Thinning of scalar vibration data

Abstract

A computer-implemented method for thinning scalar measurement data to reduce storage space required in a second data storage device to store the scalar measurement data, wherein the scalar measurement data was initially recorded in a first data storage device during a measurement period, the method comprising: (a) accessing the scalar measurement data from the first data storage device; (b) defining an amplitude range with which a plurality of amplitude values ​​of the scalar measurement data are compared; (c) setting a first or subsequent one of the amplitude values ​​as a reference amplitude value and setting a time corresponding to the first or subsequent one of the amplitude values ​​as a reference time value; (d) storing the reference amplitude value and the reference time value in the second data storage device; (e) accessing a next amplitude value of the plurality of amplitude values ​​from the first data storage device; (f) Determine whether an absolute difference between the reference amplitude value and the nearest amplitude value is greater than the amplitude range, and if the absolute difference between the reference amplitude value and the nearest amplitude value is not greater than the amplitude range: - discarding the next amplitude value by not storing it in the second data storage device; - Calculating an average measurement value based on a sum of the discarded next amplitude value and the previously discarded amplitude values ​​that are temporally adjacent to the discarded next amplitude value; - calculating a time gap value indicating a total time duration associated with the discarded next amplitude value and the previously discarded amplitude values ​​that are temporally adjacent to the discarded amplitude value; and - storing the average measurement value and the time gap value in the second data storage device; and - Go to step (g) or if the absolute difference between the reference amplitude value and the nearest amplitude value is greater than the amplitude range: - storing the next amplitude value and a time at which the next amplitude value was recorded in the second data storage device; and - setting the next amplitude value as the reference amplitude value and setting the time at which the next amplitude value was recorded as the reference time value; and (g) repeating steps (e) and (f) until all scalar measurement data recorded during the measurement period have been processed; and (h) generating a graphical amplitude-time representation of the scalar measurement data stored in the second data storage device, the graphical representation including one or more data gaps caused by discarding amplitude values ​​in step (f), the one or more data gaps having a time duration corresponding to the time gap value, and the amplitude values ​​discarded in step (f) in the one or more data gaps being replaced by artificially generated amplitude values ​​having amplitudes randomly distributed around the average measurement value.

Description

REGIONThis invention relates to the field of machine vibration data measurement and storage. More particularly, this invention relates to a system for thinning scalar vibration data to reduce data storage requirements by several orders of magnitude without losing important machine diagnostic vibration information.BACKGROUNDContinuous online machine vibration monitors may be configured to acquire and store very large amounts of scalar (trend) vibration measurement data. Emerson Process Management's model AMS 6500 ATG is an example of such a device that can capture and store several megabytes of data per hour. If there are several hundred such devices in a plant, the amount of data per hour may reach several gigabytes. Over a long period of time, the vibration data amount may become unmanageable.Therefore, a process of thinning out the large amounts of collected data without losing important vibration information is needed.JP H11-15 527 A discloses compact recording of a stable period over a long period by storing a measurement value and a time value in a data area only when it is judged that the measurement value deviates from a reference value, and overwriting the reference value with the measurement value and preparing a next reference value. The first data is sampled at time t1. When the initial value of the reference value is deviated from the measurement value a 1, a number "0" is stored in the data area of the data number 1 as the measurement value a 1 and the initial value of the time. Subsequently, the reference value is replaced by the measurement value a 1. At time t2, second data is sampled. When a difference exceeding a predetermined allowable value is detected as a comparison result of the measurement value b 1 and the reference value, the measurement value b 1 and a time difference t 2- t 1 are stored in a data number 2, and the reference value is replaced with the measurement value b 1. When the differences from the reference value in the measurement values c2-c4 in the fourth to sixth samples are not larger than the allowable value, the time differences t4-t3 to t6-t5 are added to the time value of a date numbered 3, and the time value of the date numbered 3 is set to t6-t2.US 2012 / 0 109 586 A1 discloses a measuring device and a measuring method for a continuous physical variable. The measurement apparatus includes a time unit for outputting a time base and a time scale; a sampling unit for sampling the continuous physical quantity under control of the time base and at time intervals corresponding to the Nyquist sampling theory and outputting a sample value; a decision unit for deciding whether the sample value transitions from a steady state to a transition state or transitions from the transition state to the steady state; a calculation unit for calculating a steady value for the sample value of the sampling unit in the steady state; and an output unit for outputting the start time of the steady state and the steady value X and the start time and the sample value of the transition state according to the decision result and the time scale.DE 195 35 719 A1 relates to a measured value acquisition device in which electrical voltages, currents, pulses (frequencies) and / or status signals are acquired. Such a device is also referred to as a data logger. Voltages, currents and frequencies generally represent physical quantities such as temperatures, pressures and speeds. The discrete values are referred to as measured values, and the sum of the measured values as measured data. The measured values are recorded in a time-dependent manner. These measurement data are thus also referred to as time-dependent measurement series. The measurement data is stored in various storage media such as hard disk, RAM memory.DE 20 59 511 A1 relates to a data logger for digitally recording the values of at least two variables which are sampled at intervals, such as the measurement values of load and strain in a tensile testing machine, or the measurement values of thermal conductivity and time in a gas chromatograph.JP H02-159 525 A discloses providing effective data for analysis of a cause by a method in which vibration signal data processed by a data processing means are collected at a fixed time, recorded as a waveform and read for reconstruction in diagnosis. Time series data obtained by sampling a vibration signal is subjected to Fast Fourier Transform (FFT) by a data processing means to determine data sequences of frequency components. As a result, an abnormality or an indication thereof is detected by an abnormality detecting means. The data sequences of the frequency components are sequentially input to a data recorder to be recorded there as historical data at a time of each designation change during a speed and load change or at a time of a fixed time series during a rated operation. At this point, a level filter capable of detecting a frequency component above a certain threshold required for diagnosis and analysis is used for recording. In this manner, a data amount is compressed to obtain the data over a long period of time.SUMMARYThe invention is defined in the independent claims.Depending on configuration variables, the data thinning process described herein may reduce the required amount of data storage by several orders of magnitude without losing important machine diagnostic vibration information. Some embodiments of the process may be used to thin out data that has already been stored in a database. Some embodiments may be used in a real-time process to thin out data prior to storage in a database.In general, each scalar vibration measurement has its own range of values and delta value change, which does not have a significant effect on machine vibration information. A preferred embodiment described herein provides a method for automatically assessing delta value change. In another aspect, embodiments described herein provide data storage structures for storing the thinned scalar values. In yet another aspect, embodiments described herein provide a process to display a trend graph to indicate where the scalar data has been thinned.Some embodiments described herein are directed to a computer-implemented method for thinning scalar measurement data to reduce a storage space needed in a second data storage device to store the scalar measurement data. The scalar measurement data were first recorded in a first data storage device during a measurement period. A preferred embodiment of the method includes: (a) accessing the scalar measurement data from the first data storage device; (b) setting an amplitude range to which a plurality of amplitude values of the scalar measurement data are compared; (c) setting a first or subsequent one of the amplitude values as a reference amplitude value and setting a time corresponding to the first or subsequent one of the amplitude values as a reference time value; (d) storing the reference amplitude value and the reference time value in the second data storage device; (e) accessing a next amplitude value of the plurality of amplitude values from the first data storage device; (f) determining whether an absolute difference between the reference amplitude value and the next amplitude value is larger than the amplitude range, and when the absolute difference between the reference amplitude value and the next amplitude value is not larger than the amplitude range:discarding the next amplitude value by not storing it in the second data storage device; andproceeding to step (g), orwhen the absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range:storing the next amplitude value and a time at which the next amplitude value was recorded in the second data storage device; andsetting the next amplitude value as the reference amplitude value and setting the time at which the next amplitude value was recorded as the reference time value; and(g) repeating steps (e) and (f) until all scalar measurement data recorded during the measurement period has been processed.In some embodiments, step (b) includes setting the amplitude range based on a median of a moving standard deviation of the plurality of amplitude values of the scalar measurement data over the measurement data recorded during the measurement period.In some embodiments, the first data storage device includes a data buffer in a vibration data collector, and the second data storage device includes a data storage device in the vibration data collector, and steps (a) to (g) are performed in real time while the vibration data collector records the scalar measurement data.In some embodiments, the first data storage device includes a data storage device in a vibration data collector, and the second data storage device includes a vibration database, and steps (a) to (g) are performed after the scalar measurement data is recorded in the data storage device of the vibration data collector.When the absolute difference between the reference amplitude value and the next amplitude value is larger than the amplitude range in step (f), the method includes:calculating an average measurement value based on a sum of the amplitude values discarded in step (f);calculating a time gap value indicating a total time duration associated with the amplitude values discarded in step (f); andstoring the average measurement value and the time gap value in the second data storage device.The method includes generating a graphical amplitude-time representation of the scalar measurement data stored in the second data storage device. The graph includes one or more data gaps caused by discarding amplitude values in step (f), the one or more data gaps having a time duration corresponding to the time gap value. The amplitude values discarded in step (f) are replaced in the one or more data gaps in the representation by the average measurement value or by artificially generated amplitude values having amplitudes randomly distributed around the average measurement value.In another aspect, some embodiments described herein are directed to an apparatus for thinning scalar measurement data to reduce a storage space needed to store the scalar measurement data. The apparatus includes a first data storage device in which the scalar measurement data were first recorded during a measurement period, and a second data storage device in which the scalar measurement data are stored after thinning. The apparatus also includes a processor in communication with the first and second data storage devices. The processor executes instructions to: (a) access the scalar measurement data from the first data storage device; (b) set an amplitude range to which a plurality of amplitude values of the scalar measurement data are compared; (c) set a first and subsequent one of the amplitude values as a reference amplitude value and set a time corresponding to the first or subsequent one of the amplitude values as a reference time value; (d) store the reference amplitude value and the reference time value in the second data storage device; (e) access a next amplitude value of the plurality of amplitude values from the first data storage device; (f) determining whether an absolute difference between the reference amplitude value and the next amplitude value is larger than the amplitude range, and when the absolute difference between the reference amplitude value and the next amplitude value is not larger than the amplitude range:discarding the next amplitude value by not storing it in the second data storage device; andproceeding to step (g), orwhen the absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range:storing the next amplitude value and a time at which the next amplitude value was recorded in the second data storage device; andsetting the next amplitude value as the reference amplitude value and setting the time at which the next amplitude value was recorded as the reference time value; and(g) repeating steps (e) and (f) until all scalar measurement data recorded during the measurement period has been processed.In some embodiments, the processor sets the amplitude range based on a median of a moving standard deviation of the plurality of amplitude values of the scalar measurement data over the measurement data recorded during the measurement period.In some embodiments, the first data storage device includes a data buffer in a vibration data collector, the second data storage device includes a data storage device in the vibration data collector, and the processor executes the instructions to perform steps (a) through (g) in real time while the vibration data collector records the scalar measurement data.In some embodiments, the first data storage device includes a data storage device in a vibration data collector, the second data storage device includes a vibration database, and the processor executes the instructions to perform steps (a) to (g) after the scalar measurement data is recorded in the data storage device of the vibration data collector.When the processor determines that the absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range, the processor executes instructions to:calculating an average measurement value based on a sum of the amplitude values discarded in step (f);calculating a time gap value indicating a total time duration associated with the amplitude values discarded in step (f); andstoring the average measurement value and the time gap value in the second data storage device.The processor generates a graphical amplitude-time representation of the scalar measurement data stored in the second data storage device. The graph includes one or more data gaps caused by discarding amplitude values in step (f). The one or more data gaps have a time duration corresponding to the time gap value. The amplitude values discarded in step (f) are replaced in the one or more data gaps by the average measurement value or by artificially generated amplitude values having amplitudes randomly distributed around the average measurement value.BRIEF DESCRIPTION OF THE DRAWINGSOther embodiments of the invention will become apparent from the detailed description taken in conjunction with the drawings, wherein elements are not to scale to more clearly show the details, wherein like reference numerals indicate like elements throughout the several views, and wherein: FIG. 1 illustrates an apparatus for collecting and thinning scalar measurement data according to an embodiment of the invention; FIG. 2 illustrates a diagram of scalar measurement data that has been thinned out, according to an embodiment of the invention; FIG. 3 illustrates a method for thinning scalar measurement data according to an embodiment of the invention; FIG. 4 illustrates a structure for storing thinned measurement data in a database according to an embodiment of the invention; FIG. 5 illustrates an improved method for thinning scalar measurement data according to an embodiment of the invention; FIG. 6 illustrates a relational database schema for storing thinned scalar vibration measurement data, in accordance with an embodiment of the invention; FIG. 7 illustrates options for graphically displaying thinned scalar vibration measurement data, in accordance with an embodiment of the invention; FIG. 8 illustrates an example of thinned scalar vibration measurement data collected by an online vibration data monitor, according to an embodiment of the invention; FIG. 9 illustrates a process for determining an amplitude range based on a median of a moving average standard deviation according to an embodiment of the invention; FIG. 10 illustrates an example of thinned scalar vibration measurement data collected by an online vibration data monitor with a sliding triple standard deviation representation calculated according to an embodiment of the invention; and FIG. 11 illustrates a software implementation flow of a thinning process of scalar vibration measurement data according to an embodiment of the invention.DETAILED DESCRIPTIONAs shown in FIG. 1, a vibration measurement and analysis system includes vibration sensors 16 attached to a machine 12. The engine 12 includes at least one rotating component 14, such as a shaft, supported by bearings. The vibration sensors 16 generate vibration signals representative of the vibration of the machine 12 that includes vibration components associated with the rotating component 14. The vibration signals are received, conditioned, and converted to digital and scalar time waveform data by one or more vibration data collectors, such as a portable vibration analyzer 18 or an online continuous vibration monitoring system 20. The vibration data collectors 18 and 20 include signal conditioning circuitry, analog-to-digital conversion circuitry and processing circuitry 34 for conditioning the vibration signals from the sensors 16 and for generating the scalar vibration data and time waveform vibration data based thereon. In a preferred embodiment, vibration data collectors 18 and 20 also include a data buffer 32 for short term data storage during data collection and a data storage device 30 for long term storage. The digital time waveform vibration data is preferably stored in a vibration database 22, from which the data is available for analysis by software routines executed by a processor 36 of a vibration analysis computer 24. In preferred embodiments, the system 10 includes a user interface 28, such as a touch screen, that allows a user to view graphical representations of data, select certain measurement parameters, and provide other inputs as described herein.Preferred embodiments provide a thinning process of scalar vibration data as graphically depicted in FIG. 2. This process generally includes:(1) setting an amplitude range of the vibration measurement values (ΔV) small enough so that no important engine diagnostic vibration information would be lost if all measurement values falling within this ΔV range were set to a single reference value. This ΔV range is the amplitude range between the horizontal dotted lines in FIG. 2.(2) setting the first measurement value as the reference value (at time A in FIG. 2 ) and discarding all subsequent measurement values falling within the ΔV range until a measurement value falls outside the ΔV range.(3) When a measurement value is out of the ΔV range (at time B in FIG. 2 ), set this measurement value as a new reference value, and repeat.FIG. 3 illustrates a preferred embodiment of the process of thinning scalar vibration data 100. The first step is to configure the online vibration monitor 20 to continually collect scalar vibration measurement data (step 102), including exception triggering if needed. This configuration process may include configuring the time interval between recording scalar measurements and other criteria, such as recording the scalar measurements when an alarm limit is exceeded (step 104). Examples of scalar vibration measurements include total vibration, PeakVue™ demod, peak energy, burst pulse, cepstral, periodicity, peak factor, skewness, and warping.The online vibration monitor 20 is also configured with a default value for the ΔV range for each scalar vibration measurement (step 106). Since different scalar measurement values have unique units of measure, they have unique ΔV ranges. As noted above, the standard ΔV range for each scalar measurement is preferably small enough so that no important machine diagnostic vibration information is lost if all measurement values falling within the ΔV range were fixed to a single reference value.In step 108, the online vibration monitor 20 is also configured to either store the scalar measurement data directly in the database 22 without thinning (step 112), in which case the data thinning process is performed by the vibration analysis computer 24 at a later time, or store the scalar measurement data in the internal data store 30 of the online vibration monitor 20 (step 110), and perform the data thinning process in the online vibration monitor 20 in real time. The real-time processing option reduces the original database storage requirements and reduces network traffic.The preferred embodiment of the data thinning process begins by reading an initial swing amplitude value (also referred to herein as a reference value V ref) from the data storage device 30 or database 22 (step 114) and storing V ref in the database (step 116). Initial values of a total number of discarded measurements (I cnt) and a sum of the discarded amplitude values (V sum) are set to zero (step 118). A next oscillation amplitude value (V) is then read from the data storage device 30 or the database 22 (step 120), and the value V is compared with the ΔV range (step 122).If the value V is in the ΔV range, then V sum is updated according to: and I cnt is increased according to: and the process loops back to step 120 to read the next vibration measurement value V from the data storage device 30 or the database 22 and perform the next comparison in step 122.If the value V is outside the ΔV range (step 122) and I cnt is greater than zero (step 124), then an average measurement value V ave is determined according to: and the values of V ave and I cnt are stored in the database 22 (step 128). (Some other process would be implemented to calculate a median as an alternative approach.) The process then loops back to read a new reference measurement value V ref from the data storage device 30 or database 22 (step 114) and steps 116 through 122 are repeated.If the value V is outside the ΔV range (step 122) and I cnt is not greater than zero (step 124), the process loops back to read a new reference measurement value V ref from the data storage device 30 or database 22 (step 114) and steps 116 through 122 are repeated.Conceptually, storing the thinned measurement data in the database 22 is a relatively simple process. In its simplest form, as shown in Figure 4, scalar vibration measurement data is stored as pairs of values including the sampling time and the measurement value, respectively. In the preferred embodiment, these values are stored continuously over time. As described above, the data thinning process removes the unnecessary data from the database 22, or in the case of real-time processing, the unnecessary data does not store at all until the scalar measurement values are in the ΔV range. This reduces database storage requirements. Only the average of the discarded measurement values (V ave) and the number of discarded measurement values (I cnt) are stored in the database with respect to an initial or reference measurement sampling time (T ref). This time reference is needed so that when the thinned measurement data is recovered, the appropriate gap in the measurement data can be reconstructed.FIG. 5 illustrates an improved process for thinning scalar vibration measurement data, the process including some additional steps after point "A" in the process of FIG. 3. These additional steps include recording and processing some additional values, including:a value for the maximum number of thinned measurements (I max);a value for the minimum number of thinned measurements (I min);a value for the initial or reference measurement sampling time (T ref);a value for the time gap generated by removing the discarded data in the thinning process (T gap);a value for the time of the last sample in the gap (T last), which is used in calculating T gap ;a value for the standard deviation of the thinned measured values (V stdev); andValues for V buf and T buf, which may be stored for comparison with the re-created data as described hereinafter, but which are preferably not stored, given the goal of reducing storage requirements.As shown in FIG. 5, the enhanced process includes setting the initial values for I max and I min( step 132). The I max- value is useful when the measurement data does not significantly change over a longer period of time, and ensures that real intermediate measurement data is stored. The I min- value is important for avoiding a situation where there is unnecessary oscillation of the reference and thinned data that does not store on the data memory. In a preferred embodiment, I max is set to 100 (or more) measurements and I min is set to five measurements.Step 116 of the improved process includes storing the initial oscillation measurement value V ref and the corresponding measurement sampling time T ref in the database 22.In step 120, the next vibration measurement value V and its associated time value T are read from the data storage device 30 or database 22.In step 122, the value V is compared with the ΔV range and the value I cnt is compared with I max. If the value V is in the ΔV range or the value I cnt is not greater than I max then in step 130: if the value V is outside the ΔV range or the value I cnt is greater than I max in step 122, then I cnt is compared to I min (step 134). If I cnt is greater than I min, the process proceeds to step 126. If I cnt is not greater than I min, then the process proceeds to step 124.If I cnt is greater than zero, then in step 124, the values of V buf and T buf are stored in the database 22 (step 136) and the process loops back to read a new reference measurement value V ref from the data storage device 30 or database 22 (step 114) and steps 116 through 122 are repeated.In step 126, the average measurement value V ave is determined according to and the value of T last is set to T. The value of V stdev is then calculated based on V buf, V ave and I cnt (step 138). V stdev is useful for creating a visual representation of the thinned data on a trend graph, as discussed hereinafter. T gap is then determined according toIt is important to record the T gap- value so that a scalar trend graph can be accurately reconstructed. Typically, but not always, the time between scalar measurements is constant. However, the actual sampling times of the discarded data are lost and the only way to re-create a realistic trend graph is to know the gap time. This value is also needed to estimate the time between the missing samples by dividing the gap time by the number of samples discarded.The values of I cnt, T gap, ΔV, V ave and V stdev are then stored in the database 22 with reference to T ref (step 128) and the process loops back to read a new reference measurement value V ref from the data storage device 30 or database 22 (step 114).FIG. 6 illustrates a relational database schema 200 for storing thinned scalar vibration measurement data. The trends table 204 provides a record of the time at which each scalar vibration measurement is recorded. It also refers to a trend details table that contains additional information describing the scalar data in more detail. The trend data table 202 provides a record of each recorded scalar vibration measurement with reference to the trends table 204.For each record in the trend table 204, there are multiple, such as 10 or more, records in the trend data table 202, one for each type of recorded measurement. Although each of these records is relatively small, they ultimately consume a large amount of memory (such as gigabytes) over a relatively short time and typically in a plant having many machines with multiple measurement sites on each machine. There are fewer trend records in the trend table 204 than in the trend data table 202. However, the records in the trend table 204 are typically large and therefore also consume much memory space in the database 22, and in order to effectively reduce the amount of database storage required for the scalar vibration measurements, one must not only reduce the number of records in the trend data table 202 but also reduce the number of records in the trend table 204. This is only possible if all records in the trend data table 202 are thinned out simultaneously for a particular record in the trend table 204. If so, the record in the trends table 204 may also be removed. Interestingly, this is typically the case because, generally, when the machine is operated in a steady state, all measurements being recorded stabilize and therefore can be simultaneously thinned out along with the trend table record. This maximizes the reduction in database memory required.Trend data table 202 also refers to measurement definitions table 208 that describes each measurement in detail, including units of measure. Since there are typically few of these records, the database 22 requires only a small amount of storage space for them. The thinned trend data table 210 represents a record of the thinned scalar swing measure details as listed in FIG. 6. The trend table 204 and the trend data table 202 consume a very large amount of storage space in the database 22.The trends table 204 typically has numerous "detail" fields. Since the data in most of these fields is relatively static, these fields are preferably placed in a separate table to reduce the overall database storage.It is also important to optimize the size and number of all fields in the trend table 204, trend data table 202, and thinned trend data table 210 to reduce the total memory required for the scalar vibration measurements. For long term archiving purposes, an external binary file structure is a preferred and optimal way to store the scalar vibration measurement data.FIG. 7 illustrates possible options for graphically displaying the thinned scalar vibration measurements. These options include:simply leaving a gap in the graphical display where the scalar data has been thinned out (removed);graphically displaying the mean or median measurements of the thinned original measurements; andutilizing artificially generated measurement values visually representing the original trend diagram. In one embodiment, the artificial data is generated randomly around the average measurement value and the amplitudes of the artificial data are proportional to the standard deviation of the thinned measurement data.FIG. 8 illustrates an example of thinned scalar data collected by an online vibration data monitor. The horizontal dotted lines indicate the portions of data that have been thinned out.FIG. 9 illustrates a preferred embodiment of a process for determining the ΔV range based on a median of a moving average standard deviation. As discussed hereinabove, each scalar measurement typically has a unique unit of measure and, therefore, a unique range of values. Each of these scalar measurements requires a ΔV range that is small enough so that discarded values within the range are considered unimportant as regards machine diagnostics. Although the user may first set the ΔV range to a default value, it is desirable to estimate a more reliable or representative value. Finding the median of a moving average standard deviation is one such method that provides a good measure of ΔV.As shown in FIG. 9, the method requires specifying the number of measurements (J std), which are used in calculating the standard deviation, and a number of steps for the calculation (J rep). For example, J std may be set to 25 and J rep may be set to 1000 steps (step 302). Starting from the jth measurement value, the J std- number of measurement values are read one after another and the moving standard deviations (S j) are calculated (steps 304-310). The median average value of the standard deviations (S j) is then calculated (step 312) and ΔV is set to three times the median average value (step 314). In the preferred embodiment, the median average is used rather than the average because the median average gradually removes the largest and smallest values, thereby eliminating peaks in the data that would distort the ΔV range.FIG. 10 illustrates the thinned scalar data of FIG. 8 along with a graph of the sliding triple standard deviation calculated in steps 304-310. The dashed line at the bottom of Figure 10 indicates the median average of the sliding triple standard deviation for the corresponding range of thinned data.The process of Figure 9 is preferably repeated periodically, such as weekly or monthly, depending on the rate at which measurements are taken. Since this process is rather numerically intensive, it is preferred not to carry it out continuously.FIG. 11 illustrates a software implementation flow for an embodiment of the process of thinning scalar vibration measurement data. As the "Note" box indicates, the preferred settings provide 30 measurements / second. Accordingly, although different rates could be used, the ranges of configuration parameters would require adjustment. In a preferred embodiment, the timer flow diagram decision box is implemented by an event timer and the minimum and maximum settings in the "Annotations" box are implemented as preferences in the software. An alternative embodiment may include a wait time (either in number of days or number of measurements) before the data thinning process is applied. This would ensure that the user would have the option of viewing some complete data before thinning it out.The foregoing description of preferred embodiments for this invention has been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obvious modifications or variations are possible in light of the above teachings. The embodiments are chosen and described in an effort to provide the best modes for carrying out the principles of the invention and its practical application, thereby enabling one of ordinary skill in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated. All such modifications and variations are within the scope of the invention as determined by the appended claims when interpreted in accordance with the scope to which they are fairly, legally and equitably entitled.

Claims

A computer-implemented method for thinning scalar measurement data to reduce a storage space required in a second data storage device to store the scalar measurement data, the scalar measurement data first being recorded in a first data storage device during a measurement period, the method comprising: (a) accessing the scalar measurement data from the first data storage device; (b) setting an amplitude range to which a plurality of amplitude values of the scalar measurement data are compared; (c) setting a first or subsequent one of the amplitude values as a reference amplitude value and setting a time corresponding to the first or subsequent one of the amplitude values as a reference time value; (d) storing the reference amplitude value and the reference time value in the second data storage device; (e) accessing a next amplitude value of the plurality of amplitude values from the first data storage device; (f) determining whether an absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range, and if the absolute difference between the reference amplitude value and the next amplitude value is not greater than the amplitude range: discarding the next amplitude value by not storing it in the second data storage device; calculating an average measurement value based on a sum of the discarded next amplitude value and the previously discarded amplitude values that are temporally adjacent to the discarded next amplitude value; calculating a time gap value indicating a total time duration associated with the discarded next amplitude value and the previously discarded amplitude values that are temporally adjacent to the discarded amplitude value; and storing the average measurement value and the time gap value in the second data storage device; and proceeding to step (g) or if the absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range: storing the next amplitude value and a time at which the next amplitude value was recorded in the second data storage device; and setting the next amplitude value as the reference amplitude value and setting the time at which the next amplitude value was recorded as the reference time value; and (g) repeating steps (e) and (f) until all scalar measurement data recorded during the measurement period has been processed; (h) generating an amplitude-time graphical representation of the scalar measurement data stored in the second data storage device, wherein the graphical representation includes one or more data gaps caused by discarding amplitude values in step (f), wherein the one or more data gaps have a time duration corresponding to the time gap value, and wherein the amplitude values discarded in step (f) are replaced in the one or more data gaps by artificially generated amplitude values having amplitudes randomly distributed around the average measurement value.The method of claim 1, wherein step (b) further comprises setting the amplitude range based on a median of a moving standard deviation of the plurality of amplitude values of the scalar measurement data over the measurement data recorded during the measurement period.The method of claim 1, wherein the first data storage device comprises a data buffer in a vibration data collector and the second data storage device comprises a data storage device in the vibration data collector, and steps (a) to (g) are performed in real time while the vibration data collector records the scalar measurement data.The method of claim 1, wherein the first data storage device comprises a data storage device in a vibration data collector and the second data storage device comprises a vibration database, and steps (a) to (g) are performed after the scalar measurement data is recorded in the data storage device of the vibration data collector.The method of claim 1, further comprising generating an amplitude-time graphical representation of the scalar measurement data stored in the second data storage device, wherein the graphical representation includes one or more data gaps caused by discarding amplitude values in step (f), wherein the one or more data gaps have a time duration corresponding to the time gap value, and wherein the amplitude values discarded in step (f) are replaced in the one or more data gaps with the average measurement value.An apparatus for thinning scalar measurement data to reduce a storage space required to store the scalar measurement data, comprising: a first data storage device in which the scalar measurement data is first recorded during a measurement period; a second data storage device in which the scalar measurement data is stored after thinning; a processor in communication with the first and second data storage devices, the processor executing instructions to: (a) access the scalar measurement data from the first data storage device; (b) set an amplitude range to which a plurality of amplitude values of the scalar measurement data are compared; (c) set a first or subsequent one of the amplitude values as a reference amplitude value and set a time corresponding to the first or subsequent one of the amplitude values as a reference time value; (d) storing the reference amplitude value and the reference time value in the second data storage device; (e) accessing a next amplitude value of the plurality of amplitude values from the first data storage device; (f) determining whether an absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range, and if the absolute difference between the reference amplitude value and the next amplitude value is not greater than the amplitude range: discarding the next amplitude value by not storing it in the second data storage device; calculating an average measurement value based on a sum of the discarded next amplitude value and the previously discarded amplitude values that are temporally adjacent to the discarded next amplitude value; calculating a time gap value indicating a total time duration associated with the discarded next amplitude value and the previously discarded amplitude values that are temporally adjacent to the discarded amplitude value; and storing the average measurement value and the time gap value in the second data storage device; and proceeding to step (g) or if the absolute difference between the reference amplitude value and the next amplitude value is greater than the amplitude range: storing the next amplitude value and a time at which the next amplitude value was recorded in the second data storage device; and setting the next amplitude value as the reference amplitude value and setting the time at which the next amplitude value was recorded as the reference time value; (g) repeating steps (e) and (f) until all scalar measurement data recorded during the measurement period has been processed; and (h) generating an amplitude-time graphical representation of the scalar measurement data stored in the second data storage device, wherein the graphical representation includes one or more data gaps caused by discarding amplitude values in step (f), wherein the one or more data gaps have a time duration corresponding to the time gap value, and wherein the amplitude values discarded in step (f) are replaced in the one or more data gaps by artificially generated amplitude values having amplitudes randomly distributed around the average measurement value.The apparatus of claim 6, wherein the processor sets the amplitude range based on a median of a moving standard deviation of the plurality of amplitude values of the scalar measurement data over the measurement data recorded during the measurement period.The apparatus of claim 6, wherein: the first data storage device comprises a data buffer in a vibration data collector; the second data storage device comprises a data storage device in the vibration data collector; and the processor executes the instructions to perform steps (a) through (g) in real time while the vibration data collector records the scalar measurement data.The apparatus of claim 6, wherein: the first data storage device comprises a data storage device in a vibration data collector; the second data storage device comprises a vibration database; and the processor executes the instructions to perform steps (a) to (g) after the scalar measurement data is recorded in the data storage device of the vibration data collector.The apparatus of claim 6, wherein the processor generates an amplitude-time graphical representation of the scalar measurement data stored in the second data storage device, wherein the graphical representation includes one or more data gaps caused by discarding amplitude values in step (f), wherein the one or more data gaps have a time duration corresponding to the time gap value, and wherein the amplitude values discarded in step (f) are replaced in the one or more data gaps by the average measurement value.

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