• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The invention relates to a method (100) for symptom identification of malfunctions of at least one power tool (1), wherein during a malfunction of the power tool (1) detected sounds (2A) produced by the power tool (1) of at least one microphone (3) at least occasionally, wherein the detected sounds (2A) after commissioning, by operating and / or controlling a user interaction system (4), are led to a signal processing system (5) and the sounds (2A) are received by the signal processing system (5) via the microphone (3). ) as audio signals (2B), and the sounds (2A) are subjected to an error diagnosis in such a way that the received audio signals (2B) and / or the data extracted from the audio signals (2B) are then transmitted to an error identification system (6), the error identification system (6) uses only those received audio signals (2B) and / or only these data extracted from the audio signals (2B), to perform an automatic tuning with at least one database (7) stored reference audio signals and / or data extracted from the reference audio signals, to perform an error classification of the malfunction of the power tool (1). (Fig. 1)
    公开号:SE1550469A1
    申请号:SE1550469
    申请日:2015-04-20
    公开日:2015-10-26
    发明作者:Florian Brucker；Nghia Dang Duc
    申请人:Bosch Gmbh Robert；
    IPC主号:
    专利说明:

    Based on this, it is therefore the object of the present invention to state, inter alia, a method for symptom identification of malfunctions of at least one power tool, which in a surprisingly simple way automatically enables a classification and location of the malfunction of a power tool and moreover such a method and such a device is not only cost-effective, but can also in particular be carried out especially operating car.
    This object is solved by the object according to claim 1.
    In order now to provide a method for symptom identification of malfunctions of at least one power tool, which in a particularly simple manner enables a classification and / or location of the malfunction of the power tool, the invention described here uses, inter alia, the idea that in the method described here during a malfunction of the power tool, the sounds produced by the power tool at least occasionally through at least one microphone. For example, the microphone is an acoustic microphone which receives sound waves.
    In a next step, after activating and / or controlling a user interaction system, the sounds detected by the microphone are passed through a signal processing system and received by the signal processing system via the microphone as audio signals. In other words, the microphone thus converts the sounds through mathematical / electrotechnical algorithms into audio signals and transports these further to signal processing systems. In particular, the signal processing system may be a structural element, which can be used as a compact, i.e. one-piece kit in a larger kit.
    In a next step, the sounds and the audio signals converted to audio signals by the signal processing system and / or by the microphone and / or data extracted from the audio signals, such as frequency profiles, may be misdiagnosed in such a way that, in particular, only the received audio signals and / or, in particular only, data extracted from the audio signals, such as frequency profiles, are then transmitted to a system for error identification, in particular starting from the signal processing system. In particular, it is conceivable that the audio signals, which are received and / or generated by the signal processing system, are further processed within the signal processing system itself.
    In this context, it is further conceivable that these data processed by the signal processing system together with additional information specified by the user and / or evaluation conditions are sent to the system for error identification. It is conceivable that the error identification system is spatially separated from the signal processing system. Namely, it is conceivable that the system fault identification is integrated in a computer network, for example a cloud-based network. In addition, the fault identification system can be stored in a cloud-compatible central server.
    It is crucial that only these received audio signals and / or only data extracted from these audio signals are used by the error identification system, to perform an automatic tuning with reference audio signals stored in at least one database and / or data extracted from these reference audio signals, in order to perform a misclassification of the power tool malfunction. In other words, an audio tuning instead of at the audio level can take place in whole or in part at a level of the extracted data.
    In other words, the error identification system uses the information stored in the database in connection with the automatic tuning described here, to enable a classification of the error type corresponding to the audio signal (in some circumstances taking into account the additional information entered by the user). To that extent, in a particularly advantageous manner, by means of the method described here, all the sources of error can be detected, identified and / or located, the behavior of which is simultaneously connected with an acoustic signal effect. During the recording of the sounds, the symptoms can be described exactly as characteristic features of malfunctions and the malfunctions associated with the special symptoms can be unambiguously identified. In particular, it may already be sufficient to provide a single microphone as an acoustic detector, in order to detect a number of malfunctions which prove to be acoustic. A larger number of special physical sensors, usually requiring a sensor for each operating function intended for monitoring, is no longer necessary.
    In addition, through the user interaction system described here, the method can be activated manually by a user of the power tool, for example for a predetermined time.
    Thus, when an unknown or intuitive sound associated with a malfunction occurs, the user starts the process, that is, the sounds are first detected.
    After the activation of the analysis process by the system of the user interaction, for example a touch screen or another input device, the method is automatically activated when sound unknown to the fault-free operation occurs for a predetermined time.
    For this purpose it is thus necessary that known sound scenes and / or extracted audio signals and / or data extracted from these audio signals regarding individual parts of the power tool, which correspond to a normal operation, are stored in a memory, i.e. in the database described here. Thus, when deviating the, for example, continuously monitored sounds from the reference audio signal stored in the database, the method can automatically, i.e. without separate external influence or setting, determine the type and / or the location of the fault on the power tool. Preferably, the error identification system displays the result of the error classification to the user interaction system, i.e. a result can be communicated optically and / or acoustically to the user of the user interaction system, which may for example comprise a monitor.
    In addition, it is conceivable in the method described here and the device for symptom identification of malfunctions described here, that at least one power tool can be brought into active connection with a number of different power tools, however, the method described here and the device described here are particularly suitable for only find use in power tools. Namely, it has been found that the method described here and the device described here in particular compact and space-saving can not only be built on or the power tools, but also that the systems described here can be adapted to user interaction and for misidentification to the concrete properties of the power tools. This may mean that the method described here and the device described here are unsuitable for carrying out an error diagnosis, for example in motor vehicles. For the use of the method described here and the device described here, for example in such motor vehicles, further conversion work and adaptations to individual systems are required, which are admittedly absolutely conceivable to carry out, however, the method described here and the device described here in particular suitable for determining malfunctions of power tools.
    According to at least one embodiment, the method for symptom identification of malfunctions comprises a first step, after which during a malfunction of the power tool generated sounds are detected by at least one microphone at least occasionally, the detected sounds in a next step after commissioning, by operating and / or controlling a system for user interaction, the sounds are received as audio signals by a signal processing system by a signal processing system via the microphone.
    The sounds may then be misdiagnosed in such a way that, in particular only, the received audio signals and / or, in particular only data extracted from the audio signals, such as frequency profiles, are then transferred to an error identification system, the error identification system only using these received audio signals and / or data extracted only from the audio signals, to perform an automatic tuning with reference audio signals stored in at least one database and / or data extracted from these reference audio signals, in order to carry out a misclassification of the malfunction of the power tool. It goes without saying that the data data extracted from the reference audio signals can also be stored in a database.
    According to at least one embodiment, an error classification of the audio signals is based on at least one analysis algorithm, which is stored in the error identification system and / or in the database, whereby the analysis algorithm performs a division and / or location of the error function of the power tool. To that extent, it is possible to use the analysis algorithm not only to process and divide the received audio signals and preferably processed by the signal processing system and / or data extracted from the audio signals into, for example, different error categories and / or locations of the power tool, but also by the analysis algorithm. once again, for example, processing, categorizing and / or further dividing the audio signals into different oscillation components, in particular with respect to their frequency spectrum and / or phase spectrum of the signals. To that extent, the analysis algorithm described here allows in a particularly reliable manner not only a determination of whether there is actually a malfunction of the power tool, but also allows, for example, the determination of the severity of the malfunction and / or an exact statement of the design component of the power tool. . It is also conceivable that in order to identify a malfunction, the audio signals analyzed and categorized by the analysis algorithm must exceed a limit value (in English: threshold), from which there is in fact an unacceptable malfunction. If a malfunction is actually determined, it is conceivable that by means of the fault identification system and / or the other systems of the device described here or the method described here, automatically and / or by the user (after issuing a warning signal) switch off the power tool. A risk of the user injuring himself is thus minimized.
    According to at least one embodiment, the microphone, the user interaction system, the signal processing system and / or the error identification system are built into at least one mobile, preferably internet-compatible terminal. In particular, the terminal may be, for example, a tablet PC and / or a mobile phone.
    Should a symptom identification of possible malfunctions be carried out on the power tool, it is thus conceivable that the power tool is brought into a near field identification area of the mobile terminal, so that the microphone to the mobile terminal during operation of the power tool, i.e. during the stay of the mobile terminal in the vicinity of the power tool. occupies the light stage and thus in a particularly simple manner makes it possible for a device for error identification to be built into at least a partially mobile, preferably Internet-compatible terminal.
    Namely, it is conceivable that after a recording of the soundstage and a conversion of the sounds into audio signals of the fault identification system, which preferably, as already mentioned above, may likewise be built into such a terminal, transmit these with a WLAN line, which in in particular should also be Internet-compatible, to an externally arranged and stored database, in order to be able to carry out the final fault classification of a possible malfunction of the power tool.
    Such a mobile system is thus particularly suitable for a very far-reaching and as far as possible unlimited use of a large number of different power tools, which can be positioned in different places.
    According to at least one embodiment, the data bank is stored in at least one central server.
    The central server may be such a server, which is part of a cloud-based network. To this extent, there is talk of a "cloud-based diagnosis" regarding the positioning of the data bank in the central server. In this case, it is necessary that the total device is supplemented with Internet-compatible means of communication. This may mean that the microphone, the user interaction system, the signal processing system and / or the error identification system are at least partially internet compatible, so that a computer network, for example a cloud-based network, can be created through the overall device.
    According to at least one embodiment, result data of the error classification are stored in the database, and these results are used for time and / or fall dynamic adaptation of the analysis algorithm. In such an embodiment, the insights obtained from the result data are thus also stored in a data bank and can be used to, for example, update the analysis algorithm described here. Thus, one speaks in professional jargon about "online learning".
    "Time dynamic adaptation" means an adaptation of the analysis algorithm, for example depending on an operating time of the power tool and / or an operating time of the device for symptom identification of malfunctions of the power tool. A "fall dynamic adaptation" is such an adaptation of the analysis algorithm. however, for example, includes a counter, which calculates how often a procedure for symptom identification of malfunctions has already been performed on the available power tool. In other words, a fall dynamic adaptation is such an adaptation, in which, for example, a counter system is integrated in the device, which includes the implementation of the method described here on the available power tool.
    Namely, it is conceivable that the method described here and the device for symptom identification of malfunctions described here are assigned to several power tools and can be carried out on several power tools. In addition, the device described here may comprise an identification means, by means of which the existing power tool can be identified, so that with respect to the currently identified power tool such a counter position and / or a time dynamic adaptation of the algorithm is performed.
    According to at least one embodiment regarding the result data data of the fault classification as mentioned, it is possible that the device described here and the method described here have means which can uniquely identify the power tool and based on the characteristics of the power tool a corresponding analysis program is introduced. corresponding to the analysis algorithm, which is unambiguously, preferably bijectively, assigned to the power tool. Thus, after the introduction, the method described here, and the device described here, respectively, are provided with data operation history for the past time. In other words, the device described here can perform a diagnosis with the data operation history regarding the power tool to be examined (eg by reconciliation with the central data bank) and can update this service history corresponding to the diagnosis.
    In this case, the user can be presented with useful information (eg contact data for the service employee responsible for maintenance, the period of validity of the guarantee, the possibility of direct initial contact, etc.).
    In particular, the microphone, the user interaction system, the signal processing system and / or the error identification system may be in data communication with a Global Positioning System.
    According to at least one embodiment, the signal processing system processes the audio signals before the forwarding to the error identification system by means of at least one data and / or algorithm filter. Such an approach thus enables, in a particularly time-saving manner, that the error identification system can analyze the thus processed audio signals particularly quickly, easily and inexpensively, without such additional data and / or algorithm filters first having to be integrated in a demanding manner into the system itself. fault identification. In other words, this enables the use of an error identification system, which has in general and not in particular means of analysis configured for the power tool and / or the signal processing system. The audio signals processed by the signal processing system are in fact passed on in a particularly general and easily decoding form to the system for error identification.
    According to at least one embodiment, by means of the user interaction system and / or at least one further interface, ape-type parameters for the power tool are entered, the apparatus-typical parameters being unambiguously assigned to the corresponding fault classification and / or a power tool. For example, in the case of the device-typical parameter, it is a type number of the power tool and / or a product designation of the power tool, which enables the system for using the interaction to uniquely identify this power tool.
    In addition, the invention described herein relates to a device for symptom identification of malfunctions of at least one power tool. In this case, the device described here for symptom identification of malfunctions of at least one power tool has the same designs and advantages as the method described here. That is, the criteria presented for the procedure described herein also apply to the device described herein and vice versa.
    According to at least one embodiment, the device described here comprises at least one microphone, which is designed and configured to at least occasionally detect the sounds generated by the power tool during a malfunction of the power tool, the detected sounds after commissioning of the device, by operating and / or controlling a system for user interaction, through a system for signal processing can be received via the microphone as an audio signal.
    The sounds are then subjected to an error diagnosis in such a way that the received audio signals and / or data extracted from the audio signals are then transferable to an error identification system, the error identification system being configured to use only these received audio signals, to perform an automatic tuning with the at least one database stored the reference audio signals and / or data extracted from the 10 reference audio signals, in order to perform a misclassification of the tool.
    In this case, the device described here has, as mentioned above, the same advantages and individual designs in connection with the method described here.
    In the following, the method described here as well as the device described here for symptom identification of a malfunction will be further elucidated with the aid of an exemplary embodiment and the associated figures.
    Fig. 1 is a schematic view of an embodiment of a method described here and a device described here.
    In the exemplary embodiment and the figure, identical or similarly functioning components are in all cases provided with the same reference numerals. The elements shown here are not illustrated in proper proportions, rather the individual elements may be excessively large for better understanding.
    In Fig. 1, by means of a schematic representation, an embodiment of a device 101 described here for symptom identification of malfunctions of a power tool 1 is shown.
    The device described here comprises a microphone 3, a system for user interaction 4, a system for signal processing 5, a system for error identification 6 and a database 7.
    In this case, a user in a first step causes the start of the diagnostic functionality via the system for user interaction 4. In this case, the system may contain at least one interface, with which the user can optionally enter additional information (eg device type, serial number).
    In a next step, the signal processing system 5 receives the sounds 2A output from the test tool 1 to be examined, which are converted by the microphone to 11 corresponding audio signals 2B, processing them by appropriate filtering and criteria extraction. In the next step, these processed audio signals and / or data extracted from the audio signals are thus sent by the signal processing system 5 (in some circumstances together with additional information specified by the user) to the error identification system 6.
    The error identification system 6 uses the information stored in a database 7 in conjunction with a suitable mathematical model for classifying the error type (in certain circumstances taking into account additional information specified by the user) corresponding to the audio signal 2B. Regarding the suitable mathematical model for classifying the audio signal 2B, this may in particular be an analysis algorithm, which is first and foremost adapted to the special power tool 1 and / or may also be focused and set on one with respect to one specially designed for the user. as a significantly important field type.
    Result data 2C regarding the error classification is stored in the database 7 and can also be used to dynamically adapt and update (in English: online-learning) the analysis algorithm.
    The error identification system 6 then sends result data and / or data regarding the error classification to the user interaction system 4, which may for example be a display screen.
    The different (sub) systems do not necessarily have to be located on the same physical device. It is conceivable, for example, to have a division into a handheld device (eg a smartphone plus the corresponding "app") and a central server for automatic analysis ("computer-based diagnosis"). In this case, it is advantageous if the total system is supplemented with suitable means of communication (eg internet compatibility) (as they are, for example, available as standard in a smartphone). 12 The diagnostic result can optionally be evaluated afterwards (eg a service employee after the diagnosis with the system presented here can check the device to be examined for this error and thus determine the correctness of the automatic diagnosis).
    After the diagnostic result has been evaluated (eg via a corresponding functionality in the system of the user interaction 4 and / or in the system for error identification (6), this evaluation is noted in the database 7 and the analysis algorithm, in particular the mathematical model of the analysis algorithm, can be adapted. correspondingly, for example time dynamically.
    However, it is still conceivable that the device 101 described here is equipped with additional optional connections for additional sensors. To the extent that the user connects these additional sensors before the diagnosis, their signals can also be used for diagnosis.
    However, such sensors are to be understood only as being completely optional and constitute only a further advantageous embodiment of the invention described herein.
    It is also conceivable that the system for fault identification described here connects a diagnosis with a data operating history for the power tool 1. Such a service prehistory can be performed with the audio signals by a reconciliation with the central database 7, so that the service history during the diagnosis also corresponds to can be adapted and updated. In this case, the user is presented with useful information (eg contact data for the service employee responsible for maintenance, the period of validity of the guarantee, the possibility of direct initial contact, etc.).
    To the extent that parts of the system can be operated on a smartphone-like platform, the system may in certain circumstances, and with the user's consent, also use additional functions and transmitter signals. Namely, it is conceivable that the microphone 3, the system for using interaction 4, the system for signal processing 5 and / or the system for error identification 6 are in data communication with a Global Positioning System (GPS), so that the exact location can always be determined for the one described here. the device 101 for fault diagnosis as well as for the power tool 1. For example, on a mobile terminal, i.e. the 13 smartphone, on which all systems of the device 101 with the exception of the data bank can be integrated and built-in, the nearest service workshop for the test the device, i.e. the power tool 1, is indicated, or the communication functions of the said smartphone can be used to get in touch with a service employee (eg via call, SMS, e-mail, etc.).
    Thus, as has already been mentioned several times above, the invention described here has the particular advantages which can be seen in the fact that the device 101 described here, in addition to at least one microphone 3, does not require any additional sensor signals. In particular, neither a body sound sensor nor a gyrometer is absolutely necessary.
    In doing so, the system not only detects the fact that a defect is present, but classifies the fault automatically and can also immediately locate it locally on the power tool 1.
    After the system has been put into operation, the internal data bank can thus also be updated automatically and the mathematical models (ie the analysis algorithm) for error diagnosis adjusted accordingly. An evaluation of the automatic diagnosis afterwards is, however, also conceivable, so that the system is thus particularly adaptable and can improve its capacity in the day-to-day operation.
    If a central database 7 is used, it can automatically use a central repository of already stored reference audio signals and / or data extracted from reference audio signals for diagnostic purposes, in order to diagnose errors. This information can then be evaluated at a later time for statistical purposes.
    The invention is not limited by the description with the aid of the exemplary embodiments and the figure. Rather, the invention encompasses any new feature as well as any combination of features, which in particular includes any combination of features in the claims, even when this feature or this combination itself is not expressly stated in the claims or in the embodiments. 14 List of reference numerals 2A 2B OONOÄUI-bUU 100 101 power tools sound audio signals result data microphone system use interactions signal processing system error identification system database central server procedure for symptom identification of malfunctions device for symptom identification of malfunctions
    权利要求:
    Claims (10)
    [1]
    Method (100) for symptom identification of malfunctions of at least one power tool (1), characterized in that - during a malfunction of the power tool (1) the sounds (ZA) generated by the power tool are detected by at least one microphone (3) at least occasionally, - the detected sounds (ZA) after commissioning, are guided by operation and / or control of a user interaction system (4), to a signal processing system (5) and the sounds (ZA) are received by the signal processing system (5) via the microphone (3). ) as audio signals (ZB), - the sounds (ZA) may be misdiagnosed in such a way that, in particular only, the received audio signals (ZB) and / or, in particular only, data extracted from the audio signals (ZB) are then transmitted to an error identification system (6), wherein - the error identification system (6) uses only those received audio signals (ZB) and / or only these data extracted from the audio signals (ZB), to effect an automatic tuning with at least e n data bank (7) stored reference audio signals and / or data extracted from the reference audio signals, in order to carry out an error classification of the malfunction of the power tool (1).
    [2]
    Method according to claim 1, characterized in that the error classification of the audio signals (ZB) is based on at least one analysis algorithm, which is stored in the system for error identification (6) and / or in the database (7), wherein by the analysis algorithm a division is performed and / or locating the malfunction of the power tool (1).
    [3]
    Method according to claim 1 or Z, characterized in that the microphone (3), the user interaction system (4), the signal processing system (5) and / or the error identification system (6) are built into at least one mobile, preferably the Internet. compatible, terminal. 16
    [4]
    Method according to one of the preceding claims, characterized in that the data bank (7) is stored in at least one central server (8).
    [5]
    Method according to one of the preceding claims, characterized in that the result data (ZC) of the error classification are stored in the data bank (7), and these results are used for time and / or fall dynamic adaptation of the analysis algorithm.
    [6]
    Method according to one of the preceding claims, characterized in that the result data (ZC) of the error classification are reconciled with a data operating history of the power tool (1) -
    [7]
    Method according to one of the preceding claims, characterized in that the microphone (3), the user interaction system (4), the signal processing system (5) and / or the error identification system (6) are in data communication with a Global Positioning System (GPS). .
    [8]
    Method according to one of the preceding claims, characterized in that the signal processing system (5) processes the audio signals (2B) before they are passed on to the error identification system (6) by means of at least one data and / or algorithm filter.
    [9]
    Method according to one of the preceding claims, characterized in that by means of the user interaction system (4) and / or at least one further interface, device-typical parameters are entered for the power tool (1), the device-typical parameters being unambiguously assigned to the corresponding fault classification and / or power tool. . 17
    [10]
    Method (100) for symptom identification of malfunctions of at least one power tool (1), characterized in that at least one microphone (3), which is designed and intended to detect those of the power tool (at least temporarily) during a malfunction of the power tool (1) 1) the generated sounds (ZA), the detected sounds (2A) after the commissioning of the device (101), are guided by operating and / or controlling a system for user interaction (4), to a system for signal processing (5) and the sounds (2A ) can be received via the microphone (3) as audio signals (2B), and the sounds (2A) may be misdiagnosed in such a way that, in particular only, the received audio signals (2B) and / or, in particular only, from the audio signals ( 2B) extracted data is then transmitted to an error identification system (6), the error identification system (6) being configured to use only those received audio signals (2A) and / or only these data extracted from the audio signals (2B), to establish an automatic tuning with reference audio signals stored in at least one database (7) and / or data extracted from the reference audio signals, in order to carry out a misclassification of the malfunction of the power tool (1).
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    法律状态:
    优先权:
    申请号 | 申请日 | 专利标题
    DE102014207784.2A|DE102014207784A1|2014-04-25|2014-04-25|Method for symptom detection of malfunction of a power tool|
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