CN113511572A - Elevator maintenance quality evaluation method and system based on big data and storage medium - Google Patents

Elevator maintenance quality evaluation method and system based on big data and storage medium Download PDF

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CN113511572A
CN113511572A CN202110608622.2A CN202110608622A CN113511572A CN 113511572 A CN113511572 A CN 113511572A CN 202110608622 A CN202110608622 A CN 202110608622A CN 113511572 A CN113511572 A CN 113511572A
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张巍
李刚
林创鲁
欧阳徕
葛友明
叶亮
李丽宁
罗永通
莫绍孟
劳伟文
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Guangzhou Special Equipment Testing And Research Institute Guangzhou Special Equipment Accident Investigation Technology Center Guangzhou Elevator Safety Operation Monitoring Center
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
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    • B66B5/0031Devices monitoring the operating condition of the elevator system for safety reasons
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
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Abstract

本申请公开了一种基于大数据的电梯维保质量评价方法、系统和存储介质,所述方法根据维保电梯故障控制效率数据、维保电梯故障处置效率数据、维保维护质量管控数据、维保客户满意度数据、维保电梯物联网监测能力数据、统计电梯故障控制效率数据、统计电梯故障处置效率数据、统计维护质量管控数据、统计客户满意度数据和统计电梯物联网监测能力数据计算待测维保单位的维保质量评价分数。本申请实施例计算待测维保单位的维保数据和所有维保单位的统计数据,根据维保数据和统计数据计算待测维保单位的维保质量评价分数,本申请采用统计数据代替阈值,提高了维保质量评价分数计算的准确性。本申请可广泛应用于电梯安全技术领域中。

Figure 202110608622

The present application discloses a big data-based elevator maintenance quality evaluation method, system and storage medium. The method is based on maintenance elevator fault control efficiency data, maintenance elevator fault handling efficiency data, maintenance quality control data, maintenance Guarantee customer satisfaction data, maintenance elevator IoT monitoring capability data, statistical elevator fault control efficiency data, statistical elevator fault handling efficiency data, statistical maintenance quality control data, statistical customer satisfaction data and statistical elevator IoT monitoring capability data to be calculated. Measure the maintenance quality evaluation score of the maintenance unit. The embodiment of the present application calculates the maintenance data of the maintenance unit to be tested and the statistical data of all the maintenance units, and calculates the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance data and the statistical data. In this application, the statistical data is used to replace the threshold value , which improves the accuracy of the calculation of the maintenance quality evaluation score. The present application can be widely used in the field of elevator safety technology.

Figure 202110608622

Description

基于大数据的电梯维保质量评价方法、系统和存储介质Elevator maintenance quality evaluation method, system and storage medium based on big data

技术领域technical field

本申请涉及电梯安全技术领域,尤其涉及一种基于大数据的电梯维保质量评价方法、系统和存储介质。The present application relates to the technical field of elevator safety, and in particular, to a method, system and storage medium for evaluating elevator maintenance quality based on big data.

背景技术Background technique

目前对电梯维护保养实行的是《特种设备安全监察条例》规定的“电梯应当至少每15日进行一次清洁、润滑、调整和检查。”这种规定的目的在于保障电梯能够得到最基本的维护保养,但是难以适应不同质量水平或不同使用环境的电梯。电梯作为损耗型设备,根据电梯性能的衰减规律,可以将电梯设备分为早发故障期、偶发故障期和故障损耗期。当电梯进入损耗期时,设备的故障率逐渐上升,性能呈逐渐下降的趋势,此阶段的预防性维保是十分重要的。随着时间的累积,若仍旧对电梯每15天进行一次预防性维保,会增大出现电梯安全事故的风险,即在预防性维保时间点之就有可能出现重大安全事故;另外,当电梯刚刚进入损耗期时,电梯设备的磨损还不太严重,根据相关经验,可以在大于15天的间隔内进行预防性维保,以此降低维保成本。The current implementation of elevator maintenance is the "Special Equipment Safety Supervision Regulations" stipulated that "elevators should be cleaned, lubricated, adjusted and inspected at least once every 15 days." The purpose of this regulation is to ensure that elevators can receive the most basic maintenance. , but it is difficult to adapt to elevators with different quality levels or different usage environments. As a loss-type equipment, elevator equipment can be divided into early failure period, occasional failure period and failure loss period according to the attenuation law of elevator performance. When the elevator enters the wear and tear period, the failure rate of the equipment gradually increases, and the performance gradually declines. Preventive maintenance at this stage is very important. With the accumulation of time, if preventive maintenance is still carried out on the elevator every 15 days, the risk of elevator safety accidents will increase, that is, major safety accidents may occur before the preventive maintenance time point; When the elevator has just entered the wear and tear period, the wear and tear of the elevator equipment is not too serious. According to relevant experience, preventive maintenance can be carried out within an interval of more than 15 days to reduce the maintenance cost.

“按需”维保就是结合每一台电梯的实际状态制定维修保养的计划,实施有针对性、有实效的维修保养。电梯的实际状态包括该台电梯的实际使用年限、运行状况、维修记录、部件磨损现状、使用环境、管理质量等。“物联网+维保”的按需维保模式,通过电梯远程监测技术手段,实现物联网线上检查维护和现场保养维护相结合的按需维保模式,使电梯维保行业越来越向着人性化、科技化方向发展。如何在新模式下对电梯的维护保养质量进行监管,引发乘客、使用单位和市场监管部门的广泛关注。"On-demand" maintenance is to formulate maintenance plans based on the actual status of each elevator, and implement targeted and effective maintenance. The actual status of the elevator includes the actual service life of the elevator, operation status, maintenance records, component wear status, use environment, management quality, etc. The on-demand maintenance mode of "Internet of Things + Maintenance" realizes the on-demand maintenance mode combining online inspection and maintenance of the Internet of Things and on-site maintenance and maintenance through the technical means of elevator remote monitoring, making the elevator maintenance industry more and more oriented towards Humanization and technology development. How to supervise the maintenance quality of elevators in the new mode has attracted extensive attention from passengers, user units and market supervision departments.

随着电梯智慧监管平台的逐步建设,电梯相关数据的收集和分析利用成为可能,目前对于电梯维保质量的评价一般基于单个电梯的维保数据,并基于阈值进行评价,这种评价方式需要人为设置阈值,导致现有的电梯维保质量评价不够准确。With the gradual construction of the elevator intelligent supervision platform, the collection, analysis and utilization of elevator-related data becomes possible. At present, the evaluation of elevator maintenance quality is generally based on the maintenance data of a single elevator and based on thresholds. This evaluation method requires artificial Setting the threshold makes the existing elevator maintenance quality evaluation inaccurate.

发明内容SUMMARY OF THE INVENTION

有鉴于此,本申请的目的是提供一种基于大数据的电梯维保质量评价方法、系统和存储介质,以提高电梯维保质量评价的准确性。In view of this, the purpose of this application is to provide a method, system and storage medium for elevator maintenance quality evaluation based on big data, so as to improve the accuracy of elevator maintenance quality evaluation.

本申请所采用的第一技术方案是:The first technical solution adopted in this application is:

一种基于大数据的电梯维保质量评价方法,包括:A method for evaluating elevator maintenance quality based on big data, comprising:

采集待测维保单位的维保电梯故障数据、维保电梯故障处置数据、维保维护质量数据、维保客户评价数据和维保电梯物联网功能情况数据;Collect maintenance elevator fault data, maintenance elevator fault handling data, maintenance quality data, maintenance customer evaluation data and maintenance elevator IoT function data of the maintenance unit to be tested;

采集所有维保单位的统计电梯故障数据、统计电梯故障处置数据、统计维护质量数据、统计客户评价数据和统计电梯物联网功能情况数据;Collect statistical elevator fault data, statistical elevator fault disposal data, statistical maintenance quality data, statistical customer evaluation data and statistical elevator IoT function data of all maintenance units;

根据所述维保电梯故障数据计算维保电梯故障控制效率数据;Calculate maintenance elevator fault control efficiency data according to the maintenance elevator fault data;

根据所述维保电梯故障处置数据计算维保电梯故障处置效率数据;Calculate maintenance elevator fault disposal efficiency data according to the maintenance elevator fault disposal data;

根据所述维保维护质量数据计算维保维护质量管控数据;Calculate maintenance quality control data according to the maintenance quality data;

根据所述维保客户评价数据计算维保客户满意度数据;Calculate maintenance customer satisfaction data according to the maintenance customer evaluation data;

根据所述维保电梯物联网功能情况数据计算维保电梯物联网监测能力数据;Calculate the monitoring capability data of the Internet of Things for the maintenance elevator according to the data on the Internet of Things function of the maintenance elevator;

根据所述统计电梯故障数据计算统计电梯故障控制效率数据;Calculate statistical elevator fault control efficiency data according to the statistical elevator fault data;

根据所述统计故障处置数据计算统计电梯故障处置效率数据;Calculate statistical elevator fault disposal efficiency data according to the statistical fault disposal data;

根据所述统计维护质量数据计算统计维护质量管控数据;Calculate statistical maintenance quality control data according to the statistical maintenance quality data;

根据所述统计客户评价数据计算统计客户满意度数据;Calculate statistical customer satisfaction data according to the statistical customer evaluation data;

根据所述统计电梯物联网功能情况数据计算统计电梯物联网监测能力数据;Calculate and count the monitoring capability data of the Internet of Things for the elevator according to the statistical data of the Internet of Things function of the elevator;

根据所述维保电梯故障控制效率数据、所述维保电梯故障处置效率数据、所述维保维护质量管控数据、所述维保客户满意度数据、所述维保电梯物联网监测能力数据、所述统计电梯故障控制效率数据、所述统计电梯故障处置效率数据、所述统计维护质量管控数据、所述统计客户满意度数据和所述统计电梯物联网监测能力数据计算所述待测维保单位的维保质量评价分数。According to the maintenance elevator fault control efficiency data, the maintenance elevator fault handling efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator IoT monitoring capability data, The statistical elevator fault control efficiency data, the statistical elevator fault handling efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data, and the statistical elevator IoT monitoring capability data are used to calculate the maintenance and maintenance to be tested. The maintenance quality evaluation score of the unit.

进一步,所述根据所述维保电梯故障控制效率数据、所述维保电梯故障处置效率数据、所述维保维护质量管控数据、所述维保客户满意度数据、所述维保电梯物联网监测能力数据、所述统计电梯故障控制效率数据、所述统计电梯故障处置效率数据、所述统计维护质量管控数据、所述统计客户满意度数据和所述统计电梯物联网监测能力数据计算所述待测维保单位的维保质量评价分数这一步骤,具体包括:Further, according to the maintenance elevator fault control efficiency data, the maintenance elevator fault handling efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator Internet of Things Monitoring capability data, the statistical elevator fault control efficiency data, the statistical elevator fault handling efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data and the statistical elevator IoT monitoring capability data to calculate the The step of the maintenance quality evaluation score of the maintenance unit to be tested includes:

根据所述维保电梯故障控制效率数据和所述统计电梯故障控制效率数据计算维保电梯故障控制效率指数;Calculate the maintenance elevator fault control efficiency index according to the maintenance elevator fault control efficiency data and the statistical elevator fault control efficiency data;

根据所述维保电梯故障处置效率数据和所述统计电梯故障处置效率数据计算维保电梯故障处置效率指数;Calculate the maintenance elevator fault disposal efficiency index according to the maintenance elevator fault disposal efficiency data and the statistical elevator fault disposal efficiency data;

根据所述维保维护质量管控数据和所述统计维护质量管控数据计算维保质量管控指数;Calculate the maintenance quality control index according to the maintenance quality control data and the statistical maintenance quality control data;

根据所述维保客户满意度数据和所述统计客户满意度数据计算维保客户满意度指数;Calculate the maintenance customer satisfaction index according to the maintenance customer satisfaction data and the statistical customer satisfaction data;

根据所述维保电梯物联网监测能力数据和所述统计电梯物联网监测能力数据计算维保电梯物联网监测能力指数;Calculate the maintenance elevator IoT monitoring capability index according to the maintenance elevator IoT monitoring capability data and the statistical elevator IoT monitoring capability data;

根据所述维保电梯故障控制效率指数、所述维保电梯故障处置效率指数、所述维保质量管控指数、所述维保客户满意度指数和所述维保电梯物联网监测能力指数计算所述待测维保单位的维保质量评价分数。According to the maintenance elevator fault control efficiency index, the maintenance elevator fault handling efficiency index, the maintenance quality control index, the maintenance customer satisfaction index and the maintenance elevator Internet of Things monitoring capability index The maintenance quality evaluation score of the maintenance unit to be tested.

进一步,所述根据所述维保电梯故障控制效率指数、所述维保电梯故障处置效率指数、所述维保质量管控指数、所述维保客户满意度指数和所述维保电梯物联网监测能力指数计算所述待测维保单位的维保质量评价分数这一步骤,具体包括:Further, according to the maintenance elevator fault control efficiency index, the maintenance elevator fault handling efficiency index, the maintenance quality control index, the maintenance customer satisfaction index and the maintenance elevator Internet of Things monitoring The step of calculating the maintenance quality evaluation score of the maintenance unit to be tested by the capability index specifically includes:

获取维保电梯故障控制效率权重向量、维保电梯故障处置效率权重向量、维保质量管控权重向量、维保客户满意度权重向量和维保电梯物联网监测能力权重向量;Obtain the weight vector of maintenance elevator fault control efficiency, maintenance elevator fault handling efficiency weight vector, maintenance quality control weight vector, maintenance customer satisfaction weight vector and maintenance elevator IoT monitoring capability weight vector;

根据所述维保电梯故障控制效率指数、所述维保电梯故障处置效率指数、所述维保质量管控指数、所述维保客户满意度指数、所述维保电梯物联网监测能力指数、所述维保电梯故障控制效率权重向量、所述维保电梯故障处置效率权重向量、所述维保质量管控权重向量、所述维保客户满意度权重向量和所述维保电梯物联网监测能力权重向量计算所述待测维保单位的维保质量评价分数。According to the maintenance elevator fault control efficiency index, the maintenance elevator fault handling efficiency index, the maintenance quality control index, the maintenance customer satisfaction index, the maintenance elevator Internet of Things monitoring capability index, the The maintenance elevator fault control efficiency weight vector, the maintenance elevator fault handling efficiency weight vector, the maintenance quality control weight vector, the maintenance customer satisfaction weight vector, and the maintenance elevator IoT monitoring capability weight The vector calculates the maintenance quality evaluation score of the maintenance unit to be tested.

进一步,所述维保电梯故障率指数的计算公式如下:Further, the calculation formula of the maintenance elevator failure rate index is as follows:

Figure BDA0003095083050000031
Figure BDA0003095083050000031

其中,g1为维保电梯故障率指数,Pfi为维保电梯故障率,

Figure BDA0003095083050000032
为统计电梯故障率。Among them, g 1 is the maintenance elevator failure rate index, P fi is the maintenance elevator failure rate,
Figure BDA0003095083050000032
For the statistics of elevator failure rate.

进一步,所述基于大数据的电梯维保质量评价方法还包括:Further, the elevator maintenance quality evaluation method based on big data also includes:

当所述维保质量评价分数小于预设分数阈值,生成维保质量警报信息。When the maintenance quality evaluation score is less than a preset score threshold, a maintenance quality alarm message is generated.

进一步,所述维保电梯困人救援及时率的计算公式如下:Further, the formula for calculating the timely rate of rescue of trapped persons in the maintenance elevator is as follows:

PRi=TRi/TRmax P Ri =T Ri /T Rmax

其中,PRi为维保电梯困人救援及时率,TRi为维保电梯困人救援响应时间,TRmax为维保电梯困人救援允许最大响应时间。Among them, P Ri is the rescue timely rate of the maintenance elevator trapped person, T Ri is the response time of the maintenance elevator trapped person rescue, and T Rmax is the maximum allowable response time of the maintenance elevator trapped person rescue.

进一步,所述基于大数据的电梯维保质量评价方法还包括:Further, the elevator maintenance quality evaluation method based on big data also includes:

计算所有维保单位的维保质量评价分数平均值和维保质量评价分数标准差;Calculate the average value of the maintenance quality evaluation score and the standard deviation of the maintenance quality evaluation score of all maintenance units;

根据所述维保质量评价分数、所述维保质量评价分数平均值和所述维保质量评价分数标准差计算维保质量评价分数标准值;Calculate the standard value of the maintenance quality evaluation score according to the maintenance quality evaluation score, the average value of the maintenance quality evaluation score, and the standard deviation of the maintenance quality evaluation score;

所述维保质量评价分数标准值的计算公式如下:The calculation formula of the standard value of the maintenance quality evaluation score is as follows:

Figure BDA0003095083050000041
Figure BDA0003095083050000041

其中,Szy为维保质量评价分数标准值,z和Z为常数,Sy为维保质量评价分数,

Figure BDA0003095083050000042
为维保质量评价分数平均值,Sσ为维保质量评价分数标准差。Among them, Szy is the standard value of the maintenance quality evaluation score, z and Z are constants, S y is the maintenance quality evaluation score,
Figure BDA0003095083050000042
is the mean value of the maintenance quality evaluation score, and S σ is the standard deviation of the maintenance quality evaluation score.

本申请所采用的第二技术方案是:The second technical solution adopted in this application is:

一种基于大数据的电梯维保质量评价系统,包括:An elevator maintenance quality evaluation system based on big data, including:

采集模块,用于采集待测维保单位的维保电梯故障数据、维保电梯故障处置数据、维保维护质量数据、维保客户评价数据和维保电梯物联网功能情况数据;采集所有维保单位的统计电梯故障数据、统计电梯故障处置数据、统计维护质量数据、统计客户评价数据和统计电梯物联网功能情况数据;The acquisition module is used to collect the maintenance elevator fault data, maintenance elevator fault disposal data, maintenance quality data, maintenance customer evaluation data and maintenance elevator IoT function data of the maintenance unit to be tested; The unit's statistical elevator fault data, statistical elevator fault disposal data, statistical maintenance quality data, statistical customer evaluation data and statistical elevator Internet of Things function data;

计算模块,用于根据所述维保电梯故障数据计算维保电梯故障控制效率数据;根据所述维保电梯故障处置数据计算维保电梯故障处置效率数据;根据所述维保维护质量数据计算维保维护质量管控数据;根据所述维保客户评价数据计算维保客户满意度数据;根据所述维保电梯物联网功能情况数据计算维保电梯物联网监测能力数据;根据所述统计电梯故障数据计算统计电梯故障控制效率数据;根据所述统计故障处置数据计算统计电梯故障处置效率数据;根据所述统计维护质量数据计算统计维护质量管控数据;根据所述统计客户评价数据计算统计客户满意度数据;根据所述统计电梯物联网功能情况数据计算统计电梯物联网监测能力数据;The calculation module is used for calculating maintenance elevator fault control efficiency data according to the maintenance elevator fault data; calculating maintenance elevator fault handling efficiency data according to the maintenance elevator fault handling data; calculating maintenance elevator fault handling efficiency data according to the maintenance quality data. Maintenance quality control data; maintenance customer satisfaction data is calculated according to the maintenance customer evaluation data; maintenance elevator Internet of Things monitoring capability data is calculated according to the maintenance elevator Internet of Things function data; maintenance elevator Internet of Things monitoring capability data; according to the statistical elevator fault data Calculate statistical elevator fault control efficiency data; calculate statistical elevator fault disposal efficiency data according to the statistical fault disposal data; calculate statistical maintenance quality control data according to the statistical maintenance quality data; calculate statistical customer satisfaction data according to the statistical customer evaluation data ; Calculate and count the monitoring capability data of the Internet of Things for elevators according to the statistical data on the functions of the Internet of Things in elevators;

评价模块,用于根据所述维保电梯故障控制效率数据、所述维保电梯故障处置效率数据、所述维保维护质量管控数据、所述维保客户满意度数据、所述维保电梯物联网监测能力数据、所述统计电梯故障控制效率数据、所述统计电梯故障处置效率数据、所述统计维护质量管控数据、所述统计客户满意度数据和所述统计电梯物联网监测能力数据计算所述待测维保单位的维保质量评价分数。The evaluation module is configured to, according to the maintenance elevator fault control efficiency data, the maintenance elevator fault handling efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator object Network monitoring capability data, the statistical elevator fault control efficiency data, the statistical elevator fault handling efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data, and the statistical elevator IoT monitoring capability data calculation institute The maintenance quality evaluation score of the maintenance unit to be tested.

本申请所采用的第三技术方案是:The third technical solution adopted in this application is:

一种基于大数据的电梯维保质量评价系统,包括:An elevator maintenance quality evaluation system based on big data, including:

至少一个处理器;at least one processor;

至少一个存储器,用于存储至少一个程序;at least one memory for storing at least one program;

当所述至少一个程序被所述至少一个处理器执行,使得所述至少一个处理器实现所述的方法。The at least one program, when executed by the at least one processor, causes the at least one processor to implement the method.

本申请所采用的第四技术方案是:The fourth technical solution adopted in this application is:

一种计算机可读存储介质,其上存储有计算机程序,所述计算机程序被处理器执行时实现所述的方法。A computer-readable storage medium having a computer program stored thereon, the computer program implementing the method when executed by a processor.

本申请实施例通过计算待测维保单位的维保数据和所有维保单位的统计数据,根据维保数据和统计数据计算待测维保单位的维保质量评价分数,相较于现有的阈值评价方法,本申请采用统计数据代替阈值,提高了维保质量评价分数计算的准确性。The embodiment of the present application calculates the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance data and statistical data by calculating the maintenance data of the maintenance unit to be tested and the statistical data of all maintenance units. For the threshold evaluation method, the present application uses statistical data to replace the threshold, which improves the accuracy of the calculation of the maintenance quality evaluation score.

附图说明Description of drawings

图1为本申请实施例基于大数据的电梯维保质量评价方法的流程图。FIG. 1 is a flowchart of an elevator maintenance quality evaluation method based on big data according to an embodiment of the present application.

具体实施方式Detailed ways

以下将结合实施例和附图对本申请的构思、具体结构及产生的技术效果进行清楚、完整的描述,以充分地理解本申请的目的、方案和效果。The concept, specific structure and technical effects of the present application will be clearly and completely described below with reference to the embodiments and accompanying drawings, so as to fully understand the purpose, solutions and effects of the present application.

下面结合附图和具体实施例对本申请做进一步的详细说明。对于以下实施例中的步骤编号,其仅为了便于阐述说明而设置,对步骤之间的顺序不做任何限定,实施例中的各步骤的执行顺序均可根据本领域技术人员的理解来进行适应性调整。此外,对于以下实施例中所述的若干个,其表示为至少一个。The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. The numbers of the steps in the following embodiments are only set for the convenience of description, and the sequence between the steps is not limited in any way, and the execution sequence of each step in the embodiments can be adapted according to the understanding of those skilled in the art Sexual adjustment. In addition, for several described in the following embodiments, it is expressed as at least one.

在本公开中所使用的单数形式的“一种”、“所述”和“该”也旨在包括多数形式,除非上下文清楚地表示其他含义。此外,除非另有定义,本文所使用的所有的技术和科学术语与本技术领域的技术人员通常理解的含义相同。本文说明书中所使用的术语只是为了描述具体的实施例,而不是为了限制本申请。本文所使用的术语“和/或”包括一个或多个相关的所列项目的任意的组合。As used in this disclosure, the singular forms "a," "the," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. Also, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. The terms used in the specification herein are for the purpose of describing specific embodiments only, and not for the purpose of limiting the application. As used herein, the term "and/or" includes any combination of one or more of the associated listed items.

本申请中监测平台收集一定周期内、一定范围内的电梯物联网、维护保养、检验检测、应急处置和用户投诉等事件数据和统计数据,提取和计算电梯运行质量评价指标,分别从电梯故障控制效率、电梯故障处置效率、维保质量管控、客户评价和电梯物联网监测能力五个维度评价电梯维保质量水平。本申请建立了电梯维保质量评价指标体系,采用多目标效应综合评价方法,建立电梯维保质量评价模型,以实现大数据驱动的电梯维保质量评价。In this application, the monitoring platform collects event data and statistical data such as elevator Internet of Things, maintenance, inspection and testing, emergency response, and user complaints within a certain period and within a certain range, extracts and calculates elevator operation quality evaluation indicators, and separates elevator fault control from elevator fault control. Elevator maintenance quality is evaluated from five dimensions: efficiency, elevator fault handling efficiency, maintenance quality control, customer evaluation and elevator IoT monitoring capabilities. This application establishes an elevator maintenance quality evaluation index system, adopts a multi-objective effect comprehensive evaluation method, and establishes an elevator maintenance quality evaluation model, so as to realize the elevator maintenance quality evaluation driven by big data.

如图1所示,本申请实施例提供了一种基于大数据的电梯维保质量评价方法,包括:As shown in FIG. 1 , an embodiment of the present application provides a big data-based elevator maintenance quality evaluation method, including:

S100、采集待测维保单位的维保电梯故障数据、维保电梯故障处置数据、维保维护质量数据、维保客户评价数据和维保电梯物联网功能情况数据;采集所有维保单位的统计电梯故障数据、统计电梯故障处置数据、统计维护质量数据、统计客户评价数据和统计电梯物联网功能情况数据;S100. Collect maintenance elevator fault data, maintenance elevator fault handling data, maintenance quality data, maintenance customer evaluation data, and maintenance elevator IoT function data of the maintenance unit to be tested; collect statistics of all maintenance units Elevator fault data, statistical elevator fault disposal data, statistical maintenance quality data, statistical customer evaluation data and statistical elevator IoT function data;

S200、根据所述维保电梯故障数据计算维保电梯故障控制效率数据;根据所述维保电梯故障处置数据计算维保电梯故障处置效率数据;根据所述维保维护质量数据计算维保维护质量管控数据;根据所述维保客户评价数据计算维保客户满意度数据;根据所述维保电梯物联网功能情况数据计算维保电梯物联网监测能力数据;根据所述统计电梯故障数据计算统计电梯故障控制效率数据;根据所述统计故障处置数据计算统计电梯故障处置效率数据;根据所述统计维护质量数据计算统计维护质量管控数据;根据所述统计客户评价数据计算统计客户满意度数据;根据所述统计电梯物联网功能情况数据计算统计电梯物联网监测能力数据;S200. Calculate maintenance elevator fault control efficiency data according to the maintenance elevator fault data; calculate maintenance elevator fault handling efficiency data according to the maintenance elevator fault handling data; calculate maintenance quality according to the maintenance and maintenance quality data Management and control data; calculation of customer satisfaction data according to the maintenance customer evaluation data; calculation of the maintenance elevator Internet of Things monitoring capability data according to the maintenance elevator Internet of Things function data; calculation of the statistical elevator according to the statistical elevator fault data fault control efficiency data; calculate statistical elevator fault disposal efficiency data according to the statistical fault disposal data; calculate statistical maintenance quality control data according to the statistical maintenance quality data; calculate statistical customer satisfaction data according to the statistical customer evaluation data; Describe the statistics of the elevator Internet of Things function data, calculate the statistics of the elevator Internet of Things monitoring capability data;

S300、根据所述维保电梯故障控制效率数据、所述维保电梯故障处置效率数据、所述维保维护质量管控数据、所述维保客户满意度数据、所述维保电梯物联网监测能力数据、所述统计电梯故障控制效率数据、所述统计电梯故障处置效率数据、所述统计维护质量管控数据、所述统计客户满意度数据和所述统计电梯物联网监测能力数据计算所述待测维保单位的维保质量评价分数。S300. According to the maintenance elevator fault control efficiency data, the maintenance elevator fault handling efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, and the maintenance elevator IoT monitoring capability data, the statistical elevator fault control efficiency data, the statistical elevator fault handling efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data, and the statistical elevator IoT monitoring capability data to calculate the to-be-measured data The maintenance quality evaluation score of the maintenance unit.

具体地,首先需要采集电梯监测平台统计时间段内电梯物联网、维护保养、检验检测、应急处置和用户投诉等环节的特征数据。提取的特征数据包括:电梯故障次数、电梯困人次数、电梯总运行次数、电梯故障间隔时间、电梯故障时间、电梯困人救援响应时间、电梯困人救援允许最大响应时间、电梯维护间隔时间、电梯维护最大允许间隔时间、电梯检验不合格项数、电梯总检验项数、电梯物联网功能检验不合格项数、电梯物联网功能总检验项数、电梯监督抽查不合格项数、电梯监督抽查总项数、用户投诉次数、满意度分数、电梯物联网故障预警功能分数、电梯物联网故障检测功能分数和电梯物联网预测性维护支持分数等。Specifically, it is first necessary to collect the characteristic data of the elevator Internet of Things, maintenance, inspection and testing, emergency response and user complaints during the statistical time period of the elevator monitoring platform. The extracted feature data includes: the number of elevator failures, the number of people trapped in the elevator, the total number of elevator operations, the interval between elevator failures, the time between elevator failures, the response time for rescue of the elevator trapped, the maximum allowable response time for the rescue of the elevator trapped, and the maintenance interval. The maximum allowable interval time for elevator maintenance, the number of unqualified items in elevator inspection, the total number of elevator inspection items, the number of unqualified items in elevator Internet of Things function inspection, the total number of elevator Internet of Things function inspection items, the number of unqualified items in elevator supervision and spot checks, and the number of elevator supervision and spot checks The total number of items, the number of user complaints, the satisfaction score, the elevator IoT fault warning function score, the elevator IoT fault detection function score, and the elevator IoT predictive maintenance support score, etc.

接着根据统计数据,提取统计时间段的总时间、统计时间段的总运行次数和故障事件发生前该电梯的连续正常运行次数。Then, according to the statistical data, extract the total time of the statistical time period, the total running times of the statistical time period and the continuous normal running times of the elevator before the fault event occurs.

事件的持续时间的计算公式为:The formula for calculating the duration of an event is:

TEh=TEs-TE0(E=F,P,C)T E h=T Es -T E0 (E=F,P,C)

其中,TEh为事件的持续时间,TEs为事件的解除时间,TE0为事件的发生时间。Among them, T Eh is the duration of the event, T Es is the release time of the event, and T E0 is the occurrence time of the event.

故障事件的持续时间的计算公式为:The formula for calculating the duration of the fault event is:

TFh=TFs-TF0 T F h = T Fs -T F0

其中,TFh为故障事件的持续时间,TFs为故障事件的解除时间,TF0为故障事件的发生时间。Among them, T Fh is the duration of the fault event, T Fs is the release time of the fault event, and T F0 is the occurrence time of the fault event.

第i次故障事件的持续时间的计算公式为:The formula for calculating the duration of the i-th fault event is:

TFhi=TFsi-TF0i T Fhi =T Fsi -T F0i

其中,TFhi为第i次故障事件的持续时间,TFsi为第i次故障事件的解除时间,TF0i为第i次故障事件的发生时间。Among them, TFhi is the duration of the ith fault event, TFsi is the release time of the ith fault event, and TF0i is the occurrence time of the ith fault event.

第i次困人事件的持续时间的计算公式为:The formula for calculating the duration of the i-th trapped event is:

TPhi=TPsi-TP0i T Phi =T Psi -T P0i

其中,TPhi为第i次困人事件的持续时间,TPsi为第i次困人事件的解除时间,TP0i为第i次困人事件的发生时间。Among them, T Phi is the duration of the i-th trapped event, T Psi is the release time of the i-th trapped event, and T P0i is the occurrence time of the i-th trapped event.

第i次电梯维护间隔时间的计算公式为:The formula for calculating the ith elevator maintenance interval is:

TMi=Tmi-Tmi-1 T Mi =T mi -T mi -1

其中,TMi为第i次电梯维护间隔时间,Tmi为第i次电梯维护时间,Tmi-1为第i-1次电梯维护时间。Among them, T Mi is the ith elevator maintenance interval time, T mi is the ith elevator maintenance time, and T mi-1 is the i-1 th elevator maintenance time.

电梯维护最大允许间隔时间为两次维保之间允许的最长时间,可记为TMmaxThe maximum allowable interval for elevator maintenance is the maximum time allowed between two maintenances, which can be recorded as T Mmax .

由此,第i次电梯维护及时率的计算公式为:Therefore, the formula for calculating the timely rate of the i-th elevator maintenance is:

PMi=TMi/TMmax P Mi =T Mi /T Mmax

其中,PMi为第i次电梯维护及时率。Among them, P Mi is the ith elevator maintenance timeliness rate.

电梯检验不合格项数为电梯检验不合格项的总数,可记为Ntf;电梯总检验项数为电梯检验项目总数,可记为Nt;电梯物联网功能检验不合格项数为物联网终端功能检测不合格项总数,可记为Niottf;电梯物联网功能总检验项数为物联网终端功能检测的项目总数,可记为NiottThe number of unqualified items in elevator inspection is the total number of unqualified items in elevator inspection, which can be recorded as N tf ; the total number of elevator inspection items is the total number of elevator inspection items, which can be recorded as N t ; the number of unqualified items in elevator Internet of Things function inspection is Internet of Things The total number of unqualified items in the terminal function detection can be recorded as Niottf ; the total number of inspection items for the elevator Internet of Things function is the total number of items detected by the Internet of Things terminal function, which can be recorded as Niott .

第i次电梯困人救援响应时间的计算公式为:The formula for calculating the response time of the i-th elevator trapped person rescue is:

TRi=TDi-TCi T Ri =T Di -T Ci

其中,TRi为第i次电梯困人救援响应时间,TDi为第i次电梯困人救援人员到达现场时刻,TCi为第i次电梯困人救援接警时刻。Among them, T Ri is the response time of the i-th elevator trapped person rescue, T Di is the time when the i-th elevator trapped person rescue personnel arrives at the scene, and T Ci is the alarm time of the i-th elevator trapped person rescue.

电梯困人救援允许最大响应时间为困人应急救援允许最大响应时间,可记为TRmaxThe maximum allowable response time for the rescue of trapped persons in the elevator is the maximum allowable response time for emergency rescue of trapped persons, which can be recorded as T Rmax .

第i次电梯困人救援及时率的计算公式为:The formula for calculating the timely rate of rescue trapped persons in the i-th elevator is:

PRi=TRi/TRmax P Ri =T Ri /T Rmax

其中,PRi为第i次电梯困人救援及时率。Among them, P Ri is the timely rescue rate of the i-th elevator trapped person.

用户投诉次数为在统计时间段内的投诉事件总数,可记为NcThe number of user complaints is the total number of complaint events in the statistical time period, which can be recorded as N c .

电梯总运行次数为统计时间段内电梯的总运行次数,其计算公式为:The total running times of the elevator is the total running times of the elevator in the statistical time period, and its calculation formula is:

NS=Ne-N0 N S =N e -N 0

其中,NS为电梯总运行次数,Ne为统计时间段结束时间的电梯累计运行次数,N0为统计时间段开始时间的电梯累计运行次数。Among them, N S is the total running times of the elevator, Ne is the cumulative running times of the elevator at the end time of the statistical time period, and N 0 is the cumulative running times of the elevator at the start time of the statistical time period.

第i次事件发生前电梯的连续正常运行次数Nni的计算公式为:The calculation formula of the continuous normal running times N ni of the elevator before the occurrence of the i-th event is:

Nni=N=N-N0i N ni =N =N -N 0i

其中,Nei为第i次事件的电梯累计运行次数,N0i为第i-1次事件的电梯累计运行次数。电梯总运行时间TS的计算公式为:Among them, N ei is the cumulative running times of the elevator in the ith event, and N 0i is the cumulative running times of the elevator in the i-1 th event. The formula for calculating the total running time of the elevator T S is:

TS=Te-Ts T S =T e -T s

其中,Te为统计时间段结束时间,Ts为统计时间段开始时间。Among them, T e is the end time of the statistical time period, and T s is the start time of the statistical time period.

计算得到上述特征数据后,需要建立电梯维保质量评价多目标控制模型;将提取到的特征数据进行分类,分别从电梯故障控制效率、电梯故障处置效率、维护质量管控、客户满意度和电梯物联网监测能力五个维度评价电梯维保质量水平。其中:After calculating the above characteristic data, it is necessary to establish a multi-objective control model for elevator maintenance quality evaluation; classify the extracted characteristic data, respectively from elevator fault control efficiency, elevator fault handling efficiency, maintenance quality control, customer satisfaction and elevator quality. The five dimensions of network monitoring capability evaluate the quality level of elevator maintenance. in:

A、电梯故障控制效率数据包括电梯故障率、电梯平均故障间隔时间和电梯困人率;A. Elevator failure control efficiency data includes elevator failure rate, elevator mean time between failures and elevator trapping rate;

B、电梯故障处置效率数据包括电梯故障平均时长和电梯困人救援及时率;B. Elevator fault handling efficiency data includes the average duration of elevator faults and the timely rescue rate of elevator trapped people;

C、维护质量管控数据包括维护及时率、检验不合格率、电梯物联网功能检验不合格率和电梯监督抽查不合格率;C. Maintenance quality control data includes maintenance timeliness rate, inspection failure rate, elevator IoT function inspection failure rate and elevator supervision and spot check failure rate;

D、客户满意度数据包括用户投诉率和满意度平均分数;D. Customer satisfaction data includes user complaint rate and average satisfaction score;

E、电梯物联网监测能力数据包括电梯物联网故障预警功能平均分数、电梯物联网故障检测功能平均分数和电梯物联网预测性维护支持平均分数。E. Elevator IoT monitoring capability data includes the average score of elevator IoT fault warning function, the average score of elevator IoT fault detection function, and the average score of elevator IoT predictive maintenance support.

上述特征数据的定义如下:The above characteristic data are defined as follows:

A:A:

维保电梯故障率Pfi的计算公式为:The formula for calculating the maintenance elevator failure rate P fi is:

Pfi=Nfi/NSi P fi =N fi /N Si

其中,Nfi为第i维保单位的维保电梯故障次数,NSi为第i维保单位的维保电梯总运行次数。Among them, N fi is the maintenance elevator failure times of the ith maintenance unit, and N Si is the total running times of the maintenance elevators of the ith maintenance unit.

统计电梯故障率

Figure BDA0003095083050000081
的计算公式为:Statistics of elevator failure rate
Figure BDA0003095083050000081
The calculation formula is:

Figure BDA0003095083050000082
Figure BDA0003095083050000082

其中,

Figure BDA0003095083050000083
为所有维保单位的统计电梯故障次数,
Figure BDA0003095083050000084
为所有维保单位的统计电梯总运行次数,n为维保单位的个数。in,
Figure BDA0003095083050000083
Count the number of elevator failures for all maintenance units,
Figure BDA0003095083050000084
It is the statistics of the total elevator running times of all maintenance units, and n is the number of maintenance units.

维保电梯平均故障间隔时间TFV的计算公式为:The calculation formula of the maintenance elevator mean time between failures T FV is:

Figure BDA0003095083050000091
Figure BDA0003095083050000091

其中,N为维保电梯故障次数,TFi为维保电梯第i次故障和第i-1次故障之间的间隔时间。统计电梯平均故障间隔时间

Figure BDA0003095083050000092
的计算公式为:Among them, N is the number of failures of the maintenance elevator, and T Fi is the interval time between the i-th failure and the i-1-th failure of the maintenance elevator. Statistics of elevator mean time between failures
Figure BDA0003095083050000092
The calculation formula is:

Figure BDA0003095083050000093
Figure BDA0003095083050000093

其中,S为统计时间段内所有维保单位所有电梯的故障总次数。Among them, S is the total number of failures of all elevators in all maintenance units in the statistical time period.

维保电梯困人率PKi的计算公式为:The formula for calculating the maintenance elevator trapping rate P Ki is:

PKi=NKi/NSi P Ki =N Ki /N Si

其中,NKi为维保电梯困人次数,NSi为维保电梯总运行次数。Among them, N Ki is the number of trapped people in the maintenance elevator, and N Si is the total running times of the maintenance elevator.

统计电梯困人率

Figure BDA0003095083050000094
的计算公式为:Statistics on elevator trapping rate
Figure BDA0003095083050000094
The calculation formula is:

Figure BDA0003095083050000095
Figure BDA0003095083050000095

B:B:

维保电梯故障平均时长TFUi的计算公式为:The calculation formula of the average duration of maintenance elevator failure T FUi is:

Figure BDA0003095083050000096
Figure BDA0003095083050000096

其中,Nfi为待测维保单位的维保电梯故障次数,TFhi为第i次故障事件的持续时间。统计电梯故障平均时长

Figure BDA0003095083050000097
的计算公式为:Among them, N fi is the maintenance elevator failure times of the maintenance unit to be tested, and T Fhi is the duration of the i-th fault event. Statistics on the average duration of elevator failures
Figure BDA0003095083050000097
The calculation formula is:

Figure BDA0003095083050000098
Figure BDA0003095083050000098

其中,S为统计时间段内所有维保单位所有电梯的故障总次数。Among them, S is the total number of failures of all elevators in all maintenance units in the statistical time period.

维保电梯困人救援及时率PKi的计算公式为:The formula for calculating the timely rate P Ki for rescue of trapped persons in maintenance elevators is:

Figure BDA0003095083050000099
Figure BDA0003095083050000099

其中,R为维保电梯困人次数,PRj为第j次电梯困人救援及时率。Among them, R is the number of trapped people in the maintenance elevator, and P Rj is the timely rescue rate of the j-th elevator trapped people.

统计电梯困人救援及时率

Figure BDA00030950830500000910
的计算公式为:Statistics on the timely rate of rescue of trapped people in elevators
Figure BDA00030950830500000910
The calculation formula is:

Figure BDA0003095083050000101
Figure BDA0003095083050000101

其中,K为统计时间段内所有维保单位所有电梯的困人总次数。Among them, K is the total number of trapped people in all elevators of all maintenance units during the statistical period.

C:C:

维保维护及时率PMVi的计算公式为:The formula for calculating the maintenance timely rate P MVi is:

Figure BDA0003095083050000102
Figure BDA0003095083050000102

其中,W为第i维保单位在统计时间段内的维保次数,PMj为第j次电梯维护及时率。Among them, W is the maintenance times of the ith maintenance unit in the statistical time period, and P Mj is the timely rate of the jth elevator maintenance.

统计维护及时率

Figure BDA0003095083050000103
的计算公式为:Statistical maintenance timeliness rate
Figure BDA0003095083050000103
The calculation formula is:

Figure BDA0003095083050000104
Figure BDA0003095083050000104

其中,B为所有维保单位在统计时间段内的总维保次数。Among them, B is the total maintenance times of all maintenance units in the statistical time period.

维保检验不合格率Ptf的计算公式为:The formula for calculating the failure rate of maintenance inspection P tf is:

Ptf=Ntfi/Nti P tf =N tfi /N ti

其中,Ntfi为第i维保单位的电梯检验不合格项数,Nti为第i维保单位的电梯总检验项数。Among them, N tfi is the number of unqualified elevator inspection items of the ith maintenance unit, and N ti is the total number of elevator inspection items of the ith maintenance unit.

统计检验不合格率

Figure BDA0003095083050000105
的计算公式为:Statistical test failure rate
Figure BDA0003095083050000105
The calculation formula is:

Figure BDA0003095083050000106
Figure BDA0003095083050000106

维保电梯物联网功能检验不合格率Piotf的计算公式为:The calculation formula of the failure rate Piotf of the maintenance elevator Internet of Things function inspection is:

Piotf=Niotfi/Nioti P iotf =N iotfi /N ioti

其中,Niotfi为第i维保单位的电梯物联网功能检验不合格项数,Nioti为第i维保单位的电梯物联网功能总检验项数。Among them, N iotfi is the number of unqualified items in the elevator IoT function inspection of the i-th maintenance unit, and N ioti is the total number of elevator IoT function inspection items of the i-th maintenance unit.

统计电梯物联网功能检验不合格率

Figure BDA0003095083050000107
的计算公式为:Statistics on the failure rate of elevator IoT function inspection
Figure BDA0003095083050000107
The calculation formula is:

Figure BDA0003095083050000108
Figure BDA0003095083050000108

维保电梯监督抽查不合格率Pccf的计算公式为:The formula for calculating the unqualified rate P ccf for maintenance elevator supervision and random inspection is:

Pccf=Nccfi/Ncci P ccf =N ccfi /N cci

其中,Nccfi为第i维保单位的电梯监督抽查不合格项数,Ncci为第i维保单位的电梯监督抽查总项数。Among them, N ccfi is the number of unqualified items of elevator supervision and random inspection of the ith maintenance unit, and N cci is the total number of elevator supervision and random inspection items of the ith maintenance unit.

统计电梯监督抽查不合格率

Figure BDA0003095083050000111
的计算公式为:Statistics on the failure rate of elevator supervision and spot checks
Figure BDA0003095083050000111
The calculation formula is:

Figure BDA0003095083050000112
Figure BDA0003095083050000112

D:D:

维保用户投诉率Ptsf的计算公式为:The formula for calculating the maintenance user complaint rate P tsf is:

Ptsf=Ntsi/Nsi P tsf =N tsi /N si

其中,Ntsi为第i维保单位的用户投诉次数,Nsi为第i维保单位的电梯维护总次数。Among them, N tsi is the number of user complaints of the ith maintenance unit, and N si is the total number of elevator maintenance times of the ith maintenance unit.

统计用户投诉率

Figure BDA0003095083050000113
的计算公式为:Statistics of user complaint rate
Figure BDA0003095083050000113
The calculation formula is:

Figure BDA0003095083050000114
Figure BDA0003095083050000114

维保满意度平均分数为Gi,即第i维保单位维保满意度调查分数。The average score of maintenance satisfaction is G i , that is, the maintenance satisfaction survey score of the i-th maintenance unit.

统计满意度平均分数

Figure BDA0003095083050000115
的计算公式为:Statistical Satisfaction Average Score
Figure BDA0003095083050000115
The calculation formula is:

Figure BDA0003095083050000116
Figure BDA0003095083050000116

维保电梯物联网故障预警功能平均分数为GWi,即第i维保单位的电梯物联网故障预警功能的评分。The average score of the maintenance elevator IoT fault early warning function is G Wi , which is the score of the elevator IoT fault early warning function of the i-th maintenance unit.

统计电梯物联网故障预警功能平均分数

Figure BDA0003095083050000117
的计算公式为:Statistics on the average score of elevator IoT fault warning function
Figure BDA0003095083050000117
The calculation formula is:

Figure BDA0003095083050000118
Figure BDA0003095083050000118

维保电梯物联网故障检测功能平均分数为GMi,即第i维保单位的电梯物联网检测功能的评分。The average score of the maintenance elevator IoT fault detection function is G Mi , which is the score of the elevator IoT detection function of the i-th maintenance unit.

统计电梯物联网故障检测功能平均分数

Figure BDA0003095083050000119
的计算公式为:Statistical average score of elevator IoT fault detection function
Figure BDA0003095083050000119
The calculation formula is:

Figure BDA00030950830500001110
Figure BDA00030950830500001110

维保电梯物联网预测性维护支持平均分数为GYi,即第i维保单位的电梯物联网预测性维护支持能力的评分。The average score for the predictive maintenance support of the maintenance elevator IoT is G Yi , which is the score of the predictive maintenance support capability of the elevator IoT of the i-th maintenance unit.

统计电梯物联网预测性维护支持平均分数

Figure BDA0003095083050000121
的计算公式为:Statistics Elevator IoT Predictive Maintenance Support Average Score
Figure BDA0003095083050000121
The calculation formula is:

Figure BDA0003095083050000122
Figure BDA0003095083050000122

在一些实施例中,采用专家评价方法,对电梯维保质量水平评价五个维度的权重进行评判。电梯故障控制效率、电梯故障处置效率、维护质量管控、客户满意度和电梯物联网监测能力五个维度的权重向量Q=(a1,a2,a3,a4,a5),其中

Figure BDA0003095083050000123
In some embodiments, the expert evaluation method is used to evaluate the weights of the five dimensions of the elevator maintenance quality level evaluation. The weight vector Q=(a 1 , a 2 , a 3 , a 4 , a 5 ) of the five dimensions of elevator fault control efficiency, elevator fault handling efficiency, maintenance quality control, customer satisfaction and elevator IoT monitoring capability, where
Figure BDA0003095083050000123

具体地,采用专家评价方法,对电梯故障控制效率相关的电梯故障率、电梯平均故障间隔时间和电梯困人率分配权重,得到权重向量Q1=(a11,a12,a13)。Specifically, the expert evaluation method is used to assign weights to the elevator failure rate, the elevator mean interval time between failures and the elevator occupancy rate related to the elevator fault control efficiency, and the weight vector Q 1 =(a 11 , a 12 , a 13 ) is obtained.

采用同样方法,对电梯故障处理效率相关的电梯故障平均时长和电梯困人救援及时率分配权重,得到权重向量Q2=(a21,a22)。Using the same method, weights are assigned to the elevator fault average duration and the elevator rescue timely rate related to the elevator fault handling efficiency, and the weight vector Q 2 =(a 21 , a 22 ) is obtained.

采用同样方法,对维护质量管控相关的维护及时率、检验不合格率、电梯物联网功能检验不合格率和电梯监督抽查不合格率分配权重,得到权重向量Q3=(a31,a32,a33,a34)。Using the same method, assign weights to the maintenance timeliness rate, inspection failure rate, elevator Internet of Things function inspection failure rate, and elevator supervision and random inspection failure rate related to maintenance quality control, and obtain a weight vector Q 3 =(a 31 ,a 32 , a 33 ,a 34 ).

采用同样方法,对客户满意度相关的用户投诉率和满意度平均分数分配权重,得到权重向量Q4=(a41,a42)。Using the same method, weights are assigned to the user complaint rate and the average satisfaction score related to customer satisfaction, and a weight vector Q 4 =(a 41 , a 42 ) is obtained.

采用同样方法,对电梯物联网监测能力相关的电梯物联网故障预警功能平均分数、电梯物联网故障检测功能平均分数和电梯物联网预测性维护支持平均分数分配权重,得到权重向量Q5=(a51,a52,a53)。Using the same method, the weights are assigned to the average score of the elevator IoT fault warning function, the elevator IoT fault detection function average score and the elevator IoT predictive maintenance support average score related to the monitoring capability of the elevator IoT, and the weight vector Q 5 = (a 51 ,a 52 ,a 53 ).

由于电梯故障率、电梯平均故障间隔时间和电梯困人率的数据结构并不相同,此处采用电梯故障率指数、电梯平均故障间隔时间指数和电梯困人率指数代替,其中:Since the data structures of elevator failure rate, elevator mean time between failures and elevator occupancy rate are not the same, the elevator failure rate index, elevator mean interval time index and elevator occupancy rate index are used instead, where:

电梯故障率指数g1的计算公式为:The calculation formula of the elevator failure rate index g 1 is:

Figure BDA0003095083050000124
Figure BDA0003095083050000124

电梯平均故障间隔时间指数g2的计算公式为:The calculation formula of the elevator mean time between failure index g 2 is:

Figure BDA0003095083050000125
Figure BDA0003095083050000125

电梯困人率指数g3的计算公式为:The formula for calculating the elevator trapping rate index g 3 is:

Figure BDA0003095083050000126
Figure BDA0003095083050000126

电梯故障处置效率中,采用电梯故障平均时长指数和电梯困人救援及时率指数代替。具体为:In the efficiency of elevator fault handling, the average elevator fault duration index and the elevator rescue timely rate index are used instead. Specifically:

电梯故障平均时长指数h1的计算公式为:The formula for calculating the average duration index h 1 of elevator failure is:

Figure BDA0003095083050000131
Figure BDA0003095083050000131

电梯困人救援及时率指数h2的计算公式为:The formula for calculating the timely rate index h 2 for rescue of trapped people in elevators is:

Figure BDA0003095083050000132
Figure BDA0003095083050000132

同样,维护及时率指数k1的计算公式为:Similarly, the formula for calculating the maintenance timeliness index k 1 is:

Figure BDA0003095083050000133
Figure BDA0003095083050000133

检验不合格率指数k2的计算公式为:The calculation formula of the inspection failure rate index k 2 is:

Figure BDA0003095083050000134
Figure BDA0003095083050000134

电梯物联网功能检验不合格率k3的计算公式为:The calculation formula of the failure rate k 3 of the elevator Internet of Things function inspection is:

Figure BDA0003095083050000135
Figure BDA0003095083050000135

电梯监督抽查不合格率指数k4的计算公式为:The formula for calculating the unqualified rate index k 4 of elevator supervision and random inspection is:

Figure BDA0003095083050000136
Figure BDA0003095083050000136

用户投诉率指数m1的计算公式为:The calculation formula of the user complaint rate index m 1 is:

Figure BDA0003095083050000137
Figure BDA0003095083050000137

满意度平均分数指数m2的计算公式为:The formula for calculating the average score index m2 of satisfaction is:

Figure BDA0003095083050000138
Figure BDA0003095083050000138

电梯物联网故障预警功能平均分数指数r1的计算公式为:The calculation formula of the average score index r 1 of the elevator IoT fault warning function is:

Figure BDA0003095083050000139
Figure BDA0003095083050000139

电梯物联网故障检测功能平均分数指数r2的计算公式为:The calculation formula of the average score index r 2 of the elevator IoT fault detection function is:

Figure BDA0003095083050000141
Figure BDA0003095083050000141

电梯物联网预测性维护支持平均分数指数r3的计算公式为:The calculation formula of the average score index r 3 of the predictive maintenance support of the elevator IoT is:

Figure BDA0003095083050000142
Figure BDA0003095083050000142

上述所有特征数据转化之后,各指数均值均会趋向于1。After all the above characteristic data are transformed, the mean of each index will tend to be 1.

得到电梯故障控制效率相关的特征矩阵:The characteristic matrix related to the efficiency of elevator fault control is obtained:

G=[g1,g2,g3]T G=[g 1 , g 2 , g 3 ] T

同样,得到电梯故障处置效率相关的特征矩阵:Similarly, the feature matrix related to the efficiency of elevator fault handling is obtained:

H=[h1,h2]T H=[h 1 ,h 2 ] T

同样,得到维护质量管控相关的特征矩阵:Similarly, the characteristic matrix related to maintenance quality control is obtained:

K=[k1,k2,k3,k4]T K=[k 1 ,k 2 ,k 3 ,k 4 ] T

同样,得到客户满意度相关的特征矩阵:Similarly, get the characteristic matrix related to customer satisfaction:

M=[m1,m2]T M=[m 1 ,m 2 ] T

同样,得到电梯物联网监测能力相关的特征矩阵:Similarly, the feature matrix related to the monitoring capability of the elevator IoT is obtained:

R=[r1,r2,r3]T R=[r 1 , r 2 , r 3 ] T

由此可得维保质量各个维度评价结果:From this, the evaluation results of each dimension of maintenance quality can be obtained:

Q1*G=a11g1+a12g2+a12g3 Q 1 *G=a 11 g 1 +a 12 g 2 +a 12 g 3

Q2*H=a21h1+a22h2 Q 2 *H=a 21 h 1 +a 22 h 2

Q3*K=a31k1+a32k2+a32k3 Q 3 *K=a 31 k 1 +a 32 k 2 +a 32 k 3

Q4*M=a41m1+a42m2 Q 4 *M=a 41 m 1 +a 42 m 2

Q5*R=a51r1+a52r2+a53r3 Q 5 *R=a 51 r 1 +a 52 r 2 +a 53 r 3

由此可得到列向量:This results in a column vector:

Figure BDA0003095083050000143
Figure BDA0003095083050000143

最后可以建立得到电梯维保质量评价模型:Finally, the elevator maintenance quality evaluation model can be established:

Figure BDA0003095083050000144
Figure BDA0003095083050000144

根据上述电梯维保质量评价模型,获得各个维保单位的维保质量评价得分,得出各维保单位在全部维保单位维保质量评价中的排名及相对位置。According to the above-mentioned elevator maintenance quality evaluation model, the maintenance quality evaluation score of each maintenance unit is obtained, and the ranking and relative position of each maintenance unit in the maintenance quality evaluation of all maintenance units are obtained.

根据维保单位维保质量评价指数分布,将质量评价分数标准化处理。标准化处理方法为:According to the distribution of the maintenance quality evaluation index of the maintenance unit, the quality evaluation score is standardized. The standardized processing method is:

Figure BDA0003095083050000151
Figure BDA0003095083050000151

其中,Szy为维保质量评价分数标准值,z和Z为常数,Sy为维保质量评价分数,

Figure BDA0003095083050000152
为维保质量评价分数平均值,Sσ为维保质量评价分数标准差。Among them, Szy is the standard value of the maintenance quality evaluation score, z and Z are constants, S y is the maintenance quality evaluation score,
Figure BDA0003095083050000152
is the mean value of the maintenance quality evaluation score, and S σ is the standard deviation of the maintenance quality evaluation score.

经过标准化处理后的维保质量评价分数分布与原始评价结果分布形状相同,也不会改变各维保单位电梯维护保养质量评价分数分布的排序。The distribution of maintenance quality evaluation scores after standardized processing is the same as the distribution of the original evaluation results, and it will not change the order of the elevator maintenance quality evaluation score distribution of each maintenance unit.

经过标准化处理后,能够从电梯维保单位维保质量评价结果上看出某个维保单位维保质量所处的位置。After standardized processing, the position of the maintenance quality of a maintenance unit can be seen from the evaluation results of the maintenance quality of the elevator maintenance unit.

根据标准化处理后的电梯维保单位维保质量评价结果分布的实际情况以及电梯安全监管要求,设置评级阈值和风险告警机制。According to the actual distribution of the maintenance quality evaluation results of the elevator maintenance unit after standardized processing and the elevator safety supervision requirements, the rating threshold and risk warning mechanism are set.

采用如下评级机制:通过系统设置,设定的阈值SL、SH。当Szy高于或等于SH时,电梯维保单位维保质量判定为1级;当Szy低于SL时,电梯维保单位维保质量判定为3级。The following rating mechanism is adopted: the thresholds SL and SH are set through system settings. When Szy is higher than or equal to SH, the maintenance quality of the elevator maintenance unit is judged to be level 1; when Szy is lower than SL, the maintenance quality of the elevator maintenance unit is judged to be level 3.

根据上述方法,电梯维保单位维保质量评级分为1级、2级、3级。可根据实际情况,实施相应管理。According to the above method, the maintenance quality rating of elevator maintenance units is divided into 1, 2 and 3. According to the actual situation, corresponding management can be implemented.

本申请还提供了一种基于大数据的电梯维保质量评价系统,包括:The application also provides a big data-based elevator maintenance quality evaluation system, including:

采集模块,用于采集待测维保单位的维保电梯故障数据、维保电梯故障处置数据、维保维护质量数据、维保客户评价数据和维保电梯物联网功能情况数据;采集所有维保单位的统计电梯故障数据、统计电梯故障处置数据、统计维护质量数据、统计客户评价数据和统计电梯物联网功能情况数据;The acquisition module is used to collect the maintenance elevator fault data, maintenance elevator fault disposal data, maintenance quality data, maintenance customer evaluation data and maintenance elevator IoT function data of the maintenance unit to be tested; The unit's statistical elevator fault data, statistical elevator fault disposal data, statistical maintenance quality data, statistical customer evaluation data and statistical elevator Internet of Things function data;

计算模块,用于根据所述维保电梯故障数据计算维保电梯故障控制效率数据;根据所述维保电梯故障处置数据计算维保电梯故障处置效率数据;根据所述维保维护质量数据计算维保维护质量管控数据;根据所述维保客户评价数据计算维保客户满意度数据;根据所述维保电梯物联网功能情况数据计算维保电梯物联网监测能力数据;根据所述统计电梯故障数据计算统计电梯故障控制效率数据;根据所述统计故障处置数据计算统计电梯故障处置效率数据;根据所述统计维护质量数据计算统计维护质量管控数据;根据所述统计客户评价数据计算统计客户满意度数据;根据所述统计电梯物联网功能情况数据计算统计电梯物联网监测能力数据;The calculation module is used for calculating maintenance elevator fault control efficiency data according to the maintenance elevator fault data; calculating maintenance elevator fault handling efficiency data according to the maintenance elevator fault handling data; calculating maintenance elevator fault handling efficiency data according to the maintenance quality data. Maintenance quality control data; maintenance customer satisfaction data is calculated according to the maintenance customer evaluation data; maintenance elevator Internet of Things monitoring capability data is calculated according to the maintenance elevator Internet of Things function data; maintenance elevator Internet of Things monitoring capability data; according to the statistical elevator fault data Calculate statistical elevator fault control efficiency data; calculate statistical elevator fault disposal efficiency data according to the statistical fault disposal data; calculate statistical maintenance quality control data according to the statistical maintenance quality data; calculate statistical customer satisfaction data according to the statistical customer evaluation data ; Calculate and count the monitoring capability data of the Internet of Things for elevators according to the statistical data on the functions of the Internet of Things in elevators;

评价模块,用于根据所述维保电梯故障控制效率数据、所述维保电梯故障处置效率数据、所述维保维护质量管控数据、所述维保客户满意度数据、所述维保电梯物联网监测能力数据、所述统计电梯故障控制效率数据、所述统计电梯故障处置效率数据、所述统计维护质量管控数据、所述统计客户满意度数据和所述统计电梯物联网监测能力数据计算所述待测维保单位的维保质量评价分数。The evaluation module is configured to, according to the maintenance elevator fault control efficiency data, the maintenance elevator fault handling efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator object Network monitoring capability data, the statistical elevator fault control efficiency data, the statistical elevator fault handling efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data, and the statistical elevator IoT monitoring capability data calculation institute The maintenance quality evaluation score of the maintenance unit to be tested.

上述方法实施例中的内容均适用于本装置系统实施例中,本系统实施例所具体实现的功能与上述方法实施例相同,并且达到的有益效果与上述方法实施例所达到的有益效果也相同。The contents in the above method embodiments are all applicable to the system embodiments of the present device, the specific functions implemented by the system embodiments are the same as the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments. .

本申请实施例还提供了一种基于大数据的电梯维保质量评价系统,包括:The embodiment of the present application also provides a big data-based elevator maintenance quality evaluation system, including:

至少一个处理器;at least one processor;

至少一个存储器,用于存储至少一个程序;at least one memory for storing at least one program;

当所述至少一个程序被所述至少一个处理器执行,使得所述至少一个处理器实现所述的方法。The at least one program, when executed by the at least one processor, causes the at least one processor to implement the method.

上述方法实施例中的内容均适用于本装置系统实施例中,本系统实施例所具体实现的功能与上述方法实施例相同,并且达到的有益效果与上述方法实施例所达到的有益效果也相同。The contents in the above method embodiments are all applicable to the system embodiments of the present device, the specific functions implemented by the system embodiments are the same as the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments. .

此外,本申请实施例还提供了一种存储介质,其中存储有处理器可执行的指令,所述处理器可执行的指令在由处理器执行时用于执行上述方法实施例中任一个技术方案所述的一种交互信息处理方法步骤。对于所述存储介质,其可以包括高速随机存取存储器,还可以包括非易失性存储器,例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。可见,上述方法实施例中的内容均适用于本存储介质实施例中,本存储介质实施例所具体实现的功能与上述方法实施例相同,并且达到的有益效果与上述方法实施例所达到的有益效果也相同。In addition, an embodiment of the present application further provides a storage medium in which processor-executable instructions are stored, and when executed by the processor, the processor-executable instructions are used to execute any one of the technical solutions in the foregoing method embodiments The steps of a method for processing interactive information. For the storage medium, it may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. It can be seen that the contents in the above method embodiments are all applicable to this storage medium embodiment, the specific functions implemented by this storage medium embodiment are the same as the above method embodiments, and the beneficial effects achieved are the same as those achieved by the above method embodiments. The effect is also the same.

应当认识到,本申请的实施例系统中所包含的层、模块、单元和/或平台等可以由计算机硬件、硬件和软件的组合、或者通过存储在非暂时性计算机可读存储器中的计算机指令来实现或实施。所述方法可以使用标准编程技术-包括配置有计算机程序的非暂时性计算机可读存储介质在计算机程序中实现,其中如此配置的存储介质使得计算机以特定和预定义的方式操作——根据在具体实施例中描述的方法和附图。每个程序可以以高级过程或面向对象的编程语言来实现以与计算机系统通信。然而,若需要,该程序可以以汇编或机器语言实现。在任何情况下,该语言可以是编译或解释的语言。此外,为此目的该程序能够在编程的专用集成电路上运行。It should be appreciated that the layers, modules, units, and/or platforms, etc. included in the systems of the embodiments of the present application may be implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory to realize or implement. The method can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the specific Methods and figures described in the Examples. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.

此外,本申请实施例系统中所包含的层、模块、单元和/或平台所对应执行的数据处理流程,其可按任何合适的顺序来执行,除非本文另外指示或以其他方式明显地与上下文矛盾。本申请实施例系统中所包含的层、模块、单元和/或平台所对应执行的数据处理流程可在配置有可执行指令的一个或多个计算机系统的控制下执行,并且可作为共同地在一个或多个处理器上执行的代码(例如,可执行指令、一个或多个计算机程序或一个或多个应用)、由硬件或其组合来实现。所述计算机程序包括可由一个或多个处理器执行的多个指令。In addition, the data processing flow corresponding to the layers, modules, units and/or platforms included in the system of the embodiments of the present application may be executed in any suitable order, unless otherwise indicated herein or otherwise clearly inconsistent with the context contradiction. The data processing flow corresponding to the layers, modules, units and/or platforms included in the system of the embodiments of the present application can be executed under the control of one or more computer systems configured with executable instructions, and can be used as a common Code (eg, executable instructions, one or more computer programs, or one or more applications) executing on one or more processors, implemented by hardware, or a combination thereof. The computer program includes a plurality of instructions executable by one or more processors.

进一步,所述系统可以在可操作地连接至合适的任何类型的计算平台中实现,包括但不限于个人电脑、迷你计算机、主框架、工作站、网络或分布式计算环境、单独的或集成的计算机平台、或者与带电粒子工具或其它成像装置通信等等。本申请系统中所包含的层、模块、单元和/或平台所对应执行的数据处理流程可以以存储在非暂时性存储介质或设备上的机器可读代码来实现,无论是可移动的还是集成至计算平台,如硬盘、光学读取和/或写入存储介质、RAM、ROM等,使得其可由可编程计算机读取,当存储介质或设备由计算机读取时可用于配置和操作计算机以执行在此所描述的过程。此外,机器可读代码,或其部分可以通过有线或无线网络传输。当此类媒体包括结合微处理器或其他数据处理器实现上文所述步骤的指令或程序时,本文所述的发明包括这些和其他不同类型的非暂时性计算机可读存储介质。当根据本申请所述的方法和技术编程时,本申请还包括计算机本身。Further, the system may be implemented in any type of computing platform operably connected to a suitable, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, stand-alone or integrated computers platform, or communicate with charged particle tools or other imaging devices, etc. The data processing flow corresponding to the layers, modules, units and/or platforms included in the system of the present application can be implemented by machine-readable codes stored in non-transitory storage media or devices, whether removable or integrated to a computing platform, such as a hard disk, an optically readable and/or writeable storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, and when the storage medium or device is read by the computer, can be used to configure and operate the computer to perform process described here. Additionally, the machine-readable code, or portions thereof, may be transmitted over wired or wireless networks. The invention described herein includes these and other various types of non-transitory computer-readable storage media when such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. This application also includes the computer itself when programmed according to the methods and techniques described in this application.

以上所述,只是本申请的较佳实施例而已,本申请并不局限于上述实施方式,只要其以相同的手段达到本申请的技术效果,凡在本申请的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本申请保护的范围之内。在本申请的保护范围内其技术方案和/或实施方式可以有各种不同的修改和变化。The above are only preferred embodiments of the present application, and the present application is not limited to the above-mentioned embodiments, as long as the technical effect of the present application is achieved by the same means, all within the spirit and principle of the present application, the Any modification, equivalent replacement, improvement, etc., shall be included within the scope of protection of this application. Various modifications and changes can be made to its technical solutions and/or implementations within the protection scope of the present application.

Claims (10)

1. A method for evaluating the maintenance quality of an elevator based on big data is characterized by comprising the following steps:
collecting maintenance elevator fault data, maintenance elevator fault disposal data, maintenance quality data, maintenance customer evaluation data and maintenance elevator internet of things function condition data of a maintenance unit to be tested; the maintenance elevator fault data comprise maintenance elevator fault times, maintenance elevator trapping times, maintenance elevator total operation times and maintenance elevator fault interval time; the maintenance elevator fault handling data comprises maintenance elevator fault time, maintenance elevator trapped rescue response time and maintenance elevator trapped rescue allowed maximum response time; the maintenance quality data of the maintenance system comprises maintenance interval time of the maintenance system elevator, maximum allowable maintenance interval time of the maintenance system elevator, the number of unqualified maintenance inspection items of the maintenance system elevator, the total number of inspection items of the maintenance system elevator, the number of unqualified inspection items of the function inspection of the Internet of things of the maintenance system elevator, the total number of inspection items of the function inspection items of the Internet of things of the maintenance system elevator, the number of unqualified inspection items of the supervision and spot check of the maintenance system elevator and the total number of supervision and spot check items of the maintenance system elevator; the customer evaluation data comprises complaint times of a maintenance user and a maintenance satisfaction degree score; the function condition data of the maintenance elevator internet of things comprises a maintenance elevator internet of things fault early warning function score, a maintenance elevator internet of things fault detection function score and a maintenance elevator internet of things predictive maintenance support score;
collecting the statistical elevator fault data, the statistical elevator fault treatment data, the statistical maintenance quality data, the statistical customer evaluation data and the statistical elevator Internet of things function condition data of all maintenance units; the statistics of the elevator fault data comprises statistics of elevator fault times, statistics of elevator trapping times, statistics of total elevator running times and statistics of elevator fault interval time; the statistic elevator fault handling data comprises statistic elevator fault time, statistic elevator trapped rescue response time and statistic elevator trapped rescue allowable maximum response time; the statistical maintenance quality data comprises statistical elevator maintenance interval time, statistical elevator maintenance maximum allowable interval time, statistical elevator inspection unqualified item number, statistical elevator total inspection item number, statistical elevator Internet of things function inspection unqualified item number, statistical elevator Internet of things function total inspection item number, statistical elevator supervision random inspection unqualified item number and statistical elevator supervision random inspection total item number; the statistical customer evaluation data comprises statistical customer complaint times and statistical satisfaction scores; the method comprises the following steps of counting elevator internet of things function condition data, including a fault early warning function score, a fault detection function score and a predictive maintenance support score of the elevator internet of things;
calculating maintenance elevator fault control efficiency data according to the maintenance elevator fault data; the maintenance elevator fault control efficiency data comprises maintenance elevator fault rate, maintenance elevator mean fault interval time and maintenance elevator crowd rate; the maintenance elevator fault rate is calculated according to the maintenance elevator fault frequency and the maintenance elevator total operation frequency; the maintenance elevator mean fault interval is obtained by calculation according to the maintenance elevator fault interval time and the maintenance elevator fault times; the man trapping rate of the maintenance elevator is calculated according to the man trapping times of the maintenance elevator and the total running times of the maintenance elevator;
calculating maintenance elevator fault disposal efficiency data according to the maintenance elevator fault disposal data; the maintenance elevator fault handling efficiency data comprises maintenance elevator fault average time and maintenance elevator trapped rescue time rate; the maintenance elevator fault average time length is obtained by calculation according to the maintenance elevator fault time and the maintenance elevator fault times; the maintenance elevator drowsiness rescue timeliness rate is calculated according to the maintenance elevator drowsiness rescue response time and the maintenance elevator drowsiness rescue allowed maximum response time;
calculating maintenance quality control data according to the maintenance quality data; the maintenance quality control data comprises maintenance timeliness rate, maintenance inspection unqualified rate, maintenance elevator Internet of things function inspection unqualified rate and maintenance elevator supervision and spot inspection unqualified rate; the maintenance timeliness rate is obtained by calculation according to the maintenance interval time of the maintenance elevator and the maximum allowable maintenance interval time of the maintenance elevator; the maintenance inspection disqualification rate is obtained by calculation according to the number of unqualified maintenance elevator inspection items and the total number of maintenance elevator inspection items; the failure rate of the function test of the Internet of things of the maintenance elevator is calculated according to the number of failure items of the function test of the Internet of things of the maintenance elevator and the total number of the function test items of the Internet of things of the maintenance elevator; the failure rate of the supervision and spot check of the maintenance elevator is calculated according to the number of failure items of the supervision and spot check of the maintenance elevator and the total number of the supervision and spot check items of the maintenance elevator;
calculating satisfaction data of the maintenance customers according to the evaluation data of the maintenance customers; the maintenance customer satisfaction data comprises maintenance user complaint rate and maintenance satisfaction average score; the complaint rate of the maintenance user is calculated according to the total running times of the maintenance elevator and the complaint times of the maintenance user; the maintenance satisfaction degree average score is obtained by calculation according to the maintenance satisfaction degree score;
calculating the monitoring capacity data of the maintenance elevator internet of things according to the data of the function condition of the maintenance elevator internet of things; the maintenance elevator internet of things monitoring capability data comprises a maintenance elevator internet of things fault early warning function average score, a maintenance elevator internet of things fault detection function average score and a maintenance elevator internet of things predictive maintenance support average score; the maintenance elevator Internet of things fault early warning function average score is obtained by calculation according to the maintenance elevator Internet of things fault early warning function score; the maintenance elevator Internet of things fault detection function average score is obtained by calculation according to the maintenance elevator Internet of things fault detection function score; the predictive maintenance support average score of the maintenance elevator internet of things is obtained by calculation according to the predictive maintenance support score of the maintenance elevator internet of things;
calculating and counting elevator fault control efficiency data according to the statistical elevator fault data; the statistic elevator fault control efficiency data comprises statistic elevator fault rate, statistic elevator mean fault interval time and statistic elevator trapping rate; the statistical elevator fault rate is obtained by calculation according to the statistical elevator fault times and the statistical elevator total operation times; the statistical elevator mean fault interval is obtained by calculation according to the statistical elevator fault interval time and the statistical elevator fault times; the statistic elevator trapping rate is calculated according to the statistic elevator trapping times and the statistic elevator total operation times;
calculating statistical elevator fault handling efficiency data according to the statistical fault handling data; the statistic elevator fault handling efficiency data comprises statistic elevator fault average time length and statistic elevator trapped rescue timeliness; the statistical elevator fault average time length is obtained by calculation according to the statistical elevator fault time and the statistical elevator fault times; the statistics of the elevator trapping rescue timeliness is obtained by calculation according to the statistics of the elevator trapping rescue response time and the statistics of the maximum elevator trapping rescue allowable response time;
calculating statistical maintenance quality control data according to the statistical maintenance quality data; the statistical maintenance quality control data comprises a statistical maintenance timeliness rate, a statistical inspection disqualification rate, a statistical elevator Internet of things function inspection disqualification rate and a statistical elevator supervision spot check disqualification rate; the statistical maintenance timeliness rate is obtained by calculation according to the statistical elevator maintenance interval time and the statistical elevator maintenance maximum allowable interval time; the statistical inspection disqualification rate is obtained by calculation according to the statistical elevator inspection disqualification item number and the statistical elevator total inspection item number; the unqualified rate of the function test of the elevator internet of things is calculated according to the unqualified item number of the function test of the elevator internet of things and the total item number of the function test of the elevator internet of things; the statistical elevator supervision spot check failure rate is obtained by calculation according to the statistical elevator supervision spot check failure item number and the statistical elevator supervision spot check total item number;
calculating statistical customer satisfaction data according to the statistical customer evaluation data; the statistical customer satisfaction data comprises statistical customer complaint rate and statistical satisfaction average score; the statistical user complaint rate is obtained by calculation according to the statistical total elevator running times and the statistical user complaint times; the statistical satisfaction degree average score is obtained by calculation according to the statistical satisfaction degree score;
calculating and counting elevator internet of things monitoring capacity data according to the elevator internet of things function condition data; the statistic elevator internet of things monitoring capability data comprises a statistic elevator internet of things fault early warning function average score, a statistic elevator internet of things fault detection function average score and a statistic elevator internet of things predictive maintenance support average score; the statistical elevator Internet of things fault early warning function average score is obtained by calculation according to the statistical elevator Internet of things fault early warning function score; the statistical elevator Internet of things fault detection function average score is obtained by calculation according to the statistical elevator Internet of things fault detection function score; the statistical elevator internet of things predictive maintenance support average score is calculated according to the statistical elevator internet of things predictive maintenance support score;
and calculating the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency data, the maintenance elevator fault treatment efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator internet of things monitoring capability data, the statistic elevator fault control efficiency data, the statistic elevator fault treatment efficiency data, the statistic maintenance quality control data, the statistic customer satisfaction data and the statistic elevator internet of things monitoring capability data.
2. The elevator maintenance quality evaluation method based on big data according to claim 1, wherein the step of calculating the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency data, the maintenance elevator fault treatment efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator internet of things monitoring capability data, the statistical elevator fault control efficiency data, the statistical elevator fault treatment efficiency data, the statistical maintenance quality control data, the statistical customer satisfaction data, and the statistical elevator internet of things monitoring capability data specifically comprises:
calculating a maintenance elevator fault control efficiency index according to the maintenance elevator fault control efficiency data and the statistical elevator fault control efficiency data; the maintenance elevator fault control efficiency index comprises a maintenance elevator fault rate index, a maintenance elevator mean fault interval time index and a maintenance elevator crowd rate index; the maintenance elevator fault rate index is obtained by calculation according to the maintenance elevator fault rate and the statistical elevator fault rate; the maintenance elevator mean fault interval time index is obtained by calculation according to the maintenance elevator mean fault interval time and the statistical elevator mean fault interval time; the maintenance elevator trapping rate index is obtained by calculation according to the maintenance elevator trapping rate and the statistical elevator trapping rate;
calculating a maintenance elevator fault disposal efficiency index according to the maintenance elevator fault disposal efficiency data and the statistical elevator fault disposal efficiency data; the maintenance elevator fault handling efficiency index comprises a maintenance elevator fault average time length index and a maintenance elevator trapped rescue time rate index; the maintenance elevator fault average time length index is obtained by calculation according to the maintenance elevator fault average time length and the statistical elevator fault average time length; the maintenance elevator trapped rescue timeliness index is obtained by calculation according to the maintenance elevator trapped rescue timeliness and the statistic elevator trapped rescue timeliness;
calculating a maintenance quality control index according to the maintenance quality control data and the statistical maintenance quality control data; the maintenance quality control index comprises a maintenance timeliness rate index, a maintenance inspection disqualification rate index, a maintenance elevator Internet of things function inspection disqualification rate index and a maintenance elevator supervision spot check disqualification rate index; the maintenance and maintenance timeliness rate index is obtained by calculation according to the maintenance and maintenance timeliness rate and the statistical maintenance timeliness rate; the maintenance inspection disqualification rate index is obtained by calculating the maintenance inspection disqualification rate and the statistical inspection disqualification rate to obtain the maintenance elevator Internet of things function inspection disqualification rate index; the maintenance elevator supervision random inspection disqualification rate index is obtained by calculation according to the maintenance elevator supervision random inspection disqualification rate and the statistic elevator supervision random inspection disqualification rate;
calculating a maintenance customer satisfaction index according to the maintenance customer satisfaction data and the statistical customer satisfaction data; the maintenance customer satisfaction index comprises a maintenance user complaint rate index and a maintenance satisfaction average score index; the complaint rate index of the maintenance user is obtained by calculation according to the complaint rate of the maintenance user and the complaint rate of the statistical user; the maintenance satisfaction degree average score index is obtained by calculation according to the maintenance satisfaction degree average score and the statistics maintenance satisfaction degree average score;
calculating a maintenance elevator Internet of things monitoring capability index according to the maintenance elevator Internet of things monitoring capability data and the statistic elevator Internet of things monitoring capability data; the maintenance elevator internet of things monitoring capability index comprises a maintenance elevator internet of things fault early warning function average score index, a maintenance elevator internet of things fault detection function average score index and a maintenance elevator internet of things predictive maintenance support average score index; the maintenance elevator Internet of things fault early warning function average score index is obtained by calculation according to the maintenance elevator Internet of things fault early warning function average score and the statistical elevator Internet of things fault early warning function average score; the maintenance elevator Internet of things fault detection function average score index is obtained by calculation according to the maintenance elevator Internet of things fault detection function average score and the statistical elevator Internet of things fault detection function average score; the index of the predictive maintenance support average of the elevator internet of things is obtained by calculation according to the predictive maintenance support average of the elevator internet of things and the statistical predictive maintenance support average of the elevator internet of things;
and calculating the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency index, the maintenance elevator fault treatment efficiency index, the maintenance quality control index, the maintenance customer satisfaction index and the maintenance elevator Internet of things monitoring capability index.
3. The elevator maintenance quality evaluation method based on big data according to claim 2, wherein the step of calculating the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency index, the maintenance elevator fault handling efficiency index, the maintenance quality control index, the maintenance customer satisfaction index and the maintenance elevator internet of things monitoring capability index specifically comprises:
obtaining a maintenance elevator fault control efficiency weight vector, a maintenance elevator fault treatment efficiency weight vector, a maintenance quality control weight vector, a maintenance customer satisfaction weight vector and a maintenance elevator internet of things monitoring capability weight vector;
and calculating a maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency index, the maintenance elevator fault treatment efficiency index, the maintenance quality control index, the maintenance customer satisfaction index, the maintenance elevator internet of things monitoring capability index, the maintenance elevator fault control efficiency weight vector, the maintenance elevator fault treatment efficiency weight vector, the maintenance quality control weight vector, the maintenance customer satisfaction weight vector and the maintenance elevator internet of things monitoring capability weight vector.
4. The elevator maintenance quality evaluation method based on big data according to claim 2, characterized in that the calculation formula of the maintenance elevator fault rate index is as follows:
Figure FDA0003095083040000051
wherein, g1To maintain the elevator fault rate index, PfiIn order to maintain the failure rate of the elevator,
Figure FDA0003095083040000052
the failure rate of the elevator is counted.
5. The big data-based quality evaluation method for maintaining the elevator according to claim 1, further comprising:
and when the maintenance quality evaluation score is smaller than a preset score threshold, generating maintenance quality alarm information.
6. The elevator maintenance quality evaluation method based on big data according to claim 1, wherein the calculation formula of the man-trapping and rescue timeliness rate of the maintenance elevator is as follows:
PRi=TRi/TRmax
wherein, PRiMaintenance of elevator entrapment rescue timeliness, TRiRescue response time, T, for maintaining elevator drowsinessRmaxThe elevator is maintained to be trapped and rescue the allowed maximum response time.
7. The big data-based quality evaluation method for maintaining the elevator according to claim 1, further comprising:
calculating the average value of the maintenance quality evaluation scores and the standard deviation of the maintenance quality evaluation scores of all maintenance units;
calculating a maintenance quality evaluation score standard value according to the maintenance quality evaluation score, the maintenance quality evaluation score average value and the maintenance quality evaluation score standard deviation;
the calculation formula of the maintenance quality evaluation score standard value is as follows:
Figure FDA0003095083040000061
wherein, SzyFor quality assessment score standard value of maintenance, Z and Z are constants, SyIn order to maintain the quality evaluation score,
Figure FDA0003095083040000062
to maintain the quality evaluation score average, SσAnd the standard deviation of the maintenance quality evaluation score is obtained.
8. An elevator maintenance quality evaluation system based on big data is characterized by comprising:
the system comprises an acquisition module, a maintenance module and a maintenance module, wherein the acquisition module is used for acquiring maintenance elevator fault data, maintenance elevator fault disposal data, maintenance quality data, maintenance customer evaluation data and maintenance elevator Internet of things function condition data of a maintenance unit to be tested; the maintenance elevator fault data comprise maintenance elevator fault times, maintenance elevator trapping times, maintenance elevator total operation times and maintenance elevator fault interval time; the maintenance elevator fault handling data comprises maintenance elevator fault time, maintenance elevator trapped rescue response time and maintenance elevator trapped rescue allowed maximum response time; the maintenance quality data of the maintenance system comprises maintenance interval time of the maintenance system elevator, maximum allowable maintenance interval time of the maintenance system elevator, the number of unqualified maintenance inspection items of the maintenance system elevator, the total number of inspection items of the maintenance system elevator, the number of unqualified inspection items of the function inspection of the Internet of things of the maintenance system elevator, the total number of inspection items of the function inspection items of the Internet of things of the maintenance system elevator, the number of unqualified inspection items of the supervision and spot check of the maintenance system elevator and the total number of supervision and spot check items of the maintenance system elevator; the customer evaluation data comprises complaint times of a maintenance user and a maintenance satisfaction degree score; the function condition data of the maintenance elevator internet of things comprises a maintenance elevator internet of things fault early warning function score, a maintenance elevator internet of things fault detection function score and a maintenance elevator internet of things predictive maintenance support score;
collecting the statistical elevator fault data, the statistical elevator fault treatment data, the statistical maintenance quality data, the statistical customer evaluation data and the statistical elevator Internet of things function condition data of all maintenance units; the statistics of the elevator fault data comprises statistics of elevator fault times, statistics of elevator trapping times, statistics of total elevator running times and statistics of elevator fault interval time; the statistic elevator fault handling data comprises statistic elevator fault time, statistic elevator trapped rescue response time and statistic elevator trapped rescue allowable maximum response time; the statistical maintenance quality data comprises statistical elevator maintenance interval time, statistical elevator maintenance maximum allowable interval time, statistical elevator inspection unqualified item number, statistical elevator total inspection item number, statistical elevator Internet of things function inspection unqualified item number, statistical elevator Internet of things function total inspection item number, statistical elevator supervision random inspection unqualified item number and statistical elevator supervision random inspection total item number; the statistical customer evaluation data comprises statistical customer complaint times and statistical satisfaction scores; the method comprises the following steps of counting elevator internet of things function condition data, including a fault early warning function score, a fault detection function score and a predictive maintenance support score of the elevator internet of things;
the calculation module is used for calculating maintenance elevator fault control efficiency data according to the maintenance elevator fault data; the maintenance elevator fault control efficiency data comprises maintenance elevator fault rate, maintenance elevator mean fault interval time and maintenance elevator crowd rate; the maintenance elevator fault rate is calculated according to the maintenance elevator fault frequency and the maintenance elevator total operation frequency; the maintenance elevator mean fault interval is obtained by calculation according to the maintenance elevator fault interval time and the maintenance elevator fault times; the man trapping rate of the maintenance elevator is calculated according to the man trapping times of the maintenance elevator and the total running times of the maintenance elevator; calculating maintenance elevator fault disposal efficiency data according to the maintenance elevator fault disposal data; the maintenance elevator fault handling efficiency data comprises maintenance elevator fault average time and maintenance elevator trapped rescue time rate; the maintenance elevator fault average time length is obtained by calculation according to the maintenance elevator fault time and the maintenance elevator fault times; the maintenance elevator drowsiness rescue timeliness rate is calculated according to the maintenance elevator drowsiness rescue response time and the maintenance elevator drowsiness rescue allowed maximum response time; calculating maintenance quality control data according to the maintenance quality data; the maintenance quality control data comprises maintenance timeliness rate, maintenance inspection unqualified rate, maintenance elevator Internet of things function inspection unqualified rate and maintenance elevator supervision and spot inspection unqualified rate; the maintenance timeliness rate is obtained by calculation according to the maintenance interval time of the maintenance elevator and the maximum allowable maintenance interval time of the maintenance elevator; the maintenance inspection disqualification rate is obtained by calculation according to the number of unqualified maintenance elevator inspection items and the total number of maintenance elevator inspection items; the failure rate of the function test of the Internet of things of the maintenance elevator is calculated according to the number of failure items of the function test of the Internet of things of the maintenance elevator and the total number of the function test items of the Internet of things of the maintenance elevator; the failure rate of the supervision and spot check of the maintenance elevator is calculated according to the number of failure items of the supervision and spot check of the maintenance elevator and the total number of the supervision and spot check items of the maintenance elevator; calculating satisfaction data of the maintenance customers according to the evaluation data of the maintenance customers; the maintenance customer satisfaction data comprises maintenance user complaint rate and maintenance satisfaction average score; the complaint rate of the maintenance user is calculated according to the total running times of the maintenance elevator and the complaint times of the maintenance user; the maintenance satisfaction degree average score is obtained by calculation according to the maintenance satisfaction degree score; calculating the monitoring capacity data of the maintenance elevator internet of things according to the data of the function condition of the maintenance elevator internet of things; the maintenance elevator internet of things monitoring capability data comprises a maintenance elevator internet of things fault early warning function average score, a maintenance elevator internet of things fault detection function average score and a maintenance elevator internet of things predictive maintenance support average score; the maintenance elevator Internet of things fault early warning function average score is obtained by calculation according to the maintenance elevator Internet of things fault early warning function score; the maintenance elevator Internet of things fault detection function average score is obtained by calculation according to the maintenance elevator Internet of things fault detection function score; the predictive maintenance support average score of the maintenance elevator internet of things is obtained by calculation according to the predictive maintenance support score of the maintenance elevator internet of things; calculating and counting elevator fault control efficiency data according to the statistical elevator fault data; the statistic elevator fault control efficiency data comprises statistic elevator fault rate, statistic elevator mean fault interval time and statistic elevator trapping rate; the statistical elevator fault rate is obtained by calculation according to the statistical elevator fault times and the statistical elevator total operation times; the statistical elevator mean fault interval is obtained by calculation according to the statistical elevator fault interval time and the statistical elevator fault times; the statistic elevator trapping rate is calculated according to the statistic elevator trapping times and the statistic elevator total operation times; calculating statistical elevator fault handling efficiency data according to the statistical fault handling data; the statistic elevator fault handling efficiency data comprises statistic elevator fault average time length and statistic elevator trapped rescue timeliness; the statistical elevator fault average time length is obtained by calculation according to the statistical elevator fault time and the statistical elevator fault times; the statistics of the elevator trapping rescue timeliness is obtained by calculation according to the statistics of the elevator trapping rescue response time and the statistics of the maximum elevator trapping rescue allowable response time; calculating statistical maintenance quality control data according to the statistical maintenance quality data; the statistical maintenance quality control data comprises a statistical maintenance timeliness rate, a statistical inspection disqualification rate, a statistical elevator Internet of things function inspection disqualification rate and a statistical elevator supervision spot check disqualification rate; the statistical maintenance timeliness rate is obtained by calculation according to the statistical elevator maintenance interval time and the statistical elevator maintenance maximum allowable interval time; the statistical inspection disqualification rate is obtained by calculation according to the statistical elevator inspection disqualification item number and the statistical elevator total inspection item number; the unqualified rate of the function test of the elevator internet of things is calculated according to the unqualified item number of the function test of the elevator internet of things and the total item number of the function test of the elevator internet of things; the statistical elevator supervision spot check failure rate is obtained by calculation according to the statistical elevator supervision spot check failure item number and the statistical elevator supervision spot check total item number; calculating statistical customer satisfaction data according to the statistical customer evaluation data; the statistical customer satisfaction data comprises statistical customer complaint rate and statistical satisfaction average score; the statistical user complaint rate is obtained by calculation according to the statistical total elevator running times and the statistical user complaint times; the statistical satisfaction degree average score is obtained by calculation according to the statistical satisfaction degree score;
calculating and counting elevator internet of things monitoring capacity data according to the elevator internet of things function condition data; the statistic elevator internet of things monitoring capability data comprises a statistic elevator internet of things fault early warning function average score, a statistic elevator internet of things fault detection function average score and a statistic elevator internet of things predictive maintenance support average score; the statistical elevator Internet of things fault early warning function average score is obtained by calculation according to the statistical elevator Internet of things fault early warning function score; the statistical elevator Internet of things fault detection function average score is obtained by calculation according to the statistical elevator Internet of things fault detection function score; the statistical elevator internet of things predictive maintenance support average score is calculated according to the statistical elevator internet of things predictive maintenance support score;
and the evaluation module is used for calculating the maintenance quality evaluation score of the maintenance unit to be tested according to the maintenance elevator fault control efficiency data, the maintenance elevator fault treatment efficiency data, the maintenance quality control data, the maintenance customer satisfaction data, the maintenance elevator internet of things monitoring capability data, the statistic elevator fault control efficiency data, the statistic elevator fault treatment efficiency data, the statistic maintenance quality control data, the statistic customer satisfaction data and the statistic elevator internet of things monitoring capability data.
9. An elevator maintenance quality evaluation system based on big data is characterized by comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method of any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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