Method and system for monitoring elevator operating conditions and elevator component conditions

Abstract

The application discloses a kind of monitoring method and system of elevator operating state, wherein: obtaining the acceleration data of elevator car in vertical direction in state monitoring process;With the sampling value of acceleration data as the basis, the acceleration data obtained is divided into multiple sampling intervals in time domain, and the acceleration data of each sampling interval is correspondingly classified as positive acceleration interval, zero acceleration interval, negative acceleration interval;According to time sequence, select a sampling interval and at least two sampling intervals located after and adjacent to the sampling interval, determine the corresponding elevator operating state of selected sampling interval according to the type arrangement order of the acceleration data of selected sampling interval.The application also discloses a kind of monitoring method and system of elevator parts state, to determine whether elevator parts fails according to the acceleration data corresponding to each elevator operating state.The application can determine the operating state of elevator using only acceleration data, with strong universality and high accuracy.

Description

[0001] This application is a divisional application of the patent application with the application date of September 4, 2020, the application number of 202010925504.X, and the name of "Monitoring method and system of elevator running state and elevator component state". TECHNICAL FIELD

[0002] The present application relates to the field of elevators, in particular to a monitoring method and system for judging the running state of an elevator and the state of an elevator component according to acceleration signals. BACKGROUND

[0003] In modern society, elevators have become an integral part of infrastructure and are the main way of commuting between floors of high-rise buildings. The failure of an elevator will bring inconvenience to people's daily life and work, and even endanger life safety. Therefore, monitoring the health status of elevator components helps to discover component failure in time and avoid serious elevator failures.

[0004] Currently, vibration acceleration signals are usually used to monitor the state of components. During the running of the elevator, compared with the acceleration and deceleration running stage of the elevator, the working state of each main component is relatively stable during the uniform speed running stage of the elevator. Therefore, using the vibration acceleration data of this state for analysis can improve the efficiency and accuracy of component health status monitoring.

[0005] There are many ways to obtain the running speed of an elevator, for example, the speed of the elevator can be calculated by the speed of the traction machine. However, this method needs to specify the relevant data interface of the elevator to be tested and calibrate the time deviation between the speed data of the elevator and the acceleration data collected by the sensor, so the universality of this method is poor in different types of elevators. In addition, the vibration acceleration sensor can be used to obtain the speed data of the elevator by integrating the collected acceleration data. Although this method can be applied to all types of elevators, the measured acceleration data is limited by the sampling frequency of the sensor, and there is a difference with the true data, so the speed data obtained by integration will also be deviated.

[0006] Therefore, how to find a method that can be applied to all elevators and quickly and accurately determine the running state of the elevator is a technical problem to be solved. SUMMARY

[0007] The technical problem to be solved by the present application is to provide a monitoring method of the running state of an elevator, which can quickly and accurately determine the running state of the elevator by using only acceleration data and is applicable to all types of elevators. Meanwhile, the present application also provides a monitoring system of the running state of an elevator, a monitoring method and system of the state of an elevator component.

[0008] In order to solve the above problems, the application provides a monitoring method for an elevator running state, the elevator running state including a static state, an acceleration state, a uniform speed state and a deceleration state, wherein:

[0009] Acceleration data of an elevator car in a vertical direction is acquired in a state monitoring process;

[0010] Based on a sampling value of the acceleration data, the acquired acceleration data is divided into a plurality of sampling intervals in a time domain, and types of the acceleration data in each sampling interval are correspondingly classified as positive acceleration intervals, zero acceleration intervals and negative acceleration intervals;

[0011] According to a time sequence, one sampling interval and at least two sampling intervals adjacent to the sampling interval are selected, and a running state corresponding to the selected sampling interval is determined according to a type arrangement order of the acceleration data of the selected sampling interval.

[0012] In a further improved technical solution, the acceleration data is preprocessed before being divided, and the preprocessing includes the following sub-steps:

[0013] Step S1, filtering and denoising processing is performed on the acquired acceleration data;

[0014] Step S2, a direct current component in the acceleration data after the filtering and denoising processing is removed, and the direct current component is a zero point offset of the acceleration data when the elevator is static.

[0015] In a further improved technical solution, the sampling interval is divided in the following manner:

[0016] All sampling time points satisfying the condition (|a×(t i -Δt)|-a thr )×(|a×(t i +Δt)-a thr )<0 are selected, wherein Δt is a sampling interval of the acceleration data, a thr is a preset acceleration threshold, a thr >0, t i is the selected sampling time point, and a is an acceleration sampling value of the selected sampling time point.

[0017] The selected sampling time point is used as a demarcation time point of the sampling interval, and acceleration sampling values corresponding to sampling time between two adjacent demarcation time points form a sampling interval.

[0018] In a further improved technical solution, the type classification method of the acceleration data in the sampling interval is as follows:

[0019] The average value of all acceleration data in each sampling interval is calculated, wherein the average value of the acceleration in the i th sampling interval is a i ;

[0020] The average value of the acceleration in each sampling interval a i is compared with the size relationship of the acceleration threshold value a thr ;

[0021] When a i >a thr , the type of the sampling interval is a positive acceleration interval;

[0022] When -a thr <a i <a thr , the type of the sampling interval is a zero acceleration interval;

[0023] When a i <-a thr , the type of the sampling interval is a negative acceleration interval.

[0024] In the further improved technical solution, the type classification method of the acceleration data in the sampling interval is as follows:

[0025] The average value of all acceleration data in each sampling interval is calculated, wherein the average value of the acceleration in the i th sampling interval is a i ;

[0026] The average value of the acceleration in each sampling interval a i is compared with the size relationship of the maximum acceleration a max in the state monitoring process;

[0027] When a i >α×a max , the type of the sampling interval is a positive acceleration interval;

[0028] When -α×a max <a i <α×a max , the type of the sampling interval is a zero acceleration interval;

[0029] When a i <-α×a thr , the type of the sampling interval is a negative acceleration interval;

[0030] Wherein, α is a weight coefficient, and α ∈ (0, 0.5].

[0031] In the further improved technical solution, the sampling duration of the divided sampling interval is judged, and when the sampling duration of a certain sampling interval is less than the interval duration threshold T thrWhen the type of the acceleration data of the adjacent sampling interval is the same, the adjacent sampling interval is merged into one sampling interval.

[0032] In the further improved technical solution, when the types of the acceleration data of the adjacent sampling intervals are the same, the adjacent sampling intervals are merged into one sampling interval.

[0033] In the further improved technical solution, the determination of the elevator running state is as follows:

[0034] One sampling interval and two sampling intervals located after the sampling interval and adjacent to the sampling interval are selected in time sequence;

[0035] If the types of the acceleration data of the selected three sampling intervals are positive acceleration interval, zero acceleration interval and negative acceleration interval in sequence, it is determined that the elevator running states corresponding to the three sampling intervals are positive acceleration state, positive uniform speed state and positive deceleration state in sequence.

[0036] If the types of the acceleration data of the selected three sampling intervals are negative acceleration interval, zero acceleration interval and positive acceleration interval in sequence, it is determined that the elevator running states corresponding to the three sampling intervals are reverse acceleration state, reverse uniform speed state and reverse deceleration state in sequence.

[0037] In the further improved technical solution, the determination of the elevator running state is as follows:

[0038] One sampling interval and three sampling intervals located after the sampling interval and adjacent to the sampling interval are selected in time sequence;

[0039] If the types of the acceleration data of the selected four sampling intervals are zero acceleration interval, positive acceleration interval, zero acceleration interval and negative acceleration interval in sequence, it is determined that the elevator running states corresponding to the four sampling intervals are static state, positive acceleration state, positive uniform speed state and positive deceleration state in sequence.

[0040] If the types of the acceleration data of the selected four sampling intervals are zero acceleration interval, negative acceleration interval, zero acceleration interval and positive acceleration interval in sequence, it is determined that the elevator running states corresponding to the four sampling intervals are static state, reverse acceleration state, reverse uniform speed state and reverse deceleration state in sequence.

[0041] Meanwhile, in order to solve the above technical problems, the application also provides a monitoring system for elevator running state, comprising:

[0042] An acceleration sensor is used to acquire acceleration data of the elevator car in the vertical direction during the running of the elevator;

[0043] A signal processing unit is used to divide and classify the acceleration data collected by the acceleration sensor into sampling intervals.

[0044] an elevator operation state judging unit for judging an elevator operation state according to the sampling interval and the corresponding acceleration data classification output by the signal processing unit;

[0045] a data transmission unit for transmitting the acceleration data and the elevator operation state;

[0046] a data storage unit for storing the acceleration data and the elevator operation state; wherein,

[0047] the signal processing unit divides the obtained acceleration data into multiple sampling intervals in the time domain according to the sampling values of the acceleration sensor and correspondingly classifies the types of acceleration data in each sampling interval into positive acceleration intervals, zero acceleration intervals and negative acceleration intervals;

[0048] the elevator operation state judging unit selects one sampling interval and at least two sampling intervals located after and adjacent to the sampling interval in time sequence, and determines the corresponding elevator operation state of the selected sampling interval according to the type arrangement order of the acceleration data of the selected sampling interval.

[0049] In addition, the application also provides an elevator component state monitoring method realized by the above elevator operation state monitoring method, wherein:

[0050] obtaining acceleration data of an elevator car in the vertical direction in a state monitoring process;

[0051] dividing the obtained acceleration data into multiple sampling intervals in the time domain according to the sampling values of the acceleration data, and correspondingly classifying the types of acceleration data in each sampling interval into positive acceleration intervals, zero acceleration intervals and negative acceleration intervals;

[0052] selecting one sampling interval and at least two sampling intervals located after and adjacent to the sampling interval in time sequence, and determining the corresponding elevator operation state of the selected sampling interval according to the type arrangement order of the acceleration data of the selected sampling interval, wherein the elevator operation state includes a static state, an acceleration state, a uniform speed state and a deceleration state;

[0053] judging whether an elevator component has a fault according to the acceleration data corresponding to each elevator operation state.

[0054] In a further improved technical solution, a feature value is extracted from the acceleration data corresponding to the uniform speed state, and whether an elevator component has a fault is judged according to the feature value.

[0055] Meanwhile, the application also provides an elevator component state monitoring system, comprising:

[0056] An acceleration sensor is configured to acquire acceleration data of the elevator car in the vertical direction during the operation of the elevator.

[0057] A signal processing unit is configured to divide and classify the acceleration data acquired by the acceleration sensor in sampling intervals.

[0058] An elevator operation state judging unit is configured to judge the operation state of the elevator according to the classification of the sampling intervals and the corresponding acceleration data output by the signal processing unit.

[0059] A data transmission unit is configured to transmit the acceleration data and the operation state of the elevator.

[0060] A data storage unit is configured to store the acceleration data and the operation state of the elevator.

[0061] A state monitoring unit is configured to judge the state of the elevator parts according to the acceleration data corresponding to the operation state of the elevator.

[0062] The signal processing unit divides the acquired acceleration data in the time domain into multiple sampling intervals according to the sampling values of the acceleration sensor and classifies the types of the acceleration data in each sampling interval as positive acceleration intervals, zero acceleration intervals and negative acceleration intervals.

[0063] The elevator operation state judging unit selects one sampling interval and at least two sampling intervals adjacent to the selected sampling interval in time sequence, and determines the operation state of the elevator corresponding to the selected sampling interval according to the type arrangement order of the acceleration data of the selected sampling interval.

[0064] In the further improved technical solution, the state monitoring unit extracts a characteristic value from the acceleration data corresponding to the uniform speed state, and judges whether the elevator parts have failed according to the characteristic value.

[0065] Compared with the prior art, the technical effects achieved by the present application are as follows:

[0066] Firstly, the elevator operation state monitoring method and system of the present application divide the acquired acceleration data into multiple sampling intervals and classify the acceleration data in the sampling intervals, and determine the operation state of the elevator according to the type arrangement order of the acceleration data of at least three adjacent sampling intervals selected in time sequence. This method does not need to further integrate the acceleration data, but can directly determine the operation state of the elevator (including positive / negative acceleration state, positive / negative uniform speed state, positive / negative deceleration state and static state) only through the acceleration data. Therefore, the present application is suitable for all types of elevators, and solves the problem of deviation of the speed data in the acceleration integration process, thereby significantly improving the accuracy.

[0067] Secondly, the elevator operation state monitoring method and system can further filter out the sampling interval corresponding to the impact that may occur during the elevator operation due to the installation defects of the elevator, so as to avoid the influence of the sudden impact during the elevator operation on the division of the sampling interval;

[0068] Thirdly, the elevator operation state monitoring method and system can determine the sampling time length of the sampling interval, and determine the elevator operation state according to the type arrangement order of the acceleration data of the four adjacent sampling intervals selected in time sequence, so as to solve the misjudgment problem caused by the short running distance of the elevator (such as moving only one floor) and the lack of uniform speed running stage during the running;

[0069] Fourthly, the elevator part state monitoring method and system directly determines the elevator operation state according to the acceleration data, and accurately detects the running state of the elevator parts according to the acceleration data of the specific operation state (such as the uniform speed state). BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 It is a schematic diagram of the elevator operation state monitoring system of the present application;

[0071] Figure 2 It is a flowchart of embodiment one of the elevator operation state monitoring method of the present application;

[0072] Figure 3 It is a flowchart of embodiment two of the elevator operation state monitoring method of the present application;

[0073] Figure 4 It is a schematic diagram of a set of acceleration data of the elevator car in the vertical direction measured during the operation of the elevator of the present application;

[0074] Figure 5 It is Figure 4 It is a data schematic diagram of the acceleration data shown after filtering and denoising, removing the direct current component and preprocessing;

[0075] Figure 6 It is Figure 5 It is a data schematic diagram of the acceleration data shown after the sampling interval division and classification according to embodiment three and embodiment four;

[0076] Figure 7 It is a marker schematic diagram of the elevator operation state determined according to the type arrangement order of the acceleration data of embodiment three or embodiment four and Figure 6

[0077] Figure 8 ​This is a schematic diagram showing the preprocessed version of another set of acceleration data of the elevator car in the vertical direction, measured during elevator operation according to the present invention.

[0078] Figure 9 To follow Example 5 Figure 8 The diagram shows the acceleration data after sampling interval division and classification.

[0079] Figure 10 According to Example 5 and Figure 9 The diagram shows the labels indicating the elevator's operating status, determined by the order of the acceleration data types.

[0080] Figure 11 This is a schematic diagram showing the preprocessed result of another set of acceleration data of the elevator car in the vertical direction, measured during elevator operation according to the present invention.

[0081] Figure 12 To follow Example 3 Figure 11 The diagram shows the acceleration data after sampling interval division and classification.

[0082] Figure 13 To follow Example Six Figure 11 The diagram shows the acceleration data after sampling interval division and classification.

[0083] Figure 14 According to Example Six and Figure 13 The diagram shows the labels indicating the elevator's operating status, determined by the order of the acceleration data types.

[0084] Figure 15 This is a schematic diagram of the elevator component status monitoring system of the present invention;

[0085] Figure 16 This is a flowchart of the elevator component status monitoring method of the present invention;

[0086] Figure 17 This is a schematic diagram of a certain characteristic value of the acceleration data of the elevator under two different operating conditions. Detailed Implementation

[0087] The embodiments of the present invention are described below with reference to the accompanying drawings and specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Specific details are set forth in the following description to provide a thorough understanding of the present invention; however, the present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be based on different viewpoints and applications. Those skilled in the art can make various similar extensions and substitutions without departing from the spirit of the present invention.

[0088] First, the elevator operation state monitoring system of the first aspect of the present application is described in conjunction with the drawings through a specific embodiment.

[0089] Figure 1 is a schematic diagram of the elevator operation state monitoring system of the present application, which comprises: an acceleration sensor 1 installed on the elevator car side, a data transmission unit 2, a data storage unit 3, a signal processing unit 4, and an elevator operation state judgment unit 5. In addition, Figure 1 Also schematically listed are some elevator components related to the elevator operation state monitoring system of the present application, including the elevator car 11, the traction steel wire rope 12, the traction sheave 13, the guide sheave 14, the counterweight 15, and the compensation rope 16. When the traction sheave 13 rotates, the elevator car 11 ascends or descends along the vertical direction under the action of the traction steel wire rope 12.

[0090] In this embodiment, the acceleration sensor 1 acquires the acceleration data of the elevator car 11 in the vertical direction during the elevator operation. The signal processing unit 4 is responsible for preprocessing the acceleration data, dividing the sampling interval, and classifying, wherein the preprocessing includes filtering and denoising the acquired acceleration data and removing the direct current component in the acceleration data after filtering and denoising, the direct current component being the zero point offset of the acceleration data when the elevator is stationary. The signal processing unit 4 divides the acquired acceleration data into multiple sampling intervals in the time domain and classifies the types of acceleration data in each sampling interval as positive acceleration interval, zero acceleration interval, and negative acceleration interval according to the sampling values of the acceleration sensor.

[0091] Second, the elevator operation state monitoring method of the second aspect of the present application is described in conjunction with the drawings through a specific embodiment.

[0092] Embodiment One

[0093] The elevator operation state monitoring method of this embodiment, as shown in Figure 2 The elevator operation state includes the static state, the acceleration state, the uniform speed state, and the deceleration state, which includes:

[0094] Obtaining acceleration data of an elevator car in a vertical direction in a state monitoring process;

[0095] According to a sample value of the acceleration data, the obtained acceleration data is divided into a plurality of sample intervals in a time domain, and types of the acceleration data in each sample interval are correspondingly classified into a positive acceleration interval, a zero acceleration interval, and a negative acceleration interval.

[0096] According to a type arrangement order of the acceleration data of the selected sample interval, a running state of the elevator corresponding to the selected sample interval is determined.

[0097] Embodiment Two

[0098] On the basis of Embodiment One, the present embodiment divides the obtained acceleration data into sample intervals after pre-processing, as shown in the following steps: Figure 3 The pre-processing includes the following sub-steps:

[0099] Step S1, filtering and denoising the obtained acceleration data, thereby reducing the interference of noise signals.

[0100] Step S2, removing a direct current component in the acceleration data after filtering and denoising, thereby reducing a measurement deviation caused by sensor zero drift, wherein the direct current component is a zero point offset of the acceleration data when the elevator is stationary.

[0101] Embodiment Three

[0102] On the basis of Embodiment Two, the present embodiment further details each step of the monitoring method of the elevator running state.

[0103] The acceleration data after pre-processing is divided into sample intervals, as follows:

[0104] All sample time points satisfying the condition (a i -Δt)-a thr )×(a i +Δt)-a thr )<0 are selected, wherein Δt is a sampling interval of the acceleration data, a thr is a preset acceleration threshold, a thr >0, t i is the selected sample time point, and a is an acceleration sample value of the selected sample time point.

[0105] The selected sample time points are used as boundary time points of the sample intervals, and acceleration sample values corresponding to a sampling time between two adjacent boundary time points form a sample interval.

[0106] More preferably, the acceleration threshold a thr The value of is close to zero.

[0107] The classification method for acceleration data types within the sampling interval is as follows:

[0108] Calculate the average value of all acceleration data within each sampling interval, where the average acceleration value of the i-th sampling interval is a. i ;

[0109] Compare the average acceleration a in each sampling interval i With the acceleration threshold a thr The size relationship (can be determined based on the elevator's performance parameters);

[0110] when a i >a thr At that time, the sampling interval is of the positive acceleration interval type;

[0111] when-a thr <a i <a thr At that time, the sampling interval is of type zero acceleration interval;

[0112] when a i <-a thr At that time, the sampling interval is of the negative acceleration interval type.

[0113] The elevator's operating status is determined as follows:

[0114] Select a sampling interval and two sampling intervals that follow and are adjacent to the sampling interval according to the time sequence;

[0115] If the acceleration data of the three selected sampling intervals are in the order of positive acceleration interval, zero acceleration interval, and negative acceleration interval, then the elevator running state corresponding to the three sampling intervals is determined to be positive acceleration state, positive constant speed state, and positive deceleration state, respectively.

[0116] If the acceleration data types of the three selected sampling intervals are negative acceleration interval, zero acceleration interval, and positive acceleration interval in sequence, then the elevator running states corresponding to the three sampling intervals are determined to be reverse acceleration state, reverse constant speed state, and reverse deceleration state in sequence.

[0117] The following uses a set of acceleration data of the elevator car in the vertical direction measured by the elevator operation monitoring system during elevator operation, combined with... Figures 4 to 7 This embodiment will be described in detail.

[0118] like Figure 4The diagram shows the vertical acceleration data of the elevator car 11 measured by the accelerometer 1 during elevator operation. The vertical axis represents the sampled acceleration value, and the horizontal axis represents the data point number. In this example, the sampling frequency of the accelerometer 1 is 4000Hz, meaning 4000 data points represent 1 second. In this embodiment of the invention, the vertically upward direction is considered the positive acceleration direction. Based on experience, it is known that... Figure 4 The acceleration data shown records one upward cycle and one downward cycle of the elevator.

[0119] because Figure 4 The raw acceleration data shown has many spikes (numerous interference signals), making it difficult to directly divide the data into sampling intervals. Therefore, it is necessary to... Figure 4 The acceleration data in the image undergoes preprocessing. The preprocessed acceleration data, including filtering, noise reduction, and removal of the DC component, is as follows: Figure 5 As shown, the preprocessed acceleration data is relatively smooth, making it easier to divide and classify the sampling intervals. Figure 5 The two horizontal lines in the image represent the acceleration thresholds used to divide the sampling intervals, namely a thr and -a thr .

[0120] According to the sampling interval division method and the acceleration data classification method of the sampling interval in this embodiment, Figure 5 The acceleration data shown is divided into sampling intervals and classified, and the results are as follows: Figure 6 As shown. Taking the first half of the data (upward cycle) as an example, combined with... Figure 5 and Figure 6 The process of dividing and classifying sampling intervals is explained in detail:

[0121] 1) For data points 4000–23200, the acceleration data are all within the threshold ±a. thr Inside, the average acceleration a i With acceleration threshold a thr The size relationship is -a thr <a i <a thr It is divided into interval 1, which is the zero acceleration interval;

[0122] 2) For data points 23200–35400, the acceleration data are all greater than the threshold a. thr Average acceleration a i With the acceleration threshold a thr The size relationship is a i >a thr It is divided into interval 2, which is the positive acceleration interval;

[0123] 3) For data points 35400–66600, the acceleration data are all within the threshold ±a. thr Inside, the average acceleration a i With acceleration threshold a thr The size relationship is -a thr <a i <a thr It is divided into interval 3, which is the zero acceleration interval;

[0124] 4) For data points 66600–78200, the acceleration is less than the threshold -a. thr Average acceleration a i With acceleration threshold a thr The size relationship is a i <-a thr It is divided into interval 4, which is the negative acceleration interval;

[0125] 5) For data points 78200–130700, the acceleration data are all within the threshold ±a. thr Inside, the average acceleration a i With acceleration threshold a thr The size relationship is -a thr <a i <a thr It is divided into 5 intervals, with interval 5 being the zero acceleration interval.

[0126] Figure 7 This is a schematic diagram of the elevator operating status label obtained after judging the order of acceleration data types in the sampling interval. Specifically, Figure 7 The definitions of the elevator's operating status labels are as follows: 0 indicates stationary, 1 indicates upward acceleration (positive acceleration), 2 indicates upward constant speed (positive constant speed), 3 indicates upward deceleration (positive deceleration), -1 indicates downward acceleration (reverse acceleration), -2 indicates downward constant speed (reverse constant speed), and -3 indicates downward deceleration (reverse deceleration). Using the first half of the data (interval 1 to interval 5) as an example, the process of determining the elevator's operating status will be explained in detail:

[0127] 1) Select interval 1, interval 2, and interval 3 according to the time sequence. The types of the three sampling intervals are zero acceleration interval, positive acceleration interval, and zero acceleration interval, respectively, which do not meet the characteristics of the upward cycle or the downward cycle.

[0128] 2) Next, select interval 2, interval 3, and interval 4. The types of the three sampling intervals are positive acceleration interval, zero acceleration interval, and negative acceleration interval, respectively, which meet the characteristics of the upward cycle. Therefore, the elevator operation states corresponding to interval 2, interval 3, and interval 4 are upward acceleration state, upward constant speed state, and upward deceleration state, respectively, and the corresponding operation state labels are 1, 2, and 3.

[0129] 3) Since the corresponding elevator running states of interval 2 to interval 4 have been judged, interval 5 and interval 6, interval 7 are selected in time sequence, and the types of the three sampling intervals are zero acceleration interval, negative acceleration interval, zero acceleration interval in turn, which does not meet the characteristics of the uplink period or the downlink period; thus, interval 1 to interval 5 have all been distinguished;

[0130] 4) Interval 1 and interval 5 belong to zero acceleration interval, but do not belong to the uplink period or the downlink period, so they are classified as static state, and the corresponding running state label is 0.

[0131] Example Four

[0132] The difference between this example and example three is that the determination method of the elevator running state selects four sampling intervals each time, which is as follows:

[0133] A sampling interval and three sampling intervals located after and adjacent to the sampling interval are selected in time sequence;

[0134] If the types of the acceleration data of the selected four sampling intervals are zero acceleration interval, positive acceleration interval, zero acceleration interval, negative acceleration interval in turn, then the corresponding elevator running states of the four sampling intervals are static state, positive acceleration state, positive uniform speed state, positive deceleration state in turn;

[0135] If the types of the acceleration data of the selected four sampling intervals are zero acceleration interval, negative acceleration interval, zero acceleration interval, positive acceleration interval in turn, then the corresponding elevator running states of the four sampling intervals are static state, reverse acceleration state, reverse uniform speed state, reverse deceleration state in turn.

[0136] This example still uses the acceleration data used in example three for illustration, specifically, still taking the first half data (interval 1 to interval 5) as an example, the judgment process of the elevator running state is specifically explained:

[0137] 1) Interval 1 and interval 2, interval 3, interval 4 are selected in time sequence first, and the types of the four sampling intervals are zero acceleration interval, positive acceleration interval, zero acceleration interval, negative acceleration interval in turn, so the corresponding elevator running states of interval 1, interval 2, interval 3, interval 4 are static state, uplink acceleration state, uplink uniform speed state, uplink deceleration state in turn, and the corresponding running state labels are 0, 1, 2, 3 respectively;

[0138] 2) Since the corresponding elevator running states of the interval 1 to the interval 4 have been judged, the interval 5 and the interval 6, the interval 7, the interval 8 are selected according to the time sequence, and the types of the four sampling intervals are in turn zero acceleration interval, negative acceleration interval, zero acceleration interval, positive acceleration interval, thus the corresponding elevator running states of the interval 5, the interval 6, the interval 7, the interval 8 are in turn static state, downward acceleration state, downward uniform speed state, downward deceleration state, and the corresponding running state labels are respectively 0, -1, -2, -3; thus, the interval 1~interval 5 have been all distinguished.

[0139] In the foregoing four embodiments, the elevator running state monitoring method divides the obtained acceleration data into multiple sampling intervals, classifies the acceleration data in the sampling intervals, and determines the elevator running state according to the type arrangement order of the acceleration data of at least three adjacent sampling intervals selected according to the time sequence, which does not need to further integrate the acceleration data, and can directly determine the elevator running state (including positive / negative acceleration state, positive / negative uniform speed state, positive / negative deceleration state, static state) by combining the interval division and arrangement order of the acceleration data with the elevator running law, thus being applicable to all types of elevators, and solving the problem of deviation of the velocity data caused in the acceleration integration process, and can significantly improve the accuracy of the elevator running state judgment result.

[0140] Embodiment five

[0141] On the basis of the embodiment two, the embodiment further specifically describes each step of the elevator running state monitoring method.

[0142] The acceleration data after the preprocessing is divided into sampling intervals, and the specific method is as follows:

[0143] All sampling time points satisfying the condition (a i -Δt)-a thr )×(a i +Δt)-a thr )<0 are selected, wherein Δt is the sampling interval of the acceleration data, a thr is a preset acceleration threshold, a thr >0, t i is the selected sampling time point, and a is the acceleration sampling value of the selected sampling time point.

[0144] The selected sampling time point is taken as the dividing time point of the sampling interval, and the acceleration sampling values corresponding to the sampling time between the adjacent two dividing time points form a sampling interval.

[0145] More preferably, the acceleration threshold a thr is close to zero.

[0146] The type classification method of acceleration data in the sampling interval is as follows:

[0147] The average value of all acceleration data in each sampling interval is calculated, wherein the acceleration average value of the i th sampling interval is a i ;

[0148] The size relationship between the acceleration average value a i of each sampling interval and the maximum acceleration a max in the state monitoring process is compared.

[0149] When a i > a max , the type of the sampling interval is a positive acceleration interval.

[0150] When - a max < a i < a max , the type of the sampling interval is a zero acceleration interval.

[0151] When a i < - a thr , the type of the sampling interval is a negative acceleration interval.

[0152] Wherein, a is a weight coefficient, a ∈ (0, 0.5].

[0153] When the types of acceleration data of adjacent sampling intervals are the same, the adjacent sampling intervals are merged into one sampling interval.

[0154] The determination method of the elevator running state is as follows:

[0155] A sampling interval and two sampling intervals located after and adjacent to the sampling interval are selected in time sequence.

[0156] If the types of acceleration data of the selected three sampling intervals are in order as a positive acceleration interval, a zero acceleration interval and a negative acceleration interval, it is determined that the running states of the three sampling intervals are in order as a positive acceleration state, a positive uniform speed state and a positive deceleration state.

[0157] If the types of acceleration data of the selected three sampling intervals are in order as a negative acceleration interval, a zero acceleration interval and a positive acceleration interval, it is determined that the running states of the three sampling intervals are in order as a reverse acceleration state, a reverse uniform speed state and a reverse deceleration state.

[0158] The following uses another group of acceleration data of the elevator car in the vertical direction measured by the elevator running state monitoring system when the elevator runs to combine Figures 8 to 10 to make a detailed description of the embodiment.

[0159] Figure 8 is another set of pre-processed results of acceleration data measured by the embodiment when the elevator is running. Compared with Figure 5 , Figure 8 there is a fluctuation interval with a larger vibration in the uniform speed phase of the upward movement, and the amplitude exceeds the acceleration threshold value a thr in embodiment three.

[0160] If the sampling interval division method of embodiment three is used to divide and classify the acceleration data shown in Figure 8 , the results are shown in Figure 9 . It can be seen that Figure 8 the fluctuation interval is divided into interval 4, and its type is a positive acceleration interval, which does not conform to the actual situation.

[0161] Figure 10 is a schematic diagram of interval division and classification of the acceleration data shown in Figure 8 according to the sampling interval division method of the embodiment. According to the division method of the embodiment, Figure 8 the average acceleration a i of interval 4 in is much smaller than a x a max (hypothetical a = 0.4), so interval 4 is classified as a zero acceleration interval; because interval 4 is a zero acceleration interval like adjacent intervals 3 and 5, interval 4 is merged with adjacent intervals 3 and 5, thereby successfully eliminating the influence of the vibration fluctuation on interval division and classification.

[0162] Figure 10 The process of determining the elevator running state according to the arrangement order of the acceleration data type in the sampling interval in Figure 10 is the same as that of embodiment three, and of course, the elevator running state of each interval in can be determined according to the elevator running state determination method in embodiment four, which can be easily realized by those skilled in the art, so it is not repeated here.

[0163] In this embodiment, the elevator running state monitoring method fully considers the vibration fluctuation in the elevator running, and uses the size relationship between the acceleration average value and the acceleration maximum value of the sampling interval to further screen out the sampling interval corresponding to the vibration impact that may occur due to elevator installation defects during elevator running, and reasonably merge this abnormal fluctuation interval, thereby avoiding the influence of sudden impact during elevator running on the division of the sampling interval.

[0164] Embodiment six

[0165] On the basis of embodiment two, this embodiment further details each step of the elevator running state monitoring method.

[0166] The acceleration data after preprocessing is divided into sampling intervals, specifically as follows:

[0167] All sampling time points satisfying the condition (|a×(t i -Δt)-a thr )×(|a×(t i +Δt)-a thr )<0 are selected, wherein Δt is the sampling interval of the acceleration data, a thr is a preset acceleration threshold, a thr >0 and close to zero, t i is the selected sampling time point, and a is the acceleration sampling value at the selected sampling time point.

[0168] The selected sampling time points are taken as the dividing time points of the sampling intervals, and the acceleration sampling values corresponding to the sampling time between two adjacent dividing time points form a sampling interval.

[0169] The sampling duration of the divided sampling interval is judged, and when the sampling duration of a sampling interval is less than the interval duration threshold T thr , the sampling interval is merged into the previous sampling interval adjacent thereto.

[0170] The type classification method of the acceleration data in the sampling interval is as follows: the average value of all acceleration data in each sampling interval is calculated, wherein the acceleration average value of the i-th sampling interval is a i ; the size relationship between the acceleration average value a i of each sampling interval and the acceleration threshold a thr is compared; when a i >a thr , the type of the sampling interval is a positive acceleration interval; when -a thr <a i <a thr , the type of the sampling interval is a zero acceleration interval; and when a i <-a thr , the type of the sampling interval is a negative acceleration interval.

[0171] Alternatively, the type classification method of the acceleration data in the sampling interval is as follows: the average value of all acceleration data in each sampling interval is calculated, wherein the acceleration average value of the i-th sampling interval is a i ; the size relationship between the acceleration average value a i of each sampling interval and the maximum acceleration a max in the state monitoring process is compared; when a i >α×a max , the type of the sampling interval is a positive acceleration interval; when -α×a max <a i<α×a max When a, the sampling interval is of type zero acceleration interval; i <-α×a thr When the sampling interval is of type negative acceleration interval, α is a weighting coefficient, α∈(0,0.5).

[0172] The elevator's operating status is determined as follows:

[0173] Select a sampling interval and three adjacent sampling intervals after the selected sampling interval according to the time sequence;

[0174] If the acceleration data of the four selected sampling intervals are in the following order: zero acceleration interval, positive acceleration interval, zero acceleration interval, and negative acceleration interval, then the elevator running state corresponding to the four sampling intervals is determined to be in the following order: stationary state, positive acceleration state, positive constant speed state, and positive deceleration state.

[0175] If the acceleration data types of the four selected sampling intervals are, in order, zero acceleration interval, negative acceleration interval, zero acceleration interval, and positive acceleration interval, then the elevator running states corresponding to the four sampling intervals are determined to be, in order, stationary state, reverse acceleration state, reverse constant speed state, and reverse deceleration state.

[0176] The following section combines another set of acceleration data of the elevator car in the vertical direction measured by the elevator operation monitoring system during elevator operation. Figures 11 to 14 This embodiment will be described in detail.

[0177] Figure 11 This is a schematic diagram showing the preprocessed result of another set of acceleration data measured during elevator operation in this embodiment. Because the elevator's travel distance is relatively short, this set of acceleration data lacks a constant velocity state. If the sampling interval is divided and classified according to Embodiment 3, the result is... Figure 12 A schematic diagram, such as Figure 12 As shown, the acceleration data in intervals 3 and 7 are within the acceleration threshold ±a. thr Therefore, the area is divided into zero acceleration intervals, which may lead to the mistaken perception that the stationary state in intervals 3 and 7 is a uniform state.

[0178] In this embodiment, a judgment is added to the sampling duration of the divided sampling intervals, because Figure 12 The sampling durations of intervals 3 and 7 are less than the interval duration threshold T. thr Therefore, interval 3 is merged into interval 2, and interval 7 is merged into interval 6. The final result is as follows: Figure 13 As shown.

[0179] According to the elevator operation status judgment method of this embodiment and Figure 13The arrangement order of the sampling interval types shown judges the elevator running state, and the result is as follows Figure 14 The specific process is shown as follows

[0180] 1) Select interval 1 and interval 2, interval 3 and interval 4, the types of the four sampling intervals are zero acceleration interval, negative acceleration interval, positive acceleration interval and zero acceleration interval in turn, which does not meet the characteristics of the uplink period or the downlink period;

[0181] 2) Select interval 2 and interval 3, interval 4 and interval 5, the types of the four sampling intervals are negative acceleration interval, positive acceleration interval, zero acceleration interval and negative acceleration interval in turn, which does not meet the characteristics of the uplink period or the downlink period;

[0182] 3) Select interval 3 and interval 4, interval 5 and interval 6, the types of the four sampling intervals are positive acceleration interval, zero acceleration interval, negative acceleration interval and positive acceleration interval in turn, which does not meet the characteristics of the uplink period or the downlink period;

[0183] 4) Select interval 4 and interval 5, interval 6 and interval 7, the types of the four sampling intervals are zero acceleration interval, negative acceleration interval, positive acceleration interval and zero acceleration interval in turn, which does not meet the characteristics of the uplink period or the downlink period;

[0184] 5) Since the arrangement order of each interval cannot meet the judgment standard of the embodiment, the uniform speed state does not exist in the elevator running state determined thereby, which is consistent with the actual situation.

[0185] In the embodiment, the elevator running state monitoring method also judges the sampling time length of the sampling interval, and determines the elevator running state according to the arrangement order of the acceleration data types of the four adjacent sampling intervals selected in time sequence, so as to solve the misjudgment problem caused by the short running distance of the elevator (such as moving only one floor) so that there is no uniform speed running stage in the running process.

[0186] Thirdly, the elevator component state monitoring system of the third aspect of the present application is described in combination with the specific embodiments and the accompanying drawings.

[0187] Figure 15 is a composition schematic diagram of the elevator component state monitoring system of the present application, in addition to the acceleration sensor 1 installed on the elevator car side, the data transmission unit 2, the data storage unit 3, the signal processing unit 4, the elevator running state judgment unit 5 included in the elevator running state monitoring system, the system also includes a state monitoring unit 6.

[0188] In the embodiment, the state monitoring unit 6 is responsible for judging the state of the elevator parts according to the acceleration data corresponding to the elevator running state, specifically, the state monitoring unit 6 extracts the required characteristic value from the acceleration data corresponding to the uniform speed state, and judges whether the elevator parts have faults according to the characteristic value. In the whole process of elevator parts state monitoring, the data transmission unit 2 is responsible for transmitting the acceleration data, the elevator running state, the characteristic value of the acceleration data and other data, and the data storage unit 3 is responsible for storing the above related data.

[0189] Among them, the characteristic value of the acceleration data for fault diagnosis is more, for example, the characteristic value in the time domain has peak-to-peak value, root mean square value, variance, kurtosis, skewness, wave crest factor, margin factor, average power, etc., the characteristic value in the frequency domain has peak frequency, average frequency, frequency skewness, frequency kurtosis, etc., in addition, it can also be the characteristic value of time-frequency domain.

[0190] Finally, the elevator parts state monitoring method of the fourth aspect of the present application is described by specific embodiments in combination with the drawings.

[0191] On the basis of the six embodiments of the aforementioned elevator running state monitoring method, the elevator parts state monitoring method of the present embodiment, as shown in Figure 16 The method judges whether the elevator parts have faults according to the acceleration data corresponding to the determined elevator running state.

[0192] Specifically, the acceleration data of a specific running state can be selected, the characteristic value reflecting the running state of the parts can be extracted, and the health status of the elevator parts can be monitored by continuously paying attention to the numerical change of the characteristic value, thereby providing the possibility for realizing elevator on-demand maintenance.

[0193] Compared with the acceleration of the elevator acceleration and deceleration, the working state of each main part of the elevator is relatively stable when the elevator runs at a uniform speed, therefore, the characteristic value is preferably extracted from the acceleration data corresponding to the uniform speed state, and the characteristic value is used to judge whether the elevator parts have faults, which can more improve the efficiency and accuracy of the health status monitoring of the parts.

[0194] Figure 17 For a certain characteristic value of the acceleration data of the elevator running at a uniform speed under two working conditions, the vertical axis is the characteristic value, the horizontal axis is the data point serial number, and each data point represents one test. "+" represents the acceleration characteristic value of the uniform speed running extracted under the normal working condition, and "△" represents the acceleration characteristic value of the uniform speed running extracted under the working condition of the part failure. Obviously, there is a significant difference between the distribution of the characteristic values under the two working conditions, therefore, the corresponding part can be judged whether it has faults according to the characteristic value.

[0195] The application is described in detail above with specific embodiments, and the above embodiments are only the preferred embodiments of the application, and the application is not limited to the above embodiments. Equivalent substitutions and improvements made by those skilled in the art without departing from the principles of the application should be considered within the scope of the technology protected by the application.

Claims

1. A method for monitoring the operating status of an elevator, wherein the elevator operating status includes a stationary state, an acceleration state, a constant speed state, and a deceleration state, characterized in that: Step S1: Obtain the acceleration data of the elevator car in the vertical direction during the status monitoring process; Step S2: Based on the sampled values ​​of the acceleration data, the acquired acceleration data is divided into multiple sampling intervals in the time domain. The method for dividing the sampling intervals is as follows: Select the condition that satisfies (|a×(t)) i -Δt)|-a thr )×(|a×(t i +Δt)|-a thr For all sampling times where Δt < 0, the selected sampling time is used as the boundary time of the sampling interval. The acceleration sampling values ​​corresponding to the sampling time between two adjacent boundary times constitute a sampling interval, where Δt is the sampling interval of the acceleration data, and a thr For the preset acceleration threshold, a thr >0, t i 'a' represents the selected sampling time, where 'a' is the acceleration sample value at the selected sampling time. Step S3: Classify the acceleration data in each sampling interval into positive acceleration intervals, zero acceleration intervals, and negative acceleration intervals. The classification method for the acceleration data in each sampling interval is as follows: Calculate the average value of all acceleration data within each sampling interval, where the average acceleration value of the i-th sampling interval is a. i Compare the average acceleration a across each sampling interval. i The maximum acceleration a during the condition monitoring process max The size relationship; when a i >α×a max When -α×a max <a i <α×a max When a, the sampling interval is of type zero acceleration interval; i <-α×a thr When the sampling interval is of type negative acceleration interval, α is a weighting coefficient, α∈(0,0.5]; Step S4: Select a sampling interval and at least two sampling intervals that are adjacent to and follow the sampling interval according to the time sequence. Determine the elevator operation status corresponding to the selected sampling interval according to the type and order of the acceleration data of the selected sampling interval.

2. The method for monitoring elevator operating status according to claim 1, characterized in that, The acceleration data is preprocessed after acquisition and then divided, wherein the preprocessing includes: The acquired acceleration data is then filtered and denoised. The DC component in the acceleration data after filtering and noise reduction is removed. The DC component is the zero-point offset of the acceleration data when the elevator is stationary.

3. The method for monitoring elevator operating status according to claim 1, characterized in that, The sampling duration of the divided sampling intervals is judged. If the sampling duration of a certain sampling interval is less than the interval duration threshold T, then... thr When that happens, the sampling interval is merged into the preceding sampling interval that is adjacent to it.

4. The method for monitoring the elevator operating status according to claim 1, characterized in that, When the acceleration data of adjacent sampling intervals are of the same type, the adjacent sampling intervals are merged into one sampling interval.

5. The method for monitoring the elevator operating status according to claim 1, characterized in that, The elevator's operating status is determined as follows: Select a sampling interval and two sampling intervals that follow and are adjacent to the sampling interval according to the time sequence; If the acceleration data of the three selected sampling intervals are in the order of positive acceleration interval, zero acceleration interval, and negative acceleration interval, then the elevator running state corresponding to the three sampling intervals is determined to be positive acceleration state, positive constant speed state, and positive deceleration state, respectively. If the acceleration data types of the three selected sampling intervals are negative acceleration interval, zero acceleration interval, and positive acceleration interval in sequence, then the elevator running states corresponding to the three sampling intervals are determined to be reverse acceleration state, reverse constant speed state, and reverse deceleration state in sequence.

6. The method for monitoring the elevator operating status according to claim 1, characterized in that, The elevator's operating status is determined as follows: Select a sampling interval and three adjacent sampling intervals after the selected sampling interval according to the time sequence; If the acceleration data of the four selected sampling intervals are in the following order: zero acceleration interval, positive acceleration interval, zero acceleration interval, and negative acceleration interval, then the elevator running state corresponding to the four sampling intervals is determined to be in the following order: stationary state, positive acceleration state, positive constant speed state, and positive deceleration state. If the acceleration data types of the four selected sampling intervals are, in order, zero acceleration interval, negative acceleration interval, zero acceleration interval, and positive acceleration interval, then the elevator running states corresponding to the four sampling intervals are determined to be, in order, stationary state, reverse acceleration state, reverse constant speed state, and reverse deceleration state.

7. A monitoring system for elevator operating status, characterized in that, include: An accelerometer is used to acquire the vertical acceleration data of the elevator car during elevator operation. The signal processing unit is used to divide and classify the acceleration data collected by the accelerometer into sampling intervals; An elevator operation status determination unit is used to determine the elevator operation status based on the sampling interval and the corresponding acceleration data output by the signal processing unit. The data transmission unit is used to transmit the acceleration data and the elevator operating status; A data storage unit is used to store the acceleration data and the elevator's operating status; wherein, The signal processing unit uses the sampled values ​​of the accelerometer as a basis to divide the acquired acceleration data into multiple sampling intervals in the time domain and classifies the type of acceleration data in each sampling interval into positive acceleration interval, zero acceleration interval, and negative acceleration interval. The elevator operation status determination unit selects a sampling interval and at least two sampling intervals that are adjacent to and follow the sampling interval according to the time sequence, and determines the elevator operation status corresponding to the selected sampling interval according to the type and arrangement order of the acceleration data of the selected sampling interval. The sampling interval is divided as follows: Select the condition that satisfies (|a×(t)) i -Δt)|-a thr )×(|a×(t i +Δt)|-a thr For all sampling times where Δt < 0, the selected sampling time is used as the boundary time of the sampling interval. The acceleration sampling values ​​corresponding to the sampling time between two adjacent boundary times constitute a sampling interval, where Δt is the sampling interval of the acceleration data, and a thr For the preset acceleration threshold, a thr >0, t i 'a' represents the selected sampling time, where 'a' is the acceleration sample value at the selected sampling time. The classification method for acceleration data types within the sampling interval is as follows: Calculate the average value of all acceleration data within each sampling interval, where the average acceleration value of the i-th sampling interval is a. i Compare the average acceleration a across each sampling interval. i The maximum acceleration a during the condition monitoring process max The size relationship; when a i >α×a max When -α×a max <a i <α×a max When a, the sampling interval is of type zero acceleration interval; i <-α×a thr When the sampling interval is of type negative acceleration interval, α is a weighting coefficient, α∈(0,0.5).

8. A method for monitoring the condition of elevator components, characterized in that, Step S1: Obtain the acceleration data of the elevator car in the vertical direction during the status monitoring process; Step S2: Based on the sampled values ​​of the acceleration data, the acquired acceleration data is divided into multiple sampling intervals in the time domain. The method for dividing the sampling intervals is as follows: Select the condition that satisfies (|a×(t)) i -Δt)|-a thr )×(|a×(t i +Δt)|-a thr For all sampling times where Δt < 0, the selected sampling time is used as the boundary time of the sampling interval. The acceleration sampling values ​​corresponding to the sampling time between two adjacent boundary times constitute a sampling interval, where Δt is the sampling interval of the acceleration data, and a thr For the preset acceleration threshold, a thr >0, t i 'a' represents the selected sampling time, where 'a' is the acceleration sample value at the selected sampling time. Step S3: Classify the acceleration data within each sampling interval into positive acceleration intervals, zero acceleration intervals, and negative acceleration intervals; the classification method for the acceleration data within the sampling intervals is as follows: Calculate the average value of all acceleration data within each sampling interval, where the average acceleration value of the i-th sampling interval is a. i Compare the average acceleration a across each sampling interval. i The maximum acceleration a during the condition monitoring process max The size relationship; when a i >α×a max When -α×a max <a i <α×a max When a, the sampling interval is of type zero acceleration interval; i <-α×a thr When the sampling interval is of type negative acceleration interval, α is a weighting coefficient, α∈(0,0.5]; Step S4: Select a sampling interval and at least two sampling intervals that are adjacent to and follow the sampling interval according to the time sequence. Determine the elevator running state corresponding to the selected sampling interval according to the type and order of the acceleration data of the selected sampling interval. The elevator running state includes stationary state, acceleration state, constant speed state, and deceleration state. Step S5: Determine whether elevator components have malfunctioned based on the acceleration data corresponding to the operating status of each elevator.

9. The method for monitoring the status of elevator components according to claim 8, characterized in that, Feature values ​​are extracted from the acceleration data corresponding to the uniform velocity state, and the elevator components are judged to have malfunctioned based on the feature values.

10. A monitoring system for the status of elevator components, characterized in that, include: An accelerometer is used to acquire the vertical acceleration data of the elevator car during elevator operation. The signal processing unit is used to divide and classify the acceleration data collected by the accelerometer into sampling intervals; An elevator operation status determination unit is used to determine the elevator operation status based on the sampling interval and the corresponding acceleration data output by the signal processing unit. The data transmission unit is used to transmit the acceleration data and the elevator operating status; A data storage unit is used to store the acceleration data and the elevator operating status; The status monitoring unit is used to determine the status of elevator components based on the acceleration data corresponding to the elevator's operating status; among which, The signal processing unit uses the sampled values ​​of the accelerometer as a basis to divide the acquired acceleration data into multiple sampling intervals in the time domain and classifies the type of acceleration data in each sampling interval into positive acceleration interval, zero acceleration interval, and negative acceleration interval. The elevator operation status determination unit selects a sampling interval and at least two sampling intervals that are adjacent to and follow the sampling interval according to the time sequence, and determines the elevator operation status corresponding to the selected sampling interval according to the type and arrangement order of the acceleration data of the selected sampling interval. The sampling interval is divided as follows: Select the condition that satisfies (|a×(t)) i -Δt)|-a thr )×(|a×(t i +Δt)|-a thr For all sampling times where Δt < 0, the selected sampling time is used as the boundary time of the sampling interval. The acceleration sampling values ​​corresponding to the sampling time between two adjacent boundary times constitute a sampling interval, where Δt is the sampling interval of the acceleration data, and a thr For the preset acceleration threshold, a thr >0, t i 'a' represents the selected sampling time, where 'a' is the acceleration sample value at the selected sampling time. The classification method for acceleration data types within the sampling interval is as follows: Calculate the average value of all acceleration data within each sampling interval, where the average acceleration value of the i-th sampling interval is a. i Compare the average acceleration a across each sampling interval. i The maximum acceleration a during the condition monitoring process max The size relationship; when a i >α×a max When -α×a max <a i <α×a max When a, the sampling interval is of type zero acceleration interval; i <-α×a thr When the sampling interval is of type negative acceleration interval, α is a weighting coefficient, α∈(0,0.5).

11. The elevator component status monitoring system according to claim 10, characterized in that, The status monitoring unit extracts feature values ​​from the acceleration data corresponding to the uniform speed state, and determines whether elevator components have malfunctioned based on the feature values.

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