CN115753796A - Scrap steel grading method and system - Google Patents
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 187
- 239000010959 steel Substances 0.000 title claims abstract description 187
- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000005260 corrosion Methods 0.000 claims abstract description 25
- 230000007797 corrosion Effects 0.000 claims abstract description 25
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- 239000000463 material Substances 0.000 description 4
- 238000007689 inspection Methods 0.000 description 3
- 239000002699 waste material Substances 0.000 description 3
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Abstract
本发明公开了一种废钢评级方法和系统，该方法包括：采集废钢图像；对废钢图像进行分割，提取废钢图像内的待识别目标；计算每个待识别目标的尺寸，并通过待识别目标的尺寸进行废钢分类定级；提取废钢图像中待识别目标的表面特征，并通过待识别目标的表面附着物判断废钢锈蚀程度；通过待识别目标的分类定级和锈蚀程度对待识别目标进行废钢综合分类定级。利用深度学习替代人工进行废钢评级，效率高、准确高、降低工人劳动强度。
The invention discloses a steel scrap rating method and system. The method comprises: collecting scrap steel images; segmenting the scrap steel images, extracting targets to be identified in the scrap steel images; calculating the size of each target to be identified, and passing the target to be identified Classification and grading of scrap steel by size; extract the surface features of the target to be identified in the scrap steel image, and judge the corrosion degree of the scrap steel through the surface attachment of the target to be identified; comprehensively classify the scrap steel by classifying and grading the target to be identified and the degree of corrosion grading. Using deep learning to replace manual scrap steel grading has high efficiency, high accuracy, and reduces labor intensity of workers.
Description
技术领域technical field
本发明涉及一种用于自动识别废钢等级的方法及系统。The invention relates to a method and system for automatically identifying scrap grades.
背景技术Background technique
废钢处理方法因材质和形状而异。易碎的和形状不规则的大块物料，采用重锤击碎。特厚、特长的大型废钢，用切割器切割成合格尺寸。厚废钢板和型钢、条钢，采用剪切机进行剪切。废薄板边角料、废钢丝、废汽车壳体等容积比重较小的轻料，用打包机压缩成块体，打捆用作炼钢原料。不同级别的废钢差别很大，在废钢中混入低级别的废钢，也可能给钢厂带来巨很大的损失。Scrap treatment methods vary by material and shape. Fragile and irregularly shaped bulk materials are crushed with a heavy hammer. Extra-thick and extra-long large steel scraps are cut into qualified sizes with cutters. Thick scrap steel plate, section steel and bar steel are cut by shearing machine. Light materials with small specific gravity such as waste sheet scraps, waste steel wires, and waste car shells are compressed into blocks by a baler, and bundled as raw materials for steelmaking. Different grades of scrap steel are very different, and mixing low-grade scrap steel in scrap steel may also bring huge losses to steel mills.
现有技术中，一般采用人工识别的方式来分辨废钢等级。而人为主观因素影响比较大，因疲劳、心情等可能会影响评价结果。其次每个人判断存在差异，没法统一。另外识别时间长，需要拉近后逐个仔细检查。In the prior art, the grade of steel scrap is generally distinguished by means of manual identification. However, human-subjective factors have a relatively large impact, because fatigue, mood, etc. may affect the evaluation results. Secondly, everyone's judgment is different, and there is no way to unify. In addition, the recognition time is long, and it is necessary to zoom in and check carefully one by one.
发明内容Contents of the invention
有鉴于此，本发明提供一种废钢评级方法，用于自动分辨废钢等级。In view of this, the present invention provides a method for grading steel scrap, which is used for automatically distinguishing the grade of steel scrap.
为解决以上技术问题，本发明的技术方案为一种废钢评级方法，其特征在于包括：In order to solve the above technical problems, the technical solution of the present invention is a steel scrap grading method, which is characterized in that it includes:
采集废钢图像；Collect scrap steel images;
对废钢图像进行分割，提取废钢图像内的待识别目标；Segment the scrap steel image and extract the target to be identified in the scrap steel image;
计算每个待识别目标的尺寸，并通过待识别目标的尺寸进行废钢分类定级；Calculate the size of each object to be identified, and classify and grade scrap steel based on the size of the object to be identified;
提取废钢图像中待识别目标的表面特征，并通过待识别目标的表面附着物判断废钢锈蚀程度；Extract the surface features of the target to be identified in the scrap steel image, and judge the corrosion degree of the scrap steel through the surface attachment of the target to be identified;
通过待识别目标的分类定级和锈蚀程度对待识别目标进行废钢综合分类定级。Through the classification and grading of the target to be identified and the degree of corrosion, the comprehensive classification and grading of steel scrap is carried out for the target to be identified.
作为一种改进，所述提取废钢图像内的待识别目标的方法为：利用实例分割人工智能神经网络模型对图像中的待识别目标进行识别后框选。As an improvement, the method for extracting the target to be identified in the scrap steel image is: using an instance segmentation artificial intelligence neural network model to identify and frame the target to be identified in the image.
作为一种改进，所述废钢分类定级的方法包括：As an improvement, the method for classifying and grading scrap steel includes:
设定不同种类废钢的尺寸指标；Set the size index of different types of steel scrap;
为不同种类废钢设定不同颜色；Set different colors for different types of scrap steel;
利用废钢分级人工智能神经网络模型根据废钢的尺寸指标对分割出来的待识别目标进行种类识别，同时预测识别准确率；Use the artificial intelligence neural network model of scrap steel classification to identify the types of the segmented objects to be identified according to the size index of scrap steel, and predict the recognition accuracy at the same time;
若识别准确率大于等于阈值，则确认识别结果并将该待识别目标标注其等级对应的颜色；若识别准确率小于阈值，则获取更高分辨率的废钢图像后再进行识别，直到识别准确率大于等于阈值或者无法获取更高分辨率的废钢图像为止；If the recognition accuracy is greater than or equal to the threshold, confirm the recognition result and mark the target to be recognized with the color corresponding to its level; if the recognition accuracy is less than the threshold, obtain a higher resolution scrap steel image and then carry out recognition until the recognition accuracy It is greater than or equal to the threshold or until a higher resolution scrap steel image cannot be obtained;
根据每种废钢所代表的颜色在图像中的占比计算各种废钢的占比，并根据各种废钢的占比对所有废钢进行整体评价。Calculate the proportion of various steel scraps according to the proportion of the color represented by each steel scrap in the image, and make an overall evaluation of all steel scraps according to the proportion of various steel scraps.
作为一种优选，将无法识别的待识别目标判定为危险品或者杂质，进行人工干预识别。As a preference, the unidentifiable target to be identified is judged as dangerous goods or impurities, and manual intervention is performed for identification.
作为一种改进，在对废钢图像进行分割之前将废钢运输车与周围环境剥离。As an improvement, the scrap hauler is decoupled from its surroundings before segmenting the scrap image.
作为一种优选，利用锈蚀程度人工智能神经网络模型判定废钢锈蚀程度。As a preference, an artificial intelligence neural network model of the degree of corrosion is used to determine the degree of corrosion of the scrap steel.
作为一种改进，由厚至薄的废钢类型设置由深至浅的颜色。As an improvement, set the color from dark to light for scrap types from thick to thin.
本发明还提供一种废钢评级系统，其特征在于包括：The present invention also provides a steel scrap grading system, which is characterized by comprising:
图像采集模块，用于采集废钢图像；Image collection module, used to collect scrap steel images;
实例分割模块，用于对废钢图像进行分割，提取废钢图像内的待识别目标；The instance segmentation module is used to segment the scrap steel image and extract the target to be identified in the scrap steel image;
废钢分类定级模块，计算每个待识别目标的尺寸，并通过待识别目标的尺寸进行废钢分类定级；The steel scrap classification and grading module calculates the size of each object to be identified, and classifies and grades steel scrap according to the size of the object to be identified;
锈蚀程度评估模块，提取废钢图像中待识别目标的表面特征，并通过待识别目标的表面附着物判断废钢锈蚀程度；The corrosion degree evaluation module extracts the surface features of the object to be identified in the scrap steel image, and judges the corrosion degree of the scrap steel through the surface attachments of the object to be identified;
综合评定模块，通过待识别目标的分类定级和锈蚀程度对待识别目标进行废钢综合分类定级。The comprehensive assessment module performs comprehensive classification and grading of steel scrap through the classification and grading of the target to be identified and the degree of corrosion.
作为一种改进，所述废钢分类定级模块包括：As an improvement, the scrap classification and grading module includes:
设定模块，用于设定不同种类废钢的尺寸指标，并为不同种类废钢设定不同颜色；The setting module is used to set the size index of different types of scrap steel, and set different colors for different types of scrap steel;
识别评估模块，用于根据废钢的尺寸指标对分割出来的待识别目标进行种类识别，同时预测识别准确率；The identification and evaluation module is used to identify the type of the segmented target to be identified according to the size index of the scrap steel, and predict the identification accuracy at the same time;
判断模块，用于根据识别准确率与阈值的关系确认废钢种类并标注其等级对应的颜色；Judgment module, used to confirm the type of scrap steel according to the relationship between the recognition accuracy rate and the threshold value and mark the color corresponding to its grade;
整体评价模块，用于根据每种废钢所代表的颜色在图像中的占比计算各种废钢的占比，并根据各种废钢的占比对所有废钢进行整体评价。The overall evaluation module is used to calculate the proportion of various steel scraps according to the proportion of the color represented by each steel scrap in the image, and perform an overall evaluation of all steel scraps according to the proportions of various steel scraps.
作为一种改进，还包括：As an improvement, also include:
环境剥离模块，用于在对废钢图像进行分割之前将废钢运输车与周围环境剥离。Environment stripping module for stripping scrap haulers from their surroundings before performing segmentation on scrap images.
本发明的有益之处在于：The benefits of the present invention are:
1、将深度学习对废钢的分割与识别从二维空间扩展到三维空间，在原来特征提取的基础上创造性的加入颜色表示厚度的三维自由度，更符合废钢验级的实际需求。1. Extend the segmentation and recognition of steel scrap by deep learning from two-dimensional space to three-dimensional space, and creatively add color to represent the three-dimensional degree of freedom of thickness on the basis of the original feature extraction, which is more in line with the actual needs of steel scrap inspection.
2、根据色块面积计算不同种类废钢所占比例极大的提高了废钢验级的准确率。2. Calculate the proportion of different types of steel scrap according to the area of the color block, which greatly improves the accuracy of steel scrap inspection.
3、根据图像中标注的废钢颜色增强了废钢的表面特征，为人工辅助验级提供了更为直观的特征。3. According to the scrap steel color marked in the image, the surface characteristics of the scrap steel are enhanced, and more intuitive features are provided for manual assisted grading.
4、可快速定位识别杂质和危险品，极大的提高了废钢验级的工作效率。4. It can quickly locate and identify impurities and dangerous goods, which greatly improves the work efficiency of steel scrap inspection.
附图说明Description of drawings
图1为本发明的流程图。Fig. 1 is a flowchart of the present invention.
图2为本发明的结构原理图。Fig. 2 is a schematic diagram of the structure of the present invention.
具体实施方式Detailed ways
为了使本领域的技术人员更好地理解本发明的技术方案，下面结合具体实施方式对本发明作进一步的详细说明。In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below in conjunction with specific embodiments.
如图1所示，本发明一种废钢评级方法，其具体步骤包括：As shown in Figure 1, a kind of steel scrap grading method of the present invention, its concrete steps comprise:
S1采集废钢图像。S1 collects scrap steel images.
废钢车进入指定位置后，摄像头逐层获取车上废钢图像，即先获取顶层废钢的图像，然后通过吸盘将顶层废钢吸走再对下层废钢进行拍摄获取图像以此类推。获取的废钢图像中包括废钢、废钢运输车辆以及周围环境，为了提高效率降低系统开销，可进行下一步操作之前可以先对图像中废钢运输车辆与周围环境进行剥离，仅对废钢车辆进行后续处理。After the scrap car enters the designated position, the camera acquires the images of the scrap steel on the car layer by layer, that is, first obtains the image of the top layer of scrap steel, then sucks the top layer of scrap steel through the suction cup, and then takes pictures of the lower layer of scrap steel to obtain images, and so on. The acquired scrap steel images include scrap steel, scrap steel transport vehicles and the surrounding environment. In order to improve efficiency and reduce system overhead, the scrap steel transport vehicles and the surrounding environment in the image can be stripped before the next operation, and only the scrap steel vehicles can be followed up.
S2对废钢图像进行分割，提取废钢图像内的待识别目标。S2 segment the scrap steel image, and extract the target to be recognized in the scrap steel image.
采集到废钢图像后，需要对图像中每块废钢进行分割便于后续识别。本实施例中，利用实例分割人工智能神经网络模型如Mask-RCNN对图像中的待识别目标进行识别后框选。After the scrap steel image is collected, it is necessary to segment each piece of scrap steel in the image for subsequent identification. In this embodiment, an instance segmentation artificial intelligence neural network model, such as Mask-RCNN, is used to identify and frame the target to be identified in the image.
S3计算每个待识别目标的尺寸，并通过待识别目标的尺寸进行废钢分类定级，具体又包括：S3 calculates the size of each target to be identified, and classifies and grades scrap steel based on the size of the target to be identified, specifically including:
S31设定不同种类废钢的尺寸指标；输入钢厂废钢种类，输入不同废钢种类所代表的厚度或尺寸，例如：废钢1厚度为8mm，剪料为50cm*50cm，轻薄压块厚度<2mm,钢筋直径>6mm……S31 sets the size index of different types of scrap steel; input the type of scrap steel from the steel mill, and input the thickness or size represented by different types of scrap steel, for example: the thickness of scrap steel 1 is 8mm, the cutting material is 50cm*50cm, the thickness of light and thin briquetting <2mm, steel bar Diameter>6mm...
S32为不同种类废钢设定不同颜色；输入废钢种类颜色，不同废钢用不同颜色。本实施例中，由厚至薄的废钢类型设置由深至浅的颜色。S32 sets different colors for different types of steel scrap; input the color of the type of steel scrap, and use different colors for different types of steel scrap. In this embodiment, the color is set from dark to light according to the type of steel scrap from thick to thin.
S33利用废钢分级人工智能神经网络模型根据废钢的尺寸指标对分割出来的待识别目标进行种类识别，同时预测识别准确率。训练好模型以后，根据提取特征对分割后的每一块废钢进行分类，计算每块分割后的废钢的最小外接矩形，根据最小外接矩形定位废钢所在位置，并显示每一块废钢分类的准确率。S33 uses the scrap steel grading artificial intelligence neural network model to identify the types of the segmented targets to be identified according to the size index of the scrap steel, and predict the recognition accuracy at the same time. After the model is trained, classify each segmented steel scrap according to the extracted features, calculate the minimum circumscribed rectangle of each segmented scrap steel, locate the location of the scrap steel according to the minimum circumscribed rectangle, and display the accuracy rate of each scrap steel classification.
由于废钢的角度以及暴露面积不同，其识别准确率也不同。例如正对镜头并且暴露完整的废钢识别准确率可以达到95％以上，而角度较偏暴露不全的废钢识别准确率可能只有60％。Due to the different angles and exposed areas of scrap steel, the recognition accuracy is also different. For example, the recognition accuracy of steel scraps facing the camera and fully exposed can reach more than 95%, while the recognition accuracy of steel scraps that are not fully exposed at an angle may only be 60%.
S34若识别准确率大于等于阈值，则确认识别结果并将该待识别目标标注其等级对应的颜色；若识别准确率小于阈值，则获取更高分辨率的废钢图像后再进行识别，直到识别准确率大于等于阈值或者无法获取更高分辨率的废钢图像为止。S34 If the recognition accuracy rate is greater than or equal to the threshold value, confirm the recognition result and mark the target to be recognized with the color corresponding to its level; if the recognition accuracy rate is less than the threshold value, obtain a higher resolution scrap steel image and then carry out recognition until the recognition is accurate rate is greater than or equal to the threshold or the scrap steel image with higher resolution cannot be obtained.
本实施例中，阈值设置为80％。当是被准确率大于或者等于80％时，则认为识别结果可接收并对该废钢标注与其等级对应的颜色。如果是被准确率小于80％,则推近摄像头采集分辨率更高的图像进行识别，当然如果原始图像足够清晰也可直接放大图像再次识别，直到识别准确率大于或者等于80％确认识别结果，或者无法再获取更高分辨率的图像为止。识别准确率达不到80％的废钢被认为是危险品或者杂质，需要进行人工干预识别。而此时图像已被大部分标准了不同颜色，利用人工很容易将危险品和杂质从其中分辨出来，因此也降低了人工劳动的强度。In this embodiment, the threshold is set to 80%. When the accuracy rate is greater than or equal to 80%, it is considered that the recognition result is acceptable and the color corresponding to the grade of the scrap is marked. If the accuracy rate is less than 80%, move closer to the camera to collect images with higher resolution for recognition. Of course, if the original image is clear enough, you can directly zoom in on the image for recognition again until the recognition accuracy rate is greater than or equal to 80% to confirm the recognition result. Or until a higher resolution image is no longer available. Scrap steel with an identification accuracy rate of less than 80% is considered to be a dangerous product or an impurity, and manual intervention is required for identification. At this time, the image has been mostly standardized in different colors, and it is easy to distinguish dangerous goods and impurities from it manually, thus reducing the intensity of manual labor.
S35根据每种废钢所代表的颜色在图像中的占比计算各种废钢的占比，并根据各种废钢的占比对所有废钢进行整体评价。S35 calculates the proportion of various steel scraps according to the proportion of the color represented by each steel scrap in the image, and makes an overall evaluation of all steel scraps according to the proportion of various steel scraps.
对图像中废钢所在区域中每个像素的颜色进行统计，从而获得整车废钢中每个等级的占比，从而可对整车废钢进行等级评价。The color of each pixel in the area where the scrap steel is located in the image is counted, so as to obtain the proportion of each grade in the whole vehicle scrap steel, so that the grade evaluation of the whole vehicle scrap steel can be carried out.
S4提取废钢图像中待识别目标的表面特征，并通过待识别目标的表面附着物判断废钢锈蚀程度。S4 extracts the surface features of the object to be identified in the scrap steel image, and judges the corrosion degree of the scrap steel through the surface attachments of the object to be identified.
本实施例中，同样利用锈蚀程度人工智能神经网络模型判定废钢锈蚀程度。在训练好模型后，将提取的废钢图像中识别目标的表面特征输入模型，模型根据训练好的特征库进行匹配，从而判定废钢的锈蚀程度。In this embodiment, the artificial intelligence neural network model of the degree of corrosion is also used to determine the degree of corrosion of steel scrap. After the model is trained, the surface features of the recognition target in the extracted scrap steel image are input into the model, and the model is matched according to the trained feature library to determine the corrosion degree of the scrap steel.
值得说明的是，步骤S3和步骤S4的执行并没有先后顺序，分别执行也可同时执行。It is worth noting that there is no sequence in the execution of step S3 and step S4, and they can be executed separately or simultaneously.
S5通过待识别目标的分类定级和锈蚀程度对待识别目标进行废钢综合分类定级。S5 Carry out comprehensive classification and grading of steel scrap by the classification and grading of the target to be identified and the degree of corrosion.
废钢分类定级与锈蚀程度判定完成后，可根据二者的结果进行一个综合评定，评定标准根据实际情况进行设定，本发明中不再赘述。After the classification and grading of steel scrap and the judgment of the degree of corrosion are completed, a comprehensive evaluation can be carried out according to the results of the two, and the evaluation standard is set according to the actual situation, which will not be repeated in the present invention.
如图2所示，本发明还提供一种废钢评级系统，包括：As shown in Figure 2, the present invention also provides a steel scrap grading system, including:
图像采集模块，用于采集废钢图像；Image collection module, used to collect scrap steel images;
环境剥离模块，用于在对废钢图像进行分割之前将废钢运输车与周围环境剥离；Environment stripping module for stripping scrap haulers from their surroundings before segmenting the scrap image;
实例分割模块，用于对废钢图像进行分割，提取废钢图像内的待识别目标；The instance segmentation module is used to segment the scrap steel image and extract the target to be identified in the scrap steel image;
废钢分类定级模块，计算每个待识别目标的尺寸，并通过待识别目标的尺寸进行废钢分类定级；The steel scrap classification and grading module calculates the size of each object to be identified, and classifies and grades steel scrap according to the size of the object to be identified;
锈蚀程度评估模块，提取废钢图像中待识别目标的表面特征，并通过待识别目标的表面附着物判断废钢锈蚀程度；The corrosion degree evaluation module extracts the surface features of the object to be identified in the scrap steel image, and judges the corrosion degree of the scrap steel through the surface attachments of the object to be identified;
综合评定模块，通过待识别目标的分类定级和锈蚀程度对待识别目标进行废钢综合分类定级。The comprehensive assessment module performs comprehensive classification and grading of steel scrap through the classification and grading of the target to be identified and the degree of corrosion.
所述废钢分类定级模块具体又包括：The scrap classification and grading module specifically includes:
设定模块，用于设定不同种类废钢的尺寸指标，并为不同种类废钢设定不同颜色；The setting module is used to set the size index of different types of scrap steel, and set different colors for different types of scrap steel;
识别评估模块，用于根据废钢的尺寸指标对分割出来的待识别目标进行种类识别，同时预测识别准确率；The identification and evaluation module is used to identify the type of the segmented target to be identified according to the size index of the scrap steel, and predict the identification accuracy at the same time;
判断模块，用于根据识别准确率与阈值的关系确认废钢种类并标注其等级对应的颜色；Judgment module, used to confirm the type of scrap steel according to the relationship between the recognition accuracy rate and the threshold value and mark the color corresponding to its grade;
整体评价模块，用于根据每种废钢所代表的颜色在图像中的占比计算各种废钢的占比，并根据各种废钢的占比对所有废钢进行整体评价。The overall evaluation module is used to calculate the proportion of various steel scraps according to the proportion of the color represented by each steel scrap in the image, and perform an overall evaluation of all steel scraps according to the proportions of various steel scraps.
以上仅是本发明的优选实施方式，应当指出的是，上述优选实施方式不应视为对本发明的限制，本发明的保护范围应当以权利要求所限定的范围为准。对于本技术领域的普通技术人员来说，在不脱离本发明的精神和范围内，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。The above are only preferred implementations of the present invention, and it should be noted that the above preferred implementations should not be regarded as limiting the present invention, and the scope of protection of the present invention should be based on the scope defined in the claims. For those skilled in the art, without departing from the spirit and scope of the present invention, some improvements and modifications can also be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.
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