CN109238735B - The malfunction monitoring diagnostic system of the electronic AGV of port cargo - Google Patents

The malfunction monitoring diagnostic system of the electronic AGV of port cargo Download PDF

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CN109238735B
CN109238735B CN201810897308.9A CN201810897308A CN109238735B CN 109238735 B CN109238735 B CN 109238735B CN 201810897308 A CN201810897308 A CN 201810897308A CN 109238735 B CN109238735 B CN 109238735B
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CN109238735A (en
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刘成良
黄亦翔
赵路杰
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Shanghai Jiao Tong University
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract

The present invention provides the malfunction monitoring diagnostic systems of the electronic AGV of port cargo a kind of, include AGV vehicle and server;The AGV vehicle operates on port and pier place;Sensor is installed on the AGV vehicle and/or port and pier place;Server generates malfunction monitoring diagnostic signal according to the monitoring signals of the sensor on AGV vehicle and/or port and pier place.The present invention realizes the online fault detection and fault diagnosis functions of the unmanned container carrier loader in harbour, greatly shortens the maintenance time of carrier vehicle, reduces maintenance cost, preferably meets the requirement of unmanned 24 hours high-efficient homeworks of harbour.

Description

港口货运电动AGV的故障监测诊断系统Fault Monitoring and Diagnosis System of Port Freight Electric AGV

技术领域technical field

本发明涉及自动化港口设备健康管理的技术领域,具体地,涉及一种港口货运电动AGV的故障监测诊断系统。The invention relates to the technical field of automated port equipment health management, in particular to a fault monitoring and diagnosis system for port freight electric AGVs.

背景技术Background technique

随着港口集装箱吞吐量的不断增大和港口自动化水平的不断提高,无人引导的集装箱输送小车(下面简称AGV)在港口中得到了越来越广泛的应用。在港口,AGV能够按照系统规划的路径,采用如GPS,电磁等导引技术,将集装箱按照需求在港口上进行搬运。AGV作为自动化港口中集装箱的主要运载体之一,保障其安全运行对于整个港口系统具有极端的重要性和关键性。With the continuous increase of port container throughput and the continuous improvement of port automation level, unguided container transport vehicles (hereinafter referred to as AGV) have been more and more widely used in ports. At the port, the AGV can follow the path planned by the system and use guidance technologies such as GPS and electromagnetics to move the container on the port as required. As one of the main carriers of containers in automated ports, AGVs are extremely important and critical to the entire port system to ensure their safe operation.

港口集装箱AGV具有工作时间长,工作环境恶劣的特点,在我国投入应用时间短。对其运行状况进行在线监控并通过数据对AGV相关系统的性能状况进行评估,故障类型进行判断,具有十分重要的作用。Port container AGV has the characteristics of long working hours and harsh working environment, and it has been put into use for a short time in our country. It plays a very important role to monitor its operating status online and evaluate the performance status of AGV-related systems through data and judge the type of fault.

而AGV的转动系统,尤其是传动系统中的轴承,它的好坏对于AGV的运行状态有极大的影响。为了保障自动化港口中AGV运输系统的正常运转,研发一种可靠有效的在线轴承故障诊断预测系统是极为必要的,它可以对设备故障进行提前预警,方便维修人员对相关设备进行高效维修,对于港口的高效运转具有十分重要的意义。现有技术主要存在以下三类缺陷:The quality of the AGV's rotating system, especially the bearings in the transmission system, has a great impact on the operating state of the AGV. In order to ensure the normal operation of the AGV transportation system in the automated port, it is extremely necessary to develop a reliable and effective online bearing fault diagnosis and prediction system. It can give early warning of equipment failures and facilitate maintenance personnel to efficiently maintain related equipment. For ports Efficient operation is of great significance. There are mainly following three types of defects in the prior art:

(1)目前市面上没有任何存在的港口无人集装箱运载小车的在线故障检测及诊断系统,一般根据检修计划对整体车队进行轮流离线检查,由于运载小车自身轴承等部件寿命波动极大,港口工作环境复杂,定期检查不仅需要耗费大量的时间和金钱,影响作业效率。也没有办法实现对故障的实时监控,提前按需准备维修零部件库存,提高生产效率。(1) At present, there is no online fault detection and diagnosis system for port unmanned container-carrying trolleys on the market. Generally, the entire fleet is checked off-line in turn according to the maintenance plan. Due to the large fluctuations in the service life of the bearings and other components of the trolley itself, port work The environment is complex, regular inspections not only need to consume a lot of time and money, but also affect the efficiency of work. There is also no way to realize real-time monitoring of faults, prepare maintenance parts inventory in advance and on demand, and improve production efficiency.

(2)目前关于零件可靠性分析及寿命的相关数据及推断方法大都基于实验室标准环境之下,而对于码头这种复杂环境下各个零件寿命估计还没有一个可靠的模型,目前对于零件寿命估计效果较好的方法是人工神经网络,训练人工神经网络需要大量的训练数据,传统的离线检修方法没有办法提供训练人工神经网络需要的数据。(2) At present, the relevant data and inference methods on the reliability analysis and life of parts are mostly based on the laboratory standard environment, and there is no reliable model for the life estimation of each part in the complex environment of the wharf. At present, the life estimation of parts The method with better effect is the artificial neural network. Training the artificial neural network requires a large amount of training data. The traditional offline maintenance method cannot provide the data required for training the artificial neural network.

(3)目前市面上有很多现有的故障检验方法和检验设备,但其适用范围大都针对固定工况,在港口这种复杂变工况环境下,其故障诊断效果往往不是十分理想。而AGV作为在码头复杂情况中使用的大型机械,其振动信号中往往掺杂有大量的背景噪声,给信号分析带来了很大的干扰,在这些噪声中间,有一类信号是由于车辆在码头运行过程中反复启动停止,即加速减速过程中带来的线性调频信号LFM。(3) There are many existing fault inspection methods and inspection equipment on the market, but most of them are applicable to fixed working conditions. In the complex and variable working conditions of the port, the fault diagnosis effect is often not very ideal. However, AGV, as a large-scale machine used in the complex situation of the wharf, often contains a lot of background noise in its vibration signal, which brings great interference to the signal analysis. Among these noises, there is a type of signal caused by the vehicle in the wharf Repeated start and stop during operation, that is, the linear frequency modulation signal LFM brought during the acceleration and deceleration process.

发明内容Contents of the invention

针对现有技术中的缺陷,本发明的目的是提供一种港口货运电动AGV的故障监测诊断系统。Aiming at the defects in the prior art, the purpose of the present invention is to provide a fault monitoring and diagnosis system for port freight electric AGV.

根据本发明提供的港口货运电动AGV的故障监测诊断系统,包含AGV车与服务器;所述AGV车运行在港口码头场地上;The fault monitoring and diagnosing system of the port freight electric AGV provided according to the present invention includes an AGV car and a server; the AGV car runs on the port wharf site;

所述AGV车和/或港口码头场地上安装有传感器;Sensors are installed on the AGV car and/or the port terminal site;

服务器根据来自AGV车和/或港口码头场地上传感器的监测信号,生成故障监测诊断信号。The server generates fault monitoring and diagnosis signals according to the monitoring signals from the sensors on the AGV vehicle and/or the port terminal.

优选地,所述AGV车包含车身模块、传动模块、电机模块以及电池模块;Preferably, the AGV vehicle includes a body module, a transmission module, a motor module and a battery module;

以下任一个多任多个位置上:Any one or more of the following positions:

--车身模块;-- Body module;

--传动模块;-- Transmission module;

--电机模块;--Motor module;

--电池模块;-- battery module;

--港口码头场地,--The port terminal site,

安装有以下任一种或任多种传感器:Any one or more of the following sensors are installed:

--振动传感器;-- Vibration sensor;

--湿度传感器;--Humidity Sensor;

--温度传感器;--Temperature Sensor;

--电压传感器;-- voltage sensor;

--电流传感器。--current sensor.

优选地,AGV车上设置有第一信号处理模块,所述港口码头场地上设置有第二信号处理模块;Preferably, the AGV is provided with a first signal processing module, and the port terminal is provided with a second signal processing module;

所述服务器包含远程信号接收模块;The server includes a remote signal receiving module;

第一信号处理模块、第二信号处理模块分别将来自AGV车上传感器的监测信号、来自港口码头场地上传感器的监测信号进行处理,获得对应的预处理数据,并分别将对应的预处理数据发送至远程信号接收模块。The first signal processing module and the second signal processing module respectively process the monitoring signals from the sensors on the AGV and the sensors on the port terminal site to obtain the corresponding pre-processing data, and send the corresponding pre-processing data respectively to the remote signal receiving module.

优选地,所述服务器还包含远程故障监测诊断模块与数据管理模块;Preferably, the server also includes a remote fault monitoring and diagnosis module and a data management module;

远程故障监测诊断模块根据远程信号接收模块接收的预处理数据,和/或来自数据管理模块的车身运行历史数据,生成故障监测诊断信号。The remote fault monitoring and diagnosing module generates fault monitoring and diagnosing signals according to the preprocessed data received by the remote signal receiving module and/or the vehicle body operation history data from the data management module.

优选地,AGV车上传感器通过总线与第二信号处理模块相连;Preferably, the AGV on-board sensor is connected to the second signal processing module through a bus;

港口码头场地上传感器通过总线与第二信号处理模块相连;The sensors on the port terminal site are connected to the second signal processing module through the bus;

第一信号处理模块与第二信号处理模块均通过无线传输形式与远程信号接收模块进行通信;Both the first signal processing module and the second signal processing module communicate with the remote signal receiving module through wireless transmission;

远程信号接收模块通过有线形式与远程故障监测诊断模块相连;The remote signal receiving module is connected with the remote fault monitoring and diagnosis module through a wired form;

所述服务器还包含显示模块;The server also includes a display module;

所述显示模块根据接收到的故障监测诊断信号,显示以下任一种或任多种信息:The display module displays any one or more of the following information according to the received fault monitoring and diagnosis signal:

--AGV车的故障信息;--The fault information of the AGV car;

--AGV车的健康状况信息;--The health status information of the AGV vehicle;

--AGV车上零部件的剩余寿命信息。--Remaining life information of parts on the AGV.

优选地,所述远程故障监测诊断模块包含以下任一个或任多个模块:Preferably, the remote fault monitoring and diagnosis module includes any one or more of the following modules:

运行监测模块:监测AGV车整体运行情况;Operation monitoring module: monitor the overall operation of AGV vehicles;

故障定位与等级分类模块:计算AGV车上故障发生的部位及严重程度;Fault location and classification module: calculate the location and severity of the fault on the AGV;

零部件寿命估测模块:预估AGV车上零部件的剩余寿命。Parts life estimation module: Estimate the remaining life of parts on the AGV.

优选地,故障定位与等级分类模块包含轴承故障诊断模块,所述轴承故障诊断模块包含以下模块:Preferably, the fault location and grade classification module includes a bearing fault diagnosis module, and the bearing fault diagnosis module includes the following modules:

滤波模块:对预处理数据所包含的原始振动信号进行滤波,获得降噪振动信号;Filter module: filter the original vibration signal contained in the preprocessing data to obtain the noise-reduced vibration signal;

重构模块:对降噪振动信号进行重构,获得重构振动信号;Reconstruction module: reconstruct the noise reduction vibration signal to obtain the reconstructed vibration signal;

诊断结果获取模块:对重构振动信号进行诊断,获得轴承故障诊断结果。Diagnosis result acquisition module: Diagnose the reconstructed vibration signal to obtain the bearing fault diagnosis result.

优选地,所述滤波模块中,对原始振动信号进行分数阶傅里叶变换滤波,消除原始振动信号中的线性调频噪声;Preferably, in the filtering module, the original vibration signal is subjected to fractional Fourier transform filtering to eliminate chirp noise in the original vibration signal;

所述分数阶傅里叶变换通过以下公式实现:The fractional Fourier transform is realized by the following formula:

式中:fp(u)为降噪振动信号,p为自由变量分数阶次,且p∈(-2,2],u为核函数参数;In the formula: f p (u) is the noise reduction vibration signal, p is the fractional order of the free variable, and p∈(-2,2], u is the kernel function parameter;

Kp(u,t)为傅里叶变换核信号,t为时域信号;K p (u, t) is the Fourier transform kernel signal, and t is the time domain signal;

f(t)为原始振动信号;f(t) is the original vibration signal;

Aα为前置系数,α为旋转角度,且α∈(-2π,2π];A α is the front coefficient, α is the rotation angle, and α∈(-2π, 2π];

j为虚部符号;j is the imaginary part symbol;

n为整数;n is an integer;

δ()为狄拉克函数;δ() is the Dirac function;

sgn()为符号函数。sgn() is a symbolic function.

优选地,重构模块中,使用反分数阶傅里叶变换对降噪振动信号进行重构。Preferably, in the reconstruction module, the inverse fractional Fourier transform is used to reconstruct the noise-reduced vibration signal.

优选地,诊断结果获取模块包含以下模块:Preferably, the diagnostic result acquisition module includes the following modules:

模块M1:求重构振动信号的Hilbert变换对;Module M1: Find the Hilbert transform pair of the reconstructed vibration signal;

模块M2:以重构振动信号为实部,以Hilbert变换对为虚部,构建解析信号;Module M2: take the reconstructed vibration signal as the real part and the Hilbert transform pair as the imaginary part to construct the analytical signal;

模块M3:对解析信号求模得到包络信号;Module M3: calculate the modulus of the analytical signal to obtain the envelope signal;

模块M4:对包络信号进行低通滤波与快速傅里叶变换求出包络谱,根据包络谱得到调制频率、调制频率高次频谐波以及调制函数。Module M4: Perform low-pass filtering and fast Fourier transform on the envelope signal to obtain the envelope spectrum, and obtain the modulation frequency, high-order harmonics of the modulation frequency and modulation function according to the envelope spectrum.

与现有技术相比,本发明具有如下的有益效果:Compared with the prior art, the present invention has the following beneficial effects:

1、本发明实现了港口无人集装箱运载小车的在线故障检测及故障诊断功能,极大的缩短了运载车辆的维修时间,降低维修成本,更好地满足无人化码头24小时高效作业的要求。1. The present invention realizes the online fault detection and fault diagnosis function of the port unmanned container carrier trolley, which greatly shortens the maintenance time of the carrier vehicle, reduces the maintenance cost, and better meets the requirements of 24-hour efficient operation of the unmanned terminal .

2、本发明能够实时采集相关设备数据及环境数据,为人工神经网络的训练提供数据,实现对设备寿命的有效估计,及整体车队质量的有效管理。2. The present invention can collect relevant equipment data and environmental data in real time, provide data for artificial neural network training, realize effective estimation of equipment life, and effective management of overall fleet quality.

3、本发明使用分数阶傅里叶变换对信号进行滤波,能较好地去除振动信号中的背景噪声,通过对滤波后的重构信号进行包络谱分析,实现对故障的高效监测和诊断。3. The present invention uses fractional Fourier transform to filter the signal, which can better remove the background noise in the vibration signal, and realizes efficient monitoring and diagnosis of faults by performing envelope spectrum analysis on the reconstructed signal after filtering .

附图说明Description of drawings

通过阅读参照以下附图对非限制性实施例所作的详细描述,本发明的其它特征、目的和优点将会变得更明显:Other characteristics, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

图1为本发明提供的港口货运电动AGV的故障监测诊断系统的架构图;Fig. 1 is the frame diagram of the fault monitoring and diagnosis system of the port freight electric AGV provided by the present invention;

图2为轴承故障诊断流程图;Figure 2 is a flowchart of bearing fault diagnosis;

图3为分数阶傅里叶变换原理图,图中:f0为chirp类信号的中心频率;Fig. 3 is the principle diagram of fractional order Fourier transform, among the figure: f 0 is the center frequency of chirp class signal;

fm为chirp类信号的调频频率;f m is the frequency modulation frequency of chirp class signal;

u0为一个chirp类信号在分数阶傅里叶域上的投影值;u 0 is the projection value of a chirp signal on the fractional Fourier domain;

β为待测信号中一个chirp类信号分量的时频分布与时间轴的夹角;β is the angle between the time-frequency distribution of a chirp signal component in the signal to be tested and the time axis;

chirp类信号为线性调频类信号。The chirp signal is a linear frequency modulation signal.

具体实施方式Detailed ways

下面结合具体实施例对本发明进行详细说明。以下实施例将有助于本领域的技术人员进一步理解本发明,但不以任何形式限制本发明。应当指出的是,对本领域的普通技术人员来说,在不脱离本发明构思的前提下,还可以做出若干变形和改进。这些都属于本发明的保护范围。The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

在本发明的描述中,需要理解的是,术语“上”、“下”、“前”、“后”、“左”、“右”、“竖直”、“水平”、“顶”、“底”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系,仅是为了便于描述本发明和简化描述,而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作,因此不能理解为对本发明的限制。In describing the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", The orientation or positional relationship indicated by "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying the referred device Or elements must have a certain orientation, be constructed and operate in a certain orientation, and thus should not be construed as limiting the invention.

如图1所示,本发明提供的港口货运电动AGV的故障监测诊断系统,包含AGV车与服务器;所述AGV车运行在港口码头场地上;所述AGV车和/或港口码头场地上安装有传感器;服务器根据来自AGV车和/或港口码头场地上传感器的监测信号,生成故障监测诊断信号。所述AGV车包含车身模块、传动模块、电机模块以及电池模块。以下任一个多任多个位置上:车身模块、传动模块、电机模块、电池模块、港口码头场地,安装有以下任一种或任多种传感器:振动传感器、湿度传感器、温度传感器、电压传感器、电流传感器。As shown in Figure 1, the fault monitoring and diagnosis system of port freight electric AGV provided by the present invention includes AGV car and server; the AGV car runs on the port wharf site; Sensors; the server generates fault monitoring and diagnostic signals based on the monitoring signals from the sensors on the AGV vehicle and/or the port terminal. The AGV vehicle includes a body module, a transmission module, a motor module and a battery module. Any one or more of the following positions: body module, transmission module, motor module, battery module, port and wharf site, any one or more of the following sensors are installed: vibration sensor, humidity sensor, temperature sensor, voltage sensor, current sensor.

AGV车上设置有第一信号处理模块,所述港口码头场地上设置有第二信号处理模块;所述服务器包含远程信号接收模块;第一信号处理模块、第二信号处理模块分别将来自AGV车上传感器的监测信号、来自港口码头场地上传感器的监测信号进行处理,获得对应的预处理数据,并分别将对应的预处理数据发送至远程信号接收模块。所述服务器还包含远程故障监测诊断模块与数据管理模块;远程故障监测诊断模块根据远程信号接收模块接收的预处理数据,和/或来自数据管理模块的车身运行历史数据,生成故障监测诊断信号。AGV车上传感器通过总线与第二信号处理模块相连;港口码头场地上传感器通过总线与第二信号处理模块相连;第一信号处理模块与第二信号处理模块均通过无线传输形式与远程信号接收模块进行通信;远程信号接收模块通过有线形式与远程故障监测诊断模块相连。所述服务器还包含显示模块;所述显示模块根据接收到的故障监测诊断信号,显示以下任一种或任多种信息:AGV车的故障信息;AGV车的健康状况信息;AGV车上零部件的剩余寿命信息。所述远程故障监测诊断模块包含以下任一个或任多个模块:运行监测模块:监测AGV车整体运行情况;故障定位与等级分类模块:计算AGV车上故障发生的部位及严重程度;零部件寿命估测模块:预估AGV车上零部件的剩余寿命。The first signal processing module is provided on the AGV car, and the second signal processing module is provided on the port wharf site; the server includes a remote signal receiving module; the first signal processing module and the second signal processing module receive signals from the AGV car The monitoring signal from the upper sensor and the monitoring signal from the sensor on the port terminal are processed to obtain the corresponding pre-processing data, and the corresponding pre-processing data are respectively sent to the remote signal receiving module. The server also includes a remote fault monitoring and diagnosis module and a data management module; the remote fault monitoring and diagnosis module generates a fault monitoring and diagnosis signal according to the preprocessed data received by the remote signal receiving module and/or the vehicle body operation history data from the data management module. The sensor on the AGV vehicle is connected to the second signal processing module through the bus; the sensor on the port terminal site is connected to the second signal processing module through the bus; the first signal processing module and the second signal processing module are connected to the remote signal receiving module through wireless transmission Communication; the remote signal receiving module is connected with the remote fault monitoring and diagnosis module through a wired form. The server also includes a display module; the display module displays any or any of the following information according to the received fault monitoring and diagnosis signal: the fault information of the AGV car; the health status information of the AGV car; the components on the AGV car remaining life information. The remote fault monitoring and diagnosis module includes any one or more of the following modules: operation monitoring module: monitor the overall operation of the AGV vehicle; fault location and classification module: calculate the location and severity of the fault on the AGV vehicle; component life Estimation module: Estimate the remaining life of parts on the AGV.

如图2所示,实施例中,故障定位与等级分类模块包含轴承故障诊断模块,所述轴承故障诊断模块包含以下模块:滤波模块:对预处理数据所包含的原始振动信号进行滤波,获得降噪振动信号;重构模块:对降噪振动信号进行重构,获得重构振动信号;诊断结果获取模块:对重构振动信号进行诊断,获得轴承故障诊断结果。As shown in Figure 2, in the embodiment, the fault location and grade classification module includes a bearing fault diagnosis module, and the bearing fault diagnosis module includes the following modules: filtering module: filtering the original vibration signal contained in the preprocessing data to obtain the reduced noise vibration signal; reconstruction module: reconstruct the noise reduction vibration signal to obtain the reconstructed vibration signal; diagnosis result acquisition module: diagnose the reconstructed vibration signal to obtain the bearing fault diagnosis result.

所述滤波模块中,对原始振动信号进行分数阶傅里叶变换滤波,消除原始振动信号中的线性调频噪声,分数阶傅里叶变换FRFT是一种统一的视频变换,反映了信号在时域和频域上的信息,它用单一变量来表示视频信息,没有交叉项的干扰:与传统傅里叶变换相比,由于多了一个自由参量(变换阶数p)其更适合处理非平稳信号,并且由于存在较为成熟的快速离散算法,FRFT能够在合理的计算量限制下得到较好的分析结果。如图3所示,所述分数阶傅里叶变换通过以下公式实现:In the filtering module, the original vibration signal is subjected to fractional Fourier transform filtering to eliminate the chirp noise in the original vibration signal. The fractional order Fourier transform FRFT is a unified video transform that reflects the signal in the time domain. And the information in the frequency domain, it uses a single variable to represent the video information, without the interference of cross items: compared with the traditional Fourier transform, it is more suitable for dealing with non-stationary signals due to one more free parameter (transformation order p) , and due to the existence of relatively mature fast discrete algorithms, FRFT can obtain better analysis results under reasonable calculation constraints. As shown in Figure 3, the fractional Fourier transform is realized by the following formula:

式中:fp(u)为降噪振动信号,p为自由变量分数阶次,且p∈(-2,2],u为核函数参数;Kp(u,t)为傅里叶变换核信号,t为时域信号;f(t)为原始振动信号;Aα为前置系数,α为旋转角度,且α∈(-2π,2π];j为虚部符号;n为整数;δ()为狄拉克函数;sgn()为符号函数。Kp(u,t)实质上是一组调频率为cotα的chirp信号,通过改变角度α,便可以得到不同调频率的基。一旦需要滤波的chirp信号与某组基的调频率吻合,那么该信号也会在该组基上形成一个δ函数,并且由于分数傅里叶变换是一个线性变换,信号和噪声叠加后的分数阶傅里叶变换等于各自分别进行分数阶变换的叠加,利用这两点便可以对信号在分数阶傅里叶域中进行滤波。优选地,重构模块中,使用反分数阶傅里叶变换对降噪振动信号进行重构。实际应用中,还可以通过类似的算法进行如电池、电机、变速箱等部位具体诊断。In the formula: f p (u) is the noise reduction vibration signal, p is the fractional order of the free variable, and p∈(-2, 2], u is the kernel function parameter; K p (u, t) is the Fourier transform nuclear signal, t is the time domain signal; f(t) is the original vibration signal; A α is the pre-coefficient, α is the rotation angle, and α∈(-2π, 2π]; j is the symbol of the imaginary part; n is an integer; δ() is a Dirac function; sgn() is a sign function. K p (u, t) is essentially a group of chirp signals whose modulation frequency is cotα. By changing the angle α, the basis of different modulation frequencies can be obtained. Once The chirp signal that needs to be filtered coincides with the modulation frequency of a certain group base, then the signal will also form a delta function on the group base, and since the fractional Fourier transform is a linear transformation, the fractional Fourier transform after the signal and noise are superimposed The Liye transform is equal to the superposition of the fractional transform respectively, and the signal can be filtered in the fractional Fourier domain by using these two points.Preferably, in the reconstruction module, the inverse fractional Fourier transform is used to reduce the Noise and vibration signals are reconstructed. In practical applications, specific diagnosis of parts such as batteries, motors, and gearboxes can also be performed through similar algorithms.

诊断结果获取模块具体工作步骤和检验原理如下,滚动轴承等旋转机械设备故障一般具有周期性的脉冲冲击力,产生振动信号的调制现象,采用调解分析的方法,从信号中提取调制信息,分析其强度和频次就可以判断零件损伤的程度和部位。实施例中,诊断结果获取模块包含以下模块:模块M1:求重构振动信号的Hilbert变换对;模块M2:以重构振动信号为实部,以Hilbert变换对为虚部,构建解析信号;模块M3:对解析信号求模得到包络信号;模块M4:对包络信号进行低通滤波与快速傅里叶变换求出包络谱,根据包络谱得到调制频率、调制频率高次频谐波以及调制函数。The specific working steps and inspection principles of the diagnostic result acquisition module are as follows. The faults of rolling bearings and other rotating machinery equipment generally have periodic pulse impacts, which produce modulation phenomena of vibration signals. The method of mediation analysis is used to extract modulation information from the signal and analyze its intensity. And the frequency can judge the degree and location of parts damage. In an embodiment, the diagnosis result acquisition module includes the following modules: module M1: find the Hilbert transform pair of the reconstructed vibration signal; module M2: use the reconstructed vibration signal as the real part, and use the Hilbert transform pair as the imaginary part to construct the analytical signal; M3: Calculate the modulus of the analytical signal to obtain the envelope signal; Module M4: Perform low-pass filtering and fast Fourier transform on the envelope signal to obtain the envelope spectrum, and obtain the modulation frequency and high-order harmonics of the modulation frequency according to the envelope spectrum and modulation functions.

优选实施例:Preferred embodiment:

港口货运电动AGV的故障监测诊断系统包括安装在AGV车身各处的传感器,安装在港口上的传感器,AGV车载信号预处理模块,港口场地信号预处理模块,远程信号接收中心和远程故障监测及诊断中心。The fault monitoring and diagnosis system of port freight electric AGV includes sensors installed everywhere on the AGV body, sensors installed on the port, AGV vehicle signal preprocessing module, port site signal preprocessing module, remote signal receiving center and remote fault monitoring and diagnosis center.

车身上的传感器分别安装在AGV上的车架模块,传动模块,电机模块和电池模块。具体来说传感器主要包括振动传感器,温度传感器,电流传感器和电压传感器。这些传感器分别用来采集车身整体的振动数据,机械传动模块中齿轮箱、轴承等的振动数据和温度数据,驱动电机的电压,电流,温度和振动数据,动力电池组的电流,电压和温度数据。The sensors on the body are respectively installed on the frame module, transmission module, motor module and battery module of the AGV. Specifically, the sensors mainly include vibration sensors, temperature sensors, current sensors and voltage sensors. These sensors are used to collect the overall vibration data of the vehicle body, the vibration data and temperature data of the gearbox and bearings in the mechanical transmission module, the voltage, current, temperature and vibration data of the drive motor, and the current, voltage and temperature data of the power battery pack. .

在车辆正常工作的过程中,传感器采集到的数据通过总线发送到车载信号预处理模块,对信号进行基础的预处理,包括放大,滤波,调试等后,将预处理后的数据通过在港口上搭建的无线网络,将数据传送至位于港口上的远程信号接收中心。During the normal operation of the vehicle, the data collected by the sensor is sent to the on-board signal pre-processing module through the bus, and the basic pre-processing of the signal, including amplification, filtering, debugging, etc., passes the pre-processed data on the port. The built wireless network transmits the data to the remote signal receiving center located on the port.

在港口上合适的位置布置基础的气象采集单元,该单元上布置有温度和湿度传感器,用于测量港口上AGV工作的气象条件。传感器的信号通过总线传输到港口场地信号处理模块,该模块对信号进行基础的预处理,包括放大,滤波,调制等后,将预处理后的数据通过在港口上搭建的无线网络,将数据传送至位于港口上的远程信号接收中心。A basic meteorological acquisition unit is arranged at a suitable location on the port, and temperature and humidity sensors are arranged on the unit to measure the meteorological conditions for AGV work on the port. The signal of the sensor is transmitted to the signal processing module of the port site through the bus. This module performs basic preprocessing on the signal, including amplification, filtering, modulation, etc., and transmits the preprocessed data through the wireless network built on the port. to the remote signal reception center located on the port.

远程信号接收中心将接收到的信号解调之后,将信号发送给远程故障监测及诊断中心。所述远程故障监测及诊断中心同时接收来自远程数据接收中心发送的数据和来自港口AGV车辆调度中心发送的有关AGV车辆历史运行轨迹的数据,对这些数据进行分析,实时监测港口上AGV整体的运行情况,相关设备零件的健康状况,是否发生故障以及发生故障的部位。After the remote signal receiving center demodulates the received signal, it sends the signal to the remote fault monitoring and diagnosis center. The remote fault monitoring and diagnosis center simultaneously receives the data sent from the remote data receiving center and the data about the historical running track of the AGV vehicle sent from the port AGV vehicle dispatching center, analyzes these data, and monitors the overall operation of the AGV on the port in real time condition, the health status of related equipment parts, whether there is a failure and the location of the failure.

所述运行车辆健康情况的实时监测,其特征是系统将运行过程中各车辆的健康状况实时显示在设计的人机交互界面上,并对发生故障的车辆提交管理人员处理或由交由其他程序自动处理。所述故障定位及等级分类,其特征是可以指出车辆故障发生的部位及严重程度。所述相关零部件剩余寿命的估计预测,其特征是故障监测和诊断中心根据服务器中的历史数据,通过智能算法,生成模型,预估相关零件的使用寿命模型,并通过当前传感器采集到的零部件状态来预估相关零件的剩余寿命。The real-time monitoring of the health status of the running vehicles is characterized in that the system displays the health status of each vehicle during the running process on the designed human-computer interaction interface in real time, and submits the failed vehicles to the management personnel for processing or by other programs Automatic processing. The feature of the fault location and grade classification is that it can point out the location and severity of the vehicle fault. The estimation and prediction of the remaining life of the relevant parts is characterized in that the fault monitoring and diagnosis center generates a model through an intelligent algorithm based on the historical data in the server, and estimates the service life model of the relevant parts, and uses the zero collected by the current sensor Component status to estimate the remaining life of the relevant parts.

以上对本发明的具体实施例进行了描述。需要理解的是,本发明并不局限于上述特定实施方式,本领域技术人员可以在权利要求的范围内做出各种变形或修改,这并不影响本发明的实质内容。在不冲突的情况下,本申请的实施例和实施例中的特征可以任意相互组合。Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims (6)

1. a kind of malfunction monitoring diagnostic system of the electronic AGV of port cargo, which is characterized in that include AGV vehicle and server;It is described AGV vehicle operates on port and pier place;
Sensor is installed on the AGV vehicle and/or port and pier place;
Server generates malfunction monitoring diagnosis letter according to the monitoring signals of the sensor on AGV vehicle and/or port and pier place Number;
It is provided with the first signal processing module on AGV vehicle, is provided with second signal processing module on the port and pier place;
The server includes remote signal receiving module;
First signal processing module, second signal processing module respectively by AGV vehicle the monitoring signals of sensor, come from port The monitoring signals of sensor are handled on mouth harbour place, obtain corresponding preprocessed data, and respectively by corresponding pre- place Reason data are sent to remote signal receiving module;
The server also includes remote failure monitoring, diagnosing module and data management module;
Remote failure monitoring, diagnosing module is according to the received preprocessed data of remote signal receiving module, and/or comes from data pipe The vehicle body operation history data of module is managed, malfunction monitoring diagnostic signal is generated;
Sensor is connected by bus with second signal processing module on AGV vehicle;
Sensor is connected by bus with second signal processing module on port and pier place;
First signal processing module and second signal processing module pass through wireless transmission form and remote signal receiving module into Row communication;
Remote signal receiving module is connected by wired forms with remote failure monitoring, diagnosing module;
The server also includes display module;
For the display module according to the malfunction monitoring diagnostic signal received, display is following any or appoints much information:
-- the fault message of AGV vehicle;
-- the health information of AGV vehicle;
-- the remaining life information of components on AGV vehicle;
The remote failure monitoring, diagnosing module include it is following any one or appoint multiple modules:
Operational monitoring module: monitoring AGV vehicle overall operation situation;
Fault location and grade separation module: the position and severity that failure occurs on AGV vehicle are calculated;
Part life estimating module: the remaining life of components on AGV vehicle is estimated.
2. the malfunction monitoring diagnostic system of the electronic AGV of port cargo according to claim 1, which is characterized in that the AGV Vehicle includes body modules, transmission module, motor module and battery module;
Below on any one more multiple position:
-- body modules;
-- transmission module;
-- motor module;
-- battery module;
-- port and pier place,
It is equipped with following any or appoints multiple sensors:
-- vibrating sensor;
-- humidity sensor;
-- temperature sensor;
-- voltage sensor;
-- current sensor.
3. the malfunction monitoring diagnostic system of the electronic AGV of port cargo according to claim 1, which is characterized in that failure is fixed Position includes bearing failure diagnosis module with grade separation module, and the bearing failure diagnosis module includes with lower module:
Filter module: the original vibration signal for being included to preprocessed data is filtered, and obtains noise reduction vibration signal;
Reconstructed module: being reconstructed noise reduction vibration signal, obtains reconstruct vibration signal;
Diagnostic result obtains module: diagnosing to reconstruct vibration signal, obtains bearing failure diagnosis result.
4. the malfunction monitoring diagnostic system of the electronic AGV of port cargo according to claim 3, which is characterized in that the filter In wave module, Fourier Transform of Fractional Order filtering is carried out to original vibration signal, eliminates the linear frequency modulation in original vibration signal Noise;
The Fourier Transform of Fractional Order is realized by following formula:
In formula: fp(u) be noise reduction vibration signal, p be free variable fractional-order, and p ∈ (- 2,2], u is kernel functional parameter;
Kp(u, t) is Fourier transformation nuclear signal, and t is time-domain signal;
F (t) is original vibration signal;
AαFor pre-factor, α is rotation angle, and α ∈ (- 2 π, 2 π];
J is the imaginary part of symbol;
N is integer;
δ () is Dirac function;
Sgn () is sign function.
5. the malfunction monitoring diagnostic system of the electronic AGV of port cargo according to claim 4, which is characterized in that reconstruct mould In block, it is reconstructed using inverse fraction rank Fourier transform pairs noise reduction vibration signal.
6. the malfunction monitoring diagnostic system of the electronic AGV of port cargo according to claim 5, which is characterized in that diagnosis knot It includes with lower module that fruit, which obtains module:
Module M1: the Hilbert transformation pair of reconstruct vibration signal is asked;
Module M2: to reconstruct vibration signal as real part, with Hilbert transformation to for imaginary part, analytic signal is constructed;
Module M3: envelope signal is obtained to analytic signal modulus;
Module M4: low-pass filtering is carried out to envelope signal and Fast Fourier Transform (FFT) finds out envelope spectrum, is adjusted according to envelope spectrum Frequency, modulating frequency high order frequency harmonic wave and modulation function processed.
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