Abnormal detection method and detection system for elevator operation

Abstract

The invention is suitable for the technical field of elevator operation detection, and provides an elevator operation anomaly detection method and system. According to the invention, work recording and detection acquisition are carried out on the elevator; calculating an acceleration kurtosis value, a vibration kurtosis value and a noise kurtosis value; determining a current working stage, and matching a corresponding acceleration standard value, a vibration standard value and a noise standard value; comparing, and recording a multi-dimensional comparison result; and matching the operation abnormal level, and giving a corresponding abnormal level alarm. Work record data, acceleration detection data, vibration detection data and noise detection data can be obtained, an acceleration kurtosis value, a vibration kurtosis value and a noise kurtosis value are calculated, an acceleration standard value, a vibration standard value and a noise standard value are matched, multi-dimensional comparison is carried out, the operation abnormal level is determined, and corresponding abnormal level alarming is carried out. In this way, multi-dimensional detection is conducted in the elevator running process, the automation degree is high, and the abnormity in the elevator running process can be found in time.

Description

Technical Field

[0001] The present invention belongs to the technical field of elevator operation detection, and in particular relates to an abnormality detection method and a detection system for elevator operation. Background Art

[0002] Elevator operation detection is to conduct comprehensive inspection, measurement, analysis and evaluation of various performance parameters, safety devices, control systems, etc. of the elevator during operation through professional technical means and methods to ensure that the elevator operates under safe, reliable and efficient conditions.

[0003] In the prior art, detailed inspection of elevator operation usually needs to be performed when the elevator is out of service, but cannot be performed during the operation of the elevator. In addition, the inspection method is single and the degree of automation is not high, so it is impossible to detect abnormalities in the operation of the elevator in a timely manner. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide an abnormality detection method and a detection system for elevator operation, aiming to solve the technical problems existing in the prior art mentioned in the background technology.

[0005] The embodiment of the present invention is implemented as follows:

[0006] A method for detecting abnormality in elevator operation, the method specifically comprising the following steps:

[0007] Periodically record and detect the elevator operation, and periodically obtain work record data, acceleration detection data, vibration detection data, and noise detection data;

[0008] Calculating an acceleration kurtosis value, a vibration kurtosis value, and a noise kurtosis value according to the acceleration detection data, the vibration detection data, and the noise detection data;

[0009] Analyze the work record data, determine the current working stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value;

[0010] Compare the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value with the acceleration standard value, vibration standard value and noise standard value respectively, and record the multi-dimensional comparison results;

[0011] According to the multi-dimensional comparison result, the number of abnormal comparisons is determined, and according to the number of abnormal comparisons, the operation abnormality level is matched, and a corresponding abnormality level alarm is issued.

[0012] As a further limitation of the technical solution of the embodiment of the present invention, the periodic work recording and detection collection of the elevator operation, and the periodic acquisition of work record data, acceleration detection data, vibration detection data and noise detection data specifically include the following steps:

[0013] Receive detection setting information and determine anomaly detection cycle;

[0014] According to the abnormality detection cycle, periodically record the operation of the elevator and periodically obtain the work record data;

[0015] According to the abnormality detection cycle, periodic acceleration detection and collection are performed on the elevator operation, and acceleration detection data is periodically obtained;

[0016] According to the abnormality detection cycle, periodic vibration detection and collection are performed on the elevator operation to periodically obtain vibration detection data;

[0017] According to the abnormality detection cycle, periodic noise detection and collection are performed on the elevator operation, and noise detection data is periodically obtained.

[0018] As a further limitation of the technical solution of the embodiment of the present invention, the calculation formulas of the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value are:

[0019]

[0020] Among them, K a , K v and K n They are acceleration kurtosis value, vibration kurtosis value and noise kurtosis value respectively, N is the sampling length, h represents the sampling time, x aj 、x vj and x nj are the signal values ​​at sampling time j in acceleration detection data, vibration detection data and noise detection data respectively, and are the average values ​​of the signals in the acceleration detection data, vibration detection data and noise detection data, respectively, a , σ v and σ n are the acceleration standard deviation, vibration standard deviation and noise standard deviation, respectively, a , b v and b n They are acceleration calculation coefficient, vibration calculation coefficient and noise calculation coefficient respectively.

[0021] As a further limitation of the technical solution of the embodiment of the present invention, the analyzing of the work record data, determining the current working stage, and matching the corresponding acceleration standard value, vibration standard value, and noise standard value specifically include the following steps:

[0022] Analyze the work record data to determine the current floor information and the operation floor information;

[0023] Analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information;

[0024] Determine the current working stage according to the current floor information and the optimized floor information;

[0025] According to the current working stage, the corresponding acceleration standard value, vibration standard value and noise standard value are matched.

[0026] As a further limitation of the technical solution of the embodiment of the present invention, the step of comparing the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value, respectively, and recording the multi-dimensional comparison results specifically comprises the following steps:

[0027] Compare the acceleration kurtosis value with the acceleration standard value and record the acceleration comparison result;

[0028] Compare the vibration kurtosis value with the vibration standard value and record the vibration comparison results;

[0029] Compare the noise kurtosis value with the noise standard value and record the noise comparison result;

[0030] The acceleration comparison result, the vibration comparison result and the noise comparison result are integrated to generate a multi-dimensional comparison result.

[0031] As a further limitation of the technical solution of the embodiment of the present invention, the determining of the number of abnormal comparisons according to the multi-dimensional comparison results, matching the operation abnormality level according to the abnormal comparison number, and performing the corresponding abnormality level alarm specifically includes the following steps:

[0032] Determining the number of abnormal comparisons according to the multi-dimensional comparison results;

[0033] According to the said exception comparison quantity, matching the operation exception level;

[0034] Generate corresponding level alarm information according to the abnormal operation level;

[0035] According to the level of alarm information, a corresponding abnormal level alarm is issued.

[0036] An abnormality detection system for elevator operation, the system comprises an operation detection acquisition module, a kurtosis value calculation module, a standard value stage matching module, a multi-dimensional comparison recording module and an abnormality level alarm module, wherein:

[0037] The operation detection and collection module is used to periodically record and detect the operation of the elevator, and periodically obtain the operation record data, acceleration detection data, vibration detection data and noise detection data;

[0038] A kurtosis value calculation module, used for calculating the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value according to the acceleration detection data, the vibration detection data and the noise detection data;

[0039] A standard value stage matching module is used to analyze the work record data, determine the current work stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value;

[0040] A multi-dimensional comparison and recording module is used to compare the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value respectively, and record the multi-dimensional comparison results;

[0041] The abnormal level alarm module is used to determine the abnormal comparison quantity according to the multi-dimensional comparison result, match the operation abnormal level according to the abnormal comparison quantity, and issue a corresponding abnormal level alarm.

[0042] As a further limitation of the technical solution of the embodiment of the present invention, the operation detection acquisition module specifically includes:

[0043] A cycle determination unit, configured to receive detection setting information and determine an abnormality detection cycle;

[0044] A work recording unit, used to periodically record the operation of the elevator according to the abnormality detection cycle, and periodically obtain work record data;

[0045] An acceleration detection unit, used to perform periodic acceleration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain acceleration detection data;

[0046] A vibration detection unit, used to perform periodic vibration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain vibration detection data;

[0047] The noise detection unit is used to perform periodic noise detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain noise detection data.

[0048] As a further limitation of the technical solution of the embodiment of the present invention, the standard value stage matching module specifically includes:

[0049] A work analysis unit, used to analyze the work record data to determine the current floor information and the operation floor information;

[0050] An information optimization unit, used to analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information;

[0051] A stage determination unit, configured to determine a current working stage according to the current floor information and the optimized floor information;

[0052] The standard value matching unit is used to match the corresponding acceleration standard value, vibration standard value and noise standard value according to the current working stage.

[0053] As a further limitation of the technical solution of the embodiment of the present invention, the abnormal level alarm module specifically includes:

[0054] A quantity determination unit, used to determine the number of abnormal comparisons according to the multi-dimensional comparison result;

[0055] A level matching unit, used for matching the operation exception level according to the exception comparison quantity;

[0056] An information generating unit, configured to generate corresponding level alarm information according to the abnormal operation level;

[0057] The abnormal alarm unit is used to make corresponding abnormal level alarm according to the level alarm information.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The embodiment of the present invention records and detects the elevator; calculates the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value; determines the current working stage, matches the corresponding acceleration standard value, vibration standard value and noise standard value; makes a comparison, records the multi-dimensional comparison result; matches the operation abnormality level, and issues a corresponding abnormality level alarm. It is able to obtain work record data, acceleration detection data, vibration detection data and noise detection data, calculate the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value, match the acceleration standard value, vibration standard value and noise standard value, make a multi-dimensional comparison, determine the operation abnormality level, and issue a corresponding abnormality level alarm, thereby performing multi-dimensional detection during the operation of the elevator, and the degree of automation is high, and abnormalities during the operation of the elevator can be discovered in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A flow chart of an abnormality detection method for elevator operation provided by an embodiment of the present invention is shown;

[0061] Figure 2 A flowchart of work recording and detection collection in the method provided by an embodiment of the present invention is shown;

[0062] Figure 3 A flowchart of the corresponding standard value matching process in the method provided by the embodiment of the present invention is shown;

[0063] Figure 4 A flowchart of recording multi-dimensional comparison results in a method provided by an embodiment of the present invention is shown;

[0064] Figure 5 A flowchart of abnormal level alarming in the method provided by an embodiment of the present invention is shown;

[0065] Figure 6 An application architecture diagram of an abnormality detection system for elevator operation provided by an embodiment of the present invention is shown;

[0066] Figure 7 It shows a structural block diagram of the running detection and acquisition module in the system provided by the embodiment of the present invention;

[0067] Figure 8 It shows a structural block diagram of a standard value stage matching module in a system provided by an embodiment of the present invention;

[0068] Fig. 9 The structure block diagram of the abnormal level alarm module in the system provided by the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0070] It is understandable that in the prior art, detailed inspection of elevator operation usually needs to be performed when the elevator is out of service, and cannot be performed during the operation of the elevator. In addition, the inspection method is single and the degree of automation is not high, and abnormalities during elevator operation cannot be discovered in time.

[0071] To solve the above problems, an embodiment of the present invention discloses an abnormality detection method and a detection system for elevator operation. By periodically recording and detecting the elevator operation, work record data, acceleration detection data, vibration detection data and noise detection data are periodically obtained; according to the acceleration detection data, vibration detection data and noise detection data, acceleration kurtosis value, vibration kurtosis value and noise kurtosis value are calculated; the work record data is analyzed to determine the current working stage, and the corresponding acceleration standard value, vibration standard value and noise standard value are matched; the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value are compared with the acceleration standard value, vibration standard value and noise standard value respectively, and the multi-dimensional comparison results are recorded; according to the multi-dimensional comparison results, the number of abnormal comparisons is determined, and according to the number of abnormal comparisons, the operation abnormality level is matched, and the corresponding abnormality level alarm is performed. It can obtain work record data, acceleration detection data, vibration detection data and noise detection data, calculate acceleration kurtosis value, vibration kurtosis value and noise kurtosis value, match acceleration standard value, vibration standard value and noise standard value, make multi-dimensional comparison, determine the abnormal operation level, and make corresponding abnormal level alarm, so as to carry out multi-dimensional detection during the operation of the elevator, and has a high degree of automation, and can timely discover abnormalities during the operation of the elevator.

[0072] Specifically, Figure 1 A flow chart of an abnormality detection method for elevator operation provided by an embodiment of the present invention is shown.

[0073] In a preferred embodiment of the present invention, a method for detecting abnormality in elevator operation is provided, and the method specifically comprises the following steps:

[0074] Step S101: Periodically record and detect the operation of the elevator, and periodically obtain work record data, acceleration detection data, vibration detection data, and noise detection data.

[0075] In an embodiment of the present invention, by receiving the detection setting information of the elevator detection from the elevator management personnel, the detection setting information is identified, the abnormal detection cycle is determined, and then according to the abnormal detection cycle, the work record instructions, acceleration detection instructions, vibration detection instructions and noise detection instructions are periodically generated, and then according to the work record instructions, the elevator operation is periodically recorded, and the work record data is periodically obtained, according to the acceleration detection instructions, the elevator operation is periodically accelerated. Detection and collection, periodically obtain acceleration detection data, according to the vibration detection instructions, the elevator operation is periodically vibration detection and collection, periodically obtain vibration detection data, and according to the noise detection instructions, the elevator operation is periodically noise detection and collection, and noise detection data is periodically obtained.

[0076] Specifically, Figure 2A flow chart of work recording and detection collection in the method provided by an embodiment of the present invention is shown.

[0077] Among them, in the preferred embodiment provided by the present invention, the periodic work recording and detection collection of the elevator operation, and the periodic acquisition of work record data, acceleration detection data, vibration detection data and noise detection data specifically include the following steps:

[0078] Step S1011, receiving detection setting information and determining an abnormality detection cycle.

[0079] Step S1012: According to the abnormality detection cycle, periodic work records are made for the elevator operation, and work record data is periodically obtained.

[0080] Step S1013: perform periodic acceleration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain acceleration detection data.

[0081] Step S1014: perform periodic vibration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain vibration detection data.

[0082] Step S1015: Perform periodic noise detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain noise detection data.

[0083] Furthermore, the elevator operation abnormality detection method further comprises the following steps:

[0084] Step S102: Calculate the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value according to the acceleration detection data, the vibration detection data and the noise detection data.

[0085] In the embodiment of the present invention, according to Calculate the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value, where K a , K v and K n They are acceleration kurtosis value, vibration kurtosis value and noise kurtosis value respectively, N is the sampling length, j represents the sampling time, x aj 、x vj and x nj are the signal values ​​at sampling time j in acceleration detection data, vibration detection data and noise detection data respectively, and are the average values ​​of the signals in the acceleration detection data, vibration detection data and noise detection data, respectively, a , σ v and σ n are the acceleration standard deviation, vibration standard deviation and noise standard deviation, respectively, a, b v and b n They are acceleration calculation coefficient, vibration calculation coefficient and noise calculation coefficient respectively.

[0086] Step S103: Analyze the work record data, determine the current work stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value.

[0087] In an embodiment of the present invention, by analyzing the work record data, the current floor and all the operating floors of the elevator during operation are determined, and combined with the running direction of the elevator, the current floor information and the operating floor information are obtained. By analyzing the operating floor information, invalid operating floors are identified and eliminated, and optimized floor information is generated. According to the current floor information and the optimized floor information, the current working stage is determined, and then according to the current working stage, the corresponding acceleration standard value, vibration standard value and noise standard value are matched.

[0088] It can be understood that the operating floor is the floor where people manually go up and / or down during the operation of the elevator. For example, when a user needs to go down on the 5th floor and presses the down button on the 5th floor, the 5th floor is the operating floor. The operating floor information records all the operating floors and the running direction of the elevator during its current operation.

[0089] It can be understood that the invalid operating floor is based on the running direction of the elevator. If the operating floor belongs to the next floor adjacent to the current floor, the elevator will not stop at this floor during operation, then it is an invalid operating floor. For example: the current floor is the 9th floor, a certain operating floor is the 8th floor, and the running direction of the elevator is downward, then the 8th floor is an invalid operating floor.

[0090] It can be understood that the current working stage is one of all the elevator working stages, which include: preparing to stop, stopping, preparing to lift and lower, and lifting and lowering. Among them, according to the running direction of the elevator, preparing to stop is the working stage when the current floor is on the previous floor of the operating floor; stopping is the working stage when the current floor is on the operating floor; preparing to lift and lower is the working stage when the current floor is on the next floor of the operating floor; lifting and lowering is the working stage when the current floor is on other floors.

[0091] Specifically, Figure 3 A flowchart of corresponding standard value matching processing in the method provided by an embodiment of the present invention is shown.

[0092] Among them, in the preferred embodiment provided by the present invention, the analysis of the work record data, determining the current working stage, and matching the corresponding acceleration standard value, vibration standard value and noise standard value specifically include the following steps:

[0093] Step S1031, analyzing the work record data to determine the current floor information and the operation floor information.

[0094] Step S1032: Analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information.

[0095] Step S1033: determine the current working stage according to the current floor information and the optimized floor information.

[0096] Step S1034: According to the current working stage, the corresponding acceleration standard value, vibration standard value and noise standard value are matched.

[0097] Furthermore, the elevator operation abnormality detection method further comprises the following steps:

[0098] Step S104: compare the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value respectively, and record the multi-dimensional comparison results.

[0099] In an embodiment of the present invention, the acceleration kurtosis value is compared with the acceleration standard value, the acceleration comparison result is recorded, the vibration kurtosis value is compared with the vibration standard value, the vibration comparison result is recorded, and the noise kurtosis value is compared with the noise standard value, the noise comparison result is recorded, and then the acceleration comparison result, the vibration comparison result and the noise comparison result are comprehensively sorted out to generate a multi-dimensional comparison result.

[0100] Specifically, Figure 4 A flow chart for recording multi-dimensional comparison results in the method provided by an embodiment of the present invention is shown.

[0101] Among them, in the preferred embodiment provided by the present invention, the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value are compared with the acceleration standard value, the vibration standard value and the noise standard value respectively, and recording the multi-dimensional comparison results specifically includes the following steps:

[0102] Step S1041, compare the acceleration kurtosis value with the acceleration standard value, and record the acceleration comparison result.

[0103] Step S1042: Compare the vibration kurtosis value with the vibration standard value, and record the vibration comparison result.

[0104] Step S1043: compare the noise kurtosis value with the noise standard value, and record the noise comparison result.

[0105] Step S1044: Integrate the acceleration comparison result, the vibration comparison result and the noise comparison result to generate a multi-dimensional comparison result.

[0106] Furthermore, the elevator operation abnormality detection method further comprises the following steps:

[0107] Step S105: determine the number of abnormal comparisons according to the multi-dimensional comparison results, match the operation abnormality level according to the abnormal comparison number, and issue a corresponding abnormality level alarm.

[0108] In an embodiment of the present invention, the number of abnormal comparisons is determined by analyzing the multi-dimensional comparison results, and then the operation abnormality level is matched according to the abnormal comparison number. According to the operation abnormality level, the corresponding level alarm information is generated, and then the corresponding abnormal level alarm is performed according to the level alarm information.

[0109] It can be understood that the operation abnormality level is related to the number of abnormal comparisons. Specifically: when the number of abnormal comparisons is 0, the operation abnormality level is level 0; when the number of abnormal comparisons is 1, the operation abnormality level is level 1; when the number of abnormal comparisons is 2, the operation abnormality level is level 2; when the number of abnormal comparisons is 3, the operation abnormality level is level 3; the higher the operation abnormality level, the more serious the elevator operation abnormality.

[0110] Specifically, Figure 5 A flow chart of abnormal level alarming in the method provided by an embodiment of the present invention is shown.

[0111] Among them, in the preferred implementation manner provided by the present invention, determining the number of abnormal comparisons according to the multi-dimensional comparison results, matching the operation abnormality level according to the abnormal comparison number, and performing the corresponding abnormality level alarm specifically includes the following steps:

[0112] Step S1051: Determine the number of abnormal comparisons according to the multi-dimensional comparison results.

[0113] Step S1052: Match the operation exception level according to the exception comparison quantity.

[0114] Step S1053: Generate corresponding level alarm information according to the abnormal operation level.

[0115] Step S1054: according to the level alarm information, a corresponding abnormal level alarm is issued.

[0116] Furthermore, Figure 6 The application architecture diagram of the elevator operation abnormality detection system provided by an embodiment of the present invention is shown.

[0117] Among them, in another preferred embodiment provided by the present invention, an abnormality detection system for elevator operation includes:

[0118] The operation detection collection module 101 is used to periodically record and detect the operation of the elevator, and periodically obtain the operation record data, acceleration detection data, vibration detection data and noise detection data.

[0119] In an embodiment of the present invention, the operation detection collection module 101 receives the detection setting information of the elevator detection from the elevator management personnel, identifies the detection setting information, determines the abnormal detection cycle, and then periodically generates work record instructions, acceleration detection instructions, vibration detection instructions and noise detection instructions according to the abnormal detection cycle, and then periodically records the elevator operation according to the work record instructions, periodically obtains the work record data, periodically performs acceleration detection and collection on the elevator operation according to the acceleration detection instructions, periodically obtains acceleration detection data, periodically performs vibration detection and collection on the elevator operation according to the vibration detection instructions, periodically obtains vibration detection data, and periodically performs noise detection and collection on the elevator operation according to the noise detection instructions, and periodically obtains noise detection data.

[0120] Specifically, Figure 7 It shows a structural block diagram of the running detection and acquisition module 101 in the system provided by an embodiment of the present invention.

[0121] Among them, in the preferred embodiment provided by the present invention, the operation detection acquisition module 101 specifically includes:

[0122] The cycle determination unit 1011 is used to receive detection setting information and determine an abnormality detection cycle.

[0123] The work recording unit 1012 is used to periodically record the operation of the elevator according to the abnormality detection cycle and periodically obtain the work record data.

[0124] The acceleration detection unit 1013 is used to perform periodic acceleration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain acceleration detection data.

[0125] The vibration detection unit 1014 is used to perform periodic vibration detection and collection on the elevator operation according to the abnormality detection period, and periodically obtain vibration detection data.

[0126] The noise detection unit 1015 is used to perform periodic noise detection and collection on the elevator operation according to the abnormality detection period, and periodically obtain noise detection data.

[0127] Furthermore, the elevator operation abnormality detection system also includes:

[0128] The kurtosis value calculation module 102 is used to calculate the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value according to the acceleration detection data, the vibration detection data and the noise detection data.

[0129] In the embodiment of the present invention, the kurtosis value calculation module 102 is based on (a, v, n), calculate the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value, where K a , K v and K n They are acceleration kurtosis value, vibration kurtosis value and noise kurtosis value respectively, N is the sampling length, j represents the sampling time, x aj 、x vj and x nj are the signal values ​​at sampling time j in acceleration detection data, vibration detection data and noise detection data respectively, and are the average values ​​of the signals in the acceleration detection data, vibration detection data and noise detection data, respectively, a , σ v and σ n are the acceleration standard deviation, vibration standard deviation and noise standard deviation, respectively, a , b v and b n They are acceleration calculation coefficient, vibration calculation coefficient and noise calculation coefficient respectively.

[0130] The standard value stage matching module 103 is used to analyze the work record data, determine the current work stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value.

[0131] In an embodiment of the present invention, the standard value stage matching module 103 determines the current floor and all operating floors of the elevator during operation by analyzing the work record data, and obtains the current floor information and the operating floor information in combination with the running direction of the elevator. By analyzing the operating floor information, the invalid operating floors are identified and eliminated, and the optimized floor information is generated. According to the current floor information and the optimized floor information, the current working stage is determined, and then according to the current working stage, the corresponding acceleration standard value, vibration standard value and noise standard value are matched.

[0132] Specifically, Figure 8 It shows a structural block diagram of the standard value stage matching module 103 in the system provided by an embodiment of the present invention.

[0133] Among them, in the preferred implementation manner provided by the present invention, the standard value stage matching module 103 specifically includes:

[0134] The work analysis unit 1031 is used to analyze the work record data to determine the current floor information and the operation floor information.

[0135] The information optimization unit 1032 is used to analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information.

[0136] The stage determination unit 1033 is used to determine the current working stage according to the current floor information and the optimized floor information.

[0137] The standard value matching unit 1034 is used to match the corresponding acceleration standard value, vibration standard value and noise standard value according to the current working stage.

[0138] Furthermore, the elevator operation abnormality detection system also includes:

[0139] The multi-dimensional comparison recording module 104 is used to compare the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value respectively, and record the multi-dimensional comparison result.

[0140] In an embodiment of the present invention, the multidimensional comparison recording module 104 compares the acceleration kurtosis value with the acceleration standard value and records the acceleration comparison result, compares the vibration kurtosis value with the vibration standard value and records the vibration comparison result, and compares the noise kurtosis value with the noise standard value and records the noise comparison result, and then comprehensively organizes the acceleration comparison result, the vibration comparison result and the noise comparison result to generate a multidimensional comparison result.

[0141] The abnormal level alarm module 105 is used to determine the abnormal comparison quantity according to the multi-dimensional comparison result, match the operation abnormal level according to the abnormal comparison quantity, and issue a corresponding abnormal level alarm.

[0142] In an embodiment of the present invention, the abnormal level alarm module 105 determines the number of abnormal comparisons by analyzing the multi-dimensional comparison results, and then matches the operation abnormality level according to the number of abnormal comparisons, generates corresponding level alarm information according to the operation abnormality level, and then performs corresponding abnormal level alarm according to the level alarm information.

[0143] Specifically, Fig. 9 It shows a structural block diagram of the abnormal level alarm module 105 in the system provided by the embodiment of the present invention.

[0144] Among them, in the preferred implementation mode provided by the present invention, the abnormal level alarm module 105 specifically includes:

[0145] The quantity determination unit 1051 is used to determine the abnormal comparison quantity according to the multi-dimensional comparison result.

[0146] The level matching unit 1052 is used to match the operation exception level according to the exception comparison quantity.

[0147] The information generating unit 1053 is used to generate corresponding level alarm information according to the abnormal operation level.

[0148] The abnormal alarm unit 1054 is used to make a corresponding abnormal level alarm according to the level alarm information.

[0149] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0150] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0151] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for detecting abnormality in elevator operation, characterized in that: The method specifically comprises the following steps: Periodically record and detect the elevator operation, and periodically obtain work record data, acceleration detection data, vibration detection data, and noise detection data; Calculating an acceleration kurtosis value, a vibration kurtosis value, and a noise kurtosis value according to the acceleration detection data, the vibration detection data, and the noise detection data; Analyze the work record data, determine the current working stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value; Compare the acceleration kurtosis value, vibration kurtosis value and noise kurtosis value with the acceleration standard value, vibration standard value and noise standard value respectively, and record the multi-dimensional comparison results; According to the multi-dimensional comparison result, the number of abnormal comparisons is determined, and according to the number of abnormal comparisons, the operation abnormality level is matched, and a corresponding abnormality level alarm is issued.

2. The method for detecting abnormality of elevator operation according to claim 1, characterized in that: The periodic recording and detection collection of elevator operation, and the periodic acquisition of work record data, acceleration detection data, vibration detection data, and noise detection data specifically include the following steps: Receive detection setting information and determine anomaly detection cycle; According to the abnormality detection cycle, periodically record the operation of the elevator and periodically obtain the work record data; According to the abnormality detection cycle, periodic acceleration detection and collection are performed on the elevator operation, and acceleration detection data is periodically obtained; According to the abnormality detection cycle, periodic vibration detection and collection are performed on the elevator operation to periodically obtain vibration detection data; According to the abnormality detection cycle, periodic noise detection and collection are performed on the elevator operation, and noise detection data is periodically obtained.

3. The method for detecting abnormality of elevator operation according to claim 1, characterized in that: The calculation formulas of the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value are as follows: Among them, K a , K v and K n They are acceleration kurtosis value, vibration kurtosis value and noise kurtosis value respectively, N is the sampling length, j represents the sampling time, x aj 、x vj and x nj are the signal values ​​at sampling time j in acceleration detection data, vibration detection data and noise detection data respectively, and are the average values ​​of the signals in the acceleration detection data, vibration detection data and noise detection data, respectively, a , σ v and σ n are the acceleration standard deviation, vibration standard deviation and noise standard deviation, respectively, a , b v and b n They are acceleration calculation coefficient, vibration calculation coefficient and noise calculation coefficient respectively.

4. The method for detecting abnormality in elevator operation according to claim 1, characterized in that: The analyzing of the work record data to determine the current working stage and matching the corresponding acceleration standard value, vibration standard value and noise standard value specifically includes the following steps: Analyze the work record data to determine the current floor information and the operation floor information; Analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information; Determine the current working stage according to the current floor information and the optimized floor information; According to the current working stage, the corresponding acceleration standard value, vibration standard value and noise standard value are matched.

5. The method for detecting abnormality in elevator operation according to claim 1, characterized in that: The step of comparing the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value respectively, and recording the multi-dimensional comparison results specifically comprises the following steps: Compare the acceleration kurtosis value with the acceleration standard value and record the acceleration comparison result; Compare the vibration kurtosis value with the vibration standard value and record the vibration comparison results; Compare the noise kurtosis value with the noise standard value and record the noise comparison result; The acceleration comparison result, the vibration comparison result and the noise comparison result are integrated to generate a multi-dimensional comparison result.

6. The method for detecting abnormality in elevator operation according to claim 1, characterized in that: Determining the abnormal comparison quantity according to the multi-dimensional comparison result, matching the operation abnormality level according to the abnormal comparison quantity, and performing the corresponding abnormality level alarm specifically comprises the following steps: Determining the number of abnormal comparisons according to the multi-dimensional comparison results; According to the said exception comparison quantity, matching the operation exception level; Generate corresponding level alarm information according to the abnormal operation level; According to the level of alarm information, a corresponding abnormal level alarm is issued.

7. An abnormality detection system for elevator operation, characterized in that: The system includes a running detection acquisition module, a kurtosis value calculation module, a standard value stage matching module, a multi-dimensional comparison recording module and an abnormal level alarm module, wherein: The operation detection and collection module is used to periodically record and detect the operation of the elevator, and periodically obtain the operation record data, acceleration detection data, vibration detection data and noise detection data; A kurtosis value calculation module, used for calculating the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value according to the acceleration detection data, the vibration detection data and the noise detection data; A standard value stage matching module is used to analyze the work record data, determine the current work stage, and match the corresponding acceleration standard value, vibration standard value, and noise standard value; A multi-dimensional comparison and recording module is used to compare the acceleration kurtosis value, the vibration kurtosis value and the noise kurtosis value with the acceleration standard value, the vibration standard value and the noise standard value respectively, and record the multi-dimensional comparison results; The abnormal level alarm module is used to determine the abnormal comparison quantity according to the multi-dimensional comparison result, match the operation abnormal level according to the abnormal comparison quantity, and issue a corresponding abnormal level alarm.

8. The edge computing-based intelligent manufacturing system according to claim 7, characterized in that: The operation detection acquisition module specifically includes: A cycle determination unit, configured to receive detection setting information and determine an abnormality detection cycle; A work recording unit, used to periodically record the operation of the elevator according to the abnormality detection cycle, and periodically obtain work record data; An acceleration detection unit, used to perform periodic acceleration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain acceleration detection data; A vibration detection unit, used to perform periodic vibration detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain vibration detection data; The noise detection unit is used to perform periodic noise detection and collection on the elevator operation according to the abnormality detection cycle, and periodically obtain noise detection data.

9. The intelligent manufacturing system based on edge computing according to claim 7, characterized in that: The standard value stage matching module specifically includes: A work analysis unit, used to analyze the work record data to determine the current floor information and the operation floor information; An information optimization unit, used to analyze the operation floor information, eliminate invalid operation floors, and generate optimized floor information; A stage determination unit, configured to determine a current working stage according to the current floor information and the optimized floor information; The standard value matching unit is used to match the corresponding acceleration standard value, vibration standard value and noise standard value according to the current working stage.

10. The intelligent manufacturing system based on edge computing according to claim 7, characterized in that: The abnormal level alarm module specifically includes: A quantity determination unit, used to determine the number of abnormal comparisons according to the multi-dimensional comparison result; A level matching unit, used for matching the operation exception level according to the exception comparison quantity; An information generating unit, configured to generate corresponding level alarm information according to the abnormal operation level; The abnormal alarm unit is used to make corresponding abnormal level alarm according to the level alarm information.

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