# US 11,906,956 B2 · Monitoring device and monitoring method for detecting a diagnostic state > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,906,956 B2 - Document ID: US11906956B2 - Status: Granted - Kind: B2 - Application number: 17/877,645 - Filed: 2022-07-29 - Published: 2023-02-16 - Granted: 2024-02-20 - Earliest claimed: 2021-08-02 - Assignees: Pruftechnik Dieter Busch AG - Applicants: Prüftechnik Dieter Busch GmbH - Inventors: Dietrich Brunn; Jan Germer - Web page: https://patentgrep.com/patent/US11906956B2 ## CPC - G05B 19/4065: Monitoring tool breakage, life or condition - G05B 23/0221: {Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods} - G01H 1/00: Measuring {characteristics of} vibrations in solids by using direct conduction to the detector (G01H9/00, G01H11/00 take precedence) - G01H 1/003: {of rotating machines (G01H1/10 takes precedence)} - G01H 3/04: Frequency - G01H 3/10: Amplitude; Power - G01M 13/028: Acoustic or vibration analysis - G01M 13/045: Acoustic or vibration analysis - G05B 19/4183: {characterised by data acquisition, e.g. workpiece identification} - G05B 23/0235: {based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold} - G05B 2219/37351: Detect vibration, ultrasound - G05B 2219/37435: Vibration of machine - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G01H: MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES - G01M: TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR ## Abstract A monitoring device for detecting a diagnostic state of an industrial machine on the basis of vibrations associated with the industrial machine, includes at least one measurement transducer for detecting at least one first signal characterizing the vibration of the industrial machine in a time period and for detecting at least one second signal characterizing the vibration of the industrial machine in the same time period, wherein the at least one measurement transducer has at least one signal processor for evaluating the at least first signal as a first characteristic value and for evaluating the at least second signal as a second characteristic value and wherein the at least one first characteristic value and the at least one second characteristic value form a characteristic value tuple, further having a storage unit, in which different diagnostic states describing the state of the industrial machine are saved, wherein the diagnostic states are determined as a function of the characteristic value tuple, and a predefined scalar range is saved with predetermined different fixed scalar values, which define respectively an existing limit potential, wherein a respective limit potential characterizes a change in the diagnostic state, and wherein between adjacent limit potentials a diagnostic partition is formed and wherein different scalar values from the scalar range are assigned to the different diagnostic partitions and wherein different respective diagnostic partitions represent different diagnostic states of the industrial machine, and wherein the monitoring device has at least one interpolation function for mapping the characteristic value tuple on a common, unique, time-dependent scalar value in the predefined scalar range, so that by way of the time-dependent scalar value a time monitoring of the diagnostic state of the industrial machine is achieved. ## Claims ### Claim 1 A monitoring device for determining a diagnostic state of an industrial machine, comprising: at least one measurement transducer for generating at least one first signal characterizing a vibration of the industrial machine in a time period and for generating at least one second signal characterizing the vibration of the industrial machine in the same time period, wherein the at least one measurement transducer has at least one signal processor for evaluating the at least one first signal as a first characteristic value and for evaluating the at least one second signal as a second characteristic value, and wherein the first characteristic value and the second characteristic value form a characteristic value tuple, the monitoring device further comprising a storage unity in which different diagnostic states describing a state of the industrial machine are saved, wherein the different diagnostic states are determined as a function of the characteristic value tuple, and a predefined scalar range is saved with predetermined different fixed scalar values which define respectively an existing limit potential, wherein a respective limit potential characterizes a change in the diagnostic state of the industrial machine, wherein between adjacent limit potentials a diagnostic partition is formed, and wherein different scalar values from the predefined scalar range are assigned to different diagnostic partitions, and wherein the different diagnostic partitions respectively represent the different diagnostic states of the industrial machine, and wherein the monitoring device further comprises at least one interpolation function, the monitoring device being configured to use the at least one interpolation function to map the characteristic value tuple onto a common unique, time-dependent scalar value in the predefined scalar range, so that by way of the time-dependent scalar value a time-dependent monitoring of the diagnostic state of the industrial machine is achieved. ### Claim 2 (depends on 1) The monitoring device according to claim 1, wherein respective adjacent diagnostic partitions represent, with respect to criticality, consecutive diagnostic states of the industrial machine, and wherein the consecutive diagnostic states are formed at least in ascending order in a sequence of states including a false measurement, a good state, a warning state, and an alarm state. ### Claim 3 (depends on 2) The monitoring device according to claim 2, wherein a value of the time-dependent scalar value increases with respect to a criticality of the sequence of states. ### Claim 4 (depends on 1) The monitoring device according to claim 1, wherein the monitoring device is further configured, in the presence of at least one characteristic value tuple which corresponds to a change between the diagnostic states, to map the at least one characteristic value tuple to a corresponding limit potential unique to the change between the diagnostic states. ### Claim 5 (depends on 4) The monitoring device according to claim 4, wherein a plurality of potentials with intermediate sub-partitions are assigned to a respective diagnostic partition, wherein a potential is uniquely assigned to a predetermined scalar value and wherein the monitoring device is configured to map, in the presence of at least one characteristic value tuple which indicates a change between the sub-partitions, the at least one characteristic value tuple to the corresponding scalar value uniquely associated with the change between the sub-partitions. ### Claim 6 (depends on 1) The monitoring device according to claim 1, wherein the monitoring device has a plurality of interpolation functions and is further configured to select the at least one interpolation function as a function of the characteristic value tuple. ### Claim 7 (depends on 6) The monitoring device according to claim 6, wherein the interpolation functions are assigned to the different diagnostic partitions, wherein the monitoring device is further configured to map, in the presence of at least one characteristic value tuple which lies within one diagnostic partition of the diagnostic partitions, the at least one characteristic value tuple to a unique scalar value by the interpolation function assigned to the one diagnostic partition. ### Claim 8 (depends on 7) The monitoring device according to claim 7, wherein a respective diagnostic partition is assigned a plurality of potentials with sub-partitions in between, wherein the interpolation functions are assigned to different sub-partitions, wherein the monitoring device is further configured, in the presence of at least one characteristic value tuple which lies within one sub-partition of the sub-partitions, to map the at least one characteristic value tuple by the interpolation function assigned to the sub-partition to the unique scalar value. ### Claim 9 (depends on 1) The monitoring device according to claim 1, wherein an aggregating unit is provided for aggregating first characteristic values and second characteristic values determined during the time period as characteristic value tuple and coupling the characteristic value tuple to the time period. ### Claim 10 (depends on 1) The monitoring device according to claim 1, wherein the at least one measurement transducer is configured to generate periodically the at least one first signal and the at least one second signal in consecutive time periods. ### Claim 11 (depends on 10) The monitoring device according to claim 10, wherein a trigger unit is provided, which triggers the at least one measurement transducer, in order to generate the at least one first signal and the at least one second signal in the consecutive time periods. ### Claim 12 (depends on 1) The monitoring device according to claim 1, wherein the at least one measurement transducer is a piezoelectric vibration transducer. ### Claim 13 (depends on 1) The monitoring device according to claim 1, wherein a plurality of measurement transducers are provided respectively with a signal processor for detecting the at least one first signal and the at least one second signal characterizing the vibration of the industrial machine. ### Claim 14 (depends on 1) The monitoring device according to claim 1, wherein the at least one measurement transducer is configured to generate the at least one first signal and the at least one second signal characterizing the vibration of the industrial machine and to generate further signals characterizing vibrations of the industrial machine and evaluate as a plurality of characteristic values. ### Claim 15 A monitoring method for determining a diagnostic state of an industrial machine, comprising: providing at least one measurement transducer for generating at least one first signal characterizing a vibration of the industrial machine in a time period and for generating at least one second signal characterizing the vibration of the industrial machine in the same time period, providing the at least one measurement transducer with at least one signal processor for evaluating the at least one first signal as a first characteristic value and for evaluating the at least one second signal as a second characteristic value, wherein the first characteristic value and the second characteristic value form a characteristic value tuple, providing a storage unit in which different diagnostic states describing a state of the industrial machine are saved, wherein the different diagnostic states are determined as a function of the characteristic value tuple, and a predefined scalar range is saved with predefined different fixed scalar values which define respectively an existing limit potential, wherein a respective limit potential characterizes a change in the diagnostic state of the industrial machine, wherein between adjacent limit potentials a diagnostic partition is formed, and wherein different scalar values from the predefined scalar range are assigned to different diagnostic partitions, wherein the different diagnostic partitions respectively represent different diagnostic states of the industrial machine, and by way of at least one interpolation function, mapping the characteristic value tuple onto a common, unique, time-dependent scalar value in the predefined scalar range, so that by way of the time-dependent scalar value a time-dependent monitoring of the diagnostic state of the industrial machine is achieved. ### Claim 16 (depends on 15) The monitoring method according to claim 15, wherein the respective adjacent diagnostic partitions represent, with respect to criticality, consecutive diagnostic states of the industrial machine and wherein the consecutive diagnostic states are formed at least in ascending order as a false measurement, a good state, a warning state, and an alarm state. ### Claim 17 (depends on 15) The monitoring method according to claim 15, wherein in the presence of at least one characteristic value tuple which corresponds to a change between the diagnostic states, the at least one characteristic value tuple is mapped onto a corresponding scalar value unique to a limit potential associated with the change between the diagnostic states. ### Claim 18 (depends on 17) The monitoring method according to claim 17, wherein a diagnostic partition is assigned a plurality of potentials with sub-partitions lying in between, wherein a potential is assigned uniquely to a predefined scalar value and in the presence of at least one characteristic value tuple which specifies a change between the sub-partitions, the at least one characteristic value tuple is mapped to the corresponding scalar value unique to the change between the sub-partitions. ### Claim 19 (depends on 15) The monitoring method according to claim 15, further comprising providing a plurality of interpolation functions and selecting the at least one interpolation function as a function of the characteristic value tuple, wherein the interpolation functions are assigned to the different diagnostic partitions, and in the presence of at least one characteristic value tuple which lies within one diagnostic partition of the diagnostic partitions, mapping the at least one characteristic value tuple to a unique scalar value by the interpolation function assigned to the one diagnostic partition. ### Claim 20 (depends on 19) The monitoring method according to claim 19, wherein a plurality of potentials are assigned to a respective diagnostic partition with sub-partitions in between, wherein the interpolation functions are assigned to different sub-partitions, wherein in the presence of at least one characteristic value tuple which lies within one sub-partition of the sub-partitions, the at least one characteristic value tuple is mapped to the unique scalar value by the interpolation function assigned to the one sub-partition.