ADAPTIVE HIGH FREQUENCY ENERGY DETECTION

Abstract: A data collector (40) having a digital signal processing circuit (46) that receives a digitized vibration signal (59), and performs processing steps to isolate high frequency pulses (18) in the digitized vibration signal and quantify energy content of those pulses by detecting a peak negative value of the digitized peak-to-peak amplitude of the received vibration signal, and then using this peak negative value to compute a maximum peak-to-peak value of the received vibration signal. The resulting maximum peak-to-peak value comprises a peak-detected digital output signal that may be stored and/or displayed to a user as a reflection of the high frequency content of the vibration signal, or frequency transformed for storage and/or display to a user.

Description: ADAPTIVE HIGH FREQUENCY ENERGY DETECTION Field of the Invention The invention relates to collection and analysis of vibration data for the purposes of predictive maintenance. Background of the Invention There are many well known methods for collecting vibration data for performing predictive maintenance. Typically, in these methods a vibration sensor such as a piezoelectric accelero meter is mechanically coupled to the machine to be monitored. The vibration sensor collects vibrations from the macliine and converts these vibration to an electrical signal. The electrical signal is processed by suitable signal processing and converted from analog to digital form The resulting digital signal is stored for later analysis. Analysis of a vibration signal from a macliine typically involves one or both of ( 1) comparing that signal to previously collected signals to identify au variations that would be indicative of macliine wear and possible impending failure, and (2) forming a frequency spectrum of the vibration signal and evaluating this spectrum for patterns indicative of potential failures. Typically these operations are performed through the use of a data collector. A data collector includes analog signal processing electronics for receiving a vibration signal and conditioning that signal, and an analog to digital converter for digitally sampling the analog signal so that it may be stored and analyzed. Signal analysis may be performed using the data collector itself or by uploading collected and digitized signals from the data collector to a host computer where signal analysis is performed. Typically the analog front end of a data collector includes a number of selectable analog signal conditioning circuits, each selectable by controlling an analog switch for connecting the element into the signal path through the data collector. As seen in Fig. 1, a typical data collector might include a first signal conditioning section in which analog switches 12 and 22 may be used to selectively pass the incoming analog signal tliroug a liigh pass filter 14 or other analog signal processing blocks 14' and 14" (these blocks may include, e.g., low pass or band pass filters). Furthermore, a second signal conditioning section in the data collector might include additional analog switches 24 and 31 for selectively connecting the incoming vibration signal through a peak detecting circuit 30 or another analog signal processing circuit 30'. After these processing blocks, the signal may be further conditioned, and low pass filtered, and then converted from analog to digital form by an analog to digital converter, and stored in a digital memory As an example of the kmds of analysis performed with a data colleotoi, cuusidci a lotαtmg machme that geneiatc-. vibiatiυu signals at a fundamental frequency that corresponds to the frequency of rotation of the machine Durmg normal operation, additional vibration signals will be generated at higher frequencies as well. These higher frequency vibrations correspond to uiteractions of mechanical parts wlule the machme rotates, such as movements of moving parts in bearings, sliding pistons and cams. resonances of machine components, and other normal mechanical activity attendant to rotation of the macliine. If, however, a bearing or other mechanical system begms to fail, the part will begin to generate different frequency patterns For example, a bearing may develop a crack, causing a "click" to occur each tune weight is appbed to the crack the bearing, which will be leflected as uicreased lugher frequency vibration ui a vibration signal from the machme Alternatively, a sliding mechanical part may begm to fail and scrape undesirably as it moves, agaui causuig uicreased lugher frequency vibration It will be noted that collection and analysis of high frequency energy ui a vibration signal is often critical ui predictive mauitenauce analysis For tins reason, various techniques have been developed for isolatuig high frequency pulses or other high frequency information in a vibration signal. Typically, these methods further involve generating a lower frequency signal that quantifies the high frequency energy in the original signal, so that the lower frequency signal may be digitized and analyzed. Several of these techniques will be reviewed below. So-called "shock pulse" analysis, developed by SPM Instrument AB of Sweden in the 1970's, uses a special transducer having a tuned resonant frequency at 32 kHz. Thus, this transducer is most sensitive to "shock pulse" signals in this frequency band, which are often indicative of bearing defects and poor lubrication. The output of the resonant transducer is reflective of energy in the frequency band of the transducer, and is used to develop a measure on a scale of 1 to 100 of the high frequency energy in the signal, with a value near 100 indicating a failure mode. The Kurtosis method, developed by British Steel and the University of Southampton in the 1970's. applies a statistical method to isolated frequency bands, to develop a statistical parameter indicating the distribution of energy of the vibration signal in these various frequency bands. This analysis is typically perfoπned on bands from 2.5-5.0 kHz, 5- 10 kHz, 10- 20 kHz, 20-40 kHz, 40-80 kHz, and a sum is generated of the Kurtosis parameters for each of the five bands to produce an overall measure of the high frequency content in the signal. An enveloping process has been used by various predictive maintenance companies including Computational Systems Incorporated, SKF, and Diagnostics Instruments. In this process, the vibration signal is rectified and low-pass filtered, wliich has the effect of demodulating liigh frequency energy in the signal to base baud; the amplitude of the resulting signal is reflective of high frequency energy in the signal prior to demodulation. A final method, known as "spike energy detection" or alternatively "PeakVueø has been used by the assignee of the present application as well as others to generate a measure of the high frequency energy in a vibration signal. Fig. 1 illustrates the typical analog circuit components that would be used for performing spike energy detection. In Fig. I, the data collector has been configured for spike energy detection; thus, the electrical signal received from the vibration sensor is routed through analog switch 12 to high pass filter 14. As can be seen in Fig. 1, in a typical situation where the spike energy method would be useful, the transducer signal would uiclude a low frequency vibration signal ( een in Fig. 1 as a sinusoidal waveform 16), superimposed with brief spikes of liigh frequency vibration 18. High pass filter 14 removes the low frequency sinusoidal waveform from the incoming vibration signal, and passes the lugher frequency spikes 18, resulting in a signal as seen in Fig. 1 where the spikes 18 are superimposed upon a flat low frequency baseline signal 20. The output of high pass filter 14. after passing through a second analog switch 22, is delivered through analog switch 24 to a decayed peak-to- peak detector 30. Detector 30 outputs a signal reflecting the peak-to-peak amplitude of the signal received at its input. This function is aclύeved by a combination of resistors and capacitors with op-amp circuits forming near- ideal diodes. Specifically, a first portion of the detector 30 comprises capacitor C I, resistor Rl and an op-amp circuit that behaves as a near- ideal diode and is therefore illustrated as a diode Dl. Tlirough the action of diode Dl, upon each negative voltage swing of the signal delivered to detector 30, capacitor C I will accumulate a sufficient charge to have a peak voltage equal to the negative peak amplitude of the input signal. This charge will discharge from capacitor CI tlirough resistor Rl whenever the input signal is above its peak negative amplitude. The rate of discharge is determined by the time constant formed by multiplying R l times C I . Typically, tliis time constant is chosen to approximate the reciprocal of the cutoff frequency of the liigh pass filter 14. As a consequence, only those frequencies of interest above the cutoff frequency will pass tlirough capacitor CI and be delivered to the second portion of detector 30. The second portion of detector 30 comprises a second op-amp circuit that behaves as a buffer and near-ideal diode, and accordingly is illustrated as a buffer B 1 and diode D2. The output of tlus op-amp circuit is delivered to a parallel connection of a capacitor C2 and lesistor R2. Due to the presence of diode D2, capacitor C2 w ill be charged to the \ oltage across resistor Rl and diode D l whenever that voltage is greater than the voltage currently across capacitor C2. Thus, capacitor C2 charges to a value representative of the peak-to-peak value of the input signal, comprised of the sum of the capacitor CI voltage produced by the first portion of detector 30 and the positive peak amplitude of the mput signal. Capacitor C2 discharges charge accumulated ui tlus manner tlu'ough resistor R2, at a rate detemuned by the time constant formed by multiplying R2 times C2. This time constant is normally chosen to be proportional to the period of repetition of the spikes in the input signal. As a consequence of the long tune constant R2C2, the waveform output from detector 30 has a sawtooth-like waveform 32 with a substantial low fi cquciu-} component This w aveform can be readily digitized, and compared with previously recorded vibration signals and/or frequency transformed for anal) sis, as described above. A difficulty inherent in the various high frequency energy detection methods described above is their lack of flexibility In each of the above-described methods, specified frequency bands of the mcoinmg vibration signal are isolated using special purpose analog cucuitiy If ditfciciit applications or different machines requii'e the use of different frequency bands, redundant analog circuitry would need to be included in the data coOector: i.e., the data collector would need to have multiple high pass filters and multiple peak-to-peak detectors, one for each frequency band of interest. Alternatively, the filters and detectors in the data collector may be made adjustable, but this would also require complexity, namely, in the filters and detectors, analog switches would need to be included to select between circuit components of different values, in order to change the frequency bands and time constants of the circuit. Tliis approach may also encounter problems with noise due to the number of switches that are included in the analog signal path. Accordingly, there is a need for a data coOector and data collection method that is suitable for detection of lύgh frequency energy in a signal, facilitating use in a wide range of applications. Summary of the Invention In accordance with principles of the present invention, tlus need is met by a data collector having a digital signal processing circuit that receives a digitized vibration signal after the signal has been converted by an analog to digital converter to a digital form, and performs processing steps to isolate high frequency pulses in the digitized vibration signal and quantify energy content of those pulses. In accordance with principles of the present invention, the vibration signal is digitized by an analog to digital converter at a sampluig rate that is sufficient to reproduce lughest frequency of interest in the input signal. Then, the digital signal processmg cucuit performs high frequency pulse isolation and energy quantification upon the lesultmg digital signal. In the described embodunent. the digital signal processmg circuit performs amplitude detection by detectmg a peak-to-peak amplitude of the received vibration signal. Specifically, the digital signal processmg circuit compares the digital signal to a peak negative value and when the signal exceeds the peak negative value the peak negative value is updated to be equal to the digital signal Then, the digital signal processmg cucuit compares a maxunum peak-to-peak value to the difference between the digital signal and the peak negative value, and if the difference is larger, the maxunum peak-to- peak value is updated. PeriodicaOy, the maxunum peak-to-peak value and peak negative value are reduced m magnitude by a deca\ factor, such that the peak negative value and maxunum peak-to-peak value decay over tune. In tins described embodiment, the maxunum pcak-to-peak value comprises a peak-detected digital output signal that may be stoied and/or displayed to a user as a reflection of the high frequency content of the vibration signal Furthermore, the digital signal processing circuit also performs a frequency transformation (e g , a Fast Fourier Tiausfomi) upon the maximum peak-to-peak value to dei ive a spectrum for the maximum peak-to- peak value for storage and/or display to a user. This digital methodology for high frequency analysis produces a resulting peak-detected output signal that is analogized to those produced using analog circuitry in known data coOectors. Accordingly, users that are knowledgeable in the analysis of peak-detected waveforms produced by prior data coOectors. may readϋy reapply this knowledge to the peak- detected digital output signal produced m accordance with principles of the present invention. It is a significant aspect of the present invention that the decay factors used in computing the maxunum peak-to-peak value and peak negative value are determined by the digital signal processing circuit and may be readtfy changed. As a consequence, lύgh frequency processing performed by the digital signal processing circuit may be readily adapted to the particular frequency characteristics of the machine being anahzed for predictive maintenance. Importantly, this adaptation may be made without any modification to the analog circuitry of the data collector. In the described embodiment, the digital signal processing circuit is in the form of a software programmable processor performing a software-defined signal processing procedure to implement the methods described above. In this embodiment, adjustment of parameters is further sunpOfied by adapting the software-defined procedure to obtam these parameteis from a storage location, and to permit a user to define these parameters as desired The abo\ e and other objects and advantages ot the present mvention shaO be nude apparent horn the accompanyuig draw mgs and the description thereof Brief Description ot the Drawing The accompanyuig drawmgs, which are mcorporated in and constitute a part ot this specification, illustrate embodunents ot the mvention and, together with a general description of the mvention given above, and the detailed description of the embodiments given below, serve to explain the principles ot the inv ention Fig. 1 is a block diagram ot a conventional data coOector mcluding spike enei gy analog signal piocessing circuitry. Fig 2 is a block diagram ot a data coOector ui accordance with prmciples ot the present mvention tor pertoπumg digital signal processmg ot lugh frequency eneigy m a vibration signal. Fig 3 is a process diagram lllustratmg the processmg steps carried for ard b the digital signal processor illustrated m Fig 2, and Fig. 4 is a flow chart of operations performed by the digital signal processor of claim 2 in processing high frequency energy in a vibration signal in accordance with principles of the present invention. DetaUed Description of Specific Embodiments Referring now to Fig. 2. a data coOector 40 in accordance with principles of the present mvention can be described. Functional blocks of the data coOector are Ulustrated in Fig. 2 to facilitate the description of the operations contemplated by the present invention. It will be appreciated, however, that a data coOector suitable for carrying out the principles of the present invention may take many forms. In one embodiment, a suitable data coOector comprises a data coOector available from the assignee of the present invention under the model name dataPAC 1500. .Another suitable data coUector is disclosed ui U.S. Patent 5.633,81 1 issued to Canada et al., and assigned to Computational Systems Incorporated, wliich describes a data coOector sold by Computational Systems Incorporated, the disclosure of which is incorporated herein by reference. Alternatively, another suitable data coOector is a palmtop computer having a sound interface card therein for receiving digital vibration data such as is disclosed in U.S. Patent 5,808,903 issued to Scliiltz et al. and assigned to the assignee of the present application. the disclosure of wliich is also incorporated herein by reference. Regardless of the embodiment of data coOector that is utilized, the data collector will comprise analog signal processing circuits 42 for receiving a signal from a vibration sensor such as a piezoelectric accelerometer and conditioning this signal for sampling and conversion to a digital format. The operations perfoπned by circuits 42 may include gain and offset correction and various filtering operations, as weϋ as low pass filtering for anti-aliasing. An analog to digital (A/D) converter 44 receives the output of signal processing circuits 42 and converts this analog signal to a digitized form. .A/D converter 44 is a liigh sampling rate liigh resolution data converter programmed to sample its analog input signal at a sampling rate at least twice the maximum frequency of interest in the vibration signal. A suitable A/D converter for tins puipose is sold by Burr-Brown as part no. DSP 101 or DSP 102. The digitized vibration signal generated by A D converter 44 is delivered to a digital signal processor 46. Digital signal processor 46 may comprise a special purpose digital signal processor operating under the control of suitable software, a general purpose microprocessor operating under the control of suitable software, or a discrete logic circuit for processing digital signals in the manner described below. Each of these embodiments is within the scope of the present invention, however, the following description will focus upon embodiments of the invention in which digital signal processor 46 is a programmable circuit operating under the control of softw are. Processor 46 is coupled to a keypad and display 48 for mteractmg with a user of the data coOector 40. Kevpad and display may comprise the keypad and display incorporated into a laptop computer, or the touch screen incorporated into a palmtop computer, or a custom display and surrounding function keys on a special purpose data coOector. Processor 46 is further coupled to a storage device 50 for storing digital data, including (where processor 46 is a programmable circuit) software for operating the processor to carry out the methods of the present invention, as vveO as stored digitized vibration signals and/or processed versions thereof. Storage device 50 and processor 46. or either of them, may optionaOy interface tlirough a host interface circuit 52 to deliver stored data from storage de ice 50 to a host computer 54. Host computer 54 may include software for evaluatmg or archiving digital signals stored by the data coOector 40. In such an embodiment, some or aO of the analysis steps described in connection with Fig. 3 may be performed in a host computer upon digital data stored by data coOector 40. Alternatively, data coOector 40 may include sufficient processing power and digital storage to fuOy process and archive digital signals collected bv the data collector, in wliich case host interface 52 and host computer 54 may not be needed. Wlule both embodunents are witlim the scope ot the present mvention. the to owmg discussion will focus upon embodiments of the invention m which digital signal processor 46 is a programmable cucuit operatmg under the control ot software. Host mtertace 52 may take any of a variety of foπns. mcluding a serial interface such as RS-232 or USB coupled to a PC, an Ethernet or other network coiuiection coimected through network cabling, a parallel port connection, or other suitable foπns. Furthennore, host computer 54 may comprise a palmtop, laptop, or desktop PC, or a mono- or multi-processor server. Reten-mg now to Fig. 3. an explanation can be given of steps pertoπned by the data coOector and or host computer of Fig. 2. in accordance with principles of the present mvention. A digitized vibration signal 59 deOvered by A/D converter 44 to digital signal processoi 46 that is a good candidate tor lugh frequency processmg is illustrated in Fig. 3 Tins signal 59 comprises a low frequency vibration signal (seen in Fig. 3 as a sinusoidal waveform 16), superimposed with brief spikes of liigh frequency vibration 18. Digital signal processor 46 performs an initial routuie for filtermg and optionaOy decimatmg the digitized signal. SpecificaOy, processor 46 performs a digital signal processmg routine upon the received digital signal that implements a low-pass or band-pass filter As illustrated at 60 in Fig. 3, this filtermg routme may be response e to stored parameters available to softwaie m processoi 46 to select a desued hequency band of interest e g , the tiltei may be a band-pass filtei havmg a lower cutoff frequency selectable between 100 Hz, 200 Hz, 500 Hz. 1 kHz. 2 kHz and 5 kHz, and an uppei cutoff h equency ot 65 kHz Othei ti equencv bands muv also be utilized foi different applications EssentiaOy. the lowei cutoff frequencv must be above the fundamental maclune vibration frequency that is reflected by the suiusoidal low frequency signal 16 leceived by digital signal piocessoi 46 The uppei cutoff hequency must be at a sufficiently lugh frequency to aOo the brief spikes 18 of lugh hequency signal to be passed with muuinal attenuation oi distortion The upper cutoff frequencv is also limited by the analog anti-alias filtei mg that is peitoimed on the signal pnoi to A/D convei sion In the dlustiuted cinboduneiit, the uppei cutoff hequency is 65 kHz Band pass filteπng perfoπned bv pi ocessoi 46 l emoves the low frequencv sinusoidal wavetoπn 16 from the mcommg vibi ation signal and passes the higher frequency spikes 18 lesultmg m a signal 61 as seen in Fig 3 where the spikes 18 aie supeπmposed upon a flat low hequenev baseline signal 20 Havmg thus isolated the lugh frequency spikes through band pass filtei mg, m a second processmg step, digital signal processor 46 performs a digital signal processmg routme, described ui greater detail below with reference to Fig. 4. to generate a peak-to-peak detected signal. The peak-to- peak detection signal processing routine includes decay time constants causing the resulting waveform to have a sawtooth-like wavefoπn 32 with a substantial low frequency component. This sawtooth- like digital signal wavefoπn is analogous to the analog signal produced using analog circuitry in known data coOectors. Accordingly, it can be processed in an analogous manner by displaying its average amplitude or time waveform as depicted at 62 or 64 in Fig. 3. or by perfoπning a Fast Fourier Transform or other frequency transfoπn and displaying the energy spectrum for the signal as depicted at 66 in Fig. 3. Users that are knowledgeable in the analysis of peak-detected waveforms produced by prior data coOectors, and in them amplitude, time and frequency domain appearance, may readily reapply this knowledge to the peak-detected digital output signal produced in accordance with principles of the present invention to perfoπn predictive maintenance analysis. RefeiTing now to Fig. 4, the process perfonned by the digital signal processor 46 in processing a vibration signal in response to user input can be explained in greater detaO. In a first step 70, a user of the system identifies band pass frequencies for the digital band pass filtering illustrated at 60 in Fig. 3. SpecϋϊcaOy, the user specifies a lower cutoff frequency, e.g., by selecting one of 100 Hz. 200 Hz, 500 Hz. 1 kHz, 2 kHz or 5 kHz, and optionally selects an upper cutoff " frequency. In step 70, the user also identities the expected frequency fD at wliich a defect signal is likely to be seen, and the number of harmonics, n, of this expected frequency that are of interest for display and analysis. The upper cutoff frequency, if it is specified by the u.ser. must be large enough to pass aO of the brief spikes 18, and a confirmation of tliis may be included in step 70. In a subsequent step 72, this user-provided infoπnation is used to compute parameters for the digital processing that is perfoπned in the subsequent processes. SpecificaOy, these parameters include a time constant τl and a second time constant τ2. The time constant τl is computed as 0.000324 seconds when the u.ser specifies in step 70 a lower bandpass cutoff frequency of 2 kHz or 5 kHz, and τl is computed as 0.0069 seconds when the user specifies in step 70 a lower bandpass cutoff frequency of less than or equal to 1 kHz. The time constant τ2 is computed as 2.07/(2 *π*fD) or 2.07*n/(2*π*fmaxj . As wiO be appreciated, the first foπnula τ2 time constant establishes an appropriate decay rate to display the desired defect frequency fD at near maximum amplitude, whereas the second foπnula for the τ2 time constant ensures that n hannonics of the defect frequency tD will be displayed, where fmax is the maxunum frequency that iO be captured by the A/D converter. After computing these parameters in step 72. digital processing commences. Fust, in step 74, values for the peak negative sample and the maxunum peak to peak value are uiitialized at zero. Then, ui step 76, the digitized vibration signal is recei ed from the .A/D converter 44 The signal is then band-passed filtei ed in step 78 bv applv mg the bandpass tilteπng algorithm with the frequencies specified m step 70 The resultmg filtered stream of samples are received by a peak detection algorithm. In step 80, a sample is received, and in a loop comprismg steps 82, 84, 86. 88. 90 and 92, tlus sample is processed. Theiealter, ui step 96 a subsequent sample is received, and processmg returns to step 82 to process the new sample. In the first step 82 of the loop identified above, the current sample is evaluated to detennme w hether it is more negative than the stored peak negative sample If so, then m step 84 the peak negative sample is replaced with the current sample value As a consequence, the peak negative sample will alvvavs have the most negative sample that has been previously encountered, or a decav ed version thereof If in step 82 the current sample is not more negative than the peak negative sample, processmg contmues to step 86 in which the difference between the cuiTcnt sample and the [leak negative sample is computed, and compared to the stored decayed maxunum peak to peak value If the current difference is larger than the stored decayed maxunum peak to peak value, then ui step 88 the stored decayed maxunum peak to peak v alue is replaced ith the current difference. As a consequence, the stored decayed maxunum peak to peak value will always reflect the largest decayed peak-to-peak value of the incoming samples that has been previously encountered. After step 84 or 88. or unmediately after step 86 if the current difference is less than the stored maximum peak to peak value, processing continues to steps 90 and 92. in wliich steps are taken to apply the decay time constants τ 1 and τ2 to the stored peak negative value and maximum peak to peak value. SpecifϊcaOy. in step 90, the peak negative sample is multiplied by a factor exp(-T/τl) , where exp() represents the natural exponential operation, and T is the time period between digital samples. Simϋarly, in step 92, the maximum peak to peak value is multipOed by a factor exp(-T/τ2) . It will be appreciated that these operations cause the peak negative value and maximum peak to peak value to decay over time with an exponential decay characteristic having the time constants τl and τ2, respectively. After step 92. in addition to receiving a new sample value in step 96, other operations are perfomied upon the computed value for the maximum peak to peak value. SpecifϊcaOy, in step 94, the decayed maximum peak to peak value computed in the preceding steps is delivered to subsequent processes that display a spike energy time wavefoπn, or compute a Fast Fourier Transform of the decayed maximum peak to peak value to generate a spectral display. The resulting time and spectral displays are analogous to those produced by prior instrumentation utilizing solely analog spike energy detection circuitry, and thus can be utuized readOy by those persons experienced in using prior analog spike energy detection circuitry. The decayed maximum peak to peak value is also used in step 98 to compute an "overall" spike energy value, analogous to that created by some prior data collectors. In prior data coOectors sold by the assignee of the present appOcation, the "overaO" spike energy value is created by an analog spike energy circuit. In this circuit, the time constant of the RC filter formed by capacitor C2 and resistor R2 of Fig. 1. is 0.03 seconds. The output of the spike detection circuit is then fed through a low pass filter having a cutoff at 0.1 Hz. The resulting essentially DC value indicates the "overaO" energy of spikes in the input signal. To produce an analogous signal using the present mvention. a compensation is perfoπned to correct the time constant τl: specifically, τ2 is coirected such that it is no less than 0.03 seconds. To do this, if τ2 is less than 0.03 seconds, in step 98 the maximum peak to peak value is multiplied by a compensatory factor equal to exp(-T/(.03-τ2) ι . The combined effect of this compensatory factor and the factor used in step 92 is equal to multiplying the maximum peak to peak value by a factor of exp(-T/.03). Thus, if the value of τ2 is less than 0 03 seconds, the compensatory step 98 adjusts the maxunum peak to peak value to sunulate a τ2 of 0 03 seconds Λttei the compensation ot step 8 is pei tomied. as needed, in step 100 the resultmg maxunum peak-to-peak value samples are fed to a digital low pass filtermg process, havmg a cutoff frequency at 0 1 Hz This is analogous to the low pass filtermg used to compute "overaO" spike energy values m prior data coOectors Then, the resultmg low pass filtered samples are displayed, as a DC value, to mdicate the "overall" spike energy m the received vibration signal. This "overaO" value is readily analogous to those generated by prior data coOectors and can therefore be readily used by those persons experienced with the analogous values generated by data collectors having analog peak detection functions. Wlule the piescnt mvention has been tOustiatcd by a description ot various embodiments and wlule these embodunents have been described in considerable detail, it is not the uitention ot the applicants to restrict or m any way limit the scope of the appended clauns to such detaU. Additional advantages and modifications wul readilv appear to those skilled ui the art. The mvention in its broader aspects is therefore not limited to the specific details, representative apparatus and method, and illustrative example shown and described. Accordingly, departuies may be made from such details withou t departing from the spirit or scope of appUcant's general inventive concept. What is claimed is:

Claims: Claims 1. A data collector for detecting and quantifying liigh frequency energy in a received vibration signal, comprising an analog to digital convener converting said vibration signal to a digitized vibration signal at a sampling rate that is sufficient to reproduce a highest frequency of interest in said vibration signal, and a digital signal processing circuit that receives said digitized vibration signal and perfoπns processing steps to isolate liigh fi-equency pulses in the digitized vibration signal, and process said lugh frequency pulses to quantify energy content of the isolated pulses. 2. The data coOector of claim 1 wherein as part of quantifying energy content of isolated pulses said digital signal processing circuit detects a maximum peak-to-peak amplitude of said digitized vibration signal. 3. The data coOector of claim 2 wherein said digital signal processing circuit detects a peak-to-peak amplitude of " said digitized vibration signal by comparing a current sample of said digitized vibration signal to a peak value and when the excursion of said current sample from zero exceeds said peak value then said digital signal processing cucuit updates said peak value to be equal to said current sample. 4 The data coOector of claun 3 wherein said peak v alue is a peak negative value and said digital signal processmg circuit detects a peak-to-peak amplitude ot said digitized vibration signal by comparing a maximum peak-to- peak value to a difference between said current sample and said peak negative value, and if the difference is larger, updatmg said maxunum peak-to-peak value 5 The data collector of claim 3 wherein said digital signal processmg cucuit peπodicaOy reduces said peak value ot said digitized vibration signal by a factor such that said peak value decays over tune. 6. The data coOector of claun 5 whereui said digital signal processmg cucuit is lesponsive to user put to altei said tactoi . w heieby quantification of high frequency energy content by said digital signal processmg cucuit can be adapted to frequency characteristics ot said vibration signal. 7. The data coOector of claim 6 whereui said digital signal processmg cucuit comprises a software programmable processor perform g a software-defined signal processing procedure, said softw are-defined procedure adapted to obtaui said factor from a storage location, and to permit a user to define said factor and stoic said factoi m said storage location 8. The data coOector of claun 2 whereui said digital signal processmg cucuit peπodicaOy reduces said maximum peak-to-peak amplitude of said digitized vibration signal by a factor such that said maxunum peak-to- peak amphtude decays over time 9 The data coUectoi ot claun 8 w hereui said digital signal processmg cucuit is responsive to user mput to alter said factor, whereby quantification of liigh frequency energy content by said digital signal processoi can be adapted to frequency characteristics ot said vibration signal 10 The data coOector ot claim 9 whereui said digital signal processmg cucuit comprises a softwaie programmable processor pertoπnmg a software-defined signal processmg procedure, said softw are-defined procedure adapted to obtam said factor from a storage location, and to permit a user to define said factor and store said factoi ui said storage location 1 1 The data coOector ot claun 2 furthei compπsuig α storage device, said digital signal processmg cucuit stormg said maxunum peak-to- peak value in said storage device 12. The data coOector ot claun 2 further compπsuig a display, said digital signal processing cucuit displayuig said maxunum peak-to-peak value on said display 13. The data coOector ot claun 2 wherein said digital signal processing urcuit further pertoπiis a frequencv transtomiation upon the maxunum peak-to-peak value to denve a spectrum tor the maxunum peak-to- peak value 14 The data collector ot claun 13 whereui said frequency transtomiation is α Fast Fourier Transtoπii 15 The data coOector of claim 1 whereui said digital signal processmg circuit comprises a software programmable processor pertoπnuig a soft ai e-defincd signal processmg proceduie 16. A method of detectmg and quantifymg lugh frequency energy ui a received vibration signal, compnsuig convertmg said vibration signal to a digitized vibration signal at a sampung rate that is sufficient to reproduce a highest frequency ot mterest in said vibration signal, and receivmg said digitized vibration signal, isolating lugh frequencv pulses the digitized v ibration signal, and processmg said lugh frequency pulses to quantify energy content of the isolated pulses 17 The method of claun 16 wherein quantifying energy content ot isolated pulses comprises detecting α maximum peak-to-peak amplitude ot said digitized vibration signal. 18 The method of claun 17 whereui detectmg a peak-to-peak amplitude ot said digitized vibration signal comprises comparing a cui τeιιt sample ot said digitized vibration signal to a peak value, and when the excursion ot said cuirent sample from zero exceeds said peak value, updatmg said peak value to be equal to said cuirent sample. 19. The method of claim 18 wherein said peak value is a peak negative value and a peak-to-peak amphtude of said digitized vibration signal is detected by comparing a maximum peak-to-peak value to a difference between said cuirent sample and said peak negative value, and if the difference is larger, updating said maxunum peak-tυ-peak value 20. The method of claim 18 further comprising periodicaOy reducing said peak value of said digitized vibration signal by a factor such that said peak value decays over time. 21. The method of claim 20 further comprising responding to user input to alter said factor, whereby quantification of liigh frequency energy content can be adapted to frequency characteristics of said vibration signal. 22. The method of claim 21 further comprising obtaining said factor from a storage location, and permitting a user to define said factor and store said factor in said storage location. 23. The method of claim 17 further comprising periodically reducing said maximum peak-to-peak amplitude of said digitized vibration signal by a factor such that said maximum peak-to-peak amphtude decays over time. 24. The method of claim 23 further comprising responding to user input to alter said factor, whereby quantification of liigh frequencv energv content can be adapted to frequency characteristics of said vibration signal. 25. The method of claim 24 further comprising obtaining said factor from a storage location, and permitting a user to define said factor and store said factor in said storage location. 26. The method of claim 17 further comprising storing aid maximum peak-to-peak value in a storage device. 27. The method of claim 17 further comprising displaying said maximum peak-to-peak value on said display. 28. The method of claim 17 further comprising perfoπning a frequencv transfoπiiation upon the maximum peak-to-peak value to derive a spectrum for the maximum peak-to-peak value. 9. The method of claim 28 w herein said frequency transfoπnation a Fast Fourier Transfoim

Inventors: STOUTENBURG DONN V, XU MING, STOUTENBURG, DONN, V., XU, MING
Applicants: ENTEK IRD INTERNAT CORP, ENTEK IRD INTERNATIONAL CORPORATION
Application year: 2000
Main classification: G01M7
IPC codes: G01M7