摘要：【中文】一种钩尾销安全吊的螺栓、螺母缺失检测方法,解决了现有纯人工观测图像的方式对货运列车的钩尾销、安全吊、螺栓、螺母缺失的故障检查存在高成本、低效率的问题，属于货运列车故障检测领域。本发明包括：使用SSD神经网络对全车图像中钩尾销安全吊的螺栓、螺母进行粗定位，获取子图；对子图中钩尾销安全吊螺栓和螺母位置进行标注，构建训练集；采用MS‑RCNN神经网络拟合训练集，得到训练权重参数，将训练权重参数加载到MS‑RCNN神经网络和SSD神经网络中，构建推测模型；将待测货运列车的全车图像输入至推测模型中，对货运列车钩尾销安全吊的螺栓、螺母是否缺失进行检测，若螺栓和螺母缺失的置信度分数高于设定阈值，则进行报警。 【EN】A bolt and nut missing detection method for a coupler yoke key safety crane solves the problems of high cost and low efficiency of fault detection of the coupler yoke key, the safety crane, the bolt and the nut missing of a freight train in the existing pure manual image observation mode, and belongs to the field of fault detection of freight trains. The invention comprises the following steps: roughly positioning a bolt and a nut of a coupler yoke key safety crane in the whole vehicle image by using an SSD (solid State disk) neural network to obtain a subgraph; marking the positions of a coupler yoke pin safety lifting bolt and a nut in the subgraph to construct a training set; fitting a training set by adopting an MS-RCNN neural network to obtain training weight parameters, loading the training weight parameters into the MS-RCNN neural network and an SSD neural network, and constructing a conjecture model; inputting the whole image of the freight train to be detected into the guessing model, detecting whether the bolt and the nut of the coupler yoke key safety crane of the freight train are missing or not, and giving an alarm if the confidence score of the missing of the bolt and the nut is higher than a set threshold value.

摘要：【中文】一种基于深度学习的闸瓦插销丢失检测方法，属于货运列车检测技术领域。本发明是为了解决目前依靠人工查看图像的检测方式存在高成本、低效率等问题，以及现有的图像自动处理技术进行检测存在准确率低的问题。本发明首先获取货车图像，然后从图像中确定待识别部件的感兴趣区域并提取出待识别部件的感兴趣区域图像；利用训练好的深度学习模型分割闸瓦插销对应的图像；根据深度学习模型分割的结果，利用图像处理方法进一步获得分割部件的信息，根据先验规则，进行闸瓦插销丢失的判定。本发明主要用于闸瓦插销丢失检测。 【EN】A brake shoe bolt loss detection method based on deep learning belongs to the technical field of freight train detection. The invention aims to solve the problems of high cost, low efficiency and the like of the traditional detection mode of manually checking images and the problem of low accuracy of the detection of the traditional image automatic processing technology. Firstly, acquiring a truck image, then determining an interested area of a component to be identified from the image and extracting an interested area image of the component to be identified; segmenting the image corresponding to the brake shoe bolt by using the trained deep learning model; and further obtaining the information of the segmentation component by using an image processing method according to the segmentation result of the deep learning model, and judging the brake shoe bolt loss according to a prior rule. The invention is mainly used for detecting the loss of the brake shoe bolt.

摘要：【中文】铁路货车滚轴承甩油故障检测方法，本发明涉及铁路货车故障检测方法。本发明的目的是为了解决现有铁路货车滚轴承甩油故障检测准确率差，效率低的问题。过程为：一、线阵图像获取；二、粗定位；三、数据集图像预处理；四、故障目标分类：四一：搭建神经网络分类模型；四二：把预处理后的数据集图像归一化作为训练集输入到神经网络分类模型中；四三：神经网络分类模型损失函数是所有三预处理后的数据集图像的交叉熵损失函数的平均值；四四：更新神经网络分类模型的权重参数；四五：获得训练好的神经网络分类模型；五、判断待测铁路货车线阵图像是否为滚动轴承甩油故障图像。本发明用于货车滚轴承甩油故障检测领域。 【EN】The invention discloses a fault detection method for oil slinging of a rolling bearing of a railway wagon, and relates to a fault detection method for a railway wagon. The invention aims to solve the problems of poor accuracy and low efficiency of the conventional detection of the oil throwing fault of the rolling bearing of the railway wagon. The process is as follows: firstly, acquiring a linear array image; secondly, coarse positioning; thirdly, preprocessing a data set image; fourthly, classifying fault targets: and fourthly: building a neural network classification model; fourthly, two: normalizing the preprocessed data set image to be a training set and inputting the training set into a neural network classification model; fourthly, three: the neural network classification model loss function is the average value of the cross entropy loss functions of all the three preprocessed data set images; fourthly, four: updating the weight parameters of the neural network classification model; and fourthly, fifthly: obtaining a trained neural network classification model; and fifthly, judging whether the linear array image of the railway wagon to be detected is the oil throwing fault image of the rolling bearing. The invention is used for the field of oil throwing fault detection of the truck roller bearing.

摘要：【中文】闸瓦折断目标检测方法，本发明涉及铁路货车故障检测方法。本发明的目的是为了解决现有方法对列车闸瓦图像进行检查，存在成本高、效率低下、准确性低的问题。过程为：一、线阵图像获取；二、粗定位；三、生成对抗网络DCGAN，基于对抗网络DCGAN生成故障图像；对抗网络由判别模型和生成模型两部分组成，其中判别器中采用下采样的卷积，生成器中采用上采样的卷积；具体过程为：三一：构建对抗网络DCGAN判别模型；三二：构建对抗网络DCGAN生成模型；四、建立深度学习训练数据集；五、故障目标分割；六、基于训练好的分割网络模型进行预测，得到故障部件的信息。本发明的有益效果为：本发明用于铁路货车故障检测领域。 【EN】The invention discloses a brake shoe breakage target detection method, and relates to a fault detection method for a railway wagon. The invention aims to solve the problems of high cost, low efficiency and low accuracy of the existing method for checking the train brake shoe image. The process is as follows: firstly, acquiring a linear array image; secondly, coarse positioning; thirdly, generating a countermeasure network DCGAN, and generating a fault image based on the countermeasure network DCGAN; the countermeasure network consists of a discrimination model and a generation model, wherein the discriminator adopts the convolution of down sampling, and the generator adopts the convolution of up sampling; the specific process is as follows: a third step: constructing a DCGAN discrimination model of the confrontation network; and III: constructing an antagonistic network DCGAN generation model; fourthly, establishing a deep learning training data set; fifthly, dividing a fault target; and sixthly, predicting based on the trained segmentation network model to obtain the information of the fault component. The invention has the beneficial effects that: the invention is used for the field of fault detection of rail wagons.

摘要：【中文】一种挡键丢失检测方法，属于货运列车检测技术领域。本发明是为了挡键丢失的人工图像检测方式存在效率低、准确率低的问题，以及环境因素导致的图像检测方式准确率低的问题。本发明利用包含挡键的感兴趣区域的图像训练神经网络的模型，得到训练好的神经网络的模型权重，把模型精度从32位转换成16位精度；采集过车图像并裁剪出包含挡键的感兴趣区域，加载转换成16位精度的神经网络的模型权重，进行神经网络的预测，根据得到的挡键坐标信息，利用人工先验规则，进行故障的判定。主要用于挡键丢失故障检测。 【EN】A method for detecting loss of a stop key belongs to the technical field of freight train detection. The invention aims to solve the problems of low efficiency and low accuracy of an artificial image detection mode with lost blocking keys and the problem of low accuracy of the image detection mode caused by environmental factors. The method comprises the steps of training a model of a neural network by utilizing an image of an interested area containing a blocking key to obtain the model weight of the trained neural network, and converting the model precision from 32 bits to 16 bits; acquiring a vehicle passing image, cutting out an interested area containing a blocking key, loading and converting the model weight of the neural network with 16-bit precision, predicting the neural network, and judging the fault by utilizing an artificial prior rule according to the obtained blocking key coordinate information. The method is mainly used for detecting the loss fault of the stop key.

摘要：【中文】本发明提出了一种基于雷达技术的银行卡拒件导流方法，包括：步骤S1，获取信用卡申请请求被银行拒绝的申请人信息；步骤S2，采用预设的雷达决策引擎对所述申请人的信息进行评分，获取相应的评分结果；步骤S3，将所述评分结果与预设标准进行比对，如果高于所述预设标准，则将对应的申请人信息打回银行，进行在此审查导流操作；如果高于所述预设标准，则向对应的申请人推荐与其评分结果匹配的金融渠道。本发明可以解决了现有存在的审查错误的问题。 【EN】The invention provides a bank card refusal part diversion method based on a radar technology, which comprises the following steps: step S1, obtaining the information of the applicant that the credit card application request is rejected by the bank; step S2, a preset radar decision engine is adopted to score the information of the applicant, and a corresponding scoring result is obtained; step S3, comparing the scoring result with a preset standard, if the scoring result is higher than the preset standard, returning the corresponding applicant information to the bank, and performing the examination and diversion operation; and if the preset standard is higher than the preset standard, recommending the financial channels matched with the grading results of the corresponding applicant. The invention can solve the problem of error examination in the prior art.

摘要：【中文】本发明提供一种基于微信小程序的ETC办理方法、客户端、服务器及系统，所述方法包括：进入办理ETC的微信小程序；在所述办理ETC的微信小程序中上传需要办理ETC的车牌号、用户手机号及姓名信息，并发送给ETC办理服务器；接收ETC办理服务器对所述车牌号、用户手机号及姓名信息是否可以办理ETC的审核结果。本发明实施例提供的线上办理ETC的方案，可以使用户足不出户轻松申请办理ETC，大大的解决了现有技术中必须去银行柜台办理ETC的弊端。 【EN】The invention provides an ETC transaction method, a client, a server and a system based on a WeChat applet, wherein the method comprises the following steps: entering a WeChat small program for handling ETC; uploading license plate numbers, user mobile phone numbers and name information of ETC to be handled in the ETC-handled wechat applet, and sending the license plate numbers, the user mobile phone numbers and the name information to an ETC handling server; and receiving an audit result of whether the ETC can be handled by the ETC handling server for the license plate number, the user mobile phone number and the name information. The scheme for handling the ETC online provided by the embodiment of the invention can enable a user to easily apply for handling the ETC without going out, and greatly overcomes the defect that the user must go to a bank counter to handle the ETC in the prior art.

摘要：【中文】一种智能型与景观灯配套的多功能避雨装置，包括底座，底座顶侧的中间固定连接竖管的下端，竖管外周的上部设有数个均匀圆周分布的横管，横管的内端分别与竖管的外周铰接连接，横管与竖管铰接轴的外周分别套装与竖管固定连接的第一环形斜齿轮，横管内分别轴承安装横轴，横轴的内端分别固定安装第一斜齿轮，第一斜齿轮分别与对应的第一环形斜齿轮啮合配合。本发明结构简单，构思巧妙，设有可折叠遮雨罩，减小占用空间，遮雨罩顶侧的雨水能够通过位于中心的竖管排向下水道，减少雨水溅起弄脏避雨人的裤脚。 【EN】The utility model provides an intelligent and supporting multi-functional rain sheltering device of landscape lamp, includes the base, the lower extreme of the middle fixed connection standpipe of base top side, the upper portion of standpipe periphery is equipped with the violently pipe of the even circumference distribution of several, the inner of violently managing is articulated with the periphery of standpipe respectively and is connected, violently manage the first annular helical gear of suit respectively with the periphery of standpipe articulated shaft and standpipe fixed connection, violently intraductal bearing installation cross axle respectively, the inner of cross axle is the first helical gear of fixed mounting respectively, first helical gear respectively with the first annular helical gear meshing cooperation that corresponds. The rain sheltering cover is simple in structure and ingenious in conception, the foldable rain sheltering cover is arranged, the occupied space is reduced, rainwater on the top side of the rain sheltering cover can be discharged to a sewer through the vertical pipe in the center, and rainwater splashing and polluting trouser legs of rain shelters are reduced.

摘要：本发明涉及西服定制测量及定位卡尺，包括稳定板，所述稳定板的底部活动安装有万向轮，所述稳定板的顶部固定连接有放置箱，所述放置箱的内部放置有夹持装置，所述夹持装置包括固定连接于放置箱顶部的保护箱，所述保护箱的内部活动连接有移动杆，所述移动杆的外部活动连接有弹簧，所述移动杆的顶部固定连接有拉动柄，所述移动杆的外部固定连接有限位环，所述移动杆的底部固定连接有连接杆。该西服定制测量及定位卡尺，通过拉动柄在移动时会带动移动杆、连接杆和夹持块进行移动，然后将用于测量不同位置的不同柔性卡尺分别放入放置杆内部的四个夹持槽，松开移动杆，使夹持块与夹持槽固定，对柔性卡尺进行固定，达到了便于携带的效果。

摘要：本发明提供了一种基于云平台的个性化男士西装上衣在线定制系统，系统包括定制单元、制衣列表单元、云平台处理单元和显示单元；该云平台处理单元接收来自定制单元和制衣列表单元的数据并进行处理，处理结果通过显示单元显示；客户通过定制单元输入自身数值数据；制衣列表单元用于选择男士西装上衣各个部分参数，云平台处理单元用于整合和判断各项数据；显示单元用于显示最后客户选择的西装草图。本发明客户通过定制单元的数据输入端输入自身参数，再通过数据输出端传输给云平台处理单元，然后通过制衣列表单元将所需西装上衣的配置选择好(其他未选择数据皆使用统一标准设定值)后也上传至云平台处理单元，然后经过云平台处理单元处理后制成制衣图纸即可。