the mixing drum of the asphalt mixing equipment to be detected and the camera at each monitoring time point through a laser ranging sensor on the camera, analyzing the average gray level difference value of the mixing drum images of each monitoring time point of the asphalt mixing equipment to be detected, calculating the shaking coefficient of the asphalt mixing equipment to be detected, judging whether serious shaking occurs to the asphalt mixing equipment to be detected, and carrying out shaking maintenance treatment.
2. The intelligent visual inspection method for asphalt mixing equipment according to claim 1, wherein the analyzing the ratio coefficient of the tail gas area of the asphalt mixing equipment comprises the following specific analysis methods:
Extracting each pixel point of the exhaust image corresponding to each monitoring time point from the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment, and carrying out gray scale processing on each pixel point of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment so as to obtain each pixel point corresponding gray scale value of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment Wherein x is represented as the number of each monitoring time point,/>Y is a positive integer greater than 2, n is the number of each pixel point,M is a positive integer greater than 2;
extracting each pixel point of the non-exhaust image corresponding to the non-exhaust image from the asphalt stirring equipment, and obtaining the gray value corresponding to each pixel point of the non-exhaust image corresponding to the asphalt stirring equipment ；
Calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhanced；
Analyzing gray level difference value of each pixel point of each monitoring time point of asphalt stirring equipment；
Acquiring a pre-defined gray difference value threshold value from a local database, comparing the gray difference value of each pixel point of each monitoring time point of the asphalt stirring equipment with the pre-defined gray difference value threshold value, and if the gray difference value of a certain pixel point of a certain monitoring time point of the asphalt stirring equipment is larger than the pre-defined gray difference value threshold value, marking the pixel point as the tail gas pixel point, thereby obtaining each tail gas pixel point of the monitoring time point and each tail gas pixel point of each monitoring time point of the asphalt stirring equipment;
counting the number of tail gas pixel points of each monitoring time point of asphalt stirring equipment Analyzing the ratio coefficient/>, of the tail gas area of the asphalt stirring equipmentWhere m is the number of pixels and y is the number of monitoring time points.
3. The intelligent visual inspection method for asphalt mixing equipment according to claim 2, wherein each monitoring time point of the asphalt mixing equipment corresponds to each pixel point corresponding to gray value after the contrast of the exhaust image is enhancedThe asphalt stirring equipment corresponds to gray values/>, corresponding to each pixel point after the contrast of the non-exhaust image is enhancedThe specific calculation method comprises the following steps:
Extracting a maximum value of the gray scale corresponding to each pixel point of the exhaust image corresponding to each monitoring time point from the gray scale corresponding to each pixel point of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment And gray minimum/>；
Extracting a pixel point corresponding gray maximum value j and a gray minimum value k of the non-exhaust image from the pixel point corresponding gray values of the non-exhaust image corresponding to the asphalt stirring equipment;
calculating the gray value corresponding to each pixel point after the contrast of the exhaust image corresponding to each monitoring time point of the asphalt stirring equipment is enhanced ；
Calculating the gray value corresponding to each pixel point after the contrast of the non-exhaust image corresponding to the asphalt stirring equipment is enhanced。
4. The intelligent visual detection method for asphalt mixing equipment according to claim 1, wherein the calculating method is characterized in that the temperature abnormality threat coefficient of the exhaust pipeline to which the exhaust abnormal asphalt mixing equipment belongs is as follows:
Acquiring a tail gas temperature safety threshold value of asphalt stirring equipment from a local database;
Comparing the corresponding temperature value of each pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment with the exhaust gas temperature safety threshold, if the corresponding temperature value of a certain pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment is larger than the exhaust gas temperature safety threshold, marking the pixel point as the temperature abnormal pixel point, thereby obtaining each temperature abnormal pixel point of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number p of the temperature abnormal pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, counting the number q of the pixel points of the infrared image of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the exhaust pipeline of the exhaust abnormal asphalt stirring equipment 。
5. The intelligent visual inspection method for asphalt mixing equipment according to claim 4, wherein the calculating of the abnormal temperature threat coefficient of the mixing drum of the abnormal temperature asphalt mixing equipment is as follows:
Acquiring a stirring cylinder temperature safety threshold value of asphalt stirring equipment from a local database;
Comparing the corresponding temperature value of each pixel point of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment with the safety threshold value of the temperature of the stirring barrel, counting the number r of the temperature abnormal pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment according to a method for calculating the temperature abnormal threat coefficient of the exhaust pipeline of the tail gas abnormal asphalt stirring equipment, counting the number s of the pixel points of the infrared image of the stirring barrel of the temperature abnormal asphalt stirring equipment, and calculating the temperature abnormal threat coefficient of the stirring barrel of the temperature abnormal asphalt stirring equipment 。
6. The intelligent visual inspection method for asphalt mixing equipment according to claim 2, wherein the analyzing method is characterized in that the average gray level difference value of the mixing drum image at each monitoring time point of the asphalt mixing equipment to be inspected in a shaking manner is as follows:
acquiring a mixing drum still image of the asphalt mixing device from a local database;
extracting each pixel point of each monitoring time point corresponding to the mixing drum image from each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, and carrying out gray scale processing on each pixel point of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected, thereby obtaining each pixel point corresponding to gray scale value of each monitoring time point corresponding to the mixing drum image of the asphalt mixing equipment to be detected ；
Extracting each pixel point of the stirring cylinder still image from the stirring cylinder still image of the asphalt stirring device, and obtaining the corresponding gray value of each pixel point of the stirring cylinder still image of the asphalt stirring device；
Analyzing average gray level difference value of mixing drum images of each monitoring time point of asphalt mixing equipment to be detected in shaking modeWhere m is the number of pixels and y is the number of monitoring time points.
7. The intelligent visual inspection method for asphalt mixing plant according to claim 6, wherein the calculating the shaking coefficient of the asphalt mixing plant to be detected by shaking comprises the following specific calculating method:
obtaining the distance B between the asphalt stirring equipment and the camera in a static state from a local database;
detecting the distance between a stirring cylinder and a camera of asphalt stirring equipment at each monitoring time point according to-be-shaken Calculating shaking coefficient/>, of to-be-shaken detection asphalt stirring equipmentWhere y is the number of monitoring time points.
8. The intelligent visual inspection method for asphalt mixing equipment according to claim 1, wherein the specific method for judging whether the asphalt mixing equipment to be inspected to be dithered is dithered or not and performing dithering maintenance treatment is as follows:
And acquiring a predefined shaking coefficient threshold value from a local database, comparing the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment with the predefined shaking coefficient threshold value, if the shaking coefficient of the to-be-shaken detecting asphalt mixing equipment is larger than the predefined shaking coefficient threshold value, severely shaking the to-be-shaken detecting asphalt mixing equipment, and notifying a maintenance engineer to inspect and maintain the bearings, the chains and the connecting screws.
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