CN118723742A - Elevator operation fault monitoring method and system based on Internet of Things - Google Patents
Elevator operation fault monitoring method and system based on Internet of Things Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
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Abstract
本发明公开了一种基于物联网的电梯运行故障监测方法及系统，涉及电梯运行故障监测技术领域，通过采集电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度和轴承温度的历史和实时数据，并利用物联网网关将上述数据传输到物联网平台；通过历史振动频率、振动幅值和噪音强度建立历史轴承系数Cz，利用熵权法计算各参数权重，并建立历史电机温升系数Mz数据；通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；通过实时振动频率、振动幅值和噪音强度建立实时轴承系数Ct，建立实时电机温升系数Mt数据，并通过实时数据计算实时综合系数Et及其阈值；实时监测电梯电机综合系数Et，根据数据状态选择不同的预警处理策略，确保电梯运行安全可靠。
The invention discloses an elevator operation fault monitoring method and system based on the Internet of Things, and relates to the technical field of elevator operation fault monitoring. The method and system collect historical and real-time data of motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature, and transmit the data to an Internet of Things platform by using an Internet of Things gateway; establish a historical bearing coefficient Cz by using the historical vibration frequency, vibration amplitude and noise intensity, calculate the weight of each parameter by using an entropy weight method, and establish historical motor temperature rise coefficient Mz data; establish a historical comprehensive coefficient Ez by using the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; establish a real-time bearing coefficient Ct by using the real-time vibration frequency, vibration amplitude and noise intensity, establish real-time motor temperature rise coefficient Mt data, and calculate the real-time comprehensive coefficient Et and its threshold value by using the real-time data; monitor the elevator motor comprehensive coefficient Et in real time, and select different early warning processing strategies according to the data state to ensure safe and reliable elevator operation.
Description
技术领域Technical Field
本发明涉及电梯运行故障监测技术领域，具体为一种基于物联网的电梯运行故障监测方法及系统。The present invention relates to the technical field of elevator operation fault monitoring, and in particular to an elevator operation fault monitoring method and system based on the Internet of Things.
背景技术Background Art
随着智能化技术的发展，电梯运行故障监测方法及系统已经成为电梯安全运行和维护中不可缺少的一部分。有效的智能化系统不仅提高了电梯运行的效率和质量，还大大提升了电梯的安全水平和故障响应能力。然而，在现有的电梯故障监测过程中仍然需要大量的人工介入来判断电梯运行过程中出现的复杂故障问题，但在监测中无法充分精确地响应电梯运行过程中出现的复杂故障问题。With the development of intelligent technology, elevator operation fault monitoring methods and systems have become an indispensable part of elevator safe operation and maintenance. Effective intelligent systems not only improve the efficiency and quality of elevator operation, but also greatly enhance the safety level and fault response capabilities of elevators. However, in the existing elevator fault monitoring process, a large amount of manual intervention is still required to judge the complex fault problems that occur during elevator operation, but the monitoring cannot fully and accurately respond to the complex fault problems that occur during elevator operation.
在申请公布号CN111071889A的中国发明申请中，公开了一种基于物联网的电梯状态识别系统，本发明涉及了一种基于物联网的电梯状态识别系统，所述电梯状态识别系统包括健康度分析模块，用以通过分析前一天完整的加速度数据，将前一天运行完整一天的加速度数据与设定加速度数据进行比对，评估电梯的健康状况与安全隐患，所述健康度分析模块包括加速度传感器、数据接收单元、平稳度比对单元、启停振幅比对单元、加速度变化趋势比对单元、开关门次数获取单元、阻碍时间获取单元、重开重关次数获取单元以及开关门抖动获取单元，本发明提出的基于物联网的设备状态识别系统，实时监测设备状态。In the Chinese invention application with application publication number CN111071889A, an elevator state recognition system based on the Internet of Things is disclosed. The present invention relates to an elevator state recognition system based on the Internet of Things. The elevator state recognition system includes a health analysis module for evaluating the health status and safety hazards of the elevator by analyzing the complete acceleration data of the previous day and comparing the acceleration data of the previous day's complete operation with the set acceleration data. The health analysis module includes an acceleration sensor, a data receiving unit, a smoothness comparison unit, a start-stop amplitude comparison unit, an acceleration change trend comparison unit, a door opening and closing times acquisition unit, a blocking time acquisition unit, a reopening and reclosing times acquisition unit, and a door opening and closing jitter acquisition unit. The device state recognition system based on the Internet of Things proposed by the present invention monitors the device state in real time.
在上述发明中，该该电梯状态识别系统通过分析前一天完整的加速度数据，与设定的标准加速度数据进行比对，以评估电梯的健康状况和安全风险，尽管加速度是否正常可以反映电梯的运行状态，但电梯的整体健康状况和安全风险不仅仅取决于加速度数据，因此，该电梯状态识别系统存在着问题，检测精度低，导致对电梯健康状况和安全风险的识别度不高。In the above invention, the elevator status recognition system analyzes the complete acceleration data of the previous day and compares it with the set standard acceleration data to evaluate the health status and safety risks of the elevator. Although whether the acceleration is normal can reflect the operating status of the elevator, the overall health status and safety risks of the elevator do not only depend on the acceleration data. Therefore, there are problems with the elevator status recognition system, and the detection accuracy is low, resulting in low recognition of the health status and safety risks of the elevator.
为此，本发明提供了一种基于物联网的电梯运行故障监测方法及系统。To this end, the present invention provides an elevator operation fault monitoring method and system based on the Internet of Things.
发明内容Summary of the invention
（一）解决的技术问题1. Technical issues to be resolved
针对现有技术的不足，本发明提供了一种基于物联网的电梯运行故障监测方法及系统，本发明通过物联网传感器采集电梯电机运行的参数数据，并传输到物联网平台；将电梯电机运行数据经异常值和归一化处理后，建立历史轴承系数Cz和历史电机温升系数Mz数据，通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；建立实时轴承系数Ct和实时电机温升系数Mt，通过实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et，并通过均值加减标准差法来计算实时综合系数Et的阈值r；通过实时监测电梯电机综合系数Et，根据实时数据状态选择不同的安全预警处理策略，这种实时监测和反馈机制有助于提升电梯运行的安全性和可靠性，确保电梯设备在正常范围内运行，并能快速响应任何潜在的异常情况。In view of the deficiencies of the prior art, the present invention provides an elevator operation fault monitoring method and system based on the Internet of Things. The present invention collects parameter data of elevator motor operation through an Internet of Things sensor and transmits it to an Internet of Things platform; after the elevator motor operation data is processed by abnormal values and normalization, historical bearing coefficient Cz and historical motor temperature rise coefficient Mz data are established, and a historical comprehensive coefficient Ez is established through the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; a real-time bearing coefficient Ct and a real-time motor temperature rise coefficient Mt are established, and a real-time comprehensive coefficient Et is established through the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt , and a threshold value r of the real-time comprehensive coefficient Et is calculated through the mean plus and minus standard deviation method; by real-time monitoring of the elevator motor comprehensive coefficient Et , different safety warning processing strategies are selected according to the real-time data status. This real-time monitoring and feedback mechanism helps to improve the safety and reliability of elevator operation, ensure that the elevator equipment operates within a normal range, and can quickly respond to any potential abnormal conditions.
（二）技术方案(II) Technical solution
为实现以上目的，本发明通过以下技术方案予以实现：一种基于物联网的电梯运行故障监测方法，包括如下步骤：To achieve the above objectives, the present invention is implemented through the following technical solutions: an elevator operation fault monitoring method based on the Internet of Things, comprising the following steps:
通过振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集电梯电机运行时的各项参数数据，包括电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度和轴承温度的实时数据；Vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors are used to collect various parameter data of elevator motors during operation, including real-time data of motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature;
通过物联网网关将振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集到的上述数据传输到物联网平台；The above data collected by the vibration sensor, noise sensor, thermocouple sensor, infrared temperature sensor and embedded temperature sensor are transmitted to the IoT platform through the IoT gateway;
将电梯电机运行数据经异常值和归一化处理后，利用历史振动频率、振动幅值和噪音强度建立历史轴承系数Cz；通过熵权法计算各参数权重，利用历史绕组温度、机壳温度、轴承温度建立历史电机温升系数Mz数据；通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；利用实时振动频率、振动幅值和噪音强度建立实时轴承系数Ct；利用实时绕组温度、机壳温度、轴承温度建立实时电机温升系数Mt数据；通过实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et；并通过均值加减标准差法来计算实时综合系数Et的阈值r；After the elevator motor operation data is processed by abnormal value and normalization, the historical bearing coefficient Cz is established using the historical vibration frequency, vibration amplitude and noise intensity; the weights of each parameter are calculated by the entropy weight method, and the historical motor temperature rise coefficient Mz data is established using the historical winding temperature, casing temperature and bearing temperature; the historical comprehensive coefficient Ez is established by the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; the real-time bearing coefficient Ct is established using the real-time vibration frequency, vibration amplitude and noise intensity; the real-time motor temperature rise coefficient Mt data is established using the real-time winding temperature, casing temperature and bearing temperature; the real-time comprehensive coefficient Et is established by the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt ; and the threshold r of the real-time comprehensive coefficient Et is calculated by the mean plus and minus standard deviation method;
通过实时监测电梯电机综合系数Et，根据实时数据状态选择对应的预警处理策略。By real-time monitoring of the elevator motor comprehensive coefficient Et , the corresponding early warning processing strategy is selected according to the real-time data status.
进一步的，调取电梯历史数据，通过历史振动频率、振动幅值和噪音强度数据建立历史轴承系数Cz，利用熵权法进行各参数的权重计算，首先对历史振动频率、振动幅值和噪音强度数据进行标准化处理，得到 、 和，计算每个标准化后的参数的权重比例，公式如下所示：Furthermore, the historical data of the elevator is retrieved and the historical vibration frequency is used to , vibration amplitude and noise intensity The historical bearing coefficient Cz is established based on the data, and the entropy weight method is used to calculate the weight of each parameter. First, the historical vibration frequency , vibration amplitude and noise intensity The data is standardized to obtain , and , calculate the weight ratio of each standardized parameter, the formula is as follows:
其中，i表示第i个数据的索引，i=1、2、3…、n，分别为历史振动频率、振动幅值和噪声强度的权重比例。Where i represents the index of the i- th data, i = 1, 2, 3…, n , are the weight proportions of historical vibration frequency, vibration amplitude and noise intensity respectively.
进一步的，通过每个标准化后的参数的权重比例，再计算各参数的信息熵，公式如下所示：Furthermore, the information entropy of each parameter is calculated by the weight ratio of each standardized parameter. The formula is as follows:
其中，、和表示历史振动频率、振动幅值和噪声强度的信息熵，用来衡量每个参数的不确定性，根据信息熵计算每个参数的权重，公式如下所示：in, , and The information entropy representing the historical vibration frequency, vibration amplitude and noise intensity is used to measure the uncertainty of each parameter. The weight of each parameter is calculated based on the information entropy. The formula is as follows:
其中，、和分别表示历史振动频率、振动幅值和噪声强度的信息熵的互信息量。in, , and The mutual information of the information entropy representing the historical vibration frequency, vibration amplitude and noise intensity respectively.
进一步的，根据历史振动频率、振动幅值和噪声强度的权重、和，建立历史轴承系数Cz，公式如下所示：Furthermore, according to the weights of historical vibration frequency, vibration amplitude and noise intensity , and , establish the historical bearing coefficient Cz , the formula is as follows:
+ +
其中，n表示样本的总数量，、和分别为历史振动频率、振动幅值和噪音强度数据的权重。Where n represents the total number of samples. , and are the weights of historical vibration frequency, vibration amplitude and noise intensity data respectively.
进一步的，通过历史绕组温度、机壳温度和轴承温度数据建立电机温升系数，利用熵权法进行电机温升系数的权重计算，首先对历史绕组温度、机壳温度和轴承温度数据进行标准化处理，得到、和，计算每个标准化后的参数的权重比例P ，再计算各参数的信息熵、和，根据信息熵计算各参数的权重和，利用各参数权重计算电机温升系数Mz，公式如下所示：Furthermore, through the historical winding temperature , Case temperature and bearing temperature Data to establish the motor temperature rise coefficient , the entropy weight method is used to calculate the weight of the motor temperature rise coefficient. First, the historical winding temperature , Case temperature and bearing temperature The data is standardized to obtain , and , calculate the weight ratio P of each standardized parameter , and then calculate the information entropy of each parameter , and , calculate the weight of each parameter according to information entropy and , use the weights of each parameter to calculate the motor temperature rise coefficient Mz , the formula is as follows:
+ +
其中，、和为历史绕组温度、机壳温度和轴承温度数据的权重。in, , and is the weight of the historical winding temperature, casing temperature and bearing temperature data.
进一步的，利用历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez，公式如下所示：Furthermore, the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz are used to establish the historical comprehensive coefficient Ez . The formula is as follows:
Ez= Cz+ Mz Ez= Cz+ Mz
其中，b和c为历史轴承系数Cz和历史电机温升系数Mz的所占比例系数，b为0.5，c为0.5，利用均值加减标准差法计算历史综合系数Ez的阈值r，公式如下所示：Among them, b and c are the proportion coefficients of the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz , b is 0.5, c is 0.5, and the threshold r of the historical comprehensive coefficient Ez is calculated using the mean plus minus standard deviation method. The formula is as follows:
其中，为综合系数的均值，为综合系数的标准差，根据标准差定义阈值r的范围，公式如下所示：in, is the mean of the comprehensive coefficients, is the standard deviation of the comprehensive coefficient, according to the standard deviation Define the range of the threshold r , the formula is as follows:
其中，k为误差容忍偏差，k=1、2、3。Where k is the error tolerance deviation, k = 1, 2, 3.
进一步的，通过实时振动频率、振动幅值和噪音强度数据建立实时轴承系数Ct，公式如下所示：Furthermore, through real-time vibration frequency , vibration amplitude and noise intensity The data establishes the real-time bearing coefficient Ct , and the formula is as follows:
通过实时绕组温度、机壳温度和轴承温度数据建立电机温升系数，公式如下所示：Real-time winding temperature , Case temperature and bearing temperature Data to establish the motor temperature rise coefficient , the formula is as follows:
其中，为实时电机温升系数，利用实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et，公式如下所示：in, is the real-time motor temperature rise coefficient. The real-time comprehensive coefficient Et is established using the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt. The formula is as follows:
Et= Ct+ Mt Et= Ct+ Mt
其中，Et为实时综合系数。Among them, Et is the real-time comprehensive coefficient.
进一步的，通过实时监测电梯电机运行的综合系数，查看实时综合系数是否在安全阈值范围内，并采取不同的调节策略，具体为：Furthermore, by real-time monitoring of the comprehensive coefficient of the elevator motor operation, check whether the real-time comprehensive coefficient is within the safety threshold range, and adopt different adjustment strategies, specifically:
当实时综合系数Et小于阈值r时，系统发出二级预警信号，反馈当前电梯电机运行具有轻度故障；When the real-time comprehensive coefficient Et is less than the threshold value r , the system issues a secondary warning signal, indicating that the current elevator motor operation has a minor fault;
当实时综合系数Et处于阈值r范围时，系统不发出预警信号，反馈当前电梯电机运行情况良好，不会造成安全隐患；When the real-time comprehensive coefficient Et is within the threshold r range, the system does not issue a warning signal, and feedback is given that the current elevator motor is operating well and will not cause safety hazards;
当实时综合系数Et大于阈值r时，系统发出一级预警信号，反馈当前电梯电机运行具有重度故障，停止运行。When the real-time comprehensive coefficient Et is greater than the threshold value r , the system sends out a first-level warning signal, feedback that the current elevator motor operation has a serious fault and stops running.
一种基于物联网的电梯运行故障监测系统，包括：An elevator operation fault monitoring system based on the Internet of Things, comprising:
数据采集模块，通过振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集电梯电机运行时的各项参数数据，包括电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度和轴承温度的实时数据；The data acquisition module collects various parameter data of the elevator motor during operation through vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors, including real-time data of motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature;
物联网传输模块，通过物联网网关将振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集到的上述数据传输到物联网平台；The IoT transmission module transmits the above data collected by the vibration sensor, noise sensor, thermocouple sensor, infrared temperature sensor and embedded temperature sensor to the IoT platform through the IoT gateway;
运行模块，将电梯电机运行数据经异常值和归一化处理后，利用历史振动频率、振动幅值和噪音强度建立历史轴承系数Cz；利用历史绕组温度、机壳温度、轴承温度建立历史电机温升系数Mz数据；通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；利用实时振动频率、振动幅值和噪音强度建立实时轴承系数Ct；利用实时绕组温度、机壳温度、轴承温度建立实时电机温升系数Mt数据；通过实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et；并通过均值加减标准差法来计算实时综合系数Et的阈值r；The operation module processes the elevator motor operation data after abnormal value and normalization, and uses the historical vibration frequency, vibration amplitude and noise intensity to establish the historical bearing coefficient Cz ; uses the historical winding temperature, casing temperature and bearing temperature to establish the historical motor temperature rise coefficient Mz data; establishes the historical comprehensive coefficient Ez through the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; establishes the real-time bearing coefficient Ct through the real-time vibration frequency, vibration amplitude and noise intensity; establishes the real-time motor temperature rise coefficient Mt data through the real-time winding temperature, casing temperature and bearing temperature; establishes the real-time comprehensive coefficient Et through the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt ; and calculates the threshold r of the real-time comprehensive coefficient Et through the mean plus and minus standard deviation method;
管理模块，通过实时监测电梯电机综合系数Et，根据实时数据状态选择对应的预警处理策略。The management module monitors the comprehensive coefficient Et of the elevator motor in real time and selects the corresponding early warning processing strategy according to the real-time data status.
（三）有益效果(III) Beneficial effects
本发明提供了一种基于物联网的电梯运行故障监测方法及系统，具备以下有益效果：The present invention provides an elevator operation fault monitoring method and system based on the Internet of Things, which has the following beneficial effects:
1、通过振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集电梯电机运行时的各项参数数据，包括电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度、轴承温度的历史数据和实时数据，有助于全面了解电梯电机的健康状况，提高了故障预测的准确性和及时性。1. Vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors are used to collect the historical and real-time data of various parameters of the elevator motor during operation, including motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature, which helps to fully understand the health status of the elevator motor and improve the accuracy and timeliness of fault prediction.
2、通过物联网网关将振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集到的上述数据传输到物联网平台，有效实现了数据的集中管理和分析，从而提升了电梯故障预警和维护的效率。2. The above data collected by vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors are transmitted to the IoT platform through the IoT gateway, which effectively realizes the centralized management and analysis of data, thereby improving the efficiency of elevator fault warning and maintenance.
3、将电梯电机运行数据经异常值和归一化处理后，利用历史振动频率、振动幅值和噪音强度建立历史轴承系数Cz，通过熵权法计算各参数权重，利用历史绕组温度、机壳温度、轴承温度建立历史电机温升系数Mz数据，通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；利用实时振动频率、振动幅值和噪音强度建立实时轴承系数Ct，利用实时绕组温度、机壳温度、轴承温度建立实时电机温升系数Mt数据，通过实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et；并通过均值加减标准差法来计算实时综合系数Et的阈值，有助于精确评估电梯电机的运行状态，提高了故障诊断的精确性和可靠性。3. After the elevator motor operation data is processed by abnormal value and normalization, the historical vibration frequency, vibration amplitude and noise intensity are used to establish the historical bearing coefficient Cz , the weights of each parameter are calculated by the entropy weight method, the historical winding temperature, casing temperature and bearing temperature are used to establish the historical motor temperature rise coefficient Mz data, and the historical comprehensive coefficient Ez is established through the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; the real-time vibration frequency, vibration amplitude and noise intensity are used to establish the real-time bearing coefficient Ct , the real-time winding temperature, casing temperature and bearing temperature are used to establish the real-time motor temperature rise coefficient Mt data, and the real-time comprehensive coefficient Et is established through the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt ; and the threshold of the real-time comprehensive coefficient Et is calculated by the mean plus or minus standard deviation method, which helps to accurately evaluate the operating status of the elevator motor and improve the accuracy and reliability of fault diagnosis.
4、通过实时监测电梯电机综合系数Et，根据实时数据状态选择不同的预警处理策略，有效提高了电梯运行的安全性和可靠性，确保了乘客的安全。4. By real-time monitoring of the elevator motor comprehensive coefficient Et and selecting different early warning processing strategies according to the real-time data status, the safety and reliability of elevator operation are effectively improved, ensuring the safety of passengers.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明一种基于物联网的电梯运行故障监测方法的流程示意图；FIG1 is a flow chart of an elevator operation fault monitoring method based on the Internet of Things according to the present invention;
图2为本发明一种基于物联网的电梯运行故障监测系统的结构示意图。FIG. 2 is a schematic diagram of the structure of an elevator operation fault monitoring system based on the Internet of Things according to the present invention.
具体实施方式DETAILED DESCRIPTION
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。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前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
请参阅图1，本发明提供一种基于物联网的电梯运行故障监测方法，包括如下步骤：Referring to FIG. 1 , the present invention provides an elevator operation fault monitoring method based on the Internet of Things, comprising the following steps:
通过振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集电梯电机运行时的各项参数数据，包括电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度、轴承温度的历史数据和实时数据。Vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors are used to collect various parameter data of elevator motor operation, including historical and real-time data of motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature.
通过物联网网关将振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集到的上述数据传输到物联网平台。The above data collected by the vibration sensor, noise sensor, thermocouple sensor, infrared temperature sensor and embedded temperature sensor are transmitted to the IoT platform through the IoT gateway.
调取电梯历史数据，通过历史振动频率、振动幅值和噪音强度数据建立历史轴承系数Cz，利用熵权法进行各参数的权重计算，首先对历史振动频率、振动幅值和噪音强度数据进行标准化处理，得到 、 和，计算每个标准化后的参数的权重比例，公式如下所示：Retrieve elevator historical data and use historical vibration frequency , vibration amplitude and noise intensity The historical bearing coefficient Cz is established based on the data, and the entropy weight method is used to calculate the weight of each parameter. First, the historical vibration frequency , vibration amplitude and noise intensity The data is standardized to obtain , and , calculate the weight ratio of each standardized parameter, the formula is as follows:
其中，i表示第i个数据的索引，i=1、2、3…、n，分别为历史振动频率、振动幅值和噪声强度的权重比例。Where i represents the index of the i- th data, i = 1, 2, 3…, n , are the weight proportions of historical vibration frequency, vibration amplitude and noise intensity respectively.
通过每个标准化后的参数的权重比例，再计算各参数的信息熵，公式如下所示：The information entropy of each parameter is calculated by the weight ratio of each standardized parameter. The formula is as follows:
其中，、和表示历史振动频率、振动幅值和噪声强度的信息熵，用来衡量每个参数的不确定性，根据信息熵计算每个参数的权重，公式如下所示：in, , and The information entropy representing the historical vibration frequency, vibration amplitude and noise intensity is used to measure the uncertainty of each parameter. The weight of each parameter is calculated based on the information entropy. The formula is as follows:
其中，、和分别表示历史振动频率、振动幅值和噪声强度的信息熵的互信息量。in, , and The mutual information of the information entropy representing the historical vibration frequency, vibration amplitude and noise intensity respectively.
根据历史振动频率、振动幅值和噪声强度的权重、和，建立历史轴承系数Cz，公式如下所示：According to the weight of historical vibration frequency, vibration amplitude and noise intensity , and , establish the historical bearing coefficient Cz , the formula is as follows:
+ +
其中，n表示样本的总数量，、和分别为历史振动频率、振动幅值和噪音强度数据的权重。Where n represents the total number of samples. , and are the weights of historical vibration frequency, vibration amplitude and noise intensity data respectively.
通过历史绕组温度、机壳温度和轴承温度数据建立电机温升系数，利用熵权法进行电机温升系数的权重计算，首先对历史绕组温度、机壳温度和轴承温度数据进行标准化处理，得到、和，计算每个标准化后的参数的权重比例P ，再计算各参数的信息熵、和，根据信息熵计算各参数的权重和，利用各参数权重计算电机温升系数Mz，公式如下所示：Through the historical winding temperature , Case temperature and bearing temperature Data to establish the motor temperature rise coefficient , the entropy weight method is used to calculate the weight of the motor temperature rise coefficient. First, the historical winding temperature , Case temperature and bearing temperature The data is standardized to obtain , and , calculate the weight ratio P of each standardized parameter , and then calculate the information entropy of each parameter , and , calculate the weight of each parameter according to information entropy and , use the weights of each parameter to calculate the motor temperature rise coefficient Mz , the formula is as follows:
+ +
其中，、和为历史绕组温度、机壳温度和轴承温度数据的权重。in, , and is the weight of the historical winding temperature, casing temperature and bearing temperature data.
利用历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez，公式如下所示：The historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz are used to establish the historical comprehensive coefficient Ez . The formula is as follows:
Ez= Cz+ Mz Ez= Cz+ Mz
其中，b和c为历史轴承系数Cz和历史电机温升系数Mz的所占比例系数，b为0.5，c为0.5，利用均值加减标准差法计算历史综合系数Ez的阈值r，公式如下所示：Among them, b and c are the proportion coefficients of the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz , b is 0.5, c is 0.5, and the threshold r of the historical comprehensive coefficient Ez is calculated using the mean plus minus standard deviation method. The formula is as follows:
其中，为综合系数的均值，为综合系数的标准差，根据标准差定义阈值r的范围，公式如下所示：in, is the mean of the comprehensive coefficients, is the standard deviation of the comprehensive coefficient, according to the standard deviation Define the range of the threshold r , the formula is as follows:
其中，k为误差容忍偏差，k=1、2、3。Where k is the error tolerance deviation, k = 1, 2, 3.
通过实时振动频率、振动幅值和噪音强度数据建立实时轴承系数Ct，公式如下所示：Through real-time vibration frequency , vibration amplitude and noise intensity The data establishes the real-time bearing coefficient Ct , and the formula is as follows:
通过实时绕组温度、机壳温度和轴承温度数据建立电机温升系数，公式如下所示：Real-time winding temperature , Case temperature and bearing temperature Data to establish the motor temperature rise coefficient , the formula is as follows:
其中，为实时电机温升系数，利用实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et，公式如下所示：in, is the real-time motor temperature rise coefficient. The real-time comprehensive coefficient Et is established using the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt. The formula is as follows:
Et= Ct+ Mt Et= Ct+ Mt
其中，Et为实时综合系数。Among them, Et is the real-time comprehensive coefficient.
通过实时监测电梯电机运行的综合系数，查看实时综合系数是否在安全阈值范围内，并采取不同的调节策略，具体为：By monitoring the comprehensive coefficient of the elevator motor operation in real time, check whether the real-time comprehensive coefficient is within the safety threshold range, and adopt different adjustment strategies, specifically:
当实时综合系数Et小于阈值r时，系统发出二级预警信号，反馈当前电梯电机运行具有轻度故障；When the real-time comprehensive coefficient Et is less than the threshold value r , the system issues a secondary warning signal, indicating that the current elevator motor operation has a minor fault;
当实时综合系数Et处于阈值r范围时，系统不发出预警信号，反馈当前电梯电机运行情况良好，不会造成安全隐患；When the real-time comprehensive coefficient Et is within the threshold r range, the system does not issue a warning signal, and feedback is given that the current elevator motor is operating well and will not cause safety hazards;
当实时综合系数Et大于阈值r时，系统发出一级预警信号，反馈当前电梯电机运行具有重度故障，停止运行。When the real-time comprehensive coefficient Et is greater than the threshold value r , the system sends out a first-level warning signal, feedback that the current elevator motor operation has a serious fault and stops running.
请参阅图2，本发明提供一种基于物联网的电梯运行故障监测系统，包括：Please refer to FIG. 2 , the present invention provides an elevator operation fault monitoring system based on the Internet of Things, comprising:
数据采集模块，通过振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集电梯电机运行时的各项参数数据，包括电机振动频率、振动幅值、噪音强度、绕组温度、机壳温度和轴承温度的实时数据。The data acquisition module collects various parameter data of the elevator motor during operation through vibration sensors, noise sensors, thermocouple sensors, infrared temperature sensors and embedded temperature sensors, including real-time data of motor vibration frequency, vibration amplitude, noise intensity, winding temperature, casing temperature and bearing temperature.
物联网传输模块，通过物联网网关将振动传感器、噪声传感器、热电偶传感器、红外温度传感器和嵌入式温度传感器采集到的上述数据传输到物联网平台。The IoT transmission module transmits the above data collected by the vibration sensor, noise sensor, thermocouple sensor, infrared temperature sensor and embedded temperature sensor to the IoT platform through the IoT gateway.
运行模块，将电梯电机运行数据经异常值和归一化处理后，利用历史振动频率、振动幅值和噪音强度建立历史轴承系数Cz；利用历史绕组温度、机壳温度、轴承温度建立历史电机温升系数Mz数据；通过历史轴承系数Cz和历史电机温升系数Mz建立历史综合系数Ez；利用实时振动频率、振动幅值和噪音强度建立实时轴承系数Ct；利用实时绕组温度、机壳温度、轴承温度建立实时电机温升系数Mt数据；通过实时轴承系数Ct和实时电机温升系数Mt建立实时综合系数Et；并通过均值加减标准差法来计算实时综合系数Et的阈值r。The operation module processes the elevator motor operation data through abnormal value and normalization, and then uses the historical vibration frequency, vibration amplitude and noise intensity to establish the historical bearing coefficient Cz ; uses the historical winding temperature, casing temperature and bearing temperature to establish the historical motor temperature rise coefficient Mz data; establishes the historical comprehensive coefficient Ez through the historical bearing coefficient Cz and the historical motor temperature rise coefficient Mz ; establishes the real-time bearing coefficient Ct through the real-time vibration frequency, vibration amplitude and noise intensity; establishes the real-time motor temperature rise coefficient Mt data through the real-time winding temperature, casing temperature and bearing temperature; establishes the real-time comprehensive coefficient Et through the real-time bearing coefficient Ct and the real-time motor temperature rise coefficient Mt ; and calculates the threshold r of the real-time comprehensive coefficient Et through the mean plus and minus standard deviation method.
管理模块，通过实时监测电梯电机综合系数Et，根据实时数据状态选择对应的预警处理策略。The management module monitors the comprehensive coefficient Et of the elevator motor in real time and selects the corresponding early warning processing strategy according to the real-time data status.
上述实施例，可以全部或部分地通过软件、硬件、固件或其他任意组合来实现。当使用软件实现时，上述实施例可以全部或部分地以计算机程序产品的形式实现。本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.
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| CN115159285A (en) * | 2022-07-01 | 2022-10-11 | 重庆大学 | Elevator state monitoring method and elevator state monitoring device |
| CN118255227A (en) * | 2024-04-28 | 2024-06-28 | 山东浪潮超高清视频产业有限公司 | Elevator state early warning system based on sensor data acquisition and AI algorithm |
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