JP2007206037A - Signal measuring/analyzing apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a signal measuring/analyzing apparatus which stores a plurality of waveform data efficiently and analyzes them and which can grasp the electromagnetic environment and noise environment, by analyzing and displaying the property and similarity of the waveform data which have been stored. <P>SOLUTION: The signal measuring/analyzing apparatus is provided with a data measuring part 11, which connects to a sensor 31 which outputs detected signal and which measures at least a time waveform of a signal input from the sensor 31 or one side of a frequency spectrum as waveform data showing a waveform and makes it store in a data storage section 12; a detecting element 14, which reads waveform data, detects waveform parameter which is the amount of descriptions of the waveform data, generates a record containing the waveform parameter and stores it in a database 15; an analysis section 16 which reads the waveform data, detects waveform parameter which is the amount of descriptions of waveform data and analyzes the waveform based on waveform parameter, involving a plurality of records and accumulates waveform parameter in the database 15, and analyzes the waveform, based on the assay conditions input from the waveform parameter contained in a plurality of records accumulated in the database 15; and a display control unit 18 which displays the result of assay on a display device 19. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a signal measurement and analysis apparatus that measures signal waveforms such as electromagnetic interference waves and noise and analyzes characteristics of the signal waveforms.

  In recent years, signal waveforms such as electromagnetic interference generated from electronic devices such as mobile phones and power supply devices, electromagnetic interference due to natural phenomena such as electrostatic discharge and lightning, radio waves such as amateur radio and CB radio, etc. There is a problem that causes a failure of electronic devices and electronic devices. Since the resistance to electromagnetic interference of electronic devices and the like tends to decrease as semiconductor electronic elements increase in speed and power, the problem of electromagnetic interference due to such signal waveforms is becoming more and more serious.

  In order to detect a signal waveform that causes such an electromagnetic interference problem, an electromagnetic interference cause search method (for example, refer to Patent Document 1), an electromagnetic environment measurement device (for example, refer to Patent Documents 2 and 3), and the like. Proposed. According to these technologies, electromagnetic interference detection sensors and measuring devices that measure electromagnetic interference are installed around electronic devices that may generate electromagnetic interference. The environment can be measured.

  In addition, noise problems due to noise from cars and aircraft are also getting worse. To deal with such noise problems, the signal waveform that causes noise is measured by combining a microphone with a signal measuring device or a microphone with a personal computer from the viewpoint of environmental conservation, etc. ing.

As a method for measuring such an electromagnetic environment or noise environment, various methods have been proposed in which a signal waveform detected by an external sensor is input to a measuring apparatus and measured (see, for example, Patent Documents 4 to 6). In addition, products having a function of temporarily storing a time signal detected from a measurement result in a measuring apparatus in an internal memory and displaying a peak value, a frequency spectrum, etc. are widely used (for example, Hioki Denki Corporation Memory High Coda 8826/8842, Yokogawa Electric Corporation digital oscilloscope DL7440 / DL7480).
JP-A-4-178548 JP-A-4-294285 JP-A-5-223867 JP-A-5-020472 Japanese Patent Laid-Open No. 5-11907 JP-A-5-141195

  As described above, although the generation of signal waveforms such as interference waves in the electromagnetic environment and noise environment can be grasped conventionally, for example, the analysis of signal waveforms such as electromagnetic interference waves and noise has the following problems. It was.

  (1) Statistical evaluation of data characteristics regarding a plurality of detected signal waveforms cannot be performed efficiently.

  (2) Evaluation of the relative relationship for each data regarding a plurality of detected signal waveforms cannot be performed efficiently.

  (3) It is not possible to efficiently evaluate the similarity between data relating to a newly detected signal waveform and data relating to signal waveforms detected in the past.

  (4) It is not possible to efficiently perform retrieval of data relating to waveforms detected in the past that are similar to data relating to newly detected signal waveforms.

  In order to grasp the electromagnetic environment and noise environment in view of the above problems, the present invention efficiently stores and analyzes a plurality of waveform data, and easily analyzes and displays the characteristics and similarities of the stored waveform data. It is an object of the present invention to provide a signal measurement and analysis apparatus that can perform the above.

  According to the signal measurement and analysis apparatus according to the feature of the present invention, the data measurement unit that measures the signal waveform input from the sensor and stores the waveform as waveform data, the waveform data is read, and the waveform parameter that is the feature amount of the waveform data is obtained. Based on the detection unit that detects and generates records including waveform parameters and stores them in the database, reads the stored records, and includes the waveform parameters included in multiple records stored in the database and arbitrarily specified analysis conditions An analysis unit that analyzes the waveform data, and a display unit that displays a result of the analysis in the analysis unit. Here, the “waveform data” is either a time waveform of a signal or a frequency spectrum. The “analysis condition” used in the analysis unit may be input in advance by the user and stored in the memory, or may be input by the user when executing the analysis process.

  According to the present invention having the above-described configuration, data related to signal waveforms such as electromagnetic interference and noise can be stored and analyzed to be used for analysis and countermeasures for problems caused by these signal waveforms. Also, by displaying these efficiently, it is easy for the user to grasp the status of signal waveforms such as interference waves.

  The signal measurement analyzer includes a trigger signal receiving unit that receives a trigger signal for controlling the storage of waveform data, and the data measuring unit is a trigger determination unit that determines whether the trigger signal receiving unit has received the trigger signal. If it is determined that the trigger signal has been received, it is desirable to store the waveform data. For example, when the trigger signal receiving unit is connected to an external electronic device, the “trigger signal” may be a signal that the electronic device transmits to the trigger signal receiving unit at a predetermined timing. Alternatively, when the trigger signal receiving unit is connected to the input device, the “trigger signal” may be a signal input by the user via the input device.

  The data measurement unit of the signal measurement analysis apparatus compares the signal waveform with predetermined upper and lower thresholds to determine whether the signal waveform is equal to or higher than the upper threshold or lower than the lower threshold. If it is determined that it is greater than or equal to the upper threshold or less than or equal to the lower threshold, it is desirable to store waveform data.

  As described above, the data measurement unit can measure and store waveform data at a designated timing, select and store data useful for analysis, and use it for analysis.

  The detection unit of the above signal measurement analyzer uses, as a waveform parameter from the time waveform, the peak value of the signal waveform in an arbitrary time interval, the average value of the signal waveform in an arbitrary time interval, and the energy defined in the arbitrary time interval signal waveform It is desirable to detect at least one of the quantity, the rise rate defined on the time axis, the rise time of the signal waveform defined on the time axis, or the time change rate of an arbitrary time interval.

  The detection unit of the signal measurement and analysis apparatus includes, as a waveform parameter from a frequency spectrum, a spectrum peak value between arbitrary frequency bands, a resonance frequency value giving a spectrum level higher than a predetermined value in an arbitrary frequency section, and a spectrum in an arbitrary frequency band. It is desirable to detect at least one of the average value, the energy defined by the spectral amount between arbitrary frequency bands, or the time change rate of the energy defined by the spectral amount between arbitrary frequency bands.

  The detection unit of the signal measurement and analysis apparatus arbitrarily divides the frequency spectrum as a waveform parameter, or the ratio of the frequency spectrum of each frequency band obtained by arbitrarily dividing the frequency spectrum and the total value of each frequency spectrum or the frequency spectrum. It is desirable to detect at least one from the ratio between the energy spectrum of each frequency band obtained in this way and the total value of each energy spectrum.

  It is preferable that the analysis unit of the signal measurement analyzer searches the database for a record specified by the value of the waveform parameter included in the analysis request. This “analysis request” is input by the user via the input device. The analysis unit may search for the record specified by the waveform parameter included in the analysis request when the analysis request is input. The analysis unit may store the analysis request input in advance in the memory, read the analysis request from the memory at a predetermined timing, and search for a record specified by the waveform parameter included in the analysis request.

  It is desirable that the database of the signal measurement analyzer stores a record using an identifier as a key, and the analysis unit searches the database for a record identified by the identifier included in the analysis request. This “analysis request” is input, for example, via the input device of the signal measurement analyzer.

  The analysis unit of the signal measurement analyzer calculates a cross-correlation coefficient between a waveform parameter included in a predetermined record and a waveform parameter included in another record, and the cross-correlation coefficient is within a predetermined range, It is desirable to extract a predetermined record. Here, the “predetermined record” is, for example, a record newly added to the database. Further, the “predetermined record” may be a record designated by the user via the input device from records stored in advance in the database, or a record arbitrarily selected by the analysis unit.

  The signal measurement and analysis apparatus preferably includes a correction unit that reads correction data for correcting distortion due to frequency characteristics of a signal sensor and corrects distortion.

  As described above, the accuracy of analysis in the analysis unit can be improved by correcting the distortion of the sensor in the correction unit.

  The signal measurement and analysis apparatus obtains a position to be displayed on the display screen as a clustering position by relating the contents of similar records by executing a clustering process according to a specified condition for the waveform parameters of a plurality of records, It is desirable to provide a clustering processing unit that outputs the clustering position and the contents of each record in association with each other.

  As described above, by displaying the contents of similar records in association with each other using the clustering position determined by the clustering processing unit, the user can easily understand the relationship of data regarding each accumulated signal waveform.

  According to the present invention, the electromagnetic environment and the noise environment can be grasped by efficiently storing and analyzing a plurality of waveform data and analyzing and displaying the characteristics and similarity of the stored waveform data. .

  The best mode for carrying out the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram illustrating a configuration of a signal measurement analyzer 1 according to the best embodiment of the present invention. The signal measurement / analysis apparatus 1 measures and analyzes signal waveforms such as electromagnetic interference waves and interference waves such as noise, and displays the analysis results to facilitate management of the electromagnetic environment and noise environment. Here, the “signal waveform” is a signal such as an electromagnetic interference wave transmitted via radiation or a communication line, an electromagnetic interference wave caused by a natural phenomenon, an electromagnetic interference wave such as a radio wave, and noise.

  The signal measurement / analysis apparatus 1 is connected to sensors such as the sensor 31 and the sensor 32 and inputs signal waveforms detected by the sensor 31 and the sensor 32.

  The sensor 31 is configured by any one of an antenna, a current probe, a microphone, and the like, for example. The sensor 31 can detect a signal waveform generated by the electronic device 21 by being installed in the vicinity of the electronic device 21 that may generate a signal waveform. For example, when the sensor 31 is an antenna, a signal waveform such as an electromagnetic interference wave can be detected, and when the sensor 31 is a microphone, a noise signal waveform can be detected.

  The sensor 32 is also configured by any one of an antenna, a current probe, and the like, similar to the sensor 31 described above, but is configured differently from the sensor 31 or installed at a different position. Therefore, the sensor 32 can detect a signal waveform different from that of the sensor 31.

  Here, the number of sensors connected to the signal measurement analyzer 1 is not limited, but when a plurality of sensors having different configurations or sensors installed at different positions are connected, data related to various signal waveforms is accumulated in the database. be able to. In the following description, the sensor 31 is used, but the same can be applied even if the sensor 31 is replaced with another sensor as appropriate.

  As shown in FIG. 1, the signal measurement and analysis apparatus 1 is functionally configured to have a data measurement unit 11, a data storage unit 12, a trigger signal reception unit 13, a detection unit 14, a database 15, an analysis unit 16, an input device 17, and display control. The unit 18 and the display device 19 are included.

  The data measurement unit 11 includes a time waveform measurement unit 11a and a frequency spectrum measurement unit 11b, and stores the signal waveform input from the sensor 31 in the data storage unit 12 as waveform data. The data storage unit 12 includes a time waveform storage unit 12a and a frequency spectrum storage unit 12b, and temporarily stores waveform data measured by the data measurement unit 11. The data storage unit 12 is composed of, for example, a semiconductor memory.

  Specifically, the time waveform measurement unit 11a stores the result of sampling the signal waveform input from the sensor 31 and measuring the time waveform in the time waveform storage unit 12a as waveform data. Further, the frequency spectrum measurement unit 11b stores the result of sampling the signal waveform input from the sensor 31 and measuring the frequency spectrum of the signal waveform as waveform data in the frequency spectrum storage unit 12b.

  The trigger signal receiving unit 13 receives a trigger signal from a connected external device such as the electronic device 21. This trigger signal is used to start measurement in the data measurement unit 11. For example, when the trigger signal receiving unit 13 is connected to an external electronic device 21 as shown in FIG. 1, the trigger signal may be a signal that the electronic device transmits to the trigger signal receiving unit 13 at a predetermined timing. . Alternatively, when the trigger signal receiving unit 13 is connected to the input device 17 of the signal measurement analyzer 1 (not shown), the trigger signal may be a signal input via the input device 17 by the user. .

  The detection unit 14 reads the waveform data from the data storage unit 12 and detects a waveform parameter that is a feature amount of the waveform data. Further, the detection unit 14 stores the detected waveform parameter in the database 15. The waveform parameter detected by the detection unit 14 is, for example, a feature value obtained by quantifying a peak value in the time domain, a peak value in the frequency domain, or the like. The number of waveform parameters detected by the detection unit 14 is not limited, and a plurality of waveform parameters may be detected from one waveform data.

  The database 15 accumulates and stores records including waveform data measured by the data measurement unit 11 and waveform parameters detected by the detection unit 14. FIG. 2 is an example of data stored in the database 15. As shown in FIG. 2, each record is measured by the data measurement unit 11 using the “measurement date and time” when the sensor detects the signal waveform that is the source of the waveform data, using the “waveform data identifier” that identifies the waveform data as a key. The “time waveform” and “frequency spectrum” which are the waveform data obtained, the “waveform parameter” detected by the detection unit 14, the “analysis condition” used for calculating the frequency spectrum of the signal, and the type of the sensor 31. It consists of “sensor condition”, “noise type” and the like.

  When the waveform parameter is detected by the detection unit 14 in the database 15, a record including the detected waveform parameter is newly generated and stored. Further, in the database 15, in addition to the record generated based on the signal waveform detected by the sensor 31, a record for generating a reference signal as an example of noise and including a parameter or the like based on the reference signal May be stored. In the example of FIG. 2, the waveform data identifiers “i + 1” and “i + 2” are records relating to such a reference signal. In this case, the record identified by the waveform data identifier “i + 1” is a record relating to a reference signal that is noise of a CB wave. Therefore, when the “value of the waveform parameter included in the record having the waveform data identifier“ i + 1 ”” correlates with the “value of the waveform parameter of the arbitrary record”, the arbitrary record relates to the noise of the CB wave. Is determined.

  The analysis unit 16 analyzes the data read from the database 15 according to specified conditions. For example, the analysis unit 16 searches for a record that matches a newly input specific condition, or searches for a record that is similar to the newly input data and determines the type of data to execute the analysis process.

  The display control unit 18 displays the data stored in the database 15 and the analysis result in the analysis unit 16 on the display device 19. The display device 19 is a display and is measured by the time waveform or frequency spectrum measurement unit 11b measured by the time waveform measurement unit 11a together with the analysis result in the analysis unit 16, for example, according to the operation instruction signal from the display control unit 18. The frequency spectrum, the value of the waveform parameter detected by the detection unit 14 and the like are displayed.

  Here, the signal measurement analysis apparatus 1 shown in FIG. 1 has a time waveform measurement unit 11a and a frequency spectrum measurement unit 11b in the data measurement unit 11, but if either one is included, the signal measurement / analysis device 1 in FIG. The same effect as the signal measurement analyzer 1 shown can be obtained. In this case, the data storage unit 12 only needs to include a storage unit corresponding to the measurement unit.

<Processing in signal measurement analyzer>
FIG. 3 is a flowchart for explaining processing in the signal measurement analyzer 1. The data measurement unit 11 performs measurement processing on the signal waveform input from the sensor 31, and stores the waveform data measured from the signal waveform in the data storage unit 12 (S1).

  Thereafter, the detection unit 14 executes detection processing on the waveform data read from the data storage unit 12, detects a waveform parameter that is a feature amount of the waveform data from the waveform data (S2), and includes the detected waveform parameter. A new record is generated and added to the database 15 and stored (S3).

  The analysis unit 16 performs an analysis process on the data read from the database 15 at a predetermined timing (S4). Thereafter, the display control unit 18 displays the analysis result obtained by the analysis process in step S04 on the display device 19 (S5).

Subsequently, processing in each step will be described.
<< Measurement process >>
First, the measurement process (S1 in FIG. 3) executed by the data measurement unit 11 will be described.

  The following (1) to (3) are conceivable as examples of signal waveforms to be measured, and these are common to the time waveform measurement unit 11a and the frequency spectrum measurement unit 11b.

(1) The data measurement unit 11 has threshold determination means (not shown) for determining whether the input signal waveform is equal to or greater than a predetermined threshold or less than a predetermined threshold, and is equal to or greater than a predetermined threshold by the threshold determination means. Alternatively, a signal waveform determined to be less than or equal to a threshold value.
(2) The data measuring unit 11 has trigger determining means (not shown) for determining whether or not the trigger signal receiving unit 13 has received the trigger signal, and this trigger determining means has determined that the trigger signal has been received. The signal waveform temporarily stored in the data storage unit 12 at the time.
(3) The data measuring unit 11 has trigger determining means (not shown) for determining whether or not the trigger signal receiving unit 13 has received the trigger signal, and this trigger determining means has determined that the trigger signal has been received. A signal waveform that is input to the data measuring unit 11 later.

  Note that a general-purpose oscilloscope or the like is used to measure the time waveform in the time waveform 11a. Also, a frequency spectrum measurement unit 11b is used to measure the frequency spectrum in the frequency spectrum measurement unit 11b, and a “real-time analysis method” for time-frequency conversion of a signal measured in the time domain is used. For example, a “frequency sweep tuning method” for sweeping the center frequency for each pass band, and a “real time method” for analyzing signals passing through a plurality of pass frequency analysis filters.

<< Detection process >>
Next, the detection process (S2 in FIG. 3) executed by the detection unit 14 will be described.
As an example of the timing at which the detection process is started, the timing at which new waveform data is stored in the data storage unit 12 can be considered.

  When the detection process starts, the detection unit 14 detects a waveform parameter based on the frequency spectrum obtained from the time waveform read from the time waveform storage unit 12a. Alternatively, the detection unit 14 detects the waveform parameter based on the frequency spectrum read from the frequency spectrum storage unit 12b.

  An example of processing for detecting a waveform parameter from a time waveform read from the time waveform storage unit 12a in the detection unit 14 will be described with reference to FIG. The detection unit 14 performs time-frequency conversion on the time waveform (FIG. 4A) read from the time waveform storage unit 12a to obtain a frequency spectrum (FIG. 4B). Thereafter, the detection unit 14 obtains an energy spectrum E (n) for each frequency band designated in advance from the obtained frequency spectrum (FIG. 4B). Subsequently, as shown in Equation 1, the detection unit 14 obtains a ratio R (n) in the total value ΣE of the energy spectrum of each band for each obtained energy spectrum E (n), thereby obtaining this ratio R (N) detects the feature quantity of one time signal as the waveform parameter R (n).

  In the example shown in FIG. 4, the energy spectrum of each frequency band is used. However, instead of the energy spectrum, the frequency spectrum of each frequency band may be used as a waveform parameter.

  As described above, the detection unit 14 can detect a waveform parameter that is a feature amount of a signal that does not have a specific resonance frequency by widely using information on the frequency of the detected signal to obtain a waveform parameter.

  In the example described above with reference to FIG. 4, the example in which the waveform parameter is detected based on the frequency spectrum obtained from the time waveform measured by the time waveform measuring unit 11a has been described. However, the signal measurement analysis without the time waveform measuring unit 11a is performed. In the case of the apparatus, the same result can be obtained even if the waveform parameter is detected from the frequency spectrum measured by the frequency spectrum measuring unit 11b. The same result can be obtained even if a waveform parameter such as a peak value is detected from the time waveform measured by the time waveform measuring unit 11a.

  Here, as an example of a waveform parameter that the detection unit 14 detects from a time waveform, “a peak value of a signal waveform in an arbitrary time interval”, “an average value of a signal waveform in an arbitrary time interval”, “an arbitrary time interval” Defined energy amount, “Rise rate of signal waveform defined on time axis”, “Rise time of signal waveform defined on time axis”, “Time change rate of arbitrary time interval”, etc. . Further, as examples of waveform parameters detected by the detection unit 14 from the frequency spectrum, “spectrum peak value between arbitrary frequency bands”, “resonance frequency value giving a spectral level equal to or higher than a predetermined value in an arbitrary frequency section”, “arbitrary frequency value” There are "average spectral value in frequency band", "energy defined by spectral amount between arbitrary frequency bands", "time change rate of energy defined by spectral amount between arbitrary frequency bands", and the like.

  In addition, the detection unit 14 may include “the ratio of the frequency spectrum of each frequency band obtained by arbitrarily dividing the frequency spectrum and the total value of each frequency spectrum” or “each frequency band obtained by arbitrarily dividing the frequency spectrum. The ratio of the energy spectrum of each and the total value of each energy spectrum ”may be detected as a waveform parameter.

<< Analysis process >>
Next, an analysis process (the process of S4 in FIG. 3) executed by the analysis unit 16 will be described.
As an example of the timing at which the analysis process is started, the timing at which a new record is added and stored in the database 15 or the timing at which an analysis operation request is input via the input device can be considered. These timings may be freely selected and used by the user.

When the analysis process is started, the analysis unit 16 reads data from the database 15 and analyzes the data. The analysis method in the analysis unit 16 includes the following method (1) or (2).
(1) A method in which when an analysis request is input, a record that matches a value specified as a condition in the analysis request is searched for as an analysis result. In this case, values specified as conditions include “waveform data identifier value” and “waveform parameter value”. This analysis request is an operation instruction signal for operating the analysis process, and is input by the user via the input device 17.

  (2) Calculate a cross-correlation coefficient between a predetermined record (evaluation data) to be evaluated and another record (comparison target data), and extract a record (comparison target data) having a predetermined correlation The method of analysis results. For example, when an analysis process is started at a timing when a new record is accumulated in the database 15, the record newly accumulated in the database 15 is used as evaluation data, and other records are used as comparison target data. In addition, when the analysis process is started at the timing when the analysis request for operating the analysis process is input, the record specified by the request is used as the evaluation data from among the records stored in the database 15, and each other record is compared. The target data. In addition, when analysis processing is performed at a predetermined timing (such as periodically), there is a method in which the analysis unit 16 arbitrarily selects a record to be evaluated data and uses each other record as comparison target data.

  For example, the analysis result by the analysis method (1) is displayed on the display device 19 as a result screen 100 as shown in FIG. A result screen 100 shown in FIG. 5 is an example in which a record whose waveform data identifier is “1” in the data shown in FIG. 2 is searched and displayed as a result display unit 100a by analysis processing.

  In the case of the analysis method (2), as shown in FIG. 6, the analysis unit 16 extracts the waveform parameter (“Data A” in FIG. 6 S41) of the record that is the evaluation data, and calculates the cross-correlation coefficient. It is set as a value to be used for calculation (S41), data is read from the database 15, and waveform parameters ("Data1, Data2 ..." in FIG. 6 S42) of the record that is the comparison target data are extracted and the cross correlation coefficient It is set as another value used for the calculation of (S42). Note that the evaluation data A in S41 in FIG. 6 is assumed to be either waveform data measured by the data measuring unit 11 or waveform data already recorded in the database unit 15.

  Subsequently, the analysis unit 16 calculates a cross-correlation coefficient for the waveform parameter of the evaluation data and the waveform parameter of the comparison target data set in steps S41 and S42 (S43), and analyzes the data (S44). Thereafter, the analysis unit 16 outputs the result screen data including the analysis result in step S44 to the display control unit 18 (S45).

  The display control unit 18 displays the analysis result on the display device 19 based on the result screen data input from the analysis unit 16 (S5). Step S5 shown in FIG. 6 is the same process as step S5 in FIG.

  As described above, in the case of analysis using the calculation of the cross-correlation coefficient, the analysis unit 16 evaluates the calculation used for calculating the cross-correlation coefficient, for example, when the calculated cross-correlation coefficient is equal to or greater than a predetermined threshold. The signal waveform specified by the data is extracted, identified as noise, and used as the analysis result. Further, the result screen data output by the analysis unit 16 includes the analysis result, and the display control unit 18 displays the result screen 110 as illustrated in FIG. 7 including information on the evaluation data extracted as the signal waveform on the display device 19. To display.

  The result screen 110 shown in FIG. 7 includes a time waveform display unit 110a that displays a time waveform, and a cross-correlation coefficient display unit 110b that displays the correlation that is the result calculated by the analysis process. In the example shown in FIG. 7, the correlation between the evaluation data and the comparison target data is displayed according to a value designated in advance. For example, “CB wave” has a cross-correlation coefficient of “1.00”. Therefore, it is evaluated as “high similarity”, and “electric railway noise” has a cross-correlation coefficient of “0.35”, so that the characteristics of the evaluation signal can be easily grasped, such as “low similarity”. I can do it.

  As described above, in the method (1), a record that matches a value input as a condition is detected from the data stored in the database 15, and the nature of the signal waveform specified by the predetermined value is grasped. be able to. In the method (2), the cross-correlation coefficient between the evaluation data and the evaluation target data stored in the database 15 is obtained, and the property of the signal waveform specified by the correlated evaluation data can be grasped. it can.

  Therefore, according to the signal measurement and analysis apparatus according to the best embodiment of the present invention, data related to signal waveforms such as measured electromagnetic interference and noise is accumulated, stored, analyzed, and managed in the electromagnetic environment and noise environment. By doing so, it can be used for analysis and countermeasures of signal waveforms such as interference waves. Specifically, analysis includes statistical evaluation of the characteristics of data related to a plurality of detected signal waveforms, evaluation of relative relationships for each data related to the detected signal waveforms, and data related to newly detected signal waveforms. In addition, it is possible to execute the evaluation of the similarity of the data related to the signal waveform detected in the past, the search of the data related to the signal waveform detected in the past similar to the data related to the newly detected signal waveform, and the like.

  In addition, according to the signal measurement and analysis apparatus according to the preferred embodiment of the present invention, it is possible to efficiently display a result of analysis such as past data search or correlated data search, thereby providing a signal to the user. Makes it easy to understand the waveform status. Further, by measuring waveform data, detecting waveform parameters, and analyzing signal waveforms in one apparatus, it is possible to improve the efficiency of the apparatus configuration.

<Modification 1>
FIG. 8 is a block diagram illustrating a configuration of a signal measurement analyzer 1a according to a modification of the best embodiment of the present invention. As shown in FIG. 8, the signal measurement analyzer 1 a is different from the signal measurement analyzer 1 in that it includes a correction unit 41 and a correction data storage unit 42. Since the sensor 31 has a certain frequency characteristic, the detected signal is distorted by this frequency characteristic. Therefore, the signal measurement analyzer 1a corrects the distortion due to this frequency characteristic.

  The correction data storage unit 42 stores in advance data for correcting distortion due to frequency characteristics of the signal waveform obtained from each sensor 31 connected to the signal measurement analyzer 1a. The correction unit 41 reads data stored in the correction data storage unit 42 and corrects distortion caused by the frequency characteristics of the sensor 31 with respect to the frequency spectrum used by the detection unit 14 in detection processing.

  Specifically, the correction data storage unit 42 stores in advance correction data for associating a characteristic value representing the detection sensitivity characteristic of the sensor 31 with a reference value that is an arbitrary value that can be measured by the sensor 31. . Further, when the correction unit 41 starts the correction process, the correction unit 41 reads out the correction data from the correction data storage unit 42, and the frequency spectrum sampled at an arbitrary interval is smaller than the reference value by a predetermined value or more. Corrects an arbitrary value of the spectrum by increasing the change ratio of the characteristic value, and if an arbitrary value of the frequency spectrum is larger than the reference value by a predetermined value or more, decreases the arbitrary value of the frequency spectrum by the change ratio of the characteristic value To correct. Thereafter, the correction unit 41 outputs a value corrected by increasing or decreasing to the detection unit 14. Further, when correcting data for a time waveform, the time waveform stored in the time waveform storage unit 12a is time-frequency converted, and then the frequency characteristics of the sensor 31 are corrected in the same manner as described above.

  As described above, by correcting the distortion of the signal detected by the sensor in the correction unit, it is possible to improve the accuracy of the analysis result in the analysis unit.

<Modification 2>
FIG. 9 is a block diagram illustrating a configuration of a signal measurement analyzer 1b according to another modification of the best embodiment of the present invention. As shown in FIG. 9, the signal measurement analyzer 1 b is different from the signal measurement analyzer 1 in that it includes a clustering processing unit 43.

  The clustering processing unit 43 performs a clustering process on a plurality of data specified by the waveform parameters according to the specified condition, and obtains a clustering position of the dimension specified by the condition. The clustering position represents the corresponding position of each waveform data in the clustering processing result. By this clustering position, the relationship between data specified by the waveform parameter of each record can be expressed. In the clustering process, the optimization process is repeated a number of times that is specified in advance and the number of times that considers the convergence level of the optimization function by a widely used algorithm. Further, when the clustering process is completed under the designated conditions, the clustering processing unit 43 outputs result data in which the data specified by each waveform parameter is associated with the obtained clustering position.

  As a waveform parameter clustering algorithm, a general self-organization processing method (see “T. Kohonen,“ Self-organizing maps ”, Springer, Berlin, Heidelberg New York [2nd edition], 1997.”), K -means method (see “J. Han and M. Kamber,“ Data minig concept and techniques ”, Academic Press, 2001)), hierarchical clustering method (see“ Miyamoto, “Cluster Analysis” Morikita Publishing, 1999 ”), etc. Is used. As the number of dimensions of the clustering position, one-dimensional, two-dimensional plane, or three-dimensional is specified in advance for the self-organization processing method, and two-dimensional for the K-means method or hierarchical clustering method. Is assigned.

  FIG. 10 is a diagram for explaining an example of clustering processing using the self-organization processing method. First, the clustering processing unit 43 extracts waveform parameters and sets them as input data for all records to be clustered (S61). Further, the clustering processing unit 43 sets the clustering size and the convergence condition during the optimization process (S62). In steps S61 and S62, the clustering processing unit 43 may set using the conditions set in the signal measurement analyzer 1b in advance, or according to the operation request input by the user via the input device 19. It may be set.

  Subsequently, the clustering processing unit 43 initializes a load vector corresponding to the designated clustering size (S63), and sets input data based on the clustering size set in step S62 (S64).

  Thereafter, the clustering processing unit 43 repeats the optimization process for updating the load vector so that the similarity between the set input data and the load vector is increased until the condition set in step S62 is satisfied (until the process is converged). (S66, S67).

  When the optimization process is completed (YES in S67), the analysis unit 16 determines a display area from the relationship of each data specified under the condition where the optimization process has converged, and sets the clustering position as the display area. Result data that is determined and associated with each data is output as a result of the clustering process, and the display control unit 18 displays a result screen on the display device 19 (S68).

  FIG. 11 is an example of a result screen 120 that displays an analysis result when eight input data are selected by the clustering process and the set number of dimensions is two. The result screen 120 includes a clustering result display unit 120a that displays the result of the clustering process.

  For example, in the clustering result display unit 120a, the information element of the clustering position is the x coordinate, the other information element is the y coordinate, and Data1 to Data8 are the contents indicating the waveform data corresponding to each clustering position by the x coordinate and the y coordinate. Place it at a fixed position and display it. In the example of FIG. 11, Data 7, Data 6, and Data 8 are displayed adjacent to each other, so that the user can visually determine that the characteristics of the waveform data corresponding to these data are similar. . When the number of dimensions is 1, the clustering result display unit 120a displays each data on a straight line, and when the number of dimensions is 3, the clustering result display unit 120a displays each data in a three-dimensional space. To do.

  Thus, by displaying the relative relationship of the data regarding a plurality of signal waveforms as visual information, the user can easily grasp the similarity regarding the plurality of signal waveforms.

It is a block diagram explaining the structure of the signal measurement analyzer which concerns on the best embodiment of this invention. It is an example of the data memorize | stored in the database of a signal measurement analyzer. It is a flowchart explaining the process in a signal measurement analyzer. It is a figure explaining an example of the process which detects a waveform parameter from a time waveform in a detection part. It is an example of the result screen displayed on a display apparatus. It is a figure explaining an example of an analysis process. It is another example of the result screen displayed on a display apparatus. It is a block diagram explaining the structure of the signal measurement analyzer which concerns on the modification of the best embodiment of this invention. It is a block diagram explaining the structure of the signal measurement analyzer which concerns on the other modification of the best embodiment of this invention. It is a figure explaining an example of a clustering process. It is an example of the result screen displayed on a display apparatus.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1, 1a, 1b ... Signal measurement analyzer 11 ... Data measurement part 11a ... Time waveform measurement part 11b ... Frequency spectrum measurement part 12 ... Data storage part 12a ... Time waveform storage part 12b ... Frequency spectrum storage part 13 ... Trigger signal receiving part DESCRIPTION OF SYMBOLS 14 ... Detection part 15 ... Database 16 ... Analysis part 17 ... Input device 18 ... Display control part 19 ... Display apparatus 21 ... Electronic device 31, 32 ... Sensor 41 ... Correction | amendment part 42 ... Correction data storage part 43 ... Clustering process part

Claims (11)

A data measuring unit connected to a sensor that outputs a detected signal and measuring at least one of a time waveform or a frequency spectrum of the signal input from the sensor;
A data storage unit for storing the signal measured in the data measurement unit as waveform data;
A detection unit that reads the waveform data from the data storage unit, detects a waveform parameter that is a feature amount of the waveform data from the waveform data, and generates a record including the waveform parameter;
A database unit for storing records including the waveform parameters;
An analysis unit that reads records accumulated from the database unit and analyzes waveform data based on one or more waveform parameters accumulated in the database unit and an arbitrarily specified analysis condition;
A display unit for displaying an analysis result in the analysis unit;
A signal measurement and analysis apparatus comprising: A trigger signal receiving unit for receiving a trigger signal for controlling storage of the waveform data;
The data measurement unit has a trigger determination unit that determines whether or not the trigger signal reception unit has received a trigger signal. When the trigger determination unit determines that the trigger signal has been received, the measured waveform data The signal measurement / analysis apparatus according to claim 1, wherein the signal measurement / analysis apparatus is stored in the database unit. The data measurement unit includes threshold determination means that compares the signal with predetermined upper and lower thresholds to determine whether the signal is equal to or higher than the upper threshold or lower than the lower threshold. The signal measurement analyzer according to claim 1, wherein when the means determines that the signal is equal to or higher than the upper threshold or lower than the lower threshold, the measured waveform data is stored in the database unit. The detection unit, as a waveform parameter from the time waveform,
The peak value of the waveform in any time interval,
Average value of the waveform in any time interval,
The amount of energy defined in any time interval,
Waveform rise rate defined on the time axis,
Rise time of the waveform defined on the time axis,
Or the rate of time change in any time interval,
The signal measurement analyzer according to claim 1, wherein at least one of the signals is detected. The detection unit, as a waveform parameter from the frequency spectrum,
Spectral peak value between any frequency bands,
Resonance frequency value giving a spectral level above a predetermined value in an arbitrary frequency interval,
Spectral average value in any frequency band,
Energy defined by the amount of spectrum between any frequency band,
Or the rate of time change of energy defined by the amount of spectrum between any frequency bands,
The signal measurement analyzer according to claim 1, wherein at least one of the signals is detected. The detection unit, as the waveform parameter,
The ratio of the frequency spectrum of each frequency band obtained by arbitrarily dividing the frequency spectrum and the total value of each frequency spectrum,
Or the ratio between the energy spectrum of each frequency band obtained by arbitrarily dividing the frequency spectrum and the total value of each energy spectrum,
The signal measurement analyzer according to claim 1, wherein at least one of the signals is detected.   The analysis unit, when an analysis request including a waveform parameter value is input from an input device, searches the database unit for a record specified by the waveform parameter value included in the analysis request. Item 1. The signal measurement analyzer according to Item 1. The database unit stores a record using an identifier as a key,
2. The signal measurement and analysis apparatus according to claim 1, wherein, when the analysis request including the identifier is input, the analysis unit searches the database unit for a record identified by the identifier included in the analysis request.   The analysis unit calculates a cross-correlation coefficient between a waveform parameter included in a predetermined record stored in the database unit and a waveform parameter included in another record, and the cross-correlation coefficient is within a predetermined range. 2. The signal measurement analysis apparatus according to claim 1, wherein if there is, the predetermined record is extracted.   A correction unit that reads the correction data from a correction data storage unit in which correction data for correcting distortion due to the frequency characteristics of the sensor of the signal input from the sensor is stored, and corrects the distortion; 2. The signal measurement and analysis apparatus according to claim 1, wherein Clustering processing is performed on the waveform parameters of multiple records according to the specified conditions, the contents of similar records are related, and the positions to be displayed on the display screen are obtained as clustering positions. The signal measurement analysis apparatus according to claim 1, further comprising a clustering processing unit that outputs the contents in association with each other.

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