CN111445466B - Bolt anti-leakage screwing detection method, equipment and medium - Google Patents

Bolt anti-leakage screwing detection method, equipment and medium Download PDF

Info

Publication number
CN111445466B
CN111445466B CN202010250562.7A CN202010250562A CN111445466B CN 111445466 B CN111445466 B CN 111445466B CN 202010250562 A CN202010250562 A CN 202010250562A CN 111445466 B CN111445466 B CN 111445466B
Authority
CN
China
Prior art keywords
bolt
detected
torsion
image
color data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010250562.7A
Other languages
Chinese (zh)
Other versions
CN111445466A (en
Inventor
李彦祯
刘强
金长新
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shandong Inspur Scientific Research Institute Co Ltd
Original Assignee
Shandong Inspur Scientific Research Institute Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shandong Inspur Scientific Research Institute Co Ltd filed Critical Shandong Inspur Scientific Research Institute Co Ltd
Priority to CN202010250562.7A priority Critical patent/CN111445466B/en
Publication of CN111445466A publication Critical patent/CN111445466A/en
Application granted granted Critical
Publication of CN111445466B publication Critical patent/CN111445466B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0004Industrial image inspection
    • G06T7/0008Industrial image inspection checking presence/absence
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/90Determination of colour characteristics
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10004Still image; Photographic image
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30108Industrial image inspection
    • G06T2207/30164Workpiece; Machine component
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • General Factory Administration (AREA)
  • Image Analysis (AREA)

Abstract

The embodiment of the application provides a bolt anti-screwing detection method, equipment and medium, which are used for acquiring a bolt torsion image to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line. And determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected. And secondly, respectively carrying out color detection on each bolt torsion area to obtain a corresponding color detection result. And finally, determining whether the bolt is missed to be screwed or not in the product to be detected according to the color detection result. Through the scheme, the production cost of the product can be reduced to a great extent, the detection efficiency is improved, and the development of enterprises is promoted.

Description

Bolt anti-leakage screwing detection method, equipment and medium
Technical Field
The application relates to the technical field of detection, in particular to a bolt anti-leakage screwing detection method, equipment and medium.
Background
Threaded connections are widely used in various industries, such as in the machine industry, with bolts being the most common threaded connection in threaded connections. When mass production of products requiring bolting is performed, how to detect whether the bolts on the products are screwed down becomes an important link in the production process of the products.
In the prior art, the problems can be solved through an automatic paint dispensing sleeve. In the mass production process, the automatic paint-dispensing sleeve automatically coats the color on the top of the bolt when the bolt is screwed, and the top of the bolt cannot be coated with the color if the bolt is not screwed. However, after each automatic painting sleeve operation is completed, a special worker is required to check whether the bolts are screwed down, so that the workload is increased to a great extent, the working efficiency is low, and the production cost is increased.
Based on the method and the device, how to provide a method or device for detecting the leakage-proof screwing of the bolt can reduce the workload and improve the working efficiency.
Disclosure of Invention
The embodiment of the specification provides a bolt anti-screwing detection method, equipment and medium, which are used for solving the following technical problems in the prior art: in the mass production process, when the anti-leakage screwing detection is carried out on the bolts of the products, a large amount of manpower and material resources are required to be consumed, the production efficiency is low, and the production cost is high.
The embodiment of the specification adopts the following technical scheme:
a method of detecting leakage of a bolt, the method comprising:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the torsion areas of the bolts to obtain corresponding color detection results;
and determining whether the product to be detected is missed to be screwed or not according to the color detection result.
In one possible implementation manner, the color detection is performed on each bolt torsion area to obtain a corresponding color detection result, which specifically includes:
carrying out HSV color space recognition on the torsion areas of the bolts to obtain HSV color data of the torsion areas of the bolts;
wherein the color detection result includes corresponding HSV color data.
In one possible implementation manner, according to the color detection result, determining whether the product to be detected has a missing bolt includes:
according to the color detection result, determining HSV color data of each bolt torsion area;
determining whether each HSV color data is matched with corresponding preset color data;
and under the condition that each HSV color data is matched with the corresponding preset color data, determining that the to-be-detected product is not in screw missing.
In one possible implementation, the HSV color data includes: a hue value, a saturation value, a brightness value;
the determining whether the HSV color data is matched with corresponding preset color data specifically includes:
and under the condition that the tone value, the saturation value and the brightness value in the HSV color data do not exceed the corresponding preset threshold range, determining that the HSV color data are matched with the preset color data.
In one possible implementation, the method further includes:
under the condition that the HSV color data of the bolt torsion area is not matched with corresponding preset color data, determining that the bolt corresponding to the bolt torsion area is not screwed;
under the condition that the bolt corresponding to the bolt torsion area is not screwed, corresponding identification is carried out on the bolt torsion area of the bolt which is not screwed in the bolt torsion image to be detected, and a corresponding identification image is obtained;
and sending the identification image to a corresponding user terminal so that the user terminal can display the identification image to a corresponding user.
In one possible implementation manner, determining, according to the bolt torque image to be detected, a bolt torque area of the bolt torque image to be detected specifically includes:
determining the identification information of the product to be detected;
and determining each bolt torsion area of the bolt torsion image to be detected based on a preset rule and according to the identification information.
In one possible implementation manner, the bolt torsion image to be detected is: and the image acquisition device arranged on the production line is used for carrying out corresponding shooting on the product to be detected.
In one possible implementation, the product to be detected is an engine.
A bolt leakage prevention detection apparatus, the apparatus comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the torsion areas of the bolts to obtain corresponding color detection results;
and determining whether the product to be detected is missed to be screwed or not according to the color detection result.
A non-volatile computer storage medium storing computer-executable instructions for bolt anti-blowup detection, the computer-executable instructions configured to:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the bolt torsion areas to obtain corresponding color detection results;
and determining whether the product to be detected is missed to be screwed or not according to the color detection result.
The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect: and determining a corresponding bolt torsion area through a to-be-detected bolt torsion image of the to-be-detected product, carrying out color detection on the bolt torsion area, and determining whether the to-be-detected product is missed to be screwed by the obtained color detection result. Compared with the traditional detection method for the missing screwing of the bolt, the production cost of the product can be reduced to a great extent, the detection efficiency is improved, and the development of enterprises is promoted. And, adopt HSV color space discernment, compared with other traditional color space discernment, can describe the color more directly perceivedly, obtain more accurate color detection result.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flowchart of a method for detecting leakage of bolts according to an embodiment of the present disclosure;
fig. 2 is an application scenario diagram of a bolt anti-leakage detection method provided in an embodiment of the present application;
FIG. 3 is another flowchart of a method for detecting leakage of bolts according to an embodiment of the present disclosure;
fig. 4 is an interactive schematic diagram of a method for detecting leakage of bolts according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a bolt anti-leakage detection device according to an embodiment of the present disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present specification more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the disclosure, are intended to be within the scope of the present application based on the embodiments described herein.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
Bolts, as the most common mechanical parts in the prior art, are widely used in various industries in cooperation with nuts. In the prior art, whether the bolt of the detection product is screwed up or not usually needs a manual mode to detect, a large amount of manpower and material resources are consumed, the production cost is increased, and meanwhile, the production efficiency is lower.
Based on the above, the embodiments of the present application provide a method, an apparatus, and a medium for detecting leakage prevention of a bolt, so as to solve the above problems.
Fig. 1 is a flowchart of a method for detecting leakage of a bolt according to an embodiment of the present disclosure. As shown in fig. 1, the method for detecting leakage of a bolt according to the embodiment of the present disclosure includes:
s101, a server acquires a torsion image of a bolt to be detected of a product to be detected.
The torsion image of the bolt to be detected is an image obtained after an automatic paint-dispensing process on a production line.
In an embodiment of the present application, the bolt torsion image to be detected may be obtained by corresponding shooting of a product to be detected by an image acquisition device disposed on a production line. It should be noted that a product to be detected may have a plurality of torsion images of the bolt to be detected, and the number of torsion images of the bolt to be detected is determined according to the type of the product to be detected. For example, a product to be detected is in a cube structure, wherein three faces are provided with bolts, and the product to be detected can be provided with three torsion images of the bolts to be detected.
In the process of mass production of products, in order to improve the working efficiency and the product productivity, a mode of a production line is often adopted for mass production. As shown in fig. 2, the production line of the product may be divided into a plurality of processes, and the product to be inspected from the bolt-up process reaches the automatic painting process. Automatic paint dispensing equipment (such as an automatic paint dispensing cylinder) arranged in the automatic paint dispensing process automatically coats the head plane of the screwed bolt with color, and the head plane of the unscrewed bolt cannot be coated with color.
As shown in fig. 2, after the product is subjected to an automatic paint-dispensing process, the product enters a bolt anti-leakage screwing detection process, an image acquisition device can be arranged on the bolt anti-leakage screwing detection process, and a part of the product with a bolt is shot to obtain a torsion image of the bolt to be detected of the product to be detected.
A plurality of image acquisition devices can be arranged in the bolt anti-leakage screwing detection procedure, and one image acquisition device can also be arranged. Different products have different positions for arranging the bolts due to the unique characteristics. Under the condition that a plurality of positions of a certain type of products to be detected need to be detected in a bolt anti-leakage screwing mode, corresponding mechanical arms can be matched with all image acquisition equipment, the positions of the image acquisition equipment are controlled through the mechanical arms according to relevant information of the products to be detected, and the positions of the products to be detected are shot respectively.
The image capturing device may be a video camera, a camera, or an industrial camera. Compared with the traditional civil camera, the industrial camera has higher image stability, high transmission capability and high anti-interference capability.
Furthermore, a corresponding sensor can be arranged in the bolt anti-leakage screwing detection area so as to identify whether a product to be detected reaches the bolt anti-leakage screwing detection area, and after the fact that the product to be detected reaches the bolt anti-leakage screwing detection area is monitored, the PC client controls the image acquisition equipment to shoot.
S102, determining each bolt torsion area corresponding to the bolt torsion image to be detected according to the bolt torsion image to be detected.
In some embodiments of the present application, the determining the bolt torque area corresponding to the bolt torque image to be detected may be implemented by the following manner:
the identification information of the product to be detected can be determined first;
and determining each bolt torsion area of the bolt torsion image to be detected based on a preset rule and according to the identification information of the product to be detected.
The identification information may be, for example, a digital ID for uniquely representing a product to be inspected. For example, the identification information of the product a to be detected is 00001, and the identification information of the product B to be detected is 00002. The identification information of the product to be detected mentioned here may be pre-assigned.
In the present specification, determining the identification information of the product to be detected may be performed at least in two ways:
the first, can be the staff input while producing the product to be checked;
secondly, the identification information can be attached to the product to be detected in advance, and corresponding identification equipment is arranged on the production line to identify the identification information. For example, the identification information is attached to the product to be detected in the form of a two-dimensional code, and the identification information can be identified through a corresponding two-dimensional code scanner.
In the specification of the application, a pre-labeled template of a product to be detected can be pre-stored, and the association relationship between the template and the identification information is determined. The pre-labeled template referred to herein may be an image labeled for each bolt position. According to the determined identification information of the product to be detected, a template corresponding to the identification information can be determined. And matching the bolt torsion image to be detected with a corresponding template, and determining the bolt torsion area.
It should be noted that in the present specification, only one bolt may be included in each bolt torsion area, so as to better perform color recognition.
S103, respectively performing color detection on the torsion areas of the bolts to obtain corresponding color detection results.
Specifically, HSV color space recognition is carried out on each bolt torsion area, and HSV color data of each bolt torsion area are obtained.
The color detection result comprises the HSV color data, wherein the HSV color data comprises a tone value, a saturation value and a brightness value.
S104, determining whether the bolt is missed to be screwed or not in the product to be detected according to the color detection result.
Specifically, according to the color detection result, HSV color data of each bolt torsion area are determined;
determining whether each HSV color data is matched with corresponding preset color data;
under the condition that each HSV color data is matched with corresponding preset color data, it is determined that the to-be-detected product is not in bolt missing screwing.
In some embodiments of the present application, determining whether each HSV color data matches a corresponding preset color data may be accomplished by:
and under the condition that the hue value H, the saturation value S and the brightness value V in the HSV color data do not exceed the corresponding preset threshold range, determining that the HSV color data are matched with the preset color data.
The ranges of the hue value H, saturation value S, and brightness value V of the various colors in the HSV color space are shown in table 1 below:
TABLE 1
Figure BDA0002435331670000071
Figure BDA0002435331670000081
It should be noted that the preset threshold range corresponding to the hue value, the preset threshold range corresponding to the saturation value, and the preset threshold range corresponding to the brightness value may be different. In the embodiment of the present application, the above-mentioned preset threshold range may be set according to actual situations.
In addition, in the specification of the application, besides the HSV color data is obtained through the HSV color space identification so as to judge whether the bolt torsion area is missed to be screwed, the RGB color data can be obtained through RGB color space identification, and whether the bolt is missed to be screwed or not is determined through the RGB color data.
Compared with RGB color space identification, HSV color space identification can more intuitively express the brightness, the tone and the eye-present degree of the color, and comparison between the colors is convenient, for example, the range of tone dimension of blue in the HSV color space is 100-124. The RGB channels do not reflect object specific color information well.
It should be noted that if RGB color data is obtained in the early stage, the RGB color data of the image may be converted into HSV color data by a corresponding conversion algorithm, for example, openCV module.
In some embodiments of the present application, in order to enable corresponding staff to more conveniently know the condition of missing a bolt of a product to be detected, the method for detecting missing a bolt provided in the embodiments of the present application further includes the following steps, as shown in fig. 3:
s301, the server determines that the bolt corresponding to the bolt torsion area is not screwed under the condition that HSV color data of the bolt torsion area is not matched with corresponding preset color data.
The method for determining whether the HSV color data matches the corresponding preset color data is described above and will not be described herein.
S302, under the condition that the bolt corresponding to the bolt torsion area is not screwed, corresponding identification is carried out on the bolt torsion area of the bolt which is not screwed in the bolt torsion image to be detected, and a corresponding identification image is obtained.
The bolt torsion area for the missed bolt screwing can be identified in the form of corresponding symbols, figures, colors and the like, for example, fork numbers are marked in the bolt torsion area for the missed bolt screwing.
In the present specification, the area of the bolt torque that is not screwed may be identified, and the area of the bolt torque that is not screwed may be identified by a corresponding symbol, a graph, a color, or the like, and the manner of identifying the area of the bolt torque that is not screwed is different from the manner of identifying the area of the bolt torque that is not screwed, for example, a box is marked in the area of the bolt torque that is not screwed.
S303, the identification image is sent to the corresponding user terminal so that the user terminal can display the identification image to the corresponding user.
Through the scheme, the identification image is sent to corresponding staff, so that the missed screwed bolts can be conveniently and accurately positioned in time, and the working efficiency is improved.
In the specification of the application, besides sending the identification image to the corresponding user terminal, a corresponding alarm can be sent when the condition that the bolt of the product to be detected is not screwed can be detected.
In addition, in the present specification, data related to the detection of the bolt anti-unscrewing may be stored, for example, color detection results, identification images, and the like, and data analysis may be performed based on the recorded data at a later stage.
Engines are machines capable of converting other forms of energy into mechanical energy and are widely used in various industries. The structure of the engine is provided with a large number of bolt structures, and the working cost for detecting whether the bolts are missed to be screwed is high in the process of producing the transmitter. Therefore, the bolt anti-screwing detection method provided by the embodiment of the application can be applied to the production process of the engine, so that the production cost of the transmitter is saved, and the production efficiency is improved.
It should be noted that, besides being applied to the aspect of an engine, the bolt anti-tightening detection method provided by the embodiment of the application can be widely applied to other aspects, and is not limited to the engine.
In the specification of the application, an engine is taken as a product to be detected as an example, and the method for detecting the anti-screwing of the bolt is described. Fig. 4 is an interaction schematic diagram of a bolt anti-leakage detection method provided in an embodiment of the present application, as shown in fig. 4, when a PC client detects that an engine reaches a bolt anti-leakage detection area, the PC client opens client software, obtains engine information (i.e. identification information) from a production system, generates a corresponding instruction according to the engine information, sends the instruction to a corresponding camera, organizes the camera to shoot an engine, obtains a bolt torsion image to be detected, and sends the bolt torsion image to be detected to a server. The service end obtains engine information from the PC client through web service, and extracts characteristics of the bolt torsion image to be detected according to the engine information to obtain corresponding bolt torsion areas. After the service end obtains the torsion areas of each bolt, the torsion areas of each bolt are detected, the obtained detection results are stored in a database and are sent to the PC client, and the PC client can send the detection results to the production system for storage.
According to the bolt anti-leakage screwing detection method, the corresponding bolt torsion area is determined through the to-be-detected bolt torsion image of the to-be-detected product, color detection is carried out on the bolt torsion area, and whether the to-be-detected product is in bolt missing screwing or not is determined through the obtained color detection result. Through the technical scheme, compared with the traditional bolt missing detection method, the production cost of products can be reduced to a great extent, the detection efficiency is improved, and the development of enterprises is promoted. And, adopt HSV color space discernment, compared with other traditional color space discernment, can describe the color more directly perceivedly, obtain more accurate color detection result.
Fig. 5 is a schematic structural diagram of a bolt anti-leakage detection device according to an embodiment of the present application, as shown in fig. 5, the device includes:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the torsion areas of the bolts to obtain corresponding color detection results;
and determining whether the product to be detected is missed to be screwed or not according to the color detection result.
The embodiment of the application also provides a nonvolatile computer storage medium for detecting the leakage of the bolt, which stores computer executable instructions, wherein the computer executable instructions are set as follows:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the bolt torsion areas to obtain corresponding color detection results;
and determining whether the product to be detected is missed to be screwed or not according to the color detection result.
All embodiments in the application are described in a progressive manner, and identical and similar parts of all embodiments are mutually referred, so that each embodiment mainly describes differences from other embodiments. In particular, for the apparatus and medium embodiments, the description is relatively simple, as it is substantially similar to the method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not described in detail herein.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims (7)

1. A method for detecting leakage of a bolt, the method comprising:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the torsion areas of the bolts to obtain corresponding color detection results;
determining whether the product to be detected is missed to be screwed or not according to the color detection result;
the color detection is carried out on the torsion area of each bolt to obtain a corresponding color detection result, and the method specifically comprises the following steps:
carrying out HSV color space recognition on the torsion areas of the bolts to obtain HSV color data of the torsion areas of the bolts;
wherein the color detection result comprises corresponding HSV color data;
according to the color detection result, determining whether the product to be detected has the missing bolt, specifically comprises:
according to the color detection result, determining HSV color data of each bolt torsion area;
determining whether each HSV color data is matched with corresponding preset color data;
under the condition that each HSV color data is matched with corresponding preset color data, determining that the to-be-detected product is not in bolt missing screwing;
under the condition that the HSV color data of the bolt torsion area is not matched with corresponding preset color data, determining that the bolt corresponding to the bolt torsion area is not screwed;
under the condition that the bolt corresponding to the bolt torsion area is not screwed, corresponding identification is carried out on the bolt torsion area of the bolt which is not screwed in the bolt torsion image to be detected, and a corresponding identification image is obtained;
and sending the identification image to a corresponding user terminal so that the user terminal can display the identification image to a corresponding user.
2. The method of claim 1, wherein the HSV color data comprises: a hue value, a saturation value, a brightness value;
the determining whether the HSV color data is matched with corresponding preset color data specifically includes:
and under the condition that the tone value, the saturation value and the brightness value in the HSV color data do not exceed the corresponding preset threshold range, determining that the HSV color data are matched with the preset color data.
3. The method according to claim 1, wherein determining a bolt torque area of the bolt torque image to be detected according to the bolt torque image to be detected specifically comprises:
determining the identification information of the product to be detected;
and determining each bolt torsion area of the bolt torsion image to be detected based on a preset rule and according to the identification information.
4. The method of claim 1, wherein the bolt torque image to be detected is: and the image acquisition device arranged on the production line is used for carrying out corresponding shooting on the product to be detected.
5. The method of claim 1, wherein the product to be inspected is an engine.
6. A bolt leakage prevention detection apparatus, the apparatus comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the torsion areas of the bolts to obtain corresponding color detection results;
determining whether the product to be detected is missed to be screwed or not according to the color detection result;
the color detection is carried out on the torsion area of each bolt to obtain a corresponding color detection result, and the method specifically comprises the following steps:
carrying out HSV color space recognition on the torsion areas of the bolts to obtain HSV color data of the torsion areas of the bolts;
wherein the color detection result comprises corresponding HSV color data;
according to the color detection result, determining whether the product to be detected has the missing bolt, specifically comprises:
according to the color detection result, determining HSV color data of each bolt torsion area;
determining whether each HSV color data is matched with corresponding preset color data;
under the condition that each HSV color data is matched with corresponding preset color data, determining that the to-be-detected product is not in bolt missing screwing;
under the condition that the HSV color data of the bolt torsion area is not matched with corresponding preset color data, determining that the bolt corresponding to the bolt torsion area is not screwed;
under the condition that the bolt corresponding to the bolt torsion area is not screwed, corresponding identification is carried out on the bolt torsion area of the bolt which is not screwed in the bolt torsion image to be detected, and a corresponding identification image is obtained;
and sending the identification image to a corresponding user terminal so that the user terminal can display the identification image to a corresponding user.
7. A non-volatile computer storage medium storing computer-executable instructions for bolt anti-blowup detection, the computer-executable instructions configured to:
acquiring a torsion image of a bolt to be detected of a product to be detected; the bolt torsion image to be detected is an image after passing through an automatic paint-dispensing area on a production line;
determining corresponding bolt torsion areas of the bolt torsion image to be detected according to the bolt torsion image to be detected;
respectively carrying out color detection on the bolt torsion areas to obtain corresponding color detection results;
determining whether the product to be detected is missed to be screwed or not according to the color detection result;
the color detection is carried out on the torsion area of each bolt to obtain a corresponding color detection result, and the method specifically comprises the following steps:
carrying out HSV color space recognition on the torsion areas of the bolts to obtain HSV color data of the torsion areas of the bolts;
wherein the color detection result comprises corresponding HSV color data;
according to the color detection result, determining whether the product to be detected has the missing bolt, specifically comprises:
according to the color detection result, determining HSV color data of each bolt torsion area;
determining whether each HSV color data is matched with corresponding preset color data;
under the condition that each HSV color data is matched with corresponding preset color data, determining that the to-be-detected product is not in bolt missing screwing;
under the condition that the HSV color data of the bolt torsion area is not matched with corresponding preset color data, determining that the bolt corresponding to the bolt torsion area is not screwed;
under the condition that the bolt corresponding to the bolt torsion area is not screwed, corresponding identification is carried out on the bolt torsion area of the bolt which is not screwed in the bolt torsion image to be detected, and a corresponding identification image is obtained;
and sending the identification image to a corresponding user terminal so that the user terminal can display the identification image to a corresponding user.
CN202010250562.7A 2020-04-01 2020-04-01 Bolt anti-leakage screwing detection method, equipment and medium Active CN111445466B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010250562.7A CN111445466B (en) 2020-04-01 2020-04-01 Bolt anti-leakage screwing detection method, equipment and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010250562.7A CN111445466B (en) 2020-04-01 2020-04-01 Bolt anti-leakage screwing detection method, equipment and medium

Publications (2)

Publication Number Publication Date
CN111445466A CN111445466A (en) 2020-07-24
CN111445466B true CN111445466B (en) 2023-05-05

Family

ID=71651080

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010250562.7A Active CN111445466B (en) 2020-04-01 2020-04-01 Bolt anti-leakage screwing detection method, equipment and medium

Country Status (1)

Country Link
CN (1) CN111445466B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005003658A (en) * 2003-06-10 2005-01-06 Nippon Denro Kk Bolt looseness inspection method
JP2011130652A (en) * 2009-02-19 2011-06-30 Hitachinaka Techno Center:Kk Cable connection check system, identification tag manufacturing method, and related device
WO2017092431A1 (en) * 2015-12-01 2017-06-08 乐视控股(北京)有限公司 Human hand detection method and device based on skin colour
CN108805872A (en) * 2018-07-23 2018-11-13 珠海格力智能装备有限公司 The detection method and device of product
CN109520706A (en) * 2018-11-21 2019-03-26 云南师范大学 Automobile fuse box assembly detection system, image-recognizing method and screw hole positioning mode
CN110070080A (en) * 2019-03-12 2019-07-30 上海肇观电子科技有限公司 A kind of character detecting method and device, equipment and computer readable storage medium
CN110595745A (en) * 2019-04-26 2019-12-20 深圳市豪视智能科技有限公司 Detection method for abnormality of fixing screw of equipment and related product
CN110675373A (en) * 2019-09-12 2020-01-10 珠海格力智能装备有限公司 Component installation detection method, device and system
CN110930366A (en) * 2019-10-30 2020-03-27 同济大学 Nut loosening detection method for wind power tower cylinder

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6710426B2 (en) * 2016-12-19 2020-06-17 深▲せん▼前海達闥云端智能科技有限公司Cloudminds (Shenzhen) Robotics Systems Co.,Ltd. Obstacle detection method and device

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005003658A (en) * 2003-06-10 2005-01-06 Nippon Denro Kk Bolt looseness inspection method
JP2011130652A (en) * 2009-02-19 2011-06-30 Hitachinaka Techno Center:Kk Cable connection check system, identification tag manufacturing method, and related device
WO2017092431A1 (en) * 2015-12-01 2017-06-08 乐视控股(北京)有限公司 Human hand detection method and device based on skin colour
CN108805872A (en) * 2018-07-23 2018-11-13 珠海格力智能装备有限公司 The detection method and device of product
CN109520706A (en) * 2018-11-21 2019-03-26 云南师范大学 Automobile fuse box assembly detection system, image-recognizing method and screw hole positioning mode
CN110070080A (en) * 2019-03-12 2019-07-30 上海肇观电子科技有限公司 A kind of character detecting method and device, equipment and computer readable storage medium
CN110595745A (en) * 2019-04-26 2019-12-20 深圳市豪视智能科技有限公司 Detection method for abnormality of fixing screw of equipment and related product
CN110675373A (en) * 2019-09-12 2020-01-10 珠海格力智能装备有限公司 Component installation detection method, device and system
CN110930366A (en) * 2019-10-30 2020-03-27 同济大学 Nut loosening detection method for wind power tower cylinder

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张哲 ; 朱铮涛 ; 李渊 ; 刘杰 ; .瓶盖缺陷在线自动检测技术研究.计算机技术与发展.2016,(06),全文. *
王黄博昂 ; 葛旭 ; 童立靖 ; .彩色螺栓中心点定位系统的设计与实现.信息与电脑(理论版).2016,(15),全文. *

Also Published As

Publication number Publication date
CN111445466A (en) 2020-07-24

Similar Documents

Publication Publication Date Title
CN107168294B (en) Unmanned inspection monitoring method for thermal power water system equipment
CN109726620B (en) Video flame detection method and device
CN110441316B (en) Battery surface defect detection method and detection system
CN101820550B (en) Multi-viewpoint video image correction method, device and system
CN110827280B (en) Glue detection method and device based on machine vision and glue detection equipment
CN102262093A (en) Machine vision-based on-line detection method for printing machine
CN111896232B (en) Optical machine module testing method, equipment, system and computer readable storage medium
CN104118609A (en) Labeling quality detecting method and device
CN111445466B (en) Bolt anti-leakage screwing detection method, equipment and medium
CN110517260A (en) The detection method and device of circuit board, storage medium, electronic equipment
CN115862177A (en) Equipment inspection method and device
CN112613380A (en) Machine room patrol inspection method and device, electronic equipment and storage medium
CN114119535A (en) Laser cleaning effect on-line monitoring method based on visual detection
CN109945842B (en) Method for detecting label missing and analyzing labeling error of end face of bundled round steel
CN113838003A (en) Speckle detection method, device, medium, and computer program product for image
WO2020135097A1 (en) Method and apparatus for channel switch detection of display terminal
CN117035669A (en) Enterprise safety production management method and system based on artificial intelligence
US20150116486A1 (en) Terminal device, image measuring system and method of inspection of workpiece
CN110991387A (en) Distributed processing method and system for robot cluster image recognition
CN115564769A (en) Method for detecting motor rotor doubling defect by using deep learning
CN114550102A (en) Cargo accumulation detection method, device, equipment and system
CN114170373A (en) Target object labeling method, processor, device and mixing station
CN114170138A (en) Unsupervised industrial image anomaly detection model establishing method, detection method and system
KR20240003647A (en) Ai-based machine vesion quality inspection system and quality inspection method
CN115457290A (en) Multi-header automatic identification system and multi-header automatic identification method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20230419

Address after: 250101 building S02, 1036 Chaochao Road, high tech Zone, Jinan City, Shandong Province

Applicant after: Shandong Inspur Scientific Research Institute Co.,Ltd.

Address before: Floor 6, Chaochao Road, Shandong Province

Applicant before: JINAN INSPUR HIGH-TECH TECHNOLOGY DEVELOPMENT Co.,Ltd.

TA01 Transfer of patent application right
GR01 Patent grant
GR01 Patent grant