JP6485958B2 - Abnormal sound analyzer - Google Patents

Description

  The present invention relates to an abnormal noise analysis apparatus, and more particularly to an abnormal noise analysis apparatus that determines knocking of an engine in an engine test.

  Knocking (or knocking) is a phenomenon in which unburned gas is compressed by the combustion gas in the engine cylinder and self-ignited and rapidly burns and resonates. When knocking occurs, the combustion gas propagates heat by vibration. May damage the engine. Although it is necessary to delay the ignition timing in order to suppress knocking, there is a problem that if the ignition timing is delayed, there is a problem in that the fuel consumption is lowered. Therefore, it is necessary to accurately measure and determine the occurrence of knocking.

  Auditory evaluation is widely used as a method for determining knocking (see, for example, Patent Document 1). This is a method in which the tester actually listens to the engine operating sound, hears the magnitude and frequency of abnormal sounds (abnormal sounds different from normal sounds), and evaluates the knocking state. However, there is a problem that the auditory evaluation has a large variation due to the examiner and the test environment, and the reproducibility is low. In particular, whether or not weak sounds, high-frequency sounds, and instantaneous sounds can be heard depends largely on the individual's hearing ability and experience, and it is difficult to accurately identify them unless they are skilled. For this reason, the number of people who can perform auditory evaluation is limited. Moreover, since auditory evaluation is performed by a tester, there is a problem that it cannot be applied to an automatic analysis system or an automatic conformity measurement system.

  Therefore, in recent years, in order to quantitatively determine knocking, a method using in-cylinder pressure measurement (for example, see Patent Document 2) and a method using a vibration sensor (for example, see Patent Document 3) are widely used. These methods are methods for determining knocking based on in-cylinder pressure and engine vibration, and can perform quantitative knocking determination. However, these methods have a problem that calibration is required by auditory evaluation because the determination result does not match the result of auditory evaluation.

  From such a background, there is a demand for a method for measuring knocking by the same method as the human auditory function and determining knocking, and the present applicant has proposed Patent Document 4. According to Patent Document 4, the power of the background sound is obtained by performing the time mask process based on the signal immediately before and after the engine sound detection signal and the frequency mask process based on the signal in the adjacent frequency band. The power ratio of the background sound to the power of the background sound is calculated as the knock intensity, and the presence or absence of knocking is determined. Since this method performs time mask processing and frequency mask processing in the same way as the processing performed by human auditory sense, it can obtain results equivalent to auditory evaluation and perform quantitative knock determination by signal processing. Can do.

JP 61-142367 JP2000-110652A Japanese Patent No. 3054919 JP2010-252806

  However, although the method described above is measured by the same method as the human auditory function, there is a problem that the determination accuracy as a skilled person cannot be obtained. Specifically, it can be determined by a skilled person when an abnormal sound other than the knocking sound is generated or when the knocking sound is weak, but there is a problem that the method described above is difficult.

  As a method for solving this problem, a method of finding a condition for generating a knocking sound (for example, a range of a crank angle at which the knocking sound is generated) and narrowing down data based on the generation condition can be considered. If the data is narrowed down, the knocking sound is emphasized, so that the determination of knocking can be performed with high accuracy. However, the condition for generating the knocking sound is different for each engine, and further varies depending on the engine speed, so that it is difficult to find the generation condition accurately. Even if the exact occurrence condition is found, when the data is narrowed down, some of the knocking sounds may be deleted or abnormal sounds other than the knocking sounds may remain without being removed. There was a problem that it was difficult to increase accuracy.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide an abnormal sound analyzing apparatus that can accurately specify abnormal sounds such as knocking sounds.

In order to achieve the above object, the invention according to claim 1 comprises an abnormal sound analysis comprising a detection means for detecting a sound generated by a rotating body and a signal processing means for processing a signal obtained by the detection means. In the apparatus, the signal processing means includes a process of separating the signal obtained by the detection means into a plurality of frequency bands, a process of obtaining an abnormal sound start point and a peak point for each separated frequency band, and the start point. And a process of displaying a scatter diagram showing the relationship between the rotation angle of the starting point and the size of the peak point on the display unit .

  The inventor of the present invention has obtained the knowledge that the cause of abnormal noise can be estimated by separating the sound signal into a plurality of frequency bands and obtaining the start point and peak point of the abnormal sound in each frequency band. . The present invention has been made based on such knowledge, and since the start point and peak point of abnormal noise are obtained for each separated frequency band, for example, knocking is performed from abnormal noise generated in the engine. An abnormal sound (that is, a knocking sound) as a factor can be specified. As a result, it is possible to identify the knocking sound, specify the generation condition thereof, and extract knocking sound data from a large number of abnormal sounds.

Further, according to the present invention, since the rotation angle of the rotator at which abnormal noise starts can be grasped, it is possible to identify the cause of abnormal noise that varies depending on the rotation angle. For example, when the rotating body is an engine, the crank angle at which the abnormal noise starts can be grasped, so that the cause of the abnormal noise can be specified by the crank angle, for example, the knocking sound can be accurately specified.

Furthermore , according to the present invention, since a scatter diagram is displayed, it is possible to grasp the distribution of each noise generation factor.

The invention according to claim 2 is the invention according to claim 1, wherein the scatter diagram is created for each frequency band, and the scatter diagrams for each frequency band are displayed side by side. According to the present invention, since the scatter diagrams for each frequency band are displayed side by side, it is possible to grasp at a glance the frequency pattern and the angle pattern (time pattern) of abnormal noise. Therefore, the cause of abnormal noise can be grasped, and for example, engine knock noise can be easily identified. The knocking sound is difficult to specify only by the natural frequency (sound pitch) or the peak value (sound volume) of the sound pressure, and conventionally, it has been difficult to specify the knocking sound. Then, since the frequency pattern and angle pattern of the abnormal sound can be known at a glance, the knocking sound can be easily identified.

According to a third aspect of the present invention, in the first or second aspect of the invention, the signal processing means extracts abnormal sound data that starts within a predetermined range of the rotation angle, and the extracted data includes all the frequency bands. It is characterized by calculating the sum of . According to the present invention, since the abnormal sound data starting within a predetermined range is extracted and then the magnitude thereof is calculated, the abnormal sound starting within the predetermined range (that is, the abnormal sound generated by a specific factor) is calculated. Sound) can be accurately grasped. Therefore, for example, it is possible to accurately determine the occurrence of abnormal noise that has started within the range of knocking occurrence conditions.

  According to the present invention, since the start point and peak point of abnormal noise are obtained for each separated frequency band, the cause of abnormal noise can be specified. Accordingly, it is possible to identify the knocking sound and specify the generation condition thereof, or to extract knocking sound data from a large number of abnormal sounds.

The figure which shows typically the structure of the abnormal sound analyzer of this Embodiment. Diagram showing analysis flow of abnormal noise Diagram showing data being processed by the processor Diagram showing an example of a scatter diagram Diagram showing knocking determination flow Diagram showing the effect of data narrowing

  A preferred embodiment of an abnormal sound analyzer according to the present invention will be described with reference to the accompanying drawings. An abnormal sound analysis apparatus 10 shown in FIG. 1 is an apparatus for determining knocking of the engine 12, and mainly includes a microphone 14, an angle sensor 16, a processor 18, and a display 20.

  The microphone 14 is a sensor for detecting engine sound, and is installed in the vicinity of the engine 12. The position of the microphone 14 is preferably able to accurately grasp the distance from the sound source. For example, the microphone 14 is installed at a position 40 cm from the sound source. Note that the microphone 14 only needs to obtain sound pressure, and for example, a vibration sensor may be used. In the case of a vibration sensor, the vibration sensor may be directly attached to the engine 12 and used in combination with a processing device that performs unit conversion.

  The microphone 14 is connected to the processor 18 via the amplifier 22 and the AD converter 24. The detection signal of the microphone 14 is amplified by the amplifier 22, converted into a digital signal by the AD conversion 24, and input to the processor 18.

  On the other hand, the angle sensor 16 is a sensor that detects the crank angle of the engine 12 and is connected to the processor 18 via the AD converter 28. Instead of installing the angle sensor 16, angle information may be received directly from the analysis means (ECU or the like) of the engine 12.

  The processor 18 is a means for performing various signal processing, and is connected to the display 20. The display device 20 is a device that displays a scatter diagram and a knocking determination result, which will be described later, and displays measurement conditions and the like as necessary. The scatter diagram and the knocking determination result may be output to the recording medium 28 or output to a printer (not shown) or the like.

  Next, various processes performed using the processor 18 will be described. FIG. 2 shows an abnormal sound analysis flow for identifying the cause of abnormal noise. In the flow of FIG. 2, first, the data obtained by the microphone 14 is separated into a plurality of frequency bands (step S11). The separation method is not particularly limited. For example, the separation is performed using a plurality of bandpass filters. Further, the bandwidth and the number of bands of the frequency band to be separated are not particularly limited, but may be determined as follows based on, for example, the balance between the detection accuracy of abnormal noise and the calculation load of the processor 18. First, the center frequency fc is determined using the definition of ERB (Equivalent Rectangular Bandwidth) expressed by the following equation.

式中のnはERBバンドを可聴領域に並べたときの低域側からの並び順を示す番号である。計測対象の周波数を4k〜20kHz程度であると考えnを27〜41の整数とする。このような中心周波数を持つ１５本のバンドに分離して処理を行うようにする。この時バンド幅は対数軸に対して等間隔となるようfc(n)に対してはfc(n-1/2)からfc(n+1/2)の範囲とする。なお、計測対象の音域によってｎの範囲を変えてもよい。

N in the formula is a number indicating the arrangement order from the low frequency side when the ERB bands are arranged in the audible region. The frequency to be measured is assumed to be about 4 to 20 kHz, and n is an integer of 27 to 41. The processing is performed by separating into 15 bands having such a center frequency. At this time, the bandwidth is in the range of fc (n−1 / 2) to fc (n + 1/2) for fc (n) so as to be equally spaced with respect to the logarithmic axis. Note that the range of n may be changed depending on the sound range to be measured.

  The following processing from step S12 to step S17 is performed for each separated frequency band. First, a delay correction process is performed in order to achieve synchronization between the separated frequency bands (step S12). This is because each of the above-described bandpass filters has a unique delay, and can be synchronized by applying a correction delay for each band.

  Next, the signal is squared and the sound power is calculated (step S13). In obtaining the mean square, the average width is preferably set as small as possible so that the peak is not erased by the averaging operation, and is set to, for example, two wavelengths of the band center frequency. Thereby, as shown in FIG. 3A, data in which the power on the vertical axis fluctuates greatly is obtained.

  Next, the auditory sensation A characteristic correction value is applied (step S14). The auditory sensation A characteristic correction value is a numerical value representing the approximate audible characteristic of a person, and can be approximated to an output similar to the audibility of a person. Next, the frequency mask effect is corrected (step S15). Although the method is not particularly limited, for example, considering that the high frequency band is affected by the low frequency band, a value of 0.0631 times the frequency band one lower is added. As another method, a loudness calculation chart may be used.

  Next, the time mask effect is corrected (step S16). The method is not particularly limited, but for example, considering that the auditory nerve responds fast and slows down, a primary delay filter of 0.005 sec when the volume is increased, and a primary delay filter of 0.043 sec when the volume is decreased Through. As another method, when the sound is reduced, it may be approximated that the power of the background sound is attenuated at a constant attenuation rate. Thereby, as shown in FIG.3 (b), the data which rises rapidly and falls slowly are obtained. This mimics the level of human auditory nerve activity.

  Next, an abnormal sound level is calculated (step S17). Here, the abnormal sound level expresses a human sense of abnormal sound (that is, how a person feels the abnormal sound). First, as shown in FIG. 3B, the abnormal sound level is calculated as a part where the level of the auditory nerve activity is locally maximized (in the figure, a white circle part and a part where the abnormal sound level peak point later). Then, a portion that becomes a minimum immediately before that (a portion that is a black circle in the figure and later becomes a starting point of an abnormal sound level) is searched. Then, the difference from the minimum portion to the maximum portion is obtained, and 0 is set when the maximum portion is exceeded. Thereby, the abnormal sound level as shown in FIG. Then, after obtaining the abnormal sound level, the time of the start point of the abnormal sound and the size of the peak point of the abnormal sound (hereinafter referred to as the peak value) are obtained. For example, in FIG. 3C, the time C1 of the start point of the abnormal sound C and the peak value C2 are obtained. In this way, the time and peak value of the starting point are obtained for abnormal noise, and the starting point time is converted into a crank angle. In the conversion to the crank angle, the signal from the angle sensor 16 is synchronized by performing a delay correction process based on the distance between the microphone 14 and the sound source.

  Next, the relationship between the obtained peak value and the time of the start point is output and displayed on the display 20 (step S18). At this time, a scatter diagram in which the vertical axis is plotted as the peak value of the abnormal sound level and the horizontal axis as the crank angle of the starting point is displayed, and the scattered portions are arranged vertically for each frequency band (and the crank angles are aligned). ) Display. Thereby, it is possible to grasp at a glance the distribution of the frequency band, the crank angle, and the peak value, and it is possible to grasp the occurrence of abnormal noise. In other words, by paying attention to the portion where the peak value increases, it is possible to grasp at a glance the frequency pattern and the angle pattern (time pattern) at which abnormal noise occurs. In the case of engine sound, the cause of abnormal noise can be specified by the frequency pattern and angle pattern of the abnormal noise. By looking at the above scatter diagram, not only the abnormal noise occurrence status but also the cause of abnormal noise can be determined. be able to. Therefore, it is possible to easily identify a special abnormal sound such as a knocking sound. Then, it is possible to specify the knocking noise generation condition (particularly the crank angle).

  Next, a preferable example when analyzing the knocking sound will be described. When the knocking sound is analyzed, the flow of FIG. 2 may be executed as it is, but it is preferable to perform a plurality of tests in advance and sample the data. Specifically, it is preferable to sample in two or more patterns when there is no knock sound and when a knock sound is generated. In addition, when a knock determination test is performed later on the same type of engine, it is preferable to sample for each rotation speed of the engine 12 used in the test.

  After the processing of steps S11 to S17 in FIG. 2 is performed on the sampled data, a scatter diagram as shown in FIG. 4 is displayed (step S18). The numerical values on the left side of FIG. 4 are representative values of frequencies, and 15 scatter diagrams with different frequency bands are displayed vertically. In each scatter diagram, the vertical axis represents the peak value of the abnormal sound level, and the horizontal axis represents the crank angle at the starting point. Further, data without knocking sound is displayed as “+”, and data with knocking sound is displayed as “◯”. Then, on the uppermost side, a scatter diagram in which all data is superimposed is displayed. Note that the plot may be displayed in another shape or displayed in a different color.

  According to the screen displayed in this way, it is possible to easily specify the occurrence condition of knocking. That is, since only “◯” is shown when knocking occurs, it is possible to specify the frequency band and crank angle range where knocking occurs by paying attention to only the portion “◯”. For example, it can be seen that “◯” is concentrated in the range of the crank angle of 200 degrees to 230 degrees in the frequency band of 8648 and 7743. Therefore, the range can be specified as the occurrence condition of knocking.

  As described above, according to the present embodiment, since the scatter diagram of the peak value and the crank angle is displayed for each frequency band, it is possible to easily specify the knocking sound generation condition. The knock sound generation condition may be only the crank angle, or may be a condition that combines not only the angle range but also the frequency and the abnormal sound level. The knocking occurrence conditions specified as described above can be used to extract knocking sound data during the knocking determination test by inputting the conditions to the processor 18.

  In the present embodiment, the tester specifies the occurrence of abnormal noise and the generation conditions by displaying a scatter diagram on the display device 20. However, the tester automatically specifies the sound generation without displaying it on the display device 20. Also good. For example, data having no abnormal noise (or a situation in which there is little noise) is taken, a threshold value is set according to the peak value at that time, and it is determined that abnormal noise has occurred when the threshold value is exceeded. Further, the determined abnormal sound generation condition is automatically acquired. Thereby, generation | occurrence | production of abnormal noise and generation | occurrence | production conditions can be specified automatically.

  In the present embodiment, the knocking occurrence condition is specified. However, the present invention is not limited to this, and the present invention can be widely used as a device for analyzing abnormal sounds of a device having a rotating body. Furthermore, it can also be used as a device for judging abnormal noise in real time, and by displaying the above scatter chart in real time, the tester can visually confirm the abnormal sound while judging visually by the scatter chart. Can do. At that time, if noise-free data is acquired in advance and displayed in a scatter diagram, and test data is plotted thereon, the abnormal noise can be easily grasped.

  Next, a flow when the abnormal sound analysis apparatus 10 of the present embodiment is used for a knock determination test will be described. FIG. 5 shows a knocking determination flow. The same processes as those in the flow of FIG. 2 are denoted by the same reference numerals, and detailed description thereof is omitted.

  As shown in FIG. 5, in the knocking determination flow, first, the input signal is separated into a plurality of frequency bands (step S11). Next, in order to achieve synchronization between the separated frequency bands, a delay correction process is performed (step S12). Then, the signals are squared and the sound power is calculated (step S13), and then the auditory A characteristic correction value is applied (step S14). Next, correction by the time mask effect is performed (step S15), and correction by the frequency mask effect is performed (step S16). Thereafter, an abnormal sound level is calculated in each frequency band (step S17).

Next, data is cut out under preset knocking conditions (step S28). Specifically, with respect to a range of crank angles at which knocking occurs, abnormal noise data in which the starting point of abnormal noise is within the crank angle range is extracted, and abnormal noise data outside the range is delete. At that time, data from the start point to the peak point is extracted. As a result, the abnormal sound data that is considered to be the cause of knocking remains, and the abnormal sound data that is considered to be the cause of occurrence other than knocking is deleted.
The knocking occurrence condition can be set according to the procedure of “analysis of knocking sound” described above. However, when the conditions are known in advance, it is not always necessary to go through the above procedure.

  Next, the sum total of all frequency bands is obtained (step S29). That is, the abnormal sound level in the entire frequency band is obtained by adding the abnormal sound level obtained for each frequency band. Then, it is determined that knocking has occurred when the calculated abnormal sound level value exceeds the threshold (step S30). When knocking occurs, it is notified to the operator by displaying it on the display device 20 or generating a pseudo sound.

  Next, the operation of this embodiment will be described. FIG. 6A and FIG. 6B each schematically show an example of a situation in which abnormal noise is generated. In these figures, the vertical axis indicates the noise level and the horizontal axis indicates the crank angle, and the crank angle α to β (hereinafter referred to as angle αβ) is the occurrence condition of knocking. Then, the abnormal sound A1 and the abnormal sound A3 in FIG. 6A are generated outside the range of the angle αβ and peaked outside the range, and the abnormal sound A2 occurred within the range and peaked within the range. ing. At this time, only the abnormal sound A2 is a knocking sound, and the abnormal sound A1 and the abnormal sound A3 are abnormal sounds caused by factors other than knocking. On the other hand, the abnormal sound B1 in FIG. 6B occurs outside the range of the angle αβ and reaches a peak within the range, and the abnormal sound B2 occurs within the range and reaches a peak outside the range. At this time, the abnormal sound B2 is a knocking sound, and the abnormal sound B1 is an abnormal sound caused by factors other than knocking.

If the data is simply narrowed down within the range of the angle αβ, knocking can be accurately determined in the case of FIG. 6A, whereas knocking cannot be accurately determined in the case of FIG. 6B. That is, in the case of FIG. 6A, since only the abnormal sound A2 is extracted, knocking can be accurately determined, whereas in the case of FIG. 6B, the abnormal sound B2 that is a knocking sound. The influence of the abnormal sound B1 that is not a knocking sound is greater than that, and it is difficult to determine knocking.
In contrast, in the present embodiment, data extraction is determined at the starting point of abnormal noise. For example, in the case of FIG. 6B, only the abnormal sound B2 whose start point is within the range of the angle αβ is extracted, and the abnormal sound B1 is removed because the start point is out of the range. Therefore, even in the situation of FIG. 6B, only the abnormal sound B1 suspected of knocking is extracted, so that knocking can be determined accurately.

  As described above, according to the present embodiment, the peak value and starting point of the abnormal sound are obtained, and the occurrence condition of knocking can be specified based on the peak value, and the data is narrowed down based on that. Can be performed more accurately.

  DESCRIPTION OF SYMBOLS 10 ... Knock determination apparatus, 12 ... Engine, 14 ... Microphone, 16 ... Angle sensor, 18 ... Processor, 20 ... Display device, 22 ... Amplifier, 24 ... AD converter, 26 ... AD converter, 28 ... Recording medium

Claims (3)

In an abnormal sound analysis apparatus comprising a detection means for detecting a sound generated by a rotating body, and a signal processing means for processing a signal obtained by the detection means,
The signal processing means includes
A process of separating the signal obtained by the detection means into a plurality of frequency bands;
Processing for obtaining the starting point and peak point of abnormal noise for each separated frequency band ;
A process of converting the time of the start point into a rotation angle of the rotating body;
An abnormal sound analyzing apparatus that performs a process of displaying a scatter diagram showing a relationship between a rotation angle of the start point and a size of the peak point on a display unit . 2. The abnormal sound analysis apparatus according to claim 1 , wherein the scatter diagram is created for each frequency band, and the scatter diagrams for the frequency bands are displayed side by side. 3. The signal processing unit according to claim 1, wherein the signal processing unit extracts abnormal sound data that starts within a predetermined range of the rotation angle, and obtains a sum of all the frequency bands for the extracted data. Abnormal sound analysis device.

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