CN111480196B - Sound measurement system and parameter generation device - Google Patents
Sound measurement system and parameter generation device Download PDFInfo
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- CN111480196B CN111480196B CN201780097594.4A CN201780097594A CN111480196B CN 111480196 B CN111480196 B CN 111480196B CN 201780097594 A CN201780097594 A CN 201780097594A CN 111480196 B CN111480196 B CN 111480196B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R29/00—Monitoring arrangements; Testing arrangements
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B3/00—Applications of devices for indicating or signalling operating conditions of elevators
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K15/00—Acoustics not otherwise provided for
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K15/00—Acoustics not otherwise provided for
- G10K15/02—Synthesis of acoustic waves
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- Audiology, Speech & Language Pathology (AREA)
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Abstract
A sounding body (5) is provided in the vicinity of a diagnosis target device (4) that is a measurement target. A measurement unit (6) transmits a test signal, which is a unit signal having one frequency component at each time and whose center frequency varies with time, between the sounding body (5) and the sound receiving body (2) on the time axis, and acquires a measurement signal obtained from the sound receiving body (2). An estimation unit (7) estimates the propagation characteristics of sound from the sounding body (5) to the sound receiving body (2) on the basis of the relationship between the time and the intensity of the unit signal.
Description
Technical Field
The present application relates to a sound measurement system that measures a propagation characteristic of sound, and a parameter generation device that generates a parameter for determining whether an object to be grasped is in a normal state or an abnormal state using the sound measurement system.
Background
As for measurement of the propagation characteristics of sound, for example, an apparatus shown in patent document 1 is known. The device uses a time-spread pulse (TSP: time Stretched Pulse) signal in the measurement of the propagation time of sound waves between a speaker and a microphone.
The propagation characteristics of sound are a general term for impulse response, transfer function, propagation time, distance attenuation, and the like.
Prior art literature
Patent literature
Patent document 1: japanese patent laid-open No. 2004-193782
Disclosure of Invention
Problems to be solved by the application
In the above-described conventional device, since the installation positions of the speaker and microphone are fixed, there is a problem that propagation characteristics that vary with time cannot be estimated with high accuracy.
The present application has been made to solve the above-described problems, and an object of the present application is to provide a sound measurement system capable of estimating a propagation characteristic that varies with time with high accuracy.
Means for solving the problems
The sound measurement system of the present application comprises: a sounding body provided on a fixed side or a movable side of a measurement object; a sound receiving body provided at a sound receiving point on a moving side or a fixed side opposite to the measurement object; a measurement unit that transmits a test signal, which is a plurality of unit signals each having a single frequency component at each time point and whose center frequency varies with time, from the sounding body to the receiving body, to the sounding body and transmits the test signal to the receiving body, and acquires a measurement signal obtained from the receiving body; and an estimating unit that estimates a propagation characteristic of sound from the sounding body to the sound receiving body based on a relationship between time and intensity of each of the plurality of unit signals included in the measurement signal.
Effects of the application
The sound measurement system of the present application estimates the propagation characteristics of sound from a sound generating body to a sound receiving body by transmitting a test signal from the sound generating body to the sound receiving body and propagating the test signal between the sound generating body and the sound receiving body, the test signal being formed by arranging a plurality of unit signals having one frequency component at each time point and the center frequency of the frequency component varying with time on a time axis. This makes it possible to estimate the propagation characteristics that change with time with high accuracy.
Drawings
Fig. 1 is a block diagram showing an example of application of the sound measurement system according to embodiment 1 of the present application.
Fig. 2 is a block diagram showing a sound measurement system and a parameter generation device according to embodiment 1 of the present application.
Fig. 3 is a block diagram of a sounding body in the sound measurement system according to embodiment 1 of the present application.
Fig. 4 is a block diagram of a computer that implements the sound measurement system and the parameter generation device according to embodiment 1 of the present application.
Fig. 5 is a flowchart showing the operation of the sound measurement system according to embodiment 1 of the present application.
Fig. 6 is a flowchart showing the operation of the estimating unit in the acoustic measurement system according to embodiment 1 of the present application.
Fig. 7 is an explanatory diagram of a process of estimating propagation characteristics from an acoustic signal in an estimating unit of an acoustic measurement system according to embodiment 1 of the present application.
Fig. 8 is a flowchart showing the operation of the parameter generating apparatus according to embodiment 1 of the present application.
Fig. 9 is an explanatory diagram showing a threshold value determination method in the parameter generation apparatus according to embodiment 1 of the present application.
Fig. 10 is an explanatory diagram showing another example of the threshold value determination method in the parameter generation apparatus according to embodiment 1 of the present application.
Fig. 11 is an explanatory diagram showing arrangement of unit signals in the acoustic measurement system according to embodiment 2 of the present application.
Fig. 12 is a flowchart showing the operation of the estimating unit in the acoustic measurement system according to embodiment 2 of the present application.
Fig. 13 is an explanatory diagram showing time aggregation processing in the audio measurement system according to embodiment 2 of the present application.
Fig. 14A is an explanatory view when time aggregation processing is not performed on the unit signal arrangement, and fig. 14B is an explanatory view when time aggregation processing is performed.
Fig. 15 is an explanatory diagram showing arrangement of unit signals in the acoustic measurement system according to embodiment 3 of the present application.
Fig. 16 is a flowchart showing the operation of the estimating unit in the acoustic measurement system according to embodiment 3 of the present application.
Fig. 17 is an explanatory diagram showing time integration processing in the audio measurement system according to embodiment 3 of the present application.
Fig. 18A to 18D are explanatory diagrams showing measurement examples of propagation characteristics of unit signal arrangements based on a multiplexing degree 8 in the acoustic measurement system according to embodiment 3 of the present application.
Detailed Description
In the following, modes for carrying out the present application will be described in detail with reference to the accompanying drawings.
Embodiment 1
Fig. 1 is a block diagram of an elevator system showing an example of application of a parameter generation device according to the present embodiment.
The parameter generating device is composed of a sound sensor 2 and a computer 3 mounted above the car 1, and a sounding body 5 provided near the object 4. The car 1 is a car of an elevator, and the sound sensor 2 is constituted by a microphone. The computer 3 has a USB terminal and a LAN terminal, and the sound sensor 2 is connected to the USB terminal via an audio interface circuit, not shown. A device controlled by the computer 3 is connected to the LAN terminal. The parameter generation device generates parameters for an abnormal sound diagnosis device of the elevator system shown in the figure, for example.
The measurement object 4 is a diagnosis object device in the abnormal sound diagnosis apparatus, and as the diagnosis object device, is a device located in the hoistway of the elevator. For example, there are a sheave provided on the top of a rope for driving the car 1, a sheave for supporting the car 1 from below, a car rail for preventing the car from swinging laterally, a counterweight for balancing the weight of the car 1, a speed limiter for adjusting the car speed, and the like. The sounding body 5 is constituted by a speaker or the like.
Fig. 2 is a block diagram of the sound measurement system according to embodiment 1 and the parameter generation device using the sound measurement system. The sound measurement system 21 includes a sound sensor 2, a sounding body 5, a measurement unit 6, and an estimation unit 7. The parameter generating device 22 includes an analog sound synthesizing unit 8, a sound source database (sound source DB) 9, a simulation unit 10, and a parameter storage unit 11. The sound sensor 2 is a sound receiving body in the sound measurement system 21, and is configured using a microphone. The sounding body 5 is disposed near the measurement object 4, and is configured to generate test sound corresponding to the test signal supplied from the measurement unit 6.
Fig. 3 is a structural view of the sounding body 5. As shown in the figure, the sounding body 5 is composed of a control unit 51, a communication interface (communication I/F) 52, and a speaker 53. The control unit 51 is constituted by a microcomputer, and has the following functions: the test signal is received by wireless communication with the measuring unit 6 via the communication interface 52, and the speaker 53 is driven based on the received test signal to perform output control of test sound. The communication interface 52 has an interface of a wireless LAN, and has a function of performing communication control with the measurement unit 6. The speaker 53 is a speaker for transmitting test sound into the air in the hoistway of the elevator.
Returning to fig. 2, the measurement unit 6 has the following functions: the test sound is sent from the sounding body 5, and the test sound propagated in the hoistway is acquired by the sound sensor 2. Here, as shown in fig. 7 described later, the test sound is a unit signal having one frequency component at each time point and whose center frequency varies with time, which is arranged on the time axis. As the unit signal, a time-spread pulse (TSP) signal can be used.
The estimating unit 7 has the following functions: based on the relationship between the time and the intensity of the unit signal included in the test signal, the propagation characteristics of sound from the sounding body 5 to the sound sensor 2 are estimated. The simulated sound synthesizing unit 8 has a function of generating a synthesized simulated sound of an abnormal sound using the sound sources stored in the sound source database 9. The simulation unit 10 has a function of determining parameters from the synthesized simulated sound generated by the simulated sound synthesizing unit 8. The parameter storage unit 11 is a storage unit for parameters determined by the simulation unit 10.
These sound measurement systems and parameter generation devices are configured by using the computer 3. Fig. 4 shows a hardware configuration diagram of the computer 3. As shown, the computer 3 is composed of a processor 31, a memory 32, an input-output interface (input-output I/F) 33, and a storage 34. The processor 31 is a processor for executing a program stored in the memory 32 or the storage 34, and is configured by using a CPU to realize the functions of the measuring unit 6, the estimating unit 7, the analog synthesizing unit 8, and the simulating unit 10. The memory 32 is a memory that is constituted by a RAM or the like, temporarily stores data or the like, and constitutes a work area of the processor 31. The input/output interface 33 is an interface for transmitting and receiving signals to and from the sound sensor 2 and the sounding body 5 and for communicating with other external devices. The memory 34 is a storage unit for storing various data and storing programs corresponding to the respective functions of the measuring unit 6, the estimating unit 7, the analog acoustic synthesizing unit 8, and the simulating unit 10. Further, the memory 34 realizes the sound source database 9 and the parameter storage section 11.
Next, the operation of the sound measurement system and the parameter generation device according to embodiment 1 will be described.
Fig. 5 is a flowchart showing the operation of the sound measurement system.
First, the measuring unit 6 transmits a test signal to the sounding body 5, and generates a test sound from the sounding body 5 (step ST 1). Next, the sound sensor 2 receives a test sound (step ST 3) when the car 1 of the elevator is reciprocated between the lowermost floor and the uppermost floor (step ST 2), and the test sound is sent to the measuring unit 6. The test sound received by the acoustic sensor 2 is sent from the measuring unit 6 to the estimating unit 7, and the propagation characteristics are estimated by the estimating unit 7 (step ST 4), and the propagation characteristics as the estimation result are output (step ST 5).
Fig. 6 is a flowchart showing the operation of the estimating unit 7. Fig. 7 is an explanatory diagram of a process of estimating propagation characteristics from a test signal in the estimating section 7.
First, the estimating unit 7 performs time-frequency analysis on the received waveform to obtain an intensity distribution S (t, f) on the time axis (frame t) and the frequency axis (frequency width (bin)) f (step ST 11). The received waveform is divided into frames overlapping each other, and the intensity of each frequency width is obtained by FFT (fast fourier transform) for each frame, thereby performing time-frequency analysis. In fig. 7, a period 71 represents a unit signal period, and a spectrum 72 represents a spectrum of the measurement signal. The specific frequency band 73 is a specific frequency band for obtaining the signal strength among all the frequencies of each frame.
Next, the estimating unit 7 obtains the intensities included in the specific frequency band 73 for each frame t from the intensity distribution S (t, f) as an intensity time series B (t) (step ST 12). Further, the estimating unit 7 detects a peak in the intensity time series B (t) (step ST 13). The peak detection is performed by detecting the maximum value of the intensity time series B (t). In fig. 7, peaks 74a, 74b, 74c represent detected peaks. Here, when detecting a peak from the intensity time series B (t), components other than the unit signal component included in the received signal may be erroneously detected as a peak, and therefore, the interval between detected peaks is measured, and when the interval between peaks deviates from the unit signal period, the peak is removed (step ST 14). The process of step ST14 may be performed as needed, and may be omitted.
Finally, the estimating unit 7 extracts the peak envelope 75 (see fig. 7) connecting the detected peaks as the intensity of the abnormal sound (step ST 15), and outputs the signal of the peak envelope 75 as the estimated propagation characteristic (step ST 16).
Next, the operation of the parameter generation device 22 will be described along the flowchart of fig. 8. In the following description, it is assumed that the propagation characteristics 21a are obtained by the sound measurement system 21, and the analog acoustic synthesizing section 8 of the parameter generating apparatus 22 has already obtained the propagation characteristics 21a.
Here, the parameters generated in the present embodiment are as follows.
The abnormal sound diagnosis device is as follows: and respectively judging whether the action sound of the equipment is normal or abnormal according to the action sound of the equipment in a normal state and the action sound of the equipment in an abnormal state. In such an abnormal sound diagnostic apparatus, there is a threshold value, for example, as a parameter for determining normal and abnormal.
In addition to the abnormal sound diagnostic device, for example, the deteriorated sound diagnostic device, the abnormal portion estimating device, and the deteriorated portion estimating device have parameters for diagnosing the deteriorated sound and estimating the abnormal portion and the deteriorated portion, respectively, in the device. These parameters need to be adjusted to be most suitable for the respective device. Thus, in the present embodiment, synthetic simulated sounds are used to design and adjust these parameters. In addition, in practice, in many cases, the frequency of the failure of the device is low, and it is difficult to obtain a sample of abnormal sound or degraded sound, and therefore, it is necessary to use a synthetic simulated sound.
First, in a state where the test sound is emitted from the sounding body 5, the sound sensor 2 acquires a waveform of a normal operation sound when the car 1 of the elevator reciprocates between the lowermost floor and the uppermost floor (step ST 21) (step ST 22). The normal action sounds are recorded in the memory 32. Next, the simulated sound synthesizing unit 8 selects a sound source from the sound source database 9 (step ST 23), controls the intensity of the sound source according to the estimated propagation characteristics that change with time, overlaps with the normal operation sound recorded in the memory 32, synthesizes a plurality of simulated sounds having different abnormal/normal SN ratios (for example, SN ratios in the range of 0.1dB steps and 0 to 18 dB) (step ST 24), and outputs the synthesized simulated sound to the simulation unit 10 (step ST 25). For convenience of explanation, SN ratio 0 is SN ratio- ≡and normal action sound without abnormal sound component is synthesized sound.
Next, the simulation unit 10 obtains the relationship between the parameter in the abnormal sound diagnostic apparatus and the detection rate and the false detection rate, for example, using the synthesized simulated sound generated by the simulated sound synthesizing unit 8 (step ST 26). Here, the detection rate and the false detection rate are as follows. The detection rate is a rate at which the operation sound of the device in the abnormal state is accurately determined to be abnormal. On the other hand, the false detection rate is a rate at which the operation sound of the device in the normal state is erroneously determined to be abnormal. In addition, in order to obtain the detection rate and the false detection rate with high accuracy, it is necessary to simulate the detection rate using a large number of normal sounds and abnormal sounds.
As parameters that affect the detection rate and the false detection rate, the simulation unit 10 adjusts, for example, a threshold value to be referred to by the abnormal sound diagnostic apparatus. The abnormal sound diagnostic device analyzes the operation sound during the diagnostic operation, obtains the degree of abnormality, and then compares the degree of abnormality with a threshold value to determine whether or not there is an abnormality. Therefore, the threshold value is an important parameter for determining the detection rate and the false detection rate as the performance of the abnormal sound diagnostic apparatus.
Currently, when the vector representing the threshold value is θ, the vector representing the degree of anomaly is a, and the index indicating the elements of both vectors is K (k=0, 1,2, …, K is the dimension), the simulation unit 10 determines that the vector is abnormal if a [ K ] > Θ [ K ] is established for a certain K, and otherwise the simulation unit 10 determines that the vector is normal (see the following expression).
Here, the abnormality degree vector a is calculated as follows.
A＝(Y-μ)/σ
Y is a feature vector obtained by analyzing an action sound to be diagnosed, μ is an average vector thereof, and σ is a standard deviation vector. μ and σ are feature amounts (feature vectors) X obtained by analyzing N normal operation sounds 1 ,X 2 ,…,X N (N is the number of active sounds in normal conditions) and standard deviation.
Next, the simulation unit 10 obtains, as an optimal parameter, a parameter that obtains the maximum detection rate within the allowable range of the false detection rate (step ST 27). Currently, when the threshold value θk of the index k is set as a parameter, and the horizontal axis takes this value and the vertical axis takes the error rate (0 to 100%), the characteristics shown in fig. 9 are obtained. Here, (1-detection rate) is referred to as a omission rate 91, and false detection rate is referred to as an explosion rate 92. The larger the threshold value θk, the lower the burst rate 92, whereas the higher the omission factor 91. Further, a limit value 93, which is an allowable range of the false detection rate, is set to the burst rate 92. For example, when S/N is 6dB, the burst rate 92 is 5% or less.
As one method of determining the optimum value of the threshold value θk, the omission factor 91 can be determined to be the smallest under the limit value 93, and in this case, the point θ×k in the figure becomes the optimum value.
As shown in fig. 10, the relationship between S/N and a certain threshold (ath) can be obtained using the synthesized simulation sound after S/N is changed, the modulation threshold 101 for detecting an abnormality symptom is set to be a threshold of S/N6dB, and the abnormality threshold 102 for abnormality determination is determined to be a threshold of S/N6+α dB (α is, for example, 3 dB).
Then, the simulation unit 10 outputs the obtained optimal parameters (step ST 28), and stores the parameters in the parameter storage unit 11.
Next, an example will be described in which the simulation unit 10 learns sound source position estimation parameters using synthesized simulated sound.
For example, when the parameter generating device is applied to the abnormal location estimating device, the sound source position to be estimated by the abnormal location estimating device is, for example, a car, pit, counterweight, roof, or the like in an elevator. Here, the sound source position means a position where the device generating the abnormal sound is disposed in the hoistway, that is, a height from the bottom surface of the hoistway. The abnormal-position estimating means estimates the sound source position by referring to the sound source position estimation parameter. Therefore, the simulation unit 10 optimizes the load and the deviation of the neural network, which are sound source position estimation parameters to be referred to by the abnormal location estimation device, as parameters that affect the estimation of the sound source position.
As an example thereof, the abnormal position estimating device obtains an abnormal degree curve, which is a change curve of the abnormal degree corresponding to the car position of the elevator, from an abnormal degree vector obtained by analyzing the operation sound at the time of diagnosis, inputs the abnormal degree curve to the neural network, obtains the estimated scores of the sound source position, that is, the scores of "car", "pit", "counterweight" and "top", and outputs the recognition result having the largest score as the estimated result of the sound source position. The sound source position estimation parameters of the neural network are composed of load and deviation, and are learned by using synthesized simulated sound whose sound source position is known as training data.
As described above, the sound measurement system according to embodiment 1 includes: a sounding body provided to a measurement object; a sound receiving body provided at a sound receiving point; a measurement unit for transmitting a test signal between the sound generating body and the sound receiving body, and obtaining a test signal obtained from the sound receiving body, the test signal being obtained by arranging unit signals having one frequency component at each time and a center frequency of the frequency component varying with time on a time axis; and an estimating unit that estimates a propagation characteristic of sound from the sounding body to the sound receiving body based on a relationship between time and intensity of the unit signal included in the test signal, whereby the propagation characteristic that varies with time can be estimated with high accuracy.
Further, according to the sound measurement system of embodiment 1, since the unit signal is a time-spread pulse signal, the propagation characteristics of sound can be estimated with high accuracy.
Further, according to the parameter generation device of embodiment 1, since the parameter for determining whether the measurement object is in the normal state or the abnormal state is generated using the propagation characteristics estimated by the sound measurement system of embodiment 1, it is possible to obtain the parameter that enables highly accurate determination even when the propagation characteristics change with time.
Further, the parameter generation device according to embodiment 1 includes: a simulated sound synthesizing unit that generates a synthesized simulated sound using the propagation characteristics estimated by the estimating unit; and a simulation unit that determines parameters using synthesized simulated sound, thereby obtaining parameters that can be determined with higher accuracy.
Embodiment 2
The sound receiving signal includes, as noise, device noise (normal operation sound) and external noise in addition to the test signal component emitted from the sounding body. In particular, since the frequency components of the impulsive noise are concentrated in time, the possibility of false detection as a peak is high. Therefore, in embodiment 2, a sound measurement system in which impact noise is removed and influence on propagation characteristic estimation is described. The configuration in the drawings as the sound measurement system and the parameter generation device is the same as that shown in fig. 2, and therefore, will be described with reference to fig. 2.
The estimation unit 7 according to embodiment 2 is configured to perform frequency analysis on the unit signal, and to determine propagation characteristics by shifting the time axis so that the components of the unit signal become the same time for each frequency. Other configurations as the sound measurement system and the parameter generation device are the same as those of embodiment 1.
Next, the operation of embodiment 2 will be described.
Fig. 11 is an explanatory diagram showing the arrangement of unit signals in embodiment 2. As shown, the estimation unit 7 obtains the arrangement of the unit signals 112 in the unit signal period 111. The estimation unit 7 performs time integration processing on the unit signal arrangement. Fig. 12 is a flowchart showing the operation of the estimating unit 7.
First, the estimation unit 7 performs time-frequency analysis on the waveforms of the acquired unit signal arrangement to obtain intensity distributions S (t, f) on the time axis (frame t) and the frequency axis (frequency width f) (step ST 31). Next, the intensity distribution S' (t, f) obtained by shifting the time axis by the time shift amount d (f) corresponding to the frequency f is obtained for each frequency width f component of the intensity distribution S (t, f) (step ST 32). Here, the time offset d (fc) for the frequency f=fc is calculated using the following equation.
d(fc)＝fc/(Fs/2)*Tw
Here, fs is a sampling frequency, tw is a time length (coinciding with a period) of a unit signal. Further, a frame offset number nd (fc) in which the time offset d (fc) is converted into a frame number (discrete value) is calculated by the following equation.
nd(fc)＝int(d(fc)/fp+0.5)
Here, fp is a frame interval (frame period), int (x) is an integer function for an argument, and 0.5 is a number for reducing a suspension error associated with the integer.
Therefore, the intensity distribution S' (t, f=fc) after the time axis is shifted is calculated by the following equation.
S’(t,f＝fc)＝S(t+nd(fc),f＝fc)
Fig. 13 is an explanatory diagram showing the processing of steps ST31 and ST32 described above.
The time-frequency distribution of the original unit signal (the unit signal arrangement shown in fig. 11) is represented by diagonal stripes shown in fig. 13, and the time-assembled signal after the time axis shift is represented by vertical stripes in fig. 13. That is, the unit signal 132 of the unit signal period 131 is shifted in time axis, and a time-integrated signal (shifted unit signal) 133 is obtained. Here, the arrow to the left indicates the time shift amount with respect to the original unit signal in each frequency (the time shift amount corresponds to nd (fc) calculated above assuming fc as each frequency).
Next, the estimating unit 7 obtains the intensities included in the specific frequency band for each frame t from the intensity distribution S' (t, f) of the time-integrated signals, and sets the intensities as an intensity time series B (t) (step ST 33). Further, the estimating unit 7 detects a peak in the intensity time series B (t) (step ST 34). The peak detection is performed by detecting the maximum value of the intensity time series B (t). Here, when detecting a peak from the intensity time series B (t), components other than the unit signal component included in the received signal may be erroneously detected as a peak, and therefore, the interval between detected peaks is measured, and if the interval between peaks deviates from the unit signal period, the peak is removed (step ST 35). The process of step ST35 may be performed as needed, or may be omitted.
Finally, the estimating unit 7 extracts a peak envelope curve connecting the detected peaks (step ST 36), corrects the time delay due to the time shift (step ST 37), and outputs the extracted peak envelope curve as an estimated propagation characteristic (step ST 38).
Fig. 14A shows a time-frequency intensity distribution when impact noise (which can be regarded as interference estimated for propagation characteristics) is superimposed on an acoustic signal, and a peak envelope estimated from the time-frequency intensity distribution. The unit signal component 141a in the acoustic signal is represented by diagonal stripes, and the impulsive noise (disturbance 142 a) is represented by vertical stripes. Thus, as the intensity in the specific frequency band 143, the peak 145a among the peaks 144a to 146a is a higher value than the peaks 144a and 146a due to the influence of the interference 142 a. Thus, peak envelope 147a differs from estimate 148 in the absence of interference due to the effect of peak 145 a.
Fig. 14B shows a time-frequency distribution obtained by applying a frequency-dependent time offset to the time-frequency distribution of fig. 14A and a peak envelope estimated from the time-frequency distribution. The unit signal component 141b after time shift is represented as a vertical stripe, and the disturbance 142b after time shift is represented as a diagonal stripe. As a result, the peak envelope 147b is also close to the estimated result 148 in the absence of the disturbance shown in fig. 14A, because the influence of the disturbance 142b after the time shift is not present in the peaks 144b to 146b, which are the intensities of the specific frequency bands 143.
As is clear from a comparison of fig. 14A and 14B, the influence of the impact disturbance is removed from the estimated propagation characteristics as a result of the frequency-dependent time shift.
As described above, according to the acoustic measurement system of embodiment 2, the estimation unit obtains the propagation characteristics by shifting the time axis for each frequency so that the intensities of the unit signals are equal to each other, and thus, for example, even in the presence of impulsive noise, the propagation characteristics can be estimated with high accuracy.
Embodiment 3
In embodiments 1 and 2 in which unit signals having a multiplexing degree of 1 are used, the interval between peaks constituting the peak envelope becomes the period of the unit signal. When the propagation characteristics change rapidly with respect to time, it is necessary to measure the propagation characteristics at a period shorter in time than the period of the unit signal. Therefore, as embodiment 3, a sound measurement system capable of satisfactorily measuring propagation characteristics even when the propagation characteristics change rapidly with respect to time is described. In the present embodiment, the case where the multiplexing degree of the unit signal arrangement is set to 2 is described in order to avoid the complexity of the description, but the present embodiment can be applied to a case where the multiplexing degree is 3 or more, for example, 8. The configuration in the drawings as the sound measurement system and the parameter generation device is the same as that shown in fig. 2, and therefore, will be described with reference to fig. 2.
The measurement unit 6 according to embodiment 3 is configured to use a unit signal arrangement in which a plurality of unit signals each having a timing offset are multiplexed on a time axis, as a test signal. The estimating unit 7 is configured to divide the frequencies based on the degree of multiplexing of the multiplexed unit signal arrangement, and to determine the propagation characteristics by shifting the time axis for each frequency so that the intensities of the unit signals become the same for each division. Other configurations as the sound measurement system and the parameter generation device are the same as those of embodiment 1.
Next, the operation of embodiment 3 will be described.
Fig. 15 is an explanatory diagram showing the arrangement of unit signals in embodiment 3. As shown in the figure, the estimation unit 7 obtains an arrangement of unit signals 152 in a unit signal period 151 of a multiplexing degree 2. That is, the unit signal arrangement is obtained by multiplexing 2 unit signals 152 in the unit signal period 151. The estimation unit 7 performs time integration processing on the unit signal arrangement. Fig. 16 is a flowchart showing the operation of the estimating unit 7. Here, the degree of multiplexing is set to m.
First, the estimating unit 7 performs time-frequency analysis on the received waveform to obtain an intensity distribution S (t, f) on the time axis (frame t) and the frequency axis (frequency width f) (step ST 41). Next, the intensity distribution S' (t, f) obtained by shifting the time axis by the time shift amount d (f) corresponding to the frequency f is obtained for each frequency width f component of the intensity distribution S (t, f) (step ST 42). Here, the time offset d (fc) for the frequency f=fc is calculated using the following equation.
The m-divided frequency bands are divided into m-divided frequency bands, the index ix of the m-divided frequency band to which fc belongs is obtained, and the time offset d (fc) is calculated from ix as follows.
bw＝(Fs/2)/m
ix＝int(fc/bw)
d(fc)＝(fc-bw*ix)/(Fs/2)*Tw
Here, m is the multiplexing degree, bw is the bandwidth of the band divided by m, ix is the index of the band to which fc belongs, fs is the sampling frequency, tw is the time length (coinciding with the period) of the unit signal.
Further, a frame offset number nd (fc) in which the time offset d (fc) is converted into a frame number (discrete value) is calculated by the following equation.
nd(fc)＝int(d(fc)/fp+0.5)
Here, fp is a frame interval (frame period), int (x) is an integer function for an argument, and 0.5 is a number for reducing a suspension error associated with the integer.
Therefore, the intensity distribution S' (t, f=fc) after the time axis is shifted is calculated by the following equation.
S’(t,f＝fc)＝S(t+nd(fc),f＝fc)
Fig. 17 is an explanatory diagram showing the processing of steps ST41 and ST42 described above.
The time-frequency distribution of the original unit signal (the unit signal arrangement shown in fig. 15) is represented by diagonal stripes shown in fig. 17, and the time-gathered signal after the time axis shift is represented by vertical stripes in fig. 17. That is, the time-axis offset is performed on the unit signal 172 of the unit signal period 171 of the multiplexing degree 2, and the time-integrated signal (offset unit signal) 173 of the multiplexing degree 2 is obtained. Here, the arrow to the left indicates the time shift amount with respect to the original unit signal in each frequency (the time shift amount corresponds to nd (fc) calculated above assuming fc as each frequency).
Next, the estimating unit 7 obtains the intensities included in the specific frequency band B for each frame t from the intensity distribution S' (t, f) of the time-integrated signals, and sets the intensities as an intensity time series B (t) (step ST 43). Further, the estimating unit 7 detects a peak in the intensity time series B (t) (step ST 44). The peak detection is performed by detecting the maximum value of the intensity time series B (t). Here, when detecting a peak from the intensity time series B (t), components other than the unit signal component included in the received signal may be erroneously detected as a peak, and therefore, the interval between detected peaks is measured, and when the interval between peaks deviates from the unit signal period, the peak is removed (step ST 45). The process of step ST45 may be omitted if necessary.
Finally, the estimating unit 7 extracts a peak envelope curve connecting the detected peaks (step ST 46), corrects the time delay due to the time shift (step ST 47), and outputs the extracted peak envelope curve as an estimated propagation characteristic (step ST 48).
When comparing the non-multiplexed time-integrated signal (fig. 13) described in embodiment 2 with the multiplexed time-integrated signal (fig. 17) of embodiment 3, the maximum amount of time shift when the time-integrated signal 173 is obtained by multiplexing is made m-th by multiplexing, and the overall delay is improved. Further, the sampling interval of the propagation characteristic becomes a fraction m of the unit signal period 171, and the sampling interval is also improved.
Fig. 18 is an explanatory diagram showing a measurement example of propagation characteristics of a unit signal arrangement based on a multiplexing degree 8. Fig. 18A shows a time-frequency intensity distribution, fig. 18B shows a time shift result, fig. 18C shows a peak detection result, and fig. 18D shows a peak envelope (propagation characteristic estimation result). In these figures, only the frequency band of 0 to 8000Hz is shown among the frequency bands of 0 to 22050 Hz. Therefore, although the degree of multiplexing seems to be about 2, the unit signal arrangement of the degree of multiplexing 8 is actually used in the frequency band of 0 to 22050 Hz. In these figures, the horizontal axis shows time (seconds), the vertical axes of fig. 18A and 18B show frequency (Hz), and the vertical axes of fig. 18C and 18D show the intensity of unit signal components.
As shown in fig. 18A, an interference component (vertical streak) 181 is mixed in the vicinity of 6 seconds. As shown by the time-shifted interference 182 in fig. 18B, the interference component 181 is dispersed by dividing the time shift of the frequency as shown by an arrow 183. As a result, as shown in fig. 18C, a peak due to interference is not detected in the peak detection result, and as a result, a good peak envelope is estimated (see fig. 18D). Further, the multiplexing degree is set to 8, and therefore, the estimation result is a time-intensive estimation result of 1/8 of the unit signal period.
As described above, according to the acoustic measurement system of embodiment 3, since the measurement unit uses the unit signal arrangement in which the plurality of unit signals whose timings are respectively shifted are multiplexed on the time axis as the test signal, the propagation characteristics can be measured favorably even when the propagation characteristics change rapidly with respect to time.
Further, according to the sound measurement system of embodiment 3, the estimation unit divides the frequencies according to the degree of multiplexing of the multiplexed unit signal arrangement, and the propagation characteristics are obtained by shifting the time axis for each frequency so that the intensities of the unit signals become the same time for each division, so that the propagation characteristics can be estimated with high accuracy even when the propagation characteristics change rapidly with respect to time.
In the above embodiments, the sound sensor 2 as the sound receiving body is provided at one portion of the car 1, but may be provided at a plurality of portions to obtain test sounds from a plurality of sound sensors 2.
In the above embodiments, the example in which the sounding body 5 is provided on the non-moving side (fixed side) and the sound sensor 2 is provided on the moving side (moving side) has been described, but the present application is not limited to this, and the present application is applicable to a device in which the sounding body 5 is provided on the moving side and the sound sensor 2 is provided on the fixed side. For example, in the monitoring device for the sound of a vehicle accident at an intersection, the sound sensor 2 is provided in the signal pillar at the intersection to monitor the sound of the vehicle accident, but the same can be applied to the device.
Further, although the above embodiments have been described as examples of the application to the elevator system, other than the above, the configuration of the sound grasping of the moving body in the factory, the sound grasping by the moving robot, and the sound grasping by the equipment including the moving body such as the vehicle or the escalator can be similarly applied.
The present application can be freely combined with each other, modified or omitted from any of the components of each embodiment within the scope of the present application.
Industrial applicability
As described above, the sound measurement system and the parameter generation device according to the present application are configured to obtain propagation characteristics when the propagation characteristics change with time, and are applied to, for example, an abnormal sound diagnosis device for an elevator.
Description of the reference numerals
1: riding a lift car; 2: a sound sensor (acoustic receiver); 3: a computer; 4: measuring an object; 5: a sounding body; 6: a measuring unit; 7: an estimation unit; 8: a simulated sound synthesizing unit; 9: a sound source database; 10: a simulation unit; 11: a parameter storage unit; 21: a sound measurement system; 22: a parameter generating device; 21a: propagation characteristics.
Claims (8)
1. A sound measurement system, comprising:
a sounding body provided on a fixed side or a movable side of a measurement object;
a sound receiving body provided at a sound receiving point on a moving side or a fixed side which is a side different from the measurement object; the sounding body arranged at the measuring object and the sounding body arranged at the sounding point are relatively moved;
a measurement unit that transmits a test signal from the sounding body to the sound receiving body and propagates the test signal from the sounding body to the sound receiving body, and acquires a test signal obtained from the sound receiving body, the test signal being obtained by arranging a plurality of unit signals having one frequency component at each time point and a center frequency of the frequency component varying with time on a time axis; and
and an estimating unit that estimates a propagation characteristic of sound from the sounding body to the sound receiving body based on a relationship between time and intensity of each of the plurality of unit signals included in the test signal.
2. A sound measurement system, comprising:
a sounding body provided on a fixed side or a movable side of a measurement object;
a sound receiving body provided at a sound receiving point on a moving side or a fixed side which is a side different from the measurement object;
a measurement unit that transmits a test signal from the sounding body to the sound receiving body and propagates the test signal from the sounding body to the sound receiving body, and acquires a test signal obtained from the sound receiving body, the test signal being obtained by arranging unit signals having a single frequency component at each time point and a center frequency of the frequency component varying with time on a time axis; and
and an estimating unit that estimates, for each frequency, a propagation characteristic of sound from the sounding body to the sound receiving body, based on a relationship between time of the unit signal and intensity after the shift, such that the intensity of the unit signal is equal to the time of the unit signal.
3. A sound measurement system, comprising:
a sounding body provided on a fixed side or a movable side of a measurement object;
a sound receiving body provided at a sound receiving point on a moving side or a fixed side which is a side different from the measurement object;
a measurement unit that transmits a test signal from the sounding body to the sound receiving body, and propagates the test signal from the sounding body to the sound receiving body, and acquires a test signal obtained from the sound receiving body, the test signal forming a unit signal arrangement in which a plurality of unit signals each having a single frequency component at each time and a center frequency of the frequency component varying with time are multiplexed on a time axis, the unit signals being staggered with respect to each other; and
and an estimating unit that estimates a propagation characteristic of sound from the sounding body to the sound receiving body based on a relationship between time and intensity of the unit signal included in the test signal.
4. The sound measurement system of claim 3, wherein,
the estimation unit multiplexes the plurality of unit signals by a multiplexing degree m on a time axis, wherein m is not less than 2,
the estimating unit estimates a propagation characteristic of sound from the sounding body to the sound receiving body by time integration processing based on a relationship between time and intensity of the unit signal included in the test signal.
5. The sound measurement system of claim 4, wherein,
the estimation unit divides frequencies according to the multiplexing degree of the multiplexed unit signal arrangement, and obtains the propagation characteristics by shifting the time axis for each frequency so that the intensities of the unit signals become the same for each division.
6. A sound measurement system, comprising:
a sounding body provided on a fixed side or a movable side of a measurement object;
a sound receiving body provided at a sound receiving point on a moving side or a fixed side which is a side different from the measurement object; the sounding body arranged at the measuring object and the sounding body arranged at the sounding point are relatively moved;
a measurement unit that transmits a test signal from the sounding body to the sound receiving body, and propagates the test signal from the sound receiving body, the test signal being obtained by arranging a unit signal having a single frequency component at each time point and a center frequency of the frequency component varying with time on a time axis, the unit signal being a time-spread pulse signal; and
and an estimating unit that estimates a propagation characteristic of sound from the sounding body to the sound receiving body based on a relationship between time and intensity of the unit signal included in the test signal.
7. A parameter generating device is characterized in that,
the parameter generating device generates a parameter for determining whether the measurement object is in a normal state or an abnormal state, using the propagation characteristics estimated by the sound measurement system according to any one of claims 1 to 6.
8. The parameter generating apparatus according to claim 7, wherein,
the parameter generation device includes:
a simulated sound synthesizing unit that generates a synthesized simulated sound using the propagation characteristics estimated by the estimating unit; and
and a simulation unit that determines the parameters using the synthesized simulated sound.
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| PCT/JP2017/046138 WO2019123633A1 (en) | 2017-12-22 | 2017-12-22 | Acoustic measurement system and parameter generation device |
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| JPWO2019123633A1 (en) | 2019-12-19 |
| JP6419392B1 (en) | 2018-11-07 |
| CN111480196A (en) | 2020-07-31 |
| KR20200075884A (en) | 2020-06-26 |
| KR102174553B1 (en) | 2020-11-05 |
| WO2019123633A1 (en) | 2019-06-27 |
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