CN116202451A - Storage hopper aggregate volume detection system and detection method based on single-point range radar - Google Patents
Storage hopper aggregate volume detection system and detection method based on single-point range radar Download PDFInfo
- Publication number
- CN116202451A CN116202451A CN202310111750.5A CN202310111750A CN116202451A CN 116202451 A CN116202451 A CN 116202451A CN 202310111750 A CN202310111750 A CN 202310111750A CN 116202451 A CN116202451 A CN 116202451A
- Authority
- CN
- China
- Prior art keywords
- aggregate
- storage hopper
- volume
- point ranging
- 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.)
- Pending
Links
- 238000003860 storage Methods 0.000 title claims abstract description 78
- 238000001514 detection method Methods 0.000 title claims abstract description 54
- 238000013528 artificial neural network Methods 0.000 claims abstract description 20
- 238000000034 method Methods 0.000 claims abstract description 13
- 230000003993 interaction Effects 0.000 claims abstract description 11
- 239000000463 material Substances 0.000 claims abstract description 7
- 238000005259 measurement Methods 0.000 claims description 16
- 238000012549 training Methods 0.000 claims description 10
- 238000012360 testing method Methods 0.000 claims description 9
- 238000013461 design Methods 0.000 claims description 3
- 238000011897 real-time detection Methods 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 description 6
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B15/00—Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/08—Systems for measuring distance only
-
- Y—GENERAL 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W30/00—Technologies for solid waste management
- Y02W30/50—Reuse, recycling or recovery technologies
- Y02W30/91—Use of waste materials as fillers for mortars or concrete
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- General Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- Preparation Of Clay, And Manufacture Of Mixtures Containing Clay Or Cement (AREA)
Abstract
本发明公开了一种基于单点测距雷达的储料斗骨料体积检测系统及检测方法，包括：储料斗；测距单元，用于获取储料斗中骨料的高度数据；控制单元，用于处理所述测距单元的检测数据并根据BP神经网络建立的骨料体积检测模型输出当前储料斗中骨料的体积数据；人机交互单元，用于储料斗中骨料的体积数据的实时显示。本发明能够实现骨料体积的实时检测，且精度高、速度快，可有效降低检测成本，减少人力物力损耗。
The invention discloses a storage hopper aggregate volume detection system and a detection method based on a single-point ranging radar, comprising: a storage hopper; a ranging unit for obtaining height data of the aggregate in the storage hopper; a control unit for Process the detection data of the ranging unit and output the volume data of the aggregate in the current storage hopper according to the aggregate volume detection model established by the BP neural network; the human-computer interaction unit is used for real-time display of the volume data of the aggregate in the storage hopper . The invention can realize the real-time detection of the aggregate volume, has high precision and high speed, can effectively reduce the detection cost, and reduce the loss of manpower and material resources.
Description
技术领域technical field
本发明涉及混凝土生产技术领域，具体地指一种基于单点测距雷达的储料斗骨料体积检测系统及检测方法。The invention relates to the technical field of concrete production, in particular to a storage hopper aggregate volume detection system and a detection method based on a single-point ranging radar.
背景技术Background technique
在混凝土搅拌站中，储料斗是为了提高生产效率，提前将需要使用的骨料进行储存的设备。在混凝土生产过程中，实时监测储料斗中的骨料体积有助于提高补料的效率，同时提高生产作业的安全性。但储料斗中的骨料体积因不断的消耗以及装载机的实时供给而发生变化，同时由于骨料在储料斗中的位置状态多变，导致难以实现储料斗中骨料的体积的实时计算检测，并且由于混凝土生产现场的环境较为恶劣，传统的仪器仪表并不能很好的对储料斗中物料的体积进行实时检测，从而会影响混凝土生产的顺利进行。In the concrete mixing plant, the storage hopper is a device that stores the aggregates that need to be used in advance in order to improve production efficiency. During concrete production, real-time monitoring of the aggregate volume in the storage hopper helps to improve the efficiency of refilling while improving the safety of production operations. However, the aggregate volume in the storage hopper changes due to continuous consumption and real-time supply from the loader. At the same time, due to the variable position and state of the aggregate in the storage hopper, it is difficult to realize real-time calculation and detection of the aggregate volume in the storage hopper. , and because the environment of the concrete production site is relatively harsh, traditional instruments and meters cannot detect the volume of the material in the storage hopper well in real time, which will affect the smooth progress of concrete production.
目前常用的混凝土搅拌站储料斗骨料体积检测方法主要有观察法和间接测量法。观察法是通过装载机司机依靠自身的工作经验及实时观察储料斗中骨料的位置及状态来估算骨料的体积。该方法需要经验丰富的装载机实时高度集中的进行观测并判断骨料体积，但这种方法不仅不能精确的得到储料斗中骨料体积数据，而且十分依赖装载机司机的经验判断；间接测量法是通过测量骨料的密度及重量来计算出骨料的体积。该方法需要在储料斗支架上安装称重传感器，但该方法仅对单体储料斗适用，对于多储料斗一体的设备并不能称量出每个单体储料斗中骨料的重量。综上所述，目前的技术无法满足混凝土搅拌站储料斗骨料体积的高精度检测，因此亟需一种低成本、高精度的混凝土搅拌站储料斗骨料体积检测方法。At present, the commonly used detection methods for the aggregate volume of storage hoppers in concrete mixing plants mainly include observation method and indirect measurement method. The observation method is to estimate the volume of the aggregate by the loader driver relying on his own work experience and observing the position and state of the aggregate in the storage hopper in real time. This method requires an experienced loader to observe and judge the aggregate volume in real time, but this method not only cannot accurately obtain the aggregate volume data in the storage hopper, but also relies heavily on the experience judgment of the loader driver; the indirect measurement method The volume of the aggregate is calculated by measuring the density and weight of the aggregate. This method needs to install a weighing sensor on the storage hopper bracket, but this method is only applicable to a single storage hopper, and the weight of the aggregate in each single storage hopper cannot be weighed for the equipment integrating multiple storage hoppers. To sum up, the current technology cannot meet the high-precision detection of the aggregate volume of the storage hopper of the concrete mixing plant, so a low-cost, high-precision detection method for the aggregate volume of the storage hopper of the concrete mixing plant is urgently needed.
发明内容Contents of the invention
本发明的目的是解决上述背景技术中，混凝土搅拌站储料斗骨料体积难以实时检测的问题，提出了一种基于单点测距雷达的储料斗骨料体积检测方法及系统。The purpose of the present invention is to solve the problem that the aggregate volume of the storage hopper of the concrete mixing plant is difficult to detect in real time in the above-mentioned background technology, and proposes a method and system for detecting the aggregate volume of the storage hopper based on single-point ranging radar.
本发明解决此技术问题所采用的技术方案是：一种基于单点测距雷达的储料斗骨料体积检测系统，包括：The technical solution adopted by the present invention to solve this technical problem is: a storage hopper aggregate volume detection system based on single-point ranging radar, including:
储料斗；storage hopper;
测距单元，用于获取储料斗中骨料的高度数据；A distance measuring unit, used to obtain the height data of the aggregate in the storage hopper;
控制单元，用于处理所述测距单元的检测数据并根据BP神经网络建立的骨料体积检测模型输出当前储料斗中骨料的体积数据；The control unit is used to process the detection data of the ranging unit and output the volume data of the aggregate in the current storage hopper according to the aggregate volume detection model established by the BP neural network;
人机交互单元，用于储料斗中骨料的体积数据的实时显示。The human-computer interaction unit is used for real-time display of the volume data of the aggregate in the storage hopper.
优选的是，所述测距单元包括多个单点测距雷达，单点测距雷达用于采集达到储料斗中骨料物料面的距离数据，其采集频率不低于0.1Hz，所述单点测距雷达通过自带的串口与控制单元进行数据传输。Preferably, the ranging unit includes a plurality of single-point ranging radars, and the single-point ranging radars are used to collect distance data reaching the aggregate material surface in the storage hopper, and the collection frequency thereof is not lower than 0.1 Hz. The point ranging radar performs data transmission with the control unit through its own serial port.
优选的是，人机交互单元由触摸屏组成，用于储料斗骨料体积数据的显示。Preferably, the human-computer interaction unit is composed of a touch screen, which is used for displaying the aggregate volume data of the storage hopper.
优选的是，控制单元的控制器为计算机。Preferably, the controller of the control unit is a computer.
本发明还提供了利用任一所述的基于单点测距雷达的储料斗骨料体积检测系统的检测方法，其特征在于，包括以下步骤：The present invention also provides a detection method using any one of the single-point ranging radar-based storage hopper aggregate volume detection systems, which is characterized in that it includes the following steps:
步骤一：在混凝土搅拌站储料斗正上方安装K个单点测距雷达，并将储料斗骨料装满，此时储料斗中骨料的体积为Vm；Step 1: Install K single-point ranging radars directly above the storage hopper of the concrete mixing plant, and fill the storage hopper with aggregate. At this time, the volume of the aggregate in the storage hopper is V m ;
步骤二：收集样本数据，在t时刻打开储料斗底部的卸料口进行卸料，t＝1，2，..，n，卸料体积为Vt，
步骤三：重复步骤二直至
步骤四：确定BP神经网络的样本集，样本的输入数据为K个单点测距雷达的距离测量值，输出数据为骨料初始体积与已卸骨料体积之差；将样本总数的90％作为训练样本，样本总数的10％作为测试样本；Step 4: Determine the sample set of the BP neural network. The input data of the sample is the distance measurement value of K single-point ranging radars, and the output data is the difference between the initial volume of the aggregate and the volume of the unloaded aggregate; 90% of the total number of samples As a training sample, 10% of the total number of samples is used as a test sample;
步骤五：根据输入数据和输出数据设计三层BP神经网络结构，BP神经网络的输入层节点数量为K，分别为K个单点测距雷达的距离测量值，即D＝(dt1，dt2，…，dtK)T；输出层节点数量为1，为骨料初始体积与已卸骨料体积之差，即V＝(Vm-Vt)；隐含层的节点数量
步骤六：利用训练样本对BP神经网络进行训练，得到骨料体积检测模型，并用测试样本测试模型的准确性；Step 6: Use the training samples to train the BP neural network to obtain the aggregate volume detection model, and use the test samples to test the accuracy of the model;
步骤七：建立好骨料体积检测模型后，将单点测距雷达的距离测量值输入到该模型即可输出储料斗中骨料的实时体积数据。Step 7: After the aggregate volume detection model is established, the distance measurement value of the single-point ranging radar is input into the model to output the real-time volume data of the aggregate in the storage hopper.
优选的是，K个单点测距雷达沿料斗正上方的周向和中心间隔设置。Preferably, K single-point ranging radars are arranged at intervals along the circumference and the center directly above the hopper.
本发明至少包括以下有益效果：本发明实时采集单点测距雷达的距离数据并通过BP神经网络训练的骨料体积检测模型输出储料斗骨料体积数据，能够实现骨料体积的实时检测，且精度高、速度快，可有效降低检测成本，减少人力物力损耗。The present invention at least includes the following beneficial effects: the present invention collects the distance data of the single-point ranging radar in real time and outputs the aggregate volume data of the storage hopper through the aggregate volume detection model trained by the BP neural network, which can realize the real-time detection of the aggregate volume, and High precision and fast speed can effectively reduce the cost of detection and reduce the loss of manpower and material resources.
本发明的其它优点、目标和特征将部分通过下面的说明体现，部分还将通过对本发明的研究和实践而为本领域的技术人员所理解。Other advantages, objectives and features of the present invention will partly be embodied through the following descriptions, and partly will be understood by those skilled in the art through the research and practice of the present invention.
附图说明Description of drawings
图1是本发明基于单点测距雷达的储料斗骨料体积检测系统构架图；Fig. 1 is the frame diagram of the storage hopper aggregate volume detection system based on single-point ranging radar in the present invention;
图2是本发明基于单点测距雷达的储料斗骨料体积检测方法的控制流程图；Fig. 2 is the control flowchart of the storage hopper aggregate volume detection method based on the single-point ranging radar in the present invention;
图3是本发明一个实施例的单点测距雷达设置正视图；Fig. 3 is a front view of a single-point ranging radar setup according to an embodiment of the present invention;
图4是本发明一个实施例的单点测距雷达设置俯视图；Fig. 4 is a top view of a single-point ranging radar arrangement according to an embodiment of the present invention;
图5是本发明一个实施例的三层BP神经网络结构图。FIG. 5 is a structural diagram of a three-layer BP neural network according to an embodiment of the present invention.
具体实施方式Detailed ways
下面结合附图对本发明进行详细、完整的说明。本领域普通技术人员在基于这些说明的情况下将能够实现本发明。在结合附图对本发明进行说明前，需要特别指出的是：本发明中在包括下述说明在内的各部分中所提供的技术方案和技术特征，在不冲突的情况下，这些技术方案和技术特征可以相互组合。The present invention will be described in detail and completely below in conjunction with the accompanying drawings. Those skilled in the art will be able to implement the present invention based on these descriptions. Before describing the present invention in conjunction with the accompanying drawings, it needs to be particularly pointed out that: the technical solutions and technical features provided in each part of the present invention, including the following description, in the case of no conflict, these technical solutions and Technical features can be combined with each other.
此外，下述说明中涉及到的本发明的实施例通常仅是本发明一部分的实施例，而不是全部的实施例。因此，基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动的前提下所获得的所有其他实施例，都应当属于本发明保护的范围。In addition, the embodiments of the present invention referred to in the following description are generally only some embodiments of the present invention, not all of them. Therefore, based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
以下结合附图及实施对本发明作进一步的详细说明，其具体实施过程如下：Below in conjunction with accompanying drawing and implementation the present invention is described in further detail, and its specific implementation process is as follows:
如图1所示，本发明提供一种基于单点测距雷达的储料斗骨料体积检测系统，包括：As shown in Figure 1, the present invention provides a storage hopper aggregate volume detection system based on single-point ranging radar, including:
储料斗；storage hopper;
测距单元，用于获取储料斗中骨料的高度数据；A distance measuring unit, used to obtain the height data of the aggregate in the storage hopper;
控制单元，用于处理所述测距单元的检测数据并根据BP神经网络建立的骨料体积检测模型输出当前储料斗中骨料的体积数据；The control unit is used to process the detection data of the ranging unit and output the volume data of the aggregate in the current storage hopper according to the aggregate volume detection model established by the BP neural network;
人机交互单元，用于储料斗中骨料的体积数据的实时显示。The human-computer interaction unit is used for real-time display of the volume data of the aggregate in the storage hopper.
工作原理：基于单点测距雷达的储料斗骨料体积检测系统首先采集多组单点测距雷达测量的距离数据以及与之对应的骨料体积数据；其次，将距离数据和与之对应的骨料体积数据整理形成样本，并将样本分为训练样本和检测样本；然后，通过BP神经网络对训练样本数据进行训练，其中训练输入值和检测输入值为单点测距雷达的距离测量值，训练输出值和检测输出值为骨料体积测量数据；最后，构建骨料体积检测模型，将单点测距雷达的距离测量值输入到该模型即可输出储料斗中骨料的实时体积数据。Working principle: The storage hopper aggregate volume detection system based on single-point ranging radar first collects multiple sets of distance data measured by single-point ranging radar and the corresponding aggregate volume data; secondly, the distance data and the corresponding The aggregate volume data is organized to form samples, and the samples are divided into training samples and detection samples; then, the training sample data is trained through the BP neural network, where the training input value and detection input value are the distance measurement value of the single-point ranging radar , the training output value and the detection output value are the aggregate volume measurement data; finally, construct the aggregate volume detection model, and input the distance measurement value of the single-point ranging radar into the model to output the real-time volume data of the aggregate in the storage hopper .
本申请的基于单点测距雷达的储料斗骨料体积检测系统的一优选实施例中，所述测距单元包括多个单点测距雷达，单点测距雷达用于采集达到储料斗中骨料物料面的距离数据，其采集频率不低于0.1Hz，所述单点测距雷达通过自带的串口与控制单元进行数据传输。In a preferred embodiment of the storage hopper aggregate volume detection system based on single-point ranging radars of the present application, the ranging unit includes a plurality of single-point ranging radars, and the single-point ranging radars are used to collect The collection frequency of the distance data on the surface of the aggregate material is not lower than 0.1 Hz, and the single-point ranging radar transmits data with the control unit through its own serial port.
本申请的基于单点测距雷达的储料斗骨料体积检测系统的一优选实施例中，人机交互单元由触摸屏组成，用于储料斗骨料体积数据的显示。In a preferred embodiment of the storage hopper aggregate volume detection system based on single-point ranging radar of the present application, the human-computer interaction unit is composed of a touch screen for displaying storage hopper aggregate volume data.
本申请的基于单点测距雷达的储料斗骨料体积检测系统的一优选实施例中，控制单元的控制器为计算机。In a preferred embodiment of the storage hopper aggregate volume detection system based on single-point ranging radar of the present application, the controller of the control unit is a computer.
在另一个实施例中，提供了一种基于单点测距雷达的储料斗骨料体积检测系统的检测方法，检测系统的系统架构主要由测距单元、控制单元和人机交互单元组成；In another embodiment, a detection method of a storage hopper aggregate volume detection system based on a single-point ranging radar is provided. The system architecture of the detection system is mainly composed of a distance measurement unit, a control unit and a human-computer interaction unit;
各单元的原理说明如下：The principle of each unit is explained as follows:
1、测距单元：测距单元由多个单点测距雷达组成，主要采集单点测距雷达达到储料斗中骨料物料面的距离数据，其采集频率不低于0.1Hz，通过自带的串口与控制单元进行数据传输；1. Ranging unit: The ranging unit is composed of multiple single-point ranging radars. It mainly collects the distance data from the single-point ranging radar to the aggregate material surface in the storage hopper. The collection frequency is not lower than 0.1Hz. Serial port and control unit for data transmission;
2、控制单元：控制单元的控制器使用计算机，控制单元接收上述测距单元测量的实时数据，并通过BP神经网络生成的骨料体积检测模型来计算储料斗中的骨料体积，并将储料斗骨料体积数据传输到人机交互单元。2. Control unit: the controller of the control unit uses a computer, and the control unit receives the real-time data measured by the above distance measuring unit, and calculates the aggregate volume in the storage hopper through the aggregate volume detection model generated by the BP neural network, and stores The hopper aggregate volume data is transmitted to the human-computer interaction unit.
3、人机交互单元：人机交互单元由触摸屏组成，用于储料斗骨料体积数据的显示。图2所示，为上述基于单点测距雷达的储料斗骨料体积检测方法的控制流程图，其具体步骤为：3. Human-computer interaction unit: The human-computer interaction unit is composed of a touch screen, which is used to display the aggregate volume data of the storage hopper. As shown in Fig. 2, it is the control flow chart of the above-mentioned storage hopper aggregate volume detection method based on single-point ranging radar, and its specific steps are:
步骤一：在混凝土搅拌站储料斗正上方安装5个单点测距雷达，并将储料斗骨料装满，此时储料斗中骨料的体积为Vm；具体的安装位置如图3和4所示，在本实施例中料斗的横截面为矩形，其中一个单点测距雷达的正投影落入料斗横截面的中心，剩余四个单点测距雷达的正投影分别落入料斗四条边的中点与料斗中心点连线的中点处。Step 1: Install 5 single-point ranging radars directly above the storage hopper of the concrete mixing plant, and fill the storage hopper with aggregate. At this time, the volume of the aggregate in the storage hopper is V m ; the specific installation position is shown in Figure 3 and As shown in 4, the cross-section of the hopper in this embodiment is rectangular, and the orthographic projection of one single-point ranging radar falls into the center of the cross-section of the hopper, and the orthographic projections of the remaining four single-point ranging radars fall into the four sides of the hopper respectively. The midpoint of the line connecting the midpoint of the side and the center point of the hopper.
步骤二：收集样本数据，在t时刻打开储料斗底部的卸料口进行卸料，t＝1，2，..，n，卸料体积为
步骤三：重复步骤二直至
步骤四：确定BP神经网络的样本集，样本的输入数据为5个单点测距雷达的距离测量值，输出数据为骨料初始体积与已卸骨料体积之差；将样本总数的90％作为训练样本，样本总数的10％作为测试样本；Step 4: Determine the sample set of the BP neural network. The input data of the sample is the distance measurement value of 5 single-point ranging radars, and the output data is the difference between the initial volume of the aggregate and the volume of the unloaded aggregate; 90% of the total number of samples As a training sample, 10% of the total number of samples is used as a test sample;
步骤五：根据输入数据和输出数据设计三层BP神经网络结构，具体的结构如图5所示。BP神经网络的输入层节点数量为5，分别为5个单点测距雷达的距离测量值，即D(dt1,dt2,dt3,dt4,dt5)T,输出层节点数量为1，为骨料初始体积与已卸骨料体积之差，即V＝(Vm-Vt)；隐含层的节点数量10，即Y＝(y1，y2，…，y10)T。Step 5: Design a three-layer BP neural network structure according to the input data and output data. The specific structure is shown in Figure 5. The number of input layer nodes of BP neural network is 5, which are the distance measurement values of five single-point ranging radars, namely D(d t1 , d t2 , d t3 , d t4 , d t5 ) T , and the number of output layer nodes is 1, is the difference between the initial volume of the aggregate and the volume of the unloaded aggregate, that is, V=(V m -V t ); the number of nodes in the hidden layer is 10, that is, Y=(y 1 , y 2 ,...,y 10 ) T.
步骤六：利用训练样本对BP神经网络进行训练，得到骨料体积检测模型，并用测试样本测试模型的准确性；Step 6: Use the training samples to train the BP neural network to obtain the aggregate volume detection model, and use the test samples to test the accuracy of the model;
步骤七：建立好骨料体积检测模型后，将单点测距雷达的距离测量值输入到该模型即可输出储料斗中骨料的实时体积数据。Step 7: After the aggregate volume detection model is established, the distance measurement value of the single-point ranging radar is input into the model to output the real-time volume data of the aggregate in the storage hopper.
尽管本发明的实施方案已公开如上，但其并不仅仅限于说明书和实施方式中所列运用，它完全可以被适用于各种适合本发明的领域，对于熟悉本领域的人员而言，可容易地实现另外的修改，因此在不背离权利要求及等同范围所限定的一般概念下，本发明并不限于特定的细节和这里示出与描述的实施例。Although the embodiment of the present invention has been disclosed as above, it is not limited to the use listed in the specification and implementation, it can be applied to various fields suitable for the present invention, and it can be easily understood by those skilled in the art Therefore, the invention is not limited to the specific details and embodiments shown and described herein without departing from the general concept defined by the claims and their equivalents.
Claims (6)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310111750.5A CN116202451A (en) | 2023-02-07 | 2023-02-07 | Storage hopper aggregate volume detection system and detection method based on single-point range radar |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310111750.5A CN116202451A (en) | 2023-02-07 | 2023-02-07 | Storage hopper aggregate volume detection system and detection method based on single-point range radar |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116202451A true CN116202451A (en) | 2023-06-02 |
Family
ID=86512338
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310111750.5A Pending CN116202451A (en) | 2023-02-07 | 2023-02-07 | Storage hopper aggregate volume detection system and detection method based on single-point range radar |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116202451A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117452887A (en) * | 2023-10-12 | 2024-01-26 | 中交第二航务工程局有限公司 | Unmanned electric loader scheduling system and method for concrete mixing plant |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0658750A2 (en) * | 1993-12-14 | 1995-06-21 | Hydrometer GmbH | Method and device for proving volume flowmeters |
| CN106548480A (en) * | 2016-12-23 | 2017-03-29 | 蚌埠学院 | A kind of agricultural product volume rapid measurement device and measuring method based on machine vision |
| CN106647827A (en) * | 2015-10-28 | 2017-05-10 | 中国石油化工股份有限公司 | Liquid feeding control method |
| CN108139256A (en) * | 2015-10-06 | 2018-06-08 | Vega格里沙贝两合公司 | Packing volume detecting system including multiple radar sensors |
| CN208000147U (en) * | 2018-03-26 | 2018-10-23 | 山推建友机械股份有限公司 | Aggregate monitoring system based on picture recognition |
| CN110543616A (en) * | 2018-12-26 | 2019-12-06 | 西安电子科技大学 | Prediction method of SMT solder paste printing volume based on industrial big data |
| CN110926426A (en) * | 2019-12-03 | 2020-03-27 | 西安科技大学 | Real-time detection device and detection method for residual muck volume of subway shield segment |
| CN112419393A (en) * | 2020-11-15 | 2021-02-26 | 浙江大学 | A real-time measuring device and method for the volume of garbage in the hopper of a garbage incinerator |
| CN113989360A (en) * | 2021-10-12 | 2022-01-28 | 江苏丰尚智能科技有限公司 | Method and device for monitoring volume of material in bin, monitoring equipment and storage medium |
-
2023
- 2023-02-07 CN CN202310111750.5A patent/CN116202451A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0658750A2 (en) * | 1993-12-14 | 1995-06-21 | Hydrometer GmbH | Method and device for proving volume flowmeters |
| CN108139256A (en) * | 2015-10-06 | 2018-06-08 | Vega格里沙贝两合公司 | Packing volume detecting system including multiple radar sensors |
| CN106647827A (en) * | 2015-10-28 | 2017-05-10 | 中国石油化工股份有限公司 | Liquid feeding control method |
| CN106548480A (en) * | 2016-12-23 | 2017-03-29 | 蚌埠学院 | A kind of agricultural product volume rapid measurement device and measuring method based on machine vision |
| CN208000147U (en) * | 2018-03-26 | 2018-10-23 | 山推建友机械股份有限公司 | Aggregate monitoring system based on picture recognition |
| CN110543616A (en) * | 2018-12-26 | 2019-12-06 | 西安电子科技大学 | Prediction method of SMT solder paste printing volume based on industrial big data |
| CN110926426A (en) * | 2019-12-03 | 2020-03-27 | 西安科技大学 | Real-time detection device and detection method for residual muck volume of subway shield segment |
| CN112419393A (en) * | 2020-11-15 | 2021-02-26 | 浙江大学 | A real-time measuring device and method for the volume of garbage in the hopper of a garbage incinerator |
| CN113989360A (en) * | 2021-10-12 | 2022-01-28 | 江苏丰尚智能科技有限公司 | Method and device for monitoring volume of material in bin, monitoring equipment and storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117452887A (en) * | 2023-10-12 | 2024-01-26 | 中交第二航务工程局有限公司 | Unmanned electric loader scheduling system and method for concrete mixing plant |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104316108B (en) | Method for establishing and analyzing online monitoring system for 500kv power transmission tower in mountain environment | |
| CN100533311C (en) | Embedded Weighing System Based on Intelligent Fuzzy Control | |
| CN101726383B (en) | Multi-rope winder steel wire rope tension test method | |
| CN109060056A (en) | A kind of river cross-section method of calculating flux of contactless radar flow measurement | |
| CN103292774B (en) | A kind of dynamic deflection metrology method of bridge | |
| CN107632168A (en) | A kind of river course two dimension flow velocity and Flow Measuring System and method | |
| CN107870201B (en) | A kind of air bubble mix light-textured soil embankment lossless detection method | |
| CN101667339B (en) | Modeling system and method based on measured traffic service level of urban road area | |
| CN107063352A (en) | Skyscraper health monitoring systems and monitoring method | |
| CN103510503B (en) | Method for monitoring rammed point soil stabilization state vibration in real time | |
| CN109919481B (en) | A multi-parameter joint real-time evaluation method for the compaction degree of roller compacted concrete | |
| CN116202451A (en) | Storage hopper aggregate volume detection system and detection method based on single-point range radar | |
| CN101825646A (en) | Device and method for measuring flow rate of thin water flow by electrolyte tracing | |
| CN106545326A (en) | A kind of long-spiral drilling machine construction monitoring system | |
| CN107843321A (en) | Method for detecting quantity of stored grains in granary based on three-dimensional force sensor | |
| CN210887351U (en) | Intelligent discrimination system for pile foundation pore-forming quality | |
| CN114659621A (en) | Bridge vibration monitoring devices | |
| CN101776679A (en) | Technology for observing slope soil erosion on fixed point by probability integration method | |
| CN108645377B (en) | Sedimentation monitoring method for comprehensive pipe gallery | |
| CN110986815A (en) | Tunnel construction monitoring and measuring method based on three-dimensional laser point cloud | |
| CN105756107A (en) | Centrifugal test model for verifying combined action of supporting structure and soil body and manufacturing method of centrifugal test model | |
| CN106338254B (en) | The quick monitoring and forecasting systems of underground engineering construction and method based on 3D laser scanning | |
| CN205067401U (en) | Thermal conductivity measuring apparatu | |
| CN118549239A (en) | A typical structure single or double strip mechanical test device | |
| CN208383337U (en) | A kind of arch bridge stiff skeleton external wrapping concrete temperature acquisition system |
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 |