JP5783551B2 - Elevator abnormal sound detection device - Google Patents

Description

  The present invention relates to an abnormal sound detection device for an elevator that detects abnormal sound in a diagnostic operation performed after an earthquake occurs.

  The conventional abnormal sound detection device includes an earthquake detector that detects the occurrence of an earthquake, diagnostic operation control means that performs diagnostic operation in a plurality of modes after the occurrence of the earthquake is detected by the earthquake detector, and an elevator car. The sound collecting means for collecting the sound in the hoistway during traveling of the car in each mode of diagnostic operation, and the abnormal sound in which a plurality of abnormal sound reference values set for each mode of diagnostic operation are stored An abnormal sound determination means for determining whether or not the sound collected by the sound collection means is an abnormal sound based on the reference value storage means and the abnormal sound reference value stored in the abnormal sound reference value storage means; By providing abnormal sound information determination means for determining whether or not abnormal noise has been detected at the same position of the hoistway in multiple runs of the car in the same mode of diagnostic operation, Carry out detection, accidental It is possible to prevent the sound of false detection occurring have been proposed (e.g., see Patent Document 1).

JP 2007-223750 A

  In a conventional elevator abnormality detection device, it is determined whether or not the collected sound is an abnormal sound using a predetermined abnormal sound reference value for the sound data. The acoustic data including the waveform and the detection time is time-series data. For example, it is not possible to distinguish an abnormal sound from a normal sound only by the sound level. Therefore, there is a problem that the sound level, frequency, waveform, detection time, etc. cannot be distinguished unless they are integrated.

  The present invention has been made to solve the above-described problems, and an object thereof is to obtain an abnormal sound detection device for an elevator that can easily distinguish abnormal sound from normal sound.

The elevator abnormal sound detecting device according to the present invention is an elevator abnormal sound detecting device for diagnosing that an elevator is in an abnormal state based on a sound generated or propagated in a hoistway. Frequency analysis is performed to obtain the frequency spectrum, the abnormal sound analysis learning means for extracting the frequency band of the peak appearing in the frequency spectrum, and periodically collected when the elevator is in a normal state Normal sound analysis learning means for obtaining a frequency spectrum by performing frequency analysis of the sound, extracting a frequency band of a peak appearing in the frequency spectrum and storing it in a storage unit as a frequency band of normal sound, and the abnormal sound analysis learning means the frequency band extracted by, abnormal sound when there is a frequency band except the frequency band of the normal sound stored in the storage unit is generated Having a abnormal sound diagnosis means for diagnosing that.

  In the elevator abnormal sound detection device according to the present invention, the frequency band of the sound collected when the elevator is operating normally is detected and stored in the storage unit, and from the sound collected during the diagnostic operation Excludes stored frequency band sounds and diagnoses the presence or absence of abnormal sounds, so it is sufficient to extract the frequency band where the peak of the frequency spectrum appears, and the possibility of misjudging normal sounds as abnormal sounds is reduced In addition, the accuracy of abnormal sound diagnosis is improved.

BRIEF DESCRIPTION OF THE DRAWINGS It is a block diagram of the elevator provided with the abnormal noise detection apparatus of the elevator which concerns on Embodiment 1 of this invention. This is the frequency spectrum of the sound collected in the hoistway by driving the elevator during midnight silence. It is a frequency spectrum of the sound collected in the hoistway when a chime is ringing around the elevator. This is the frequency spectrum of the sound collected in the elevator hoistway near the railroad crossing when the alarm is sounding. It is a flowchart which shows the procedure of the normal sound analysis learning routine which the normal sound analysis learning means which concerns on Embodiment 1 of this invention performs. It is a flowchart which shows the procedure of the abnormal sound diagnostic routine which the abnormal sound diagnostic means which concerns on Embodiment 1 of this invention performs. It is a block diagram of the elevator provided with the abnormal sound detection apparatus of the elevator which concerns on Embodiment 2 of this invention. It is a frequency spectrum of the collision sound when the counterweight collides with the elevator car. It is a frequency spectrum of the sliding sound when a main rope is caught in a hoistway apparatus. It is a flowchart which shows the procedure of the abnormal sound diagnostic routine which the abnormal sound diagnostic means based on Embodiment 2 of this invention performs.

Embodiment 1 FIG.
1 is a configuration diagram of an elevator equipped with an abnormal noise detection apparatus for an elevator according to Embodiment 1 of the present invention.
As shown in FIG. 1, an elevator according to Embodiment 1 of the present invention includes a sound collecting microphone 2 provided in an elevator car 1, an elevator control panel 3 that controls the elevator, and an abnormal sound that diagnoses sound. And a detection device 4.
The sound collection microphone 2 collects sound in the hoistway, but mainly collects normal sound and diagnostic operation. The normal sound is sound that enters from the surroundings when it is confirmed that the elevator is in a normal state. The sound collection during the diagnostic operation collects the sound generated in the hoistway when the elevator stopped by the earthquake control operation after the occurrence of an earthquake is detected by an earthquake detector (not shown).
The elevator control panel 3 has various operations and operations such as normal operation of the elevator, seismic control operation when an earthquake occurs, and diagnostic operation that automatically diagnoses whether there is any abnormality in the elevator before returning to normal operation after the occurrence of an earthquake. To control.

  The abnormal sound detection device 4 obtains a frequency spectrum by Fourier transform of the sound collected by the sound collection microphone 2 during the diagnostic operation performed after the shaking of the earthquake is stopped, and collides with the sound collected from the frequency spectrum. Digital processing unit 5 for determining whether or not a noise sound is included, collected sound data, diagnosis result, storage unit 6 for storing frequency band of normal sound used for diagnosis, line connected to communication network It has an interface 7 and a USB connector 9.

  The digital processing unit 5 periodically captures normal sound from the sound collecting microphone 2 when the elevator is in normal operation, obtains a frequency spectrum by Fourier transforming the normal sound, and the amplitude of the obtained frequency spectrum is a predetermined threshold value. In the above case, the normal sound analysis learning means 5a that stores the frequency band indicating the amplitude in the storage unit 6 as the normal sound frequency band, and the target sound collected from the sound collecting microphone 2 during the diagnostic operation are analyzed. Abnormal sound analysis learning means 5b for learning, abnormal sound diagnosis means 5c for performing abnormal sound diagnosis, and abnormal sound recording means 5d for recording abnormal sound when abnormal sound is detected by abnormal sound diagnosis. .

  The digital processing unit 5 is realized using a computer of the elevator control panel 3. That is, the program for the digital processing unit 5 is installed in the ROM of the computer of the elevator control panel 3, the installed program is read, and the sound data is processed according to the instructions of the read program.

The normal sound analysis learning means 5a analyzes and learns the sound collected during the trial operation when the elevator is newly installed and the sound collected at a predetermined period after the use of the elevator is started.
For example, normal operation is instructed to the elevator control panel 3 when the midnight surroundings are quietly wrapped, and sound is collected from the sound collecting microphone 2 over a predetermined time period when the elevator is operating normally. The frequency spectrum obtained by Fourier transforming the sound at this time does not generate a peak as shown in FIG.
Further, for example, when the chime is sounded, normal operation is commanded to the elevator control panel 3, and when the elevator is operating normally, sound is collected from the sound collecting microphone 2 over a predetermined time period. The frequency spectrum obtained by Fourier transforming the sound at this time has a peak in the chime frequency band as shown in FIG.

Further, for example, in the case of an elevator near a railroad crossing, normal operation is commanded to the elevator control panel 3 when a crossing warning is sounded, and the sound collecting microphone 2 is used over a predetermined time period when the elevator is operating normally. To collect sound. As shown in FIG. 4, the frequency spectrum obtained by Fourier transforming the sound at this time has a peak in the alarm frequency band.
Similarly, the sound of broadcasts in the hall, BGM, siren sounds of fire engines and police cars, wind noise generated during traveling on the elevator shaft during strong winds, and the like are collected.

The abnormal sound detection device 4 transmits information on the frequency band of the normal sound to the monitoring center 12 when detecting the peak of the frequency band of the normal sound, and the monitoring center 12 is installed in the elevator to be monitored. Information on the frequency band of the normal sound received is distributed to the abnormal sound detection device 4. The abnormal sound detection device 4 that has received the distribution updates the information on the frequency band of the normal sound stored in the storage unit 6 using the information on the frequency band of the normal sound that has been distributed.
As described above, since the abnormal sound detection device 4 can use the siren sound of a fire truck or police car detected during an earthquake disaster or the like for the abnormal sound diagnosis of other abnormal sound detection devices 4, the accuracy of the abnormal sound diagnosis is improved. .

  The normal sound analysis learning means 5a stores the frequency band thus analyzed in the storage unit 6 as the frequency band of normal sound used for diagnosis. In addition, although the analyzed frequency band is memorize | stored in the memory | storage part 6 as it is the first time, the analyzed frequency band and the frequency band memorize | stored in the memory | storage part 6 are compared from the second time, and the frequency band partially overlapped is new. Update to the analyzed frequency band.

Next, a normal sound analysis learning routine executed by the normal sound analysis learning means 5a will be described. FIG. 5 is a flowchart showing the procedure of a normal sound analysis learning routine executed by the normal sound analysis learning means 5a.
In step S101, the elevator is normally operated.
In step S102, the sound in the hoistway is collected over a predetermined time period.
In step S103, it is determined whether or not the collected sound includes a sound having a predetermined sound pressure or higher. If included, the process proceeds to step S104. If not, the normal sound analysis learning routine is executed. finish.

In step S104, the collected sound is Fourier transformed to obtain a frequency spectrum.
In step S105, the peak frequency band appearing in the frequency spectrum is extracted.
In step S106, the frequency band of normal sound is read from the storage unit 6.
In step S107, it is determined whether there is a normal sound frequency band in the vicinity of the extracted frequency band. If there is a normal sound frequency band in the vicinity, the process proceeds to step S108, and there is no normal sound frequency band in the vicinity. If so, the process proceeds to step S109.
In step S108, the extracted frequency band having a normal sound frequency band nearby is replaced with the normal sound frequency band and stored in the storage unit 6, and the normal sound analysis learning routine is terminated.
In step S109, the extracted frequency band having no normal sound frequency band nearby is stored in the storage unit 6 as the normal sound frequency band, and the normal sound analysis learning routine is terminated.

  The abnormal sound analysis learning means 5b performs a Fourier transform on the time-series sound data input from the sound collection microphone 2 over a predetermined time period to obtain a frequency spectrum. Then, it is determined that a peak has occurred when the amplitude of the frequency spectrum is equal to or greater than a predetermined threshold, and the frequency band is extracted.

  The abnormal sound diagnosis means 5c reads the frequency band used for diagnosis from the storage unit 6, compares the frequency band extracted by the abnormal sound analysis learning means 5b with the read frequency band, and extracts the extracted frequency that matches the read frequency band. The band is deleted, and it is determined whether or not the extracted frequency band remains. And when it does not remain, assuming that the elevator is operating normally, the traveling speed is increased and the diagnostic operation is continued. When it remains, the elevator control panel 3 is instructed to stop the diagnostic operation because it is in an abnormal state.

Next, an abnormal sound diagnosis routine executed by the abnormal sound diagnosis means 5c will be described. FIG. 6 is a flowchart showing a procedure of an abnormal sound diagnosis routine executed by the abnormal sound diagnosis means 5c.
In step S201, the elevator performs the slowest diagnostic operation.
In step S202, the sound in the hoistway is collected over a predetermined time period.
In step S203, it is determined whether or not the collected sound includes a sound having a predetermined sound pressure or higher. If included, the process proceeds to step S204. If not, the process proceeds to step S210.

In step S204, the collected sound is Fourier transformed to obtain a frequency spectrum.
In step S205, the peak frequency band appearing in the frequency spectrum is extracted.
In step S206, the frequency band of normal sound is read from the storage unit 6.
In step S207, the frequency band of the normal sound is deleted from the extracted frequency band.
In step S208, it is determined whether or not the frequency band remains. When the frequency band remains, the process proceeds to step S209. When the frequency band does not remain, the process proceeds to step S210.

In step S209, the elevator control panel is commanded to stop the diagnostic operation, and the abnormal sound diagnosis routine is terminated.
In step S210, the speed is set one step higher.
In step S211, it is determined whether or not the speed is a speed during normal operation. If the speed is a speed during normal operation, the abnormal sound diagnosis routine is terminated. If the speed is not a speed during normal operation, The process proceeds to S212.
In step S212, the diagnosis operation is performed at the set speed, and the process returns to step S202.

  The line interface (line I / F) 7 is connected to the communication network 11, and transmits a diagnosis result stored in the storage unit 6 via the communication network 11 when a request for a diagnosis result is received from the outside.

The maintenance staff connects the diagnostic result confirmation personal computer 8 to the USB connector 9 provided in the abnormal sound detection device 4 in the building where the elevator is installed, reads the diagnostic result, and displays the diagnostic result on the screen.
The monitoring person receives the diagnosis result from the abnormal sound detecting device 4 at the monitoring table 13 connected to the abnormal sound detecting device 4 via the communication network 11 in the monitoring center 12 remote from the building where the elevator is installed. Acquired and displays the diagnosis result on the screen of the monitor 13.

  In the elevator abnormal sound detection device 4 according to the first embodiment of the present invention, the frequency band of the sound collected when the elevator is operating normally is detected and stored in the storage unit 6 for diagnosis operation. Since the presence of abnormal sound is diagnosed by removing the stored frequency band sound from the collected sound, it is sufficient to extract the frequency band where the peak of the frequency spectrum appears, and normal sound is regarded as abnormal sound. The possibility of erroneous determination is reduced, and the accuracy of abnormal sound diagnosis is improved.

In addition, since the frequency band related to the normal sound is periodically updated, it is possible to cope with a change in the sound generated in the surroundings, so that the accuracy of the abnormal sound diagnosis is further improved.
Moreover, since it can implement | achieve by modifying the program of the elevator control panel 3, it can be inexpensive and can improve the precision of abnormal sound diagnosis.

Embodiment 2. FIG.
FIG. 7 is a configuration diagram of an elevator including the elevator abnormal sound detection device according to Embodiment 2 of the present invention.
The abnormal sound detecting device 4B for an elevator according to Embodiment 2 of the present invention includes an abnormal sound detecting device 4 for an elevator and abnormal sound diagnosing means 5Bc according to Embodiment 1 of the present invention, and a storage unit 6 related thereto. Since the frequency band of the abnormal sound is stored, and other than that is the same, the same reference numerals are added to the same parts and the description is omitted.
Before installing the abnormal sound detection device 4B of the elevator, the abnormal sound in the elevator hoistway collected in the past is Fourier-transformed to obtain a frequency spectrum, and a peak occurring in the obtained frequency spectrum appears. The frequency band currently being extracted is extracted.

For example, in the frequency spectrum of the collision sound generated when the elevator car and the counterweight collide, a peak appears in the frequency band B ₀ of the center frequency f ₀ as shown in FIG. Further, as shown in FIG. 9, the frequency spectrum of the sliding sound generated when the main rope is caught by the hoistway equipment has peaks over the frequency bands B _{1 to} B ₄ of the center frequencies f _{1 to} f _4. Yes. These frequency bands B ₀ and B _{1 to} B ₄ are extracted in advance.
And, when installing the abnormal sound detecting apparatus 4B elevator, stores B _0, B ₁ ~B ₄ in the storage section 6 as the frequency band of the abnormal sound.

  The abnormal sound diagnosis means 5Bc reads the normal sound frequency band used for diagnosis from the storage unit 6, compares the frequency band extracted by the abnormal sound analysis learning means 5b with the read normal sound frequency band, and reads the read normal sound. The extracted frequency band that matches the frequency band of is deleted. When the extracted frequency band remains, the abnormal frequency band used for diagnosis is read from the storage unit 6 and the remaining extracted frequency band is compared with the read abnormal frequency band to obtain the frequency of the abnormal sound. When the frequency band that coincides with the band remains, the diagnosis operation is stopped and the elevator is visually inspected because it is in an abnormal state. When the frequency band that matches the frequency band of the abnormal sound does not remain, the diagnosis operation is continued at the same speed.

Next, an abnormal sound diagnosis routine executed by the abnormal sound diagnosis means 5Bc will be described. FIG. 10 is a flowchart showing the procedure of the abnormal sound diagnosis routine executed by the abnormal sound diagnosis means 5Bc.
In step S221, the lowest speed diagnostic operation is performed on the elevator.
In step S222, the sound in the hoistway is collected over a predetermined time period.
In step S223, it is determined whether or not the collected sound includes a sound having a predetermined sound pressure or higher. If included, the process proceeds to step S224. If not, the process proceeds to step S232.

In step S224, the collected sound is Fourier transformed to obtain a frequency spectrum.
In step S225, the peak frequency band appearing in the frequency spectrum is extracted.
In step S226, the frequency band of normal sound is read from the storage unit 6.
In step S227, the frequency band of normal sound is deleted from the extracted frequency band.
In step S228, it is determined whether or not the frequency band remains. When the frequency band remains, the process proceeds to step S229. When the frequency band does not remain, the process proceeds to step S232.

In step S229, the frequency band of the abnormal sound is read from the storage unit 6.
In step S230, it is determined whether or not there is an abnormal sound frequency band among the remaining frequency bands. If there is, the process proceeds to step S231, and if not, the process returns to step S222.
In step S231, the elevator control panel 3 is instructed to stop the diagnostic operation, and the abnormal sound diagnosis routine is terminated.
In step S232, the speed is set one step higher.
In step S233, it is determined whether or not the speed is a speed during normal operation. If the speed is a speed during normal operation, the abnormal sound diagnosis routine is terminated. If the speed is not a speed during normal operation, The process proceeds to S234.
In step S234, diagnostic operation is performed at the set speed, and the process returns to step S222.

  Elevator abnormal sound detection device 4B according to Embodiment 2 of the present invention has the same effects as elevator abnormal sound detection device 4 according to Embodiment 1 of the present invention, and an abnormality stored in storage unit 6 Since it is checked again whether or not the sound is abnormal using the frequency band of the sound, the possibility that the normal sound is erroneously determined as the abnormal sound is further reduced, and the accuracy of the abnormal sound diagnosis is further improved.

  1 car, 2 sound collecting microphones, 3 elevator control panel, 4 and 4B abnormal sound detection device, 5 digital processing unit, 5a normal sound analysis learning means, 5b abnormal sound analysis learning means, 5c, 5Bc abnormal sound diagnosis means, 5d abnormality Sound recording means, 6 storage unit, 7 line interface, 8 PC for diagnosis result confirmation, 9 USB connector, 11 circuit network, 12 monitoring center, 13 monitoring console.

Claims (3)

In the elevator abnormal sound detection device that diagnoses that the elevator is in an abnormal state based on the sound generated or propagated in the hoistway,
Abnormal sound analysis learning means for obtaining a frequency spectrum by performing frequency analysis on the sound collected over a predetermined time period, and extracting a peak frequency band appearing in the frequency spectrum;
Frequency analysis of the sound collected periodically when the elevator is in a normal state to obtain a frequency spectrum, extracting a peak frequency band appearing in the frequency spectrum and storing it as a normal sound frequency band Normal sound analysis learning means to memorize,
An abnormal sound diagnosis means for diagnosing that an abnormal sound is generated when there is a frequency band other than the frequency band of the normal sound stored in the storage unit in the frequency band extracted by the abnormal sound analysis learning means ;
An abnormal sound detecting device for an elevator characterized by comprising: In the elevator abnormal sound detection device that diagnoses that the elevator is in an abnormal state based on the sound generated or propagated in the hoistway,
Abnormal sound analysis learning means for obtaining a frequency spectrum by performing frequency analysis on the sound collected over a predetermined time period, and extracting a peak frequency band appearing in the frequency spectrum;
Frequency analysis of the sound collected periodically when the elevator is in a normal state to obtain a frequency spectrum, extracting a peak frequency band appearing in the frequency spectrum and storing it as a normal sound frequency band Normal sound analysis learning means to memorize,
When the normal sound frequency band stored in the storage unit is removed from the frequency band extracted by the abnormal sound analysis learning means , and the remaining frequency band includes the frequency band of the abnormal sound detected in advance, the abnormal sound An abnormal sound diagnosis means for diagnosing the occurrence of
An abnormal sound detecting device for an elevator characterized by comprising: Means for distributing information on the frequency band of normal sound stored in the storage unit to the other abnormal sound detection devices of the elevator;
Means for updating information on the frequency band of the normal sound stored in the storage unit when receiving information on the frequency band of the normal sound from an abnormal sound detection device of another elevator. The elevator abnormal sound detection device according to claim 1 or 2 .

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