CN111517195B - Data processing method for elevator acceleration sensor - Google Patents
Data processing method for elevator acceleration sensor Download PDFInfo
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- CN111517195B CN111517195B CN202010347613.8A CN202010347613A CN111517195B CN 111517195 B CN111517195 B CN 111517195B CN 202010347613 A CN202010347613 A CN 202010347613A CN 111517195 B CN111517195 B CN 111517195B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0018—Devices monitoring the operating condition of the elevator system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0087—Devices facilitating maintenance, repair or inspection tasks
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- Indicating And Signalling Devices For Elevators (AREA)
- Maintenance And Inspection Apparatuses For Elevators (AREA)
Abstract
The invention discloses a data processing method of an elevator acceleration sensor, which comprises the following steps: s1: the method comprises the following steps that an acceleration sensor collects vibration data in the running process of an elevator according to a preset sampling frequency to obtain a vibration curve; s2: reading each of the vibration curvesThe peak value X, i.e. the maximum value and the minimum value in each segment of continuously sampled data, is sequentially and respectively marked as X0，X1，…，Xn(n is a positive integer), and storing the partial data; s3: compressing other data between two consecutive X data; s4: selecting Y values, and recording as Y values0，Y1，…，Ym(m is n-1 and m is a positive integer), wherein Y isk＝Sk*|Xk+1‑XkI (wherein 0.1. ltoreq. SkK is not less than 1, K is not less than 1 and not more than m, and K is a positive integer); s5: mixing X0～XnAnd Y0～YmRecombined into a new curve, according to X0，Y0，X1，Y1，…，Ym，XnThe order of (a) is combined into a new curve. The invention can effectively compress data and store key characteristic values of the data, thereby ensuring the effectiveness and the transmission efficiency of the elevator curve.
Description
Technical Field
The invention relates to a data processing method, in particular to a data processing method of an elevator acceleration sensor.
Background
The mechanical vibration signal transmits and bears a large amount of important information contained in the working process of mechanical equipment, and online monitoring and acquisition of the mechanical vibration signal are one of key technologies in the field of mechanical engineering, particularly fault diagnosis technology. At present, acceleration sensors are applied to elevators more frequently, and the vibration conditions of the elevators in the front-back direction, the left-right direction and the vertical direction can be obtained through the acceleration sensors. The sampling frequency of the acceleration sensor is generally high, usually 256Hz or 512Hz, and the sampling data is usually stored by using a memory and read by an external device after the elevator runs. Due to the fact that the data volume is large, especially during wireless transmission, due to the limitation of the communication speed, the transmission time of one elevator vibration curve is long, and working efficiency is affected.
The elevator acceleration sensor is mainly used for collecting vibration data in the running process of an elevator and testing the peak value of the elevator at a constant-speed section, but when the sampling frequency is lowered, data of the wave crest and the wave trough can not be collected, so that the data are inaccurate. As shown in fig. 1, 10 indicates a sampling point (x), and 20 indicates a peak valley point (o), and it is apparent that the peak valley point is not collected due to the decrease in the sampling frequency.
Disclosure of Invention
The invention aims to provide a data processing method of an elevator acceleration sensor, which can effectively compress data, save key characteristic values of the data and ensure the effectiveness and the transmission efficiency of an elevator curve.
Aiming at the purposes, the invention adopts the following technical scheme:
an elevator acceleration sensor data processing method comprises the following steps:
s1: the method comprises the following steps that an acceleration sensor collects vibration data in the running process of an elevator according to a preset sampling frequency to obtain a vibration curve;
s2: reading each peak value X in the vibration curve, namely the maximum value and the minimum value in each section of continuous sampling data, and respectively recording the values as X in turn0，X1，…，Xn(n is a positive integer), and storing the partial data;
s3: compressing other data between two consecutive X data;
s4: selecting Y values, and recording as Y values0，Y1，…，Ym(m is n-1 and m is a positive integer), wherein Y isk＝Sk*|Xk+1-XkI (wherein 0.1. ltoreq. SkK is not less than 1, k is not less than 0 and not more than m, and k is an integer);
s5: mixing X0～XnAnd Y0～YmRecombined into a new curve, according to X0，Y0，X1，Y1，…，Ym，XnThe order of (a) is combined into a new curve.
As a preferable technical scheme, the sampling frequency of the acceleration sensor is more than or equal to 256 Hz.
Preferably, the sampling frequency of the acceleration sensor is 256Hz or 512 Hz.
Preferably, in step S2, the data is stored in a memory.
As a preferred embodiment, Sk＝(Xk+1+Xk)/(2*|Xk+1-Xk|)，Yk＝(Xk+1+Xk)/2。
The invention has the beneficial effects that: the data can be effectively compressed, key characteristic values of the data can be stored, and the effectiveness and the transmission efficiency of the elevator curve are guaranteed.
Drawings
FIG. 1 is a schematic diagram of a situation where a peak and a trough cannot be acquired due to a too low sampling frequency;
FIG. 2 is a schematic diagram of reading the peak value of the vibration curve;
FIG. 3 is a schematic diagram of the synthesis of a new curve.
Detailed Description
The present invention may be further described with the aim of providing a better understanding of the objects, structure, features, and functions of the invention.
The data processing method of the elevator acceleration sensor in the preferred embodiment of the invention comprises the following steps:
s1: the acceleration sensor collects vibration data in the running process of the elevator according to a preset sampling frequency to obtain a vibration curve. In order to ensure that data of peaks and troughs can be acquired, the sampling frequency is greater than or equal to 256Hz, for example, the sampling frequency can be 256Hz or 512 Hz. Namely, enough sampling frequency is ensured, and data which cannot be acquired from wave crests and wave troughs is avoided.
S2: as shown in fig. 2, read the vibration curveThe peak values X, i.e. the maximum value and the minimum value in each segment of continuously sampled data, are sequentially and respectively marked as X0，X1，…，Xn(n is a positive integer), and the partial data is saved by a memory.
S3: other data between two consecutive X data are compressed. That is, a plurality of collected data are contained between two X data, and the collected data are communicated and compressed, so that the transmission efficiency is improved.
S4: selecting Y values, and recording as Y values0，Y1，…，Ym(m is a positive integer), wherein Y isk＝Sk*|Xk+1-XkI (wherein 0.1. ltoreq. SkIs less than or equal to 1, k is less than or equal to 0 and less than or equal to m, and k is an integer).
For example, Y0＝S0*|X1-X0|，Y1＝S1*|X2-X1And so on.
S5: mixing X0～XnAnd Y0～YmAnd recombining into a new curve. In particular, according to X0，Y0，X1，Y1，…，Ym，XnThe sequence of (a) is combined into a new curve as shown in fig. 3.
To facilitate understanding, specific numerals are illustrated below.
Let n be 2, m be 1, and X be0＝100，X1＝20，X2＝90。
Then Y is0＝S1*|20-100|＝S*80，Y1＝S290-20| ═ S70, assuming S1Take 0.7, S20.8, then Y0＝56，Y156. Then can be based on X in turn0，Y0，X1，Y1，X2I.e. 100, 56, 20, 56, 90, make up the new curve.
Preferably, Y isk＝(Xk+1+Xk) /2, such that YkExactly Xk+1And XkMedian value in between. At this time, Sk＝(Xk+1+Xk)/(2*|Xk+1-Xk|)。
Taking the above data as an example, S1＝(20+100)/(2*80)＝0.75，S2(90+20)/(2 × 70) 11/14, corresponding to Y0＝60，Y1The new curves are composed of 55, i.e. 100, 60, 20, 55, 90.
The above numbers are only examples to explain the formula in detail, and do not limit the X value and the Y value in any way.
Through the data processing method, the data can be effectively compressed, the key characteristic values of the data can be stored, and the effectiveness and the transmission efficiency of the elevator curve are ensured.
The above detailed description is only for the purpose of illustrating the preferred embodiments of the present invention, and not for the purpose of limiting the scope of the present invention, therefore, all equivalent technical changes that can be made by applying the present invention are included in the scope of the present invention.
Claims (4)
1. An elevator acceleration sensor data processing method is characterized by comprising the following steps:
s1: the method comprises the steps that an acceleration sensor collects vibration data in the running process of an elevator according to a preset sampling frequency to obtain a vibration curve, wherein the sampling frequency is more than or equal to 256 Hz;
s2: reading each peak value X in the vibration curve, namely the maximum value and the minimum value in each section of continuous sampling data, and respectively recording the values as X in turn0，X1，…，Xn(n is a positive integer), and storing the partial data;
s3: compressing other data between two consecutive X data;
s4: selecting Y values, and recording as Y values0，Y1，…，Ym(m is n-1 and m is a positive integer), wherein Y isk＝Sk*|Xk+1-XkI (wherein 0.1. ltoreq. SkK is not less than 1, k is not less than 0 and not more than m, and k is an integer);
s5: mixing X0～XnAnd Y0～YmRecombined into a new curve, according to X0，Y0，X1，Y1，…，Ym，XnThe order of (a) is combined into a new curve.
2. The elevator acceleration sensor data processing method according to claim 1, characterized in that: the sampling frequency of the acceleration sensor is 512 Hz.
3. The elevator acceleration sensor data processing method according to claim 1, characterized in that: in step S2, the data is saved in the memory.
4. The elevator acceleration sensor data processing method according to any one of claims 1 to 3, characterized in that: sk＝(Xk+1+Xk)/(2*|Xk+1-Xk|)，Yk＝(Xk+1+Xk)/2。
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JPH11171422A (en) * | 1997-12-17 | 1999-06-29 | Hitachi Ltd | Maintenance device for elevator |
| CN102491140A (en) * | 2011-12-27 | 2012-06-13 | 阳西县电梯配件有限公司 | Characteristic-signal-based elevator safety checking device and elevator safety checking method |
| CN103795419B (en) * | 2014-01-27 | 2017-08-04 | 宁波良和路桥科技有限公司 | A kind of piecewise linearity compression method of Wave data Real Time Compression |
| US10112801B2 (en) * | 2014-08-05 | 2018-10-30 | Richard Laszlo Madarasz | Elevator inspection apparatus with separate computing device and sensors |
| US9385751B2 (en) * | 2014-10-07 | 2016-07-05 | Protein Metrics Inc. | Enhanced data compression for sparse multidimensional ordered series data |
| CN104410759B (en) * | 2014-11-14 | 2017-04-05 | 广州广日电梯工业有限公司 | A kind of elevator digital speech communication device and the means of communication |
| CN104944240A (en) * | 2015-05-19 | 2015-09-30 | 重庆大学 | Elevator equipment state monitoring system based on large data technology |
| US20210279578A1 (en) * | 2018-07-05 | 2021-09-09 | Datahoist, Inc. | Elevator Maintenance Solution Leveraging IOT Data, Cloud-Based Predictive Analytics and Machine Learning |
| CN110007854A (en) * | 2019-02-21 | 2019-07-12 | 湖南大唐先一科技有限公司 | One kind being based on time series data compression method and system |
| CN110626900B (en) * | 2019-09-23 | 2021-04-06 | 猫岐智能科技（上海）有限公司 | Equipment operation abnormity judgment method |
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