CN112766638A - Method and system for analyzing working efficiency of pipeline operators based on video images - Google Patents
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Abstract
The invention relates to the technical field of video image analysis, and discloses a method and a system for analyzing the working efficiency of a pipeline operator based on video images.
Description
Technical Field
The invention relates to the technical field of video image analysis, in particular to a method and a system for analyzing the working efficiency of a pipeline operator based on video images.
Background
At present, most industrial production lines in domestic and even global enterprises still need manual operation, and the manual operation is indispensable particularly in some complex production processes.
However, there is no effective method for calculating and determining the work efficiency of the pipeline operators at the present stage, and the enterprise cannot be helped to select the operators with skillful operation, so that the operation gestures of the skilled employees cannot be analyzed to help other employees to improve the efficiency.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a method and a system for analyzing the working efficiency of the pipeline operators based on video images, which can screen out operators with skillful operation, analyze the operation gestures of the skilled operators to help other employees to improve the efficiency, quickly find out the employees who are not operated in a standard or specified manner, and correct the employees in time.
The purpose of the invention is realized by the following technical scheme:
a method for analyzing the working efficiency of pipeline operators based on video images comprises the following steps:
s101, collecting operation video data, reading the operation video data, and generating video data to be analyzed;
s102, calculating the video data to be analyzed, and generating motion trajectory data and motion period data to be analyzed;
s103, acquiring standard operation video data, and generating standard motion trajectory data and standard period data according to the standard operation video data;
s104, comparing the motion trajectory data to be analyzed with the standard motion trajectory data, and comparing the motion period data with the standard period data to generate an operation standard deviation and an operation standard value;
and S105, obtaining working efficiency data according to the operation standard deviation and the operation standard value.
In one embodiment, the read operation specifically includes the following steps:
and extracting the frame rate and the frame number in the operation video data.
In one embodiment, in the step of calculating the video data to be analyzed and generating the motion trajectory data and the motion cycle data to be analyzed, the method specifically includes the following steps:
generating a plurality of coordinate marking values for marking the operation of the staff, and connecting the coordinate marking values.
In one embodiment, the step of obtaining standard operation video data and generating standard motion trajectory data and standard period data according to the standard operation video data specifically includes the following steps:
and generating motion range data according to the standard motion trail data.
In one embodiment, the step of comparing the motion trajectory data to be analyzed with the standard motion trajectory data, and comparing the motion period data with the standard period data to generate an operation standard deviation and an operation standard value specifically includes the following steps:
and if the motion trajectory data to be analyzed accords with the motion range data and the motion period data accords with the standard period data, generating the operation standard deviation and the operation standard value.
In one embodiment, the method further includes the following steps in the step of acquiring standard operation video data and generating standard motion trajectory data and standard period data according to the standard operation video data:
and extracting and storing a key action coordinate value of the standard motion trajectory data, and comparing the key action coordinate value with the coordinate marking value to generate motion trajectory completion data.
In one embodiment, the step of acquiring operation video data, and performing a reading operation on the operation video data to generate video data to be analyzed specifically includes the following steps:
and generating a plurality of standard operation coordinate values for marking the standard operation of the staff according to the operation video data.
System based on video image analysis assembly line operating personnel work efficiency includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring operation video data, reading the operation video data and generating video data to be analyzed, and the acquisition module is also used for acquiring standard operation video data and generating standard motion track data and standard period data according to the standard operation video data;
the calculation module is used for calculating the video data to be analyzed and generating motion track data and motion cycle data to be analyzed, and the calculation module is also used for obtaining working efficiency data according to the operation standard deviation and the operation standard value; and
and the comparison module is used for comparing the motion track data to be analyzed with the standard motion track data, comparing the motion period data with the standard period data, and generating an operation standard deviation and an operation standard value.
In one embodiment, the acquisition module is further configured to extract a frame rate and a frame number in the operation video data.
In one embodiment, the acquisition module is further configured to extract and store a key action coordinate value of the standard motion trajectory data, compare the key action coordinate value with the coordinate mark value, and generate motion trajectory completion data.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention relates to a method and a system for analyzing the working efficiency of a pipeline operator based on video images, which are characterized in that operation video data which are shot by the front side of the pipeline operator relatively completely are obtained, the operation video data are read frame by frame, each frame of image has corresponding key point coordinates, the motion track data and the motion cycle data of actual operation are finally obtained, the motion track data and the motion cycle data of the actual operation are finally compared with the motion track data and the motion cycle data with standard high efficiency, the standard difference and the standard value of the actual operation are further obtained, and whether the efficiency of the pipeline operator is high or not is judged, so that an enterprise is helped to screen out operators with skillful operation, and other staff are helped to improve the efficiency by analyzing the operation gestures of skilled staff.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flowchart illustrating steps of a method for analyzing the work efficiency of a pipeline operator based on video images according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating an example of a method for analyzing the work efficiency of a pipeline operator based on video images according to an embodiment of the present invention;
FIG. 3 is a functional block diagram of a system for analyzing the work efficiency of a pipeline operator based on video images according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating another example of a method for analyzing the working efficiency of a pipeline operator based on video images according to an embodiment of the present invention.
Detailed Description
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
A method for analyzing the working efficiency of pipeline operators based on video images comprises the following steps:
s101, collecting operation video data, reading the operation video data, and generating video data to be analyzed;
s102, calculating video data to be analyzed, and generating motion trajectory data and motion period data to be analyzed;
s103, acquiring standard operation video data, and generating standard motion trajectory data and standard period data according to the standard operation video data;
s104, comparing the motion trajectory data to be analyzed with standard motion trajectory data, and comparing the motion period data with standard period data to generate an operation standard deviation and an operation standard value;
and S105, obtaining working efficiency data according to the operation standard deviation and the operation standard value.
In order to better understand the technical concept of the method for analyzing the working efficiency of the pipeline operator based on the video image and better understand the technical scheme of the method for analyzing the working efficiency of the pipeline operator based on the video image, the method for analyzing the working efficiency of the pipeline operator based on the video image comprises the following steps:
s101, collecting operation video data, reading the operation video data, and generating video data to be analyzed;
specifically, the reading operation specifically includes the steps of: frame rates and frame numbers in the operational video data are extracted.
It should be noted that, the operation video data that is shot by the front of the pipeline operator and is relatively complete is first obtained, and after the operation video data is obtained, the operation video data is read frame by frame to generate a multi-frame image, that is, the video data to be analyzed.
Step S102, calculating video data to be analyzed, and generating motion track data and motion cycle data to be analyzed;
specifically, in the step of calculating video data to be analyzed and generating motion trajectory data and motion cycle data to be analyzed, the method specifically comprises the following steps:
and generating a plurality of coordinate marking values for marking the operation of the staff, and connecting the coordinate marking values.
It should be noted that, assuming that all operations of the pipeline operator are completed by hands, further, for each frame of image, a plurality of coordinate mark values are generated, where the coordinate mark values are coordinates corresponding to key points of the hands, and the coordinate mark values use the upper left corner as an origin, as shown in fig. 2, two numbers on the left side are coordinates of key points of the left wrist, two numbers on the right side are coordinates of key points of the right wrist, and finally, the key point coordinates are connected to form motion trajectory data to be analyzed, and at the same time, time required by one work cycle of the operator, that is, the motion cycle data, is calculated.
Step S103, standard operation video data are obtained, and standard motion trajectory data and standard period data are generated according to the standard operation video data.
Specifically, the method comprises the following steps of acquiring standard operation video data, and generating standard motion trajectory data and standard period data according to the standard operation video data:
and generating motion range data according to the standard motion trail data.
It should be noted that the standard operation video data is a video of a worker completing one work cycle or multiple work cycles with high efficiency at an angle of 45 degrees obliquely above the front surface, and is obtained through the following formula: and calculating to obtain standard period data, and meanwhile, marking the coordinates of key points in the standard operation video data to obtain standard motion trajectory data.
It should be noted that, because different workers have different body types, deviation between the actual motion trajectory and the standard motion trajectory data may occur, specifically, end point data of a single working cycle is obtained according to the standard operation video data, meanwhile, cycle error range data is generated, whether the motion cycle data passes through the end point data or the cycle error range data of the single working cycle for multiple times is judged, and standard cycle data is generated, it needs to be explained that the end point data of the single working cycle refers to a coordinate point at the end of the action, the cycle error range data refers to data passing through a maximum error range with the end point of the single working cycle as the center of a circle for multiple times, if the end point passes through multiple times in a working cycle or passes through a maximum error range with the end point as the center of a circle for multiple times, the number of passes through is recorded as a judgment standard for ending the single working cycle, i.e. standard period data. Furthermore, aiming at a working video containing a plurality of working cycles, dividing a maximum error end point range by taking the end point as a central point, adding one to the end point passing number when the motion track moves to the range, and judging that one working cycle is ended when the single working cycle end point passing number of the working video is the same as the single working cycle end point passing number in the standard working video; and then, setting the end point of the working video to start new working period calculation, so that the specific working period can be clearly obtained no matter how many working periods exist, and the working efficiency can be more accurately judged.
Step S104, comparing the motion trajectory data to be analyzed with standard motion trajectory data, and comparing the motion period data with standard period data to generate an operation standard deviation and an operation standard value;
and S105, obtaining working efficiency data according to the operation standard deviation and the operation standard value.
Specifically, in the step of comparing the motion trajectory data to be analyzed with the standard motion trajectory data, and comparing the motion period data with the standard period data to generate the operation standard deviation and the operation standard value, the method specifically includes the following steps:
and if the motion trajectory data to be analyzed accords with the motion range data and the motion period data accords with the standard period data, generating an operation standard deviation and an operation standard value.
More specifically, in the step of obtaining the standard operation video data and generating the standard motion trajectory data and the standard period data according to the standard operation video data, the method further includes the following steps:
and extracting and storing key action coordinate values of the standard motion trajectory data, and comparing the key action coordinate values with the coordinate mark values to generate motion trajectory completion data.
It should be noted that, the operation standard deviation and the operation standard value are obtained by comparing the motion trajectory data to be analyzed with the standard motion trajectory data and comparing the motion period data with the standard period data, wherein in the process of comparing the motion trajectory data to be analyzed with the standard motion trajectory data, coordinate points of several key actions in the standard motion trajectory data are extracted to determine whether the operation of the worker is a complete operation process. Further, the standard deviation is most often used in probability statistics as a measure of the degree of statistical distribution. The standard deviation definition is the square root of the arithmetic mean of the standard values of the units of the population squared with their mean. It reflects the degree of dispersion between individuals within a group. The result of the degree of distribution is measured, and thus, by observing the standard deviation, it is possible to clearly observe the difference between the operation efficiency of the actual worker and the standard operation.
Further, in an embodiment, the method includes the following steps of collecting operation video data, performing a reading operation on the operation video data, and generating video data to be analyzed:
and generating a plurality of standard operation coordinate values for marking the standard operation of the staff according to the operation video data.
Here, the standard operation coordinate values refer to operation coordinates of all parts, and naturally include the above-described key operation coordinate values.
It should be noted that fig. 4 shows that the operator draws a triangle at a constant speed for 3 times, and through the test, the application identifies the movement locus of the key points of his hand and calculates the movement time.
Therefore, the method for analyzing the work efficiency of the pipeline operator based on the video images comprises the steps of obtaining operation video data which are shot by the front side and are relatively complete of the pipeline operator, reading the operation video data frame by frame, obtaining corresponding key point coordinates of each frame of image, obtaining motion track data and motion cycle data of actual operation finally, comparing the motion track data and the motion cycle data of the actual operation with standard efficient motion track data and motion cycle data, obtaining standard deviation and standard value of the actual operation, judging whether the pipeline operator is efficient or not, and helping an enterprise to select out skillful operators and help other workers to improve the efficiency by analyzing operation gestures of skilled workers.
Referring to fig. 3, a system 10 for analyzing the working efficiency of a pipeline operator based on video images includes an acquisition module 100, a calculation module 200, and a comparison module 300.
The acquisition module 100 is configured to acquire operation video data, perform a reading operation on the operation video data, and generate video data to be analyzed, and the acquisition module 100 is further configured to acquire standard operation video data and generate standard motion trajectory data and standard period data according to the standard operation video data; the acquisition module 100 is further configured to extract a frame rate and a frame number in the operation video data. The acquisition module 100 is further configured to extract and store a key motion coordinate value of the standard motion trajectory data, compare the key motion coordinate value with the coordinate mark value, and generate motion trajectory completion data. The calculation module 200 is configured to calculate video data to be analyzed, generate motion trajectory data and motion cycle data to be analyzed, and obtain work efficiency data according to the operation standard deviation and the operation standard value; the comparison module 300 is configured to compare the motion trajectory data to be analyzed with the standard motion trajectory data, and compare the motion period data with the standard period data to generate an operation standard deviation and an operation standard value.
It should be noted that the system is a system for applying the method for analyzing the work efficiency of the pipeline operator based on the video image, wherein the calculation module 200 is further configured to obtain end point data of a single work cycle according to the standard operation video data, generate cycle error range data, determine whether the motion cycle data passes through the end point data or the cycle error range data of the single work cycle for multiple times, and generate standard cycle data.
Compared with the prior art, the invention has the following advantages:
according to the method and the system 10 for analyzing the working efficiency of the pipeline operators based on the video images, the operation video data which are shot by the front and relatively complete sides of the pipeline operators are obtained, the operation video data are read frame by frame, each frame of image has the corresponding key point coordinates, the motion track data and the motion cycle data of actual operation are finally obtained, the motion track data and the motion cycle data of actual operation are finally compared with the motion track data and the motion cycle data of standard high efficiency, the standard deviation and the standard value of actual operation are further obtained, whether the pipeline operators are high efficiency or not is judged, the operation of skillful operators are screened out by an enterprise, and the operation gestures of skilled operators are analyzed to help other operators to improve the efficiency.
The above embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for analyzing the working efficiency of pipeline operators based on video images is characterized by comprising the following steps:
collecting operation video data, and reading the operation video data to generate video data to be analyzed;
calculating the video data to be analyzed, and generating motion trajectory data and motion period data to be analyzed;
acquiring standard operation video data, and generating standard motion track data and standard period data according to the standard operation video data;
comparing the motion trajectory data to be analyzed with the standard motion trajectory data, and comparing the motion period data with the standard period data to generate an operation standard deviation and an operation standard value;
and obtaining working efficiency data according to the operation standard deviation and the operation standard value.
2. The method for analyzing pipeline operator work efficiency based on video images according to claim 1, wherein the reading operation specifically comprises the steps of:
and extracting the frame rate and the frame number in the operation video data.
3. The method for analyzing the working efficiency of the operators on the basis of the video images according to the claim 2, wherein in the step of calculating the video data to be analyzed and generating the motion trajectory data and the motion period data to be analyzed, the method specifically comprises the following steps:
generating a plurality of coordinate marking values for marking the operation of the staff, and connecting the coordinate marking values.
4. The method for analyzing the working efficiency of the operators on the production line based on the video images as claimed in claim 1, wherein the steps of obtaining the standard operation video data and generating the standard motion trajectory data and the standard period data according to the standard operation video data specifically comprise the following steps:
and generating motion range data according to the standard motion trail data.
5. The method according to claim 4, wherein the step of comparing the motion trajectory data to be analyzed with the standard motion trajectory data and comparing the motion period data with the standard period data to generate an operation standard deviation and an operation standard value specifically comprises the steps of:
and if the motion trajectory data to be analyzed accords with the motion range data and the motion period data accords with the standard period data, generating the operation standard deviation and the operation standard value.
6. The method of claim 5, wherein in the step of obtaining standard operation video data and generating standard motion trajectory data and standard period data based on the standard operation video data, further comprising the steps of:
and extracting and storing a key action coordinate value of the standard motion trajectory data, and comparing the key action coordinate value with the coordinate marking value to generate motion trajectory completion data.
7. The method for analyzing the working efficiency of the operators on the basis of the video image of the production line according to claim 6, wherein the steps of collecting the operation video data, reading the operation video data and generating the video data to be analyzed specifically comprise the following steps:
and generating a plurality of standard operation coordinate values for marking the standard operation of the staff according to the operation video data.
8. System based on video image analysis pipeline operating personnel work efficiency, its characterized in that includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring operation video data, reading the operation video data and generating video data to be analyzed, and the acquisition module is also used for acquiring standard operation video data and generating standard motion track data and standard period data according to the standard operation video data;
the calculation module is used for calculating the video data to be analyzed and generating motion track data and motion cycle data to be analyzed, and the calculation module is also used for obtaining working efficiency data according to the operation standard deviation and the operation standard value; and
and the comparison module is used for comparing the motion track data to be analyzed with the standard motion track data, comparing the motion period data with the standard period data, and generating an operation standard deviation and an operation standard value.
9. The system for analyzing pipeline operator work efficiency based on video images of claim 8, wherein the acquisition module is further configured to extract a frame rate and a number of frames in the operational video data.
10. The system for analyzing the work efficiency of the operators on the production line based on the video images as claimed in claim 8, wherein the collection module is further configured to extract and store key motion coordinate values of the standard motion trajectory data, compare the key motion coordinate values with the coordinate mark values, and generate motion trajectory completion data.
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