A device for determining the soundness of construction machinery.

Abstract

To propose a device that obtains a more accurate diagnostic result without depending on a voice signal in determining the soundness of construction machinery.SOLUTION: A device determining the soundness of construction machinery comprises an operation unit. The operation unit measures vibration of the construction machinery through an accelerometer, determines a weight class of the construction machinery on the basis of the vibration, measures a result of a machine operation of the construction machinery, and on the basis of the weight class and the result of the machine operation, determines the soundness of the construction machinery.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to an apparatus for determining the soundness of construction machinery.

Background Art

[0002] Regarding construction machinery, it is important to measure its basic performance, diagnose and predict potential failures in advance, perform maintenance before failures, and avoid construction interruptions. The basic performance refers to the original performance and specifications of the construction machinery. In this regard, in the market, as a tool for automatic self-diagnosis of failures (automatic self-diagnosis tool), it is required to be easy to use by unskilled personnel, inexpensive, and easy to operate.

[0003] For example, Patent Document 1 discloses, as an automatic self-diagnosis technique, in order to shorten the diagnosis time, based on the operating sound of construction machinery, the presence or absence of abnormalities in each part of the construction machinery is diagnosed, and when an abnormality is diagnosed, the cause of the abnormality is specified based on the information of the abnormal diagnosis part, and the specified result is displayed.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In the conventional technology, there is a technology that uses audio signals, but in such a technology, the measurement accuracy depends on the arrangement of audio sensors (microphones, etc.).

[0006] Also, in the conventional technology, it is required that the user correctly input the weight class of the construction machinery, but if this input is incorrect, a correct diagnosis cannot be made.

[0007] In light of these circumstances, this disclosure proposes a technology that does not rely on audio signals and that can obtain more accurate diagnostic results. [Means for solving the problem]

[0008] To address the above issues, an example of this disclosure is: A device for determining the soundness of construction machinery, The device comprises a calculation unit, The aforementioned arithmetic unit, - The vibration of the construction machine is measured via an accelerometer, - Based on the vibrations, the weight class of the construction machine is determined. -Measure the results of the mechanical operation of the construction machine, - The soundness of the construction machine is determined based on the weight class and the results of the machine operation.

[0009] Further features relating to this disclosure will become apparent from the description herein and the accompanying drawings. Furthermore, aspects of this disclosure are achieved and realized by elements and various combinations of elements and the aspects of the hereafter detailed description and the accompanying claims.

[0010] The descriptions herein are typical examples only and do not limit in any way the claims or applications of this disclosure. [Effects of the Invention]

[0011] The technology disclosed herein is independent of audio signals and can provide more accurate diagnostic results. [Brief explanation of the drawing]

[0012] [Figure 1] A diagram showing a schematic configuration example of a construction machinery diagnostic system according to one embodiment of the present disclosure. [Figure 2] A block diagram showing an example of the schematic functional configuration of the processor 10 according to this embodiment. [Figure 3] A diagram showing an example of the internal function configuration of the information acquisition unit 101 of the performance measurement device 1. [Figure 4]A diagram showing an example of the internal functional configuration of the weight classification unit 102 of the performance measurement device 1. [Figure 5] An example of the scale of noise vibration. [Figure 6] A diagram showing an example of the internal functional configuration of the operation classification unit 103 of the performance measurement device 1. [Figure 7] An example of the waveform of an acceleration signal corresponding to various operations of the same construction machine. <00​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​ [Figure 19] An example of a user interface displayed on the display screen of the performance measurement device 1 or the display screen of the user terminal 4. [Figure 20] A flowchart illustrating the performance measurement and diagnostic process according to this embodiment. [Modes for carrying out the invention]

[0013] <Example System Configuration> Figure 1 shows a schematic configuration example of a construction machinery diagnostic system (a device for determining the soundness of construction machinery) according to one embodiment.

[0014] The construction machinery diagnostic system comprises a performance measurement device 1, a sensor group 2, and a user terminal 4, and diagnoses a construction machine 3. In the system configuration example in Figure 1, the user terminal 4 and the performance measurement device 1 are shown as separate devices, but the user terminal 4 may also implement the functions of the performance measurement device 1 and the data holding / storage units. Also, in the system configuration example in Figure 1, the user terminal 4 and the sensor group 2 are shown as separate devices, but the user terminal 4 may also implement some or all of the sensor group 2.

[0015] The performance measurement device 1 includes, for example, a processor 10, a storage device 20, and a communication device 30.

[0016] Sensor group 2 consists of several different sensors that can be used in construction machinery condition diagnostic applications, and includes, for example, an accelerometer 21. Furthermore, sensor group 2 may include (but is not limited to) a microphone 22 and a camera 23. The accelerometer 21 is a micro-electromechanical system (MEMS) scale sensor that can be incorporated into a device, measuring acceleration with the ability to detect gravity and vibration. The microphone 22 may be a standalone microphone or a miniature microphone built into the performance measuring device 1. The camera 23 may be, for example, a standalone miniature camera or a miniature camera built into the performance measuring device 1 or the user terminal 4.

[0017] Construction machine 3 is a variety of construction machinery, such as a hydraulic excavator, wheel loader, or bulldozer. Construction machine 3 includes an angle sensor 13 that detects the current angle of the movable parts of construction machine 3 (for example, the boom, arm, and bucket in the case of a hydraulic excavator) in real time.

[0018] The user terminal 4 can consist of computer devices such as a smartphone, microcontroller, or personal computer (PC). The microcontroller may also be referred to as a portable controller, control board, etc. Using a smartphone or microcontroller, in particular, improves operator convenience.

[0019] The processor 10, memory device 20, and communication device 30 of the performance measurement device 1, the various sensors of the sensor group 2, and the angle sensor 13 of the construction machine 3 are connected, for example, via the communication device. The communication device 30 is also configured to transmit, for example, diagnostic results wirelessly to the user terminal 4.

[0020] The processor 10 functions as an arithmetic unit. The processor 10 is composed of an arithmetic unit such as a CPU, and generates each processing unit by reading various related programs from the memory device 20 and loading them into internal memory (not shown). Each of these processing units includes an information acquisition unit 101, a weight class classification unit 102, an operation classification unit 103, a health diagnosis unit 104, and a basic performance reporting unit 105. Details of the operation of each process will be described later.

[0021] The memory device 20 includes a weight reference value holding unit 201, a representative waveform holding unit 202 for each operation, a performance reference value holding unit 203, an operating range reference value holding unit 204, a recommendation information holding unit 205, an operation list holding unit 206, and a data storage unit 207.

[0022] The weight reference value holding unit 201 stores, for example, reference values ​​for the magnitude of noise vibration for each weight class, which serve as the basis for classifying the weight class of construction machinery to be newly diagnosed (inspected).

[0023] The operation-specific representative waveform holding unit 202 stores, for example, representative sensor waveform patterns for each machine operation, which serve as a basis for classifying machine operations to be newly diagnosed (inspected).

[0024] The performance reference value holding unit 203 holds (stores) information on the standard values ​​of the healthy state of machine operation to be inspected, as set by the manufacturer. An example of information on the standard values ​​of the healthy state is that the arm pulling operation of a particular construction machine ideally takes 3.9 seconds (or within the range of 3.9 seconds ± 0.4 seconds).

[0025] The operating range reference value holding unit 204 holds (stores), for example, a reference value (standard value) for the operating range of a construction machine. An example of reference value information for the operating range is information such as the boom raising range being from 0 degrees to 90 degrees.

[0026] The recommendation information storage unit 205 stores information on recommendations to be presented to the operator according to the condition of the construction machinery. For example, it may store information such as, "The arm cylinder appears to be malfunctioning. Please show this report to the maintenance department and have them take corrective action."

[0027] The operation list holding unit 206 stores information on all related operations for a specific diagnostic (inspection) type. Examples of operations to be diagnosed include (a) arm pulling, (b) arm pushing, (c) boom raising, (d) boom lowering, (e) bucket excavation, and (f) bucket discharge.

[0028] The data storage unit 207 consists of a storage device and stores various data handled by the performance measurement device 1 (including aggregated sensor data from the information acquisition unit 101).

[0029] <Example of a performance measurement device configuration> Figure 2 is a block diagram showing an example of the schematic functional configuration of the processor 10 according to this embodiment. The main functions of the performance measurement device 1 are realized by the information acquisition unit 101, the weight class classification unit 102, the operation classification unit 103, the health diagnosis unit 104, and the basic performance reporting unit 105.

[0030] The information acquisition unit 101 aggregates sensor data in a predetermined format and prepares it for processing. An example of sensor data is accelerometer data used to detect load vibrations of construction machinery, and an example of a load is an arm.

[0031] The weight class classification unit 102 processes the data acquired from the information acquisition unit 101 and detects, for example, the magnitude of vibration (noise vibration) when the construction machine is not in operation (i.e., when the construction machine is in standby mode). Generally, heavier construction machines exhibit smaller noise vibrations, and lighter construction machines exhibit larger noise vibrations. Therefore, by storing reference values ​​for each weight class and comparing the measured noise vibration with the reference values ​​(thresholds, standard values, etc.) stored in a database, the weight class of the construction machine can be classified.

[0032] Thus, the vibrations of construction machinery (particularly those used to determine the weight class) are measured while the machinery is in a standby state. This allows for efficient determination of the weight class without requiring any specific actions.

[0033] The motion classification unit 103 processes data acquired from, for example, the information acquisition unit 101 and the weight class classification unit 102, and outputs information on the type of motion performed during the diagnosis. One example of the processing by the motion classification unit 103 is to use the waveform detected by the accelerometer to classify the machine motion as arm pulling.

[0034] The health diagnosis unit 104 processes data acquired from, for example, the information acquisition unit 101, the weight class classification unit 102, and the motion classification unit 103, and outputs a diagnosis result indicating the health of a particular construction machine (for example, whether or not it is in a healthy state). In addition, for example, the health diagnosis unit 104 uses an accelerometer to process vibrations acquired from the motion inspection of the construction machine's arm, and outputs information indicating how long it took the machine to pull the arm based on the peak level of the vibration.

[0035] The basic performance reporting unit 105 reports (outputs) the results to the operator based on the calculation results of the health diagnosis unit 104. For example, in order to verify the correct operating range, the basic performance reporting unit 105 requests data for the operating range reference value corresponding to the current construction machine from the operating range reference value holding unit 204. The basic performance reporting unit 105 then transfers the operating range reference value information to a user terminal 4 (such as a mobile terminal (smartphone) or computer (PC)) and displays the information on its output screen. If the performance measurement device 1 is installed on the user terminal 4, the operating range reference value information will be output directly to the display screen. This allows the operator to confirm whether the operation of the construction machine during the diagnosis was within the correct operating range and to understand whether the construction machine is in a healthy condition.

[0036] <Example of internal function configuration of information acquisition unit 101> Figure 3 shows an example of the internal function configuration of the information acquisition unit 101 of the performance measurement device 1.

[0037] The information acquisition unit 101 includes a sensor sampling frequency setting unit 1011, a data format setting unit 1012, and a data acquisition time setting unit 1013.

[0038] The sensor sampling frequency setting unit 1011 has the function of setting the sampling frequency for acquiring data from any of the sensors in the sensor group 2 (for example, an accelerometer). This sampling frequency may be predetermined, or it may be determined by the operator or another user. For example, it is conceivable to set the sampling frequency for acquiring data from the accelerometer to 100 samples / second.

[0039] The data format setting unit 1012 has a function to set what format the acquired sensor data should be processed in. For example, the data format can be CSV format.

[0040] The data acquisition time setting unit 1013 has a function to set a time limit for data acquisition. The time limit can be set manually (e.g., collecting data for 20 seconds regardless of the length of the test itself) or automatically (requesting the operator to start data acquisition, perform the diagnosis (inspection), and then stop data acquisition).

[0041] <Example of internal function configuration of weight class classification unit 102> Figure 4 shows an example of the internal functional configuration of the weight class classification unit 102 of the performance measurement device 1.

[0042] The weight class classification unit 102 includes a bias removal unit 1021, an absolute value acquisition unit 1022, a noise scale extraction unit 1023, and a weight class determination unit 1024.

[0043] The bias removal unit 1021 removes the bias component (DC component) from the acceleration signal. By removing the bias, the signal can be normalized.

[0044] The absolute value acquisition unit 1022 acquires the absolute value of the acceleration signal, that is, discards the sign indicating positive or negative. Although acceleration is a vector quantity and can contain both positive and negative values, only the magnitude of the signal is referenced in subsequent processing.

[0045] The noise magnitude extraction unit 1023 extracts the noise magnitude from the signal during the period before the construction machine has started operating. After the operator instructs the performance measuring device 1 to start operation, a certain amount of time (e.g., 2 to 5 seconds) is required before the actual construction machine starts operating. Therefore, the noise vibration magnitude can be measured in a short predetermined period (e.g., 0.5 to 1 second) immediately after the instruction to start operation. The noise vibration magnitude can be obtained, for example, by averaging the signal values ​​within the period.

[0046] The weight class determination unit 1024 compares the noise vibration magnitude acquired by the noise magnitude extraction unit 1023 with a reference value of noise vibration magnitude pre-stored in the weight reference value holding unit 201, and thereby determines the weight class. The weight reference value holding unit 201 stores different reference values ​​for each weight class, and can determine the weight class based on the measured noise vibration magnitude.

[0047] Figure 5 shows examples of noise vibration magnitudes. Figure 5(a) shows the acceleration signal during arm pulling motion of a construction machine belonging to the 20-ton weight class. Figure 5(b) shows the acceleration signal during arm pulling motion of a construction machine belonging to the 40-ton weight class.

[0048] In Figure 5(a), the arm pulling motion starts at 13.4 seconds, and period 51 shows the noise vibration of a 20-ton construction machine in standby mode (i.e., before the arm pulling motion starts). In Figure 5(b), the arm pulling motion starts at 9.1 seconds, and period 52 shows the noise vibration of a 40-ton construction machine in standby mode (i.e., before the arm pulling motion starts). Thus, the magnitude of the noise vibration corresponding to 40 tons is smaller than the magnitude of the noise vibration corresponding to 20 tons.

[0049] Therefore, by storing the minimum value of the noise vibration magnitude for 20 tons as the reference value in the weight reference value holding unit 201, it is possible to correctly classify 20-ton construction machinery from 40-ton construction machinery. The reference value may also be the maximum value of the noise vibration magnitude for 40 tons, or an intermediate value between the noise vibration magnitudes of 20 tons and 40 tons.

[0050] The example in Figure 5 shows only two weight classes, but three or more weight classes may be defined.

[0051] Thus, the weight reference value holding unit 201 may store vibration thresholds associated with multiple weight classes, and the weight class of the construction machine may be determined based on these vibration thresholds. In this way, appropriate classification can be performed based on actual vibrations.

[0052] <Example of internal function configuration of the operation classification unit 103> Figure 6 shows an example of the internal functional configuration of the operation classification unit 103 of the performance measurement device 1.

[0053] The motion classification unit 103 comprises a feature analysis unit 1031, a pattern matching unit 1032, and a classification unit 1033.

[0054] The feature analysis unit 1031 analyzes various features and collects further information regarding the operation of the construction machine. An example of feature analysis is the analysis of the peak amplitude and decay (referred to as roll-off in this specification) shape of the signal from the accelerometer 21.

[0055] The pattern matching unit 1032 compares the information obtained from the feature analysis unit 1031 with the patterns stored in the operation-specific representative waveform holding unit 202, and extracts matching patterns (for example, those within a predetermined error range).

[0056] The classification unit 1033 determines (identifies) the type of operation being performed based on the matching results from the pattern matching unit.

[0057] Figure 7 shows examples of acceleration signal waveforms corresponding to various operations of the same construction machine. Six types of operations are shown: arm pulling, arm pushing, bucket excavation, bucket soil discharge, boom raising, and boom lowering. Each operation has a unique waveform pattern at its start and end, and based on the measured waveform pattern, it is possible to determine which operation the measured acceleration signal corresponds to. The start and end points of each operation can also be identified.

[0058] The pattern features used to distinguish between operations include, for example, the amplitude and attenuation. The signal roll-off portion has a different shape for each operation and occurs at different times for each operation. Pattern matching can be performed using both the amplitude features (e.g., peak value and / or peak amplitude) and the roll-off portion features.

[0059] The patterns used as the basis for pattern matching are pre-stored in the operation-specific representative waveform holding unit 202. Patterns are stored for each operation. Furthermore, patterns may be stored for each weight class.

[0060] Furthermore, the patterns may be used for classifying weight classes. For example, the operation-specific representative waveform holding unit 202 may store vibration patterns associated with multiple weight classes, and the weight class of construction machinery may be determined based on these vibration patterns. In this way, appropriate classification can be performed based on the actual vibration patterns.

[0061] <Health assessment process> Figure 8 is a flowchart illustrating the processing of the health diagnosis unit 104. First, in step S101, the health diagnosis unit 104 removes the bias from the acceleration signal. This process can be performed, for example, in the same manner as the bias removal unit 1021 of the weight class classification unit 102.

[0062] Next, in step S102, the health diagnosis unit 104 acquires the absolute value of the acceleration signal. This process can be performed, for example, in the same manner as the absolute value acquisition unit 1022 of the weight class classification unit 102.

[0063] Next, in step S103, the health diagnosis unit 104 removes noise components from the acceleration signal. Specific calculation processes for removing noise components can be appropriately designed by those skilled in the art based on prior art.

[0064] Next, in step S104, the health diagnosis unit 104 applies a low-pass filter to the acceleration signal. This smooths the signal, making the peaks clearer.

[0065] Next, in step S105, the health diagnosis unit 104 detects the first peak among the peaks of the acceleration signal. The specific calculation process for detecting the peak can be appropriately designed by a person skilled in the art based on prior art. For example, a scan for peak detection is performed based on the envelope of the acceleration signal, and a peak exceeding a predetermined threshold is detected. This threshold may be calculated adaptively, or it may be calculated based on the mean and / or variance of the acceleration. The specific details of the processing related to the envelope can be appropriately designed by a person skilled in the art based on prior art.

[0066] Next, in step S106, the health diagnosis unit 104 checks the energy of the peak. If the energy of the peak is greater than a predetermined standard (for example, if the amplitude exceeding a predetermined threshold persists for a predetermined time or longer), the peak is determined to be a true peak; otherwise, the peak is determined to be not a true peak (it is a spike). For this determination, the health diagnosis unit 104 may include an integrator.

[0067] Next, in step S107, the process branches based on the result of step S106. If the peak is a spike, the process proceeds to step S108; if the peak is a true peak, the process proceeds to step S109.

[0068] In step S108, the health diagnosis unit 104 removes the spike from the acceleration signal. Then, the health diagnosis unit 104 returns to step S105 and repeats peak detection based on the acceleration signal from which the spike has been removed.

[0069] In step S109, the health diagnosis unit 104 determines whether the peak is the first peak. If it is the first peak, the process proceeds to step S110; otherwise (for example, if it is the second peak), the process proceeds to step S114.

[0070] In step S110, the health diagnosis unit 104 performs a check for false peaks. After the operator instructs the performance measuring device 1 to start operation via the user terminal 4, they may accidentally shake the sensor group 2 or user terminal 4 by hand before placing them in the designated mounting location (for example, in the designated cup holder). In such cases, a peak unrelated to the operation of the construction machine (false peak) is detected. The health diagnosis unit 104 determines whether the peak is such a false peak. Specific examples of the determination process will be described later with reference to Figures 9 and 10.

[0071] Next, in step S111, the process branches based on the result of step S110. If the peak is a false peak, the process proceeds to step S113; if the peak is a true peak, the process proceeds to step S112.

[0072] In step S112, the health diagnosis unit 104 extracts the peak as the first peak and stores the time of occurrence of the peak. This first peak corresponds to the time when the construction machine started operating.

[0073] In step S113, the health diagnosis unit 104 removes the peak (false peak or initial peak) from the acceleration signal and returns the process to step S105.

[0074] In step S109 described above, if the peak is not the first peak (for example, if it is the second peak), the process proceeds to step S114. In step S114, the health diagnosis unit 104 extracts the peak as the second peak and stores the time of occurrence of the peak. This second peak corresponds to the time when the construction machine operation has finished.

[0075] Next, in step S115, the health diagnosis unit 104 subtracts the time of the first peak from the time of the second peak, thereby calculating the duration of the construction machine's operation. In other words, the health diagnosis unit 104 measures the start and end times of the machine's operation and calculates the duration of the machine's operation based on the start and end times. In this way, the health diagnosis unit 104 measures the results of the construction machine's operation. The health of the construction machine is determined based on this duration.

[0076] In this way, by determining the soundness of the equipment based on the duration of its operation, it becomes possible to evaluate the actual operation of construction machinery and make more accurate judgments.

[0077] Figure 9 is a flowchart illustrating the detailed processing of step S110 in Figure 8. Figure 10 is an example of an acceleration signal containing a false peak. Assume that the false peak 61 in Figure 10 is being processed in step S110.

[0078] First, in step S110a, the health diagnosis unit 104 detects the maximum value 62 of the acceleration signal.

[0079] Next, in step S110b, the health diagnosis unit 104 calculates the time difference between the time of occurrence of the false peak 61 currently being processed and the time of occurrence of the maximum value 62.

[0080] Next, in step S110c, the health diagnosis unit 104 determines whether the time difference exceeds a threshold. Normally, a certain amount of time is required from the time the operator places the sensor group 2 or user terminal 4 until the time the construction machine is started to operate (this time is, for example, more than 10 seconds). Therefore, if the threshold is set to, for example, 10 seconds, and this time difference exceeds the threshold, the peak can be determined to be a false peak. If the time difference is below the threshold, the process proceeds to step S110d. The health diagnosis unit 104 determines and stores the determination result. This determination result is used in the subsequent step S111.

[0081] In the example in Figure 10, this time difference is 16 seconds, which exceeds the threshold, so the false peak 61 can be correctly identified as a false peak and removed. In this way, the correct duration 63 is measured.

[0082] Furthermore, it is preferable that this threshold be longer than the time required for each operation of the construction machine being diagnosed. In particular, it is even more preferable that the threshold be longer than the time required for each operation when the construction machine is not in good condition.

[0083] If the time difference exceeds the threshold in step S110c, the process proceeds to step S110e. In step S110e, if it is determined to be a false peak, the process returns to step S110a, which detects the maximum value of the velocity signal.

[0084] <Example of internal function configuration of the basic performance reporting unit 105> Figure 11 shows an example of the internal functional configuration of the basic performance reporting unit 105 of the performance measurement device 1.

[0085] The basic performance reporting unit 105 includes a reference comparison unit 1051, a result reporting unit 1052, an operating range confirmation unit 1053, and a recommendation information acquisition unit 1054.

[0086] The reference comparison unit 1051 selects performance standard values ​​from among the various performance standard values ​​held in the performance standard value holding unit 203 that correspond to the determined weight class and operation, based on the classification results from the weight class classification unit 102 and the operation classification unit 103. Then, the reference comparison unit 1051 compares the diagnosis (judgment) result from the soundness diagnosis unit 104 with the selected performance standard value to determine whether the construction machine under diagnosis (specific operation: for example, arm pulling operation) is in a sound condition.

[0087] The results reporting unit 1052 creates a report on the soundness of the construction machine and transmits it, along with the raw data (measurement data), to the data storage unit 207 of the memory device 20. This makes it possible to generate a history log regarding the soundness of the construction machine.

[0088] The operating range confirmation unit 1053 obtains the operating range reference value corresponding to the classification result of the operation classification unit 103 from the operating range reference value holding unit 204 and outputs this information (displayed on the display screen) in order to confirm whether the operator of the construction machine being diagnosed performed the diagnosis within the correct operating range. For example, in the case of arm pulling, the reference operating range information held in the operating range reference value holding unit 204 is a starting angle position of 170 degrees and an ending angle position of 15 degrees, which the operator can confirm with the angle sensor 13 built into the construction machine after performing the diagnosis.

[0089] Thus, the operating range reference value holding unit 204 may store the reference start position and reference end position of the machine operation, the information acquisition unit 101 may measure the actual start position and actual end position of the machine operation, and the user terminal 4 may display the reference start position, reference end position, actual start position, and actual end position. In this way, the operator can easily confirm the results of the operation.

[0090] Based on the comparison results from the reference comparison unit 1051, the recommendation information acquisition unit 1054 acquires appropriate recommendation information corresponding to the current diagnosis from the information set pre-stored in the recommendation information storage unit 205.

[0091] <Examples of information held by the data storage unit 207> Figure 12 shows an example of the configuration of a history log list 1201, which is an example of information held by the data storage unit 207 included in the memory device 20 of the performance measurement device 1.

[0092] The history log list 1201 consists of multiple history files categorized by operation and sample for each construction machine (by weight class). For example, by selecting any history file 12012 (history log file) from the list shown in the upper part of Figure 12, the file contents shown in the lower part of Figure 12 can be viewed.

[0093] The history file is saved, for example, as a CSV file, and the title of the history file includes the date (automatically assigned by the device's OS), the construction machine's weight class (obtained from the weight class classification unit 102), operation information (obtained from the operation classification unit 103), sample number (if you want to repeat the experiment, excluding the diagnostic results for operation errors by the operator), and diagnostic results (information reported from the basic performance reporting unit 105).

[0094] In this way, the data storage unit 207 stores, in particular, the weight class, machine operation, and health status in CSV format, so that the performance measuring device 1 can output this information in CSV format. This makes data analysis in subsequent stages easier.

[0095] The lower part of Figure 12 shows an example of a history file. The history file 12012 includes the data acquisition time 120121, the raw data 120122 which is the measurement data, the operation 120123 which indicates the operation details, the sample number 120124, and the result 120125 which indicates the diagnostic result.

[0096] <Examples of information held by the performance standard value holding unit 203> Figure 13 shows an example of the configuration of performance reference value information 1301 held by the performance reference value holding unit 203 included in the memory device 20 of the performance measurement device 1.

[0097] Performance standard value information 1301 is management information that includes operation 13012, standard 13013, and tolerance 13014 for each weight class 13011.

[0098] Weight class 13011 is information indicating the weight class of the construction machine, for example, 20 tons or 40 tons. Operation 13012 is the operation of the construction machine in question, for example, arm pulling, bucket digging, etc. Criterion 13013 is, for example, the standard duration for the corresponding operation (e.g., 3.5 seconds). Tolerance 13014 indicates the range within which it is considered normal even if it does not match the criterion 13013 (tolerance: e.g., ±0.4 seconds).

[0099] The performance reference value holding unit 203 may store reference durations associated with multiple weight classes, and the soundness of the construction machine may be determined based on these reference durations for each weight class. In this way, appropriate determinations can be made specifically for each weight class.

[0100] By using the performance standard value information 1301, it becomes possible to estimate the operation of the object being diagnosed. For example, if the diagnosis result of the health diagnosis unit 104 is 3.6 seconds, and the standard value of the performance standard value information for arm pulling operation in the corresponding weight class is 3.5 seconds with an allowable error range of ±0.4 seconds, then the operation of the object being diagnosed can be estimated to be arm pulling.

[0101] <Example of information held by the operating range reference value holding unit 204> Figure 14 shows an example of the configuration of the operating range reference value information 1401 held by the operating range reference value holding unit 204 included in the memory device 20 of the performance measurement device 1.

[0102] The operating range reference value information 1401 is management information that includes the operation 14012, the start angle 14013, and the end angle 14014 for each weight class 14011.

[0103] Weight class 14011 indicates the weight class of the construction machine, for example, 20 tons or 40 tons. Operation 14012 is the operation of the construction machine in question, for example, arm pulling, bucket digging, etc. Start angle 14013 indicates the starting angle of the corresponding operation. End angle 14014 indicates the ending angle of the corresponding operation. For example, for boom lifting operation, the start angle is 0 degrees and the end angle is 90 degrees.

[0104] <Examples of information held by the operation-specific representative waveform holding unit 202> Figure 15 shows an example of the configuration of the representative waveform information 1501 for each operation held by the representative waveform holding unit 202 included in the memory device 20 of the performance measurement device 1.

[0105] The representative waveform information 1501 for each operation (150111, 150112) for each weight class 15011 consists of acquisition time information for the acquisition of the representative waveform and the corresponding waveform. It is assumed that different waveforms will be stored in this representative waveform information 1501 for all operations available for each weight class.

[0106] <Examples of information held by the recommendation information storage unit 205> Figure 16 shows an example of the configuration of recommendation information 1601 held by the recommendation information holding unit 205 included in the memory device 20 of the performance measurement device 1.

[0107] Recommendation information 1601 consists of a drift value 16011 and a recommendation content 16012 (recommended information) for a countermeasure corresponding to the drift value.

[0108] The drift value 16011 indicates how far the measurement result deviates from the standard value and is displayed as a percentage. For example, the ideal arm pull duration for a certain weight class is 3.2 seconds, and the tolerance is ±0.3 seconds, so this corresponds to (0.3 / 3.2) × 100 = 9.4%. If the measurement time was 3.4 seconds, D1 would be ((3.4-3.2) / 3.2) × 100 = 6.25%. In this case, D1 is lower than the 9.4% indicated by the drift value 16011, so the recommendation 16012 would be "The relevant part of the construction machine is in good condition. No action is required." On the other hand, for example, if the drift D2% of the measurement time is higher than the 9.4% indicated by the drift value 16011, the recommendation 16012 would be "There is a problem with the soundness of the relevant part of the construction machine. Please contact the maintenance department as soon as possible and show them this report."

[0109] In this way, it becomes possible to present recommended information in various forms, such as setting the importance (importance of action) according to the degree of deviation from the standard value. Thus, the performance measurement device 1 outputs information regarding actions to be taken for the construction machinery based on its soundness (or the result of the judgment regarding soundness). This allows the operator to take the necessary actions for the construction machinery.

[0110] <Example of information held by the operation list holding unit 206> Figure 17 shows an example of the configuration of the operation list information 1701 (table) held by the operation list holding unit 206 included in the memory device 20 of the performance measurement device 1.

[0111] The operation list information 1701 consists of a state 17011 and an operation 17012 for each weight class.

[0112] Status 17011 is information indicating whether or not the operation diagnosis has been completed. If the operation diagnosis is complete, it is indicated with a "○" mark, and if the operation diagnosis is not complete, it is indicated with an "×" mark, thereby indicating the diagnostic status of the corresponding operation. In this way, the operation list holding unit 206 stores a list containing information representing multiple machine operations.

[0113] Furthermore, additional columns may be added to allow the user to visualize the overall condition of the machine: Result 17013 (Diagnostic Result), Criterion 17014 (Criterion Value), Tolerance 17015 (Tolerance Range relative to the Criterion Value), and Others (not shown).

[0114] Operation list information 1701 can indicate whether a health diagnosis has been completed for a construction machine of a specific weight class. This allows users to check available operations and track operations that have been diagnosed and those that have not.

[0115] Furthermore, the memory device 20 of the performance measurement device 1 may be configured to pre-store operation list information 1701 in the operation list holding unit 206 for each weight class of all construction machines, where the status 17011 is blank (or the status of all operations is incomplete (×)). Alternatively, when the operator starts diagnosing the target construction machine 3, all operations of the construction machine 3 may be registered as operation list information 1701 in the operation list holding unit 206. If there is a construction machine of the same weight class that has been diagnosed in the past, the operation list information 1701 from the past can be reused (the information of the previous result 17013 and status 17011 will be reset).

[0116] <Input and Output Information> Figure 18 is a diagram comparing an example of input information 1801 to the performance measurement device 1 with an example of output information 1802 from the device 1.

[0117] Examples of input information 1801 include a start instruction (pressing the start button) to begin data collection before diagnosis and a stop instruction 18011 (pressing the stop button) to stop / end the diagnosis. However, input information 1801 is not limited to these. It is also possible to automatically stop the process when predetermined criteria are met or after a certain period of time from the start.

[0118] Output information 1802 may include, for example, an operation list 18021 (with completion status mark), the construction machine weight class 18022, the construction machine operation 18023, the operating range reference value 18024, the soundness 18025, the reference value 18026 (including tolerance), the recommendation 18027, the report 18028, and the history log 18029.

[0119] By outputting the operation list 18021, users can track which machine operations have already been diagnosed and which operations have not yet been diagnosed. As shown in Figure 17, operations that have been diagnosed can be marked with a circle ("○") to indicate that the diagnosis is complete.

[0120] By outputting the construction machinery weight class 18022, it becomes possible to check the construction machinery weight class (e.g., 20 tons) that was automatically classified in the diagnostic performed this time.

[0121] By outputting construction machine operation 18023, it becomes possible to check the operation of the construction machine that was automatically classified in the diagnostic performed this time (e.g., arm pulling).

[0122] By outputting the operating range reference value 18024, information can be provided to the operator of the construction machine to confirm whether the operation was performed correctly. For example, by outputting the reference start angle and reference end angle, the operator can compare them with the angle of the angle sensor 13 built into the construction machine 3 and confirm whether the operating range matches the reference value.

[0123] By outputting the soundness 18025, it is possible to provide information for confirming whether the part (e.g., arm) that performs the operation is in a sound state by the target operation diagnosis. As information indicating the soundness 18025, for example, it is conceivable to output the results of the most recently performed test.

[0124] By outputting the information of the reference value 18026, it is possible to provide information for confirming the reference value (including the allowable error) for diagnosis of a specific operation of a specific construction machine.

[0125] By outputting the recommendation 18027, it is possible to provide information (recommendations) for the operator (user) to interpret the information of the soundness 18025 and determine whether it is necessary to contact for maintenance.

[0126] The report 18028 can be output as information obtained by adding raw data to all the above outputs (for example, the operation list 18021, the weight class 18022 of the construction machine, the operation 18023 of the construction machine, the operation range reference value 18024, the soundness 18025, the reference value 18026, the recommendation 18027).

[0127] By outputting the history log 18029, it is possible to provide information useful for the user to track all past diagnosis contents.

[0128] <Configuration example of GUI> FIG. 19 is an example of a user interface displayed on the display screen of the performance measurement device 1 or the display screen of the user terminal 4. The user interface is configured, for example, as a GUI (Graphical User Interface). The GUI constitutes a display unit, and examples include an input GUI G1 (input screen), a running GUI G2 (running screen), and a diagnosis result display GUI G3 (result screen).

[0129] The input GUI G1 allows users to check which operations have been diagnosed and which have not yet been diagnosed. In the example in Figure 19, six operations are provided, and only the first two are shown to have been diagnosed. The input GUI G1 may also display instructions on how to start the diagnosis, or it may simply start the diagnosis by pressing a start button. Thus, the input GUI G1 is equipped with a start button as an operation unit for commanding the start of the health determination. This allows the operator to easily command the start.

[0130] The running GUI G2 indicates that the construction machine operation selected by the user (or operator) is in progress. In this example, the operator will press the stop button after the operation is complete. However, it is also possible to omit the stop button and have the operation completion automatically determined.

[0131] The GUI G3 for displaying diagnostic results shows the classified weight class, classified operation, and reference range for the operator to verify, but it may also display instructions prompting the operator to verify the operation range. In addition, the diagnostic results are displayed for reference along with the reference and tolerance range, and the drift value and recommendations are also displayed. Furthermore, the operation list (table: see Figure 17) is displayed along with information on operations marked as completed (○) or incomplete (×). In the example in Figure 19, operation O13 is marked as completed (○), and the diagnostic result is entered in the operation list.

[0132] In this way, the performance measurement device 1 or the user terminal 4 displays information indicating whether or not measurements related to each machine operation included in the list have already been performed. This ensures that the user can perform each operation without omission or duplication.

[0133] The G3 GUI for displaying diagnostic results does not need to display all of the above information; for example, it may display at least one of the weight class and machine operation (classified operation). With at least such a display, the operator can properly confirm the weight class of the construction machine or the operation they performed.

[0134] The diagnostic results display GUI G3 can include a save button and a repeat execution instruction button. When the operator (user) presses the save button, the report and raw data are saved to the history log. If the measurement was not performed correctly, the operating range was incorrect, or other problems occurred, the system can be configured so that the display screen transitions to the input GUI G1 without recording the incorrect measurement results, etc., when the operator (user) presses the repeat button.

[0135] <Performance measurement and diagnostic processing> Figure 20 is a flowchart illustrating the performance measurement and diagnostic process according to this embodiment.

[0136] (i) Step S201 The performance measurement device 1 starts operating.

[0137] (ii) Step S202 When an operator places the performance measurement device 1 (or a terminal with the same device's functions implemented (a smartphone with a built-in accelerometer)) appropriately in a designated location on the construction machine to be diagnosed (for example, inside a cup holder in a cabinet or inside a box on the floor) so that it can detect (pick up) vibrations during the operation of the construction machine, and instructs the performance measurement device 1 to start the diagnosis (for example, by pressing the diagnosis start button), the processor 10 receives the instruction. Note that the placement location may vary depending on the type of sensor.

[0138] (iii) Step S203 The operator checks the operation list information 1701 (see Figure 17) to identify any operations of the construction machine that have not yet been diagnosed, and then selects the next operation to be diagnosed. The operation list information 1701 lists all operations to be diagnosed, with completed operations marked with a circle (○) and incomplete operations marked with an X (×). Examples of construction machine operations that the operator can select include arm pulling, arm pushing, boom raising, boom lowering, bucket digging, and bucket discharge.

[0139] The operator is not required to input which operation they selected as the operation to be diagnosed. However, as a variation, the user may input the selected operation, and the processor 10 may accept that selection.

[0140] (iv) Step S204 The information acquisition unit 101 of the processor 10 starts acquiring relevant data. For example, the information acquisition unit 101 operates at least one of the sensor group 2 (for example, an accelerometer 21) and collects the data acquired by that sensor. In this way, the processor 10 measures the vibration of the construction machine via the accelerometer 21.

[0141] (v) Step S205 When the operator operates the construction machine and performs the action selected in step S204 (for example, pulling the arm), the health diagnosis unit 104 collects data acquired by at least one of the sensor group 2 during the operation and stores it in the data storage unit 207.

[0142] (vi) Step S206 The processor 10 analyzes the data collected in step S205 and generates several analysis results.

[0143] For example, the health diagnosis unit 104 calculates the time taken for the operation from the data acquired by the sensor (for example, the peak value of the vibration waveform acquired by the accelerometer), stores the analysis data (vibration waveform and time between peaks) in the data storage unit 207, and also passes it on to the operation classification unit 103.

[0144] The weight class classification unit 102 acquires the analysis data obtained by the soundness diagnosis unit 104 and identifies the weight class of the construction machine based on the analysis data. In this way, the processor 10 determines the weight class of the construction machine based on vibration.

[0145] The motion classification unit 103 acquires analysis data obtained by the health diagnosis unit 104, compares this analysis data (e.g., vibration waveform) with waveforms previously stored in the motion-specific representative waveform holding unit 202, performs matching, and identifies the motion to be diagnosed. In this process, the weight class may also be referenced.

[0146] The basic performance reporting unit 105 obtains data of operating range reference values ​​corresponding to the operations identified by the operation classification unit 103 from the operating range reference value holding unit 204, compares the operating range reference values ​​with the analysis data, and determines whether the construction machine under diagnosis is in a healthy state (or to what extent it deviates from a healthy state) with respect to that operation. In this case, the weight class may also be referred to. In this way, the processor 10 determines the health of the construction machine based on the weight class and the results of the machine operation.

[0147] (vii) Step S207 The processor 10 transmits the weight class identified by the weight class classification unit 102, the operation identified by the operation classification unit 103, the health determined by the basic performance reporting unit 105, and the operating range (including information on the operating range reference value) to, for example, a user terminal 4 (a mobile terminal (smartphone) or a computer (PC)) and displays the information on its output screen.

[0148] More specifically, the system outputs the results of comparing the operator's (user's) selected actions, the operating range (start and stop positions) to verify that the operator performed the actions correctly, and the construction machine's health (execution time) with a baseline value (manufacturing baseline value). This information can be used as a reference to determine what constitutes a healthy machine and what constitutes an unhealthy machine.

[0149] (viii) Step S208 The processor 10 obtains recommendation content 16012 (see Figure 16) corresponding to the diagnostic results of the basic performance reporting unit 105 from the recommendation information holding unit 205, and displays it, for example, on the screen of the user terminal 4 (see diagnostic result display GUI G3 (Figure 19)).

[0150] As explained in Figure 16, Recommendation Content 16012 is generated (selected) based on how much the soundness of the relevant operation of the construction machine deviates from the standard value (manufacturing standard value). For example, if the soundness of the construction machine deviates by D% from the manufacturing standard value, a recommendation such as "There is a problem with the soundness of the relevant part of the construction machine. Please contact the maintenance personnel and show them this report as soon as possible" can be issued.

[0151] (ix) Step S209 The operator determines whether the sensor data has been collected properly. If it has been collected properly, the operator presses the save button; if it has not been collected properly, the operator presses the repeat button. The processor 10 determines which button was pressed. If the save button was pressed (Yes in step S209), the process proceeds to step S210. If the repeat button was pressed (No in step S209), the process proceeds to step S204.

[0152] (x) Step S210 Processor 10 stores reports (construction machine operation type, diagnostic results, recommendation information) and raw data as a history log on a storage device. These reports and raw data can be referenced when further analysis is needed.

[0153] (xi) Step S211 The processor 10 assigns a "completed" (diagnosed) mark (○) to the operation that has been diagnosed in the operation list of the construction machine being diagnosed.

[0154] (xii) Step S212 The processor 10 determines whether the diagnosis has been completed for all operations of the construction machine being diagnosed. If the diagnosis has been completed for all operations (Yes in step S212), the process moves to step S213, and the performance measurement diagnosis process ends. If there are still operations that have not been diagnosed (No in step S212), the process moves to step S204.

[0155] <Examples> A: Example 1 (1) Example of a device that implements the functions of the performance measurement device 1 As mentioned above, a smartphone can be used as an example of a main device that implements the functions of performance measurement device 1. A MEMS (Micro Electro Mechanical System) sensor (such as an accelerometer) built into the smartphone can be used as the main sensor for data acquisition. The processing and analysis of the data acquired by the sensor (accelerometer) can be performed by the smartphone's CPU.

[0156] The smartphone's memory can be used to store raw data and its results. In this embodiment, the performance measurement and diagnostic processing function is implemented on the smartphone in the form of an application.

[0157] (2) Use Cases Examples of anticipated use cases (including operator actions) include the following:

[0158] (i) The operator presses the start button on the smartphone and places it in the cup holder on the cabinet of the construction machine.

[0159] (ii) The operator launches an application related to the performance measurement and diagnostic processing of the smartphone.

[0160] (iii) The operator selects and executes the operation of the construction machine to be diagnosed from the list of operations (for example, arm pulling).

[0161] (iv) The operator may press the start button, and the sensor (e.g., accelerometer) may start acquiring data accordingly. The start button may be omitted, in which case the sensor may start acquiring data at the time of (i) above.

[0162] (v) The operator operates the construction machinery and performs actions (e.g., pulling the arm).

[0163] (vi) While the operation is running, the smartphone's accelerometer detects vibrations inside the smartphone's casing.

[0164] (vii) After the arm retraction is complete, the operator may press the stop button to stop the data acquisition process.

[0165] (viii) The smartphone then begins analyzing the collected accelerometer data (which includes vibration levels and the start and stop times of the arm pulling motion).

[0166] (ix) Algorithm structure (the following does not restrict the execution order) (ix-1) Automatic measurement of operating time of construction machinery The data from the accelerometer 21 allows for the automatic detection of the start and stop times of construction machinery operation. (ix-2) Automatic classification of construction machinery operation By performing peak analysis of waveform data from the accelerometer 21 regarding the operation of the construction machine being diagnosed, it is possible to automatically detect which operation was performed. (ix-3) Automatic classification of construction machinery weight classes The weight class of the construction machinery being diagnosed is automatically identified.

[0167] (x) Screen output

[0168] The smartphone screen (GUI G3 for displaying diagnostic results) displays the construction machine's weight class (e.g., 20 tons), the type of operation (e.g., arm pulling), the operating reference range (e.g., starting angle 170 degrees, ending angle 10 degrees), the operation time, the reference duration and tolerance, recommendation comments (including drift values), a completion mark (〇) for recently diagnosed operations (e.g., arm pulling), an updated operation list including the results, a save button to save the report and raw data, and a repeat button to repeat the test if there is an error (e.g., operator error) (for example, if the operator performs an operation within a different operating range than the reference) (see Figure 19).

[0169] B: Example 2 As a variation of Example 1, a microcontroller such as an Arduino® with a built-in accelerometer can also be used. The microcontroller may also be called a portable controller, control board, etc. The same process described in Example 1 can be repeated (wirelessly or wired) using a microcontroller connected to a computer, and control and output visualization can be performed. Some microcontrollers have a built-in CPU and memory, and will function simply by connecting a display device.

[0170] <Summary> (i) According to this embodiment, the construction machinery diagnostic system (a device for determining the health of construction machinery) comprises a performance measuring device 1, a sensor group 2, and a user terminal 4. Based on sensor waveform data obtained by detecting the actual operation (e.g., arm pulling) performed by the construction machinery 3 (e.g., a hydraulic excavator) with a sensor (e.g., an accelerometer 21), the system performs the following processes: identifying the weight class of the construction machinery; identifying the actual operation performed; obtaining performance standard values ​​and tolerance values ​​(see Figure 13) corresponding to the identified operation from a storage device; comparing the performance standard values ​​(standard duration for the operation) and tolerance values ​​with the characteristic values ​​of the actual operation performed (e.g., time between peaks in the sensor waveform: the actual time taken for one operation (operation time)); and determining the health of the construction machinery.

[0171] In other words, if the characteristic value of the operation (operating time) is within the allowable error range of the standard value, the operation of the construction machine is judged to be in a healthy state; otherwise, it is judged to have a problem with its health. This health judgment result is output to the display unit of a user terminal 4 such as a smartphone equipped with the performance measurement device 1, or to the display unit of a user terminal 4 such as a smartphone that is independent of the performance measurement device 1. This allows the operator to see the health judgment result and determine whether maintenance of the construction machine is necessary.

[0172] (ii) The performance measuring device 1 may output to the display unit, along with the result of the determination of the soundness of the construction machine, the values ​​detected by the angle sensor 13 for the angle of a predetermined part of the construction machine at the starting position (e.g., arm or boom) and the angle of a predetermined part at the ending position when the operation of the construction machine is actually performed. This allows the operator to determine whether the operation was performed correctly. If it was not performed correctly, the diagnostic result for that operation can be discarded (reset), and the diagnosis for the same operation can be performed again.

[0173] (iii) The performance measuring device 1 may also store multiple types of recommendation information in the memory device 20 regarding countermeasures according to the degree of deviation from the performance standard value, and output the recommendation information corresponding to the soundness judgment result to the display unit along with the judgment result. If there is a problem with the soundness of the construction machine, even an inexperienced operator will be able to recognize what countermeasures should be taken.

[0174] (iv) The performance measuring device 1 further stores in the memory device 20 operation list information that shows the diagnostic status (whether the diagnosis is complete or not) and the diagnosis result for each of the multiple operations of the construction machine. In the operation list information, for operations for which the process of determining soundness has been completed, the device updates the operation list information by inputting information indicating that the diagnostic status is complete and the judgment result, and outputs the updated operation list information to the display unit. In this way, it is possible to immediately recognize to what extent the diagnosis of the entire operation of the construction machine being diagnosed has been completed.

[0175] (v) When the operator issues a save instruction (by pressing the save button displayed on the GUI G3 for displaying diagnostic results), the performance measurement device 1 saves the judgment result and the detected data of the actually performed operation as a diagnostic history log (see Figure 12) to the storage device 20. By referring to the diagnostic history log, it is possible to confirm whether the construction machine has undergone periodic health checks for each operation, and even if there are no health problems, it is possible to confirm whether deterioration is gradually progressing.

[0176] On the other hand, when the system detects repeated instructions from the operator (pressing the repeat button displayed on the GUI G3 for displaying diagnostic results), the performance measurement device 1 resets the judgment result and the sensor detection data for the identified operation, and performs the diagnosis again for the same operation. This makes it easier to verify the diagnostic results because, if the operator fails to properly perform the operation of the part of the construction machine being diagnosed (e.g., the arm), the data related to that operation is not recorded in the diagnostic history log.

[0177] (vi) As shown in Figure 18, the only information the operator needs to input to the performance measuring device 1 is the instruction to start the diagnosis (they may also input an instruction to stop the diagnosis). On the other hand, the output information of the performance measuring device 1 includes the judgment result regarding the soundness, information on the identified weight class and type of operation, information on the operating range standard value of the identified operation, the performance standard value of the identified operation, recommendation information corresponding to the judgment result, and sensor detection data of the identified operation. In this way, the operator can obtain an appropriate diagnosis result by inputting only the minimum amount of information (the number of input items can be reduced to the extreme), thus reducing the burden on the operator. In addition, even operators with little experience can obtain an appropriate diagnosis result. As a result, the possibility of human error can be reduced.

[0178] Furthermore, because it does not rely on audio signals, it enables more accurate diagnosis.

[0179] (vii) In the example above, the history logs are stored on a storage device, but by transferring and managing them on a server / cloud server, data can be centralized and updated, improving the update efficiency.

[0180] (viii) The functions of the embodiments of the present disclosure can also be realized by software program code. In this case, a storage medium on which the program code is recorded is provided to a system or device, and the computer (or CPU or MPU) of the system or device reads the program code stored on the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the embodiments described above, and the program code itself and the storage medium on which it is stored constitute the present disclosure. Examples of storage media for supplying such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, optical disks, magneto-optical disks, CD-Rs, magnetic tapes, non-volatile memory cards, ROMs, etc.

[0181] Furthermore, based on the instructions in the program code, the operating system (OS) running on the computer may perform some or all of the actual processing, thereby realizing the functions of the embodiment described above. In addition, after the program code read from the storage medium is written to the computer's memory, the computer's CPU may perform some or all of the actual processing based on the instructions in the program code, thereby realizing the functions of the embodiment described above.

[0182] Furthermore, the program code for the software that realizes the functions of the embodiment may be distributed via a network and stored in a storage means such as a hard disk or memory of the system or device, or in a storage medium such as a CD-RW or CD-R, so that when in use the system or device's computer (or CPU or MPU) reads and executes the program code stored in the storage means or storage medium.

[0183] Finally, it is important to understand that the processes and techniques described herein are not inherently related to any specific device and can be implemented by any suitable combination of components. Furthermore, a wide variety of general-purpose devices can be used according to the teachings described herein. It may be beneficial to construct a dedicated device to perform the steps of the method described herein. Also, various inventions can be formed by appropriate combinations of the multiple components disclosed in the embodiments. For example, some components may be removed from all the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate. This disclosure has been written in relation to specific examples, but these are for illustrative purposes only and not limitation in all respects. Those skilled in the art will understand that there are many combinations of hardware, software, and firmware suitable for implementing this disclosure. For example, the described software can be implemented in a wide range of programming or scripting languages ​​such as assembler, C / C++, Perl, Shell, PHP, and Java®.

[0184] Furthermore, in the embodiments described above, the control lines and information lines shown are those deemed necessary for illustrative purposes, and not all control lines and information lines are necessarily shown in the actual product. All components may be interconnected. [Explanation of symbols]

[0185] 1. Performance measurement device (device for determining the soundness of construction machinery) 2. Sensor group (device for determining the soundness of construction machinery) 3. Construction machinery 4. User terminal (device for determining the soundness of construction machinery) 10. Processor (arithmetic unit) 20 Storage Devices 30 Communication devices 21 Accelerometer 22 Microphones 23 Cameras 101 Information Acquisition Department 102 Weight Classification Section 103 Motion classification section 104 Health Assessment Department 105 Basic performance report section 201 Weight standard value holding section 202 Representative waveform holding section for each operation 203 Performance standard value holding unit 204 Operating range reference value holding unit 205 Recommendation Information Storage Unit 206 Operation List Holding Unit 207 Data Storage Section

Claims

1. A device for determining the soundness of construction machinery, The device comprises a calculation unit, The aforementioned arithmetic unit, - The vibration of the construction machine is measured via an accelerometer, - Based on the vibrations, the weight class of the construction machine is determined. -Measure the results of the mechanical operation of the construction machine, - Based on the weight class and the results of the machine operation, the soundness of the construction machine is determined. Device.

2. The apparatus according to claim 1, wherein the vibration is measured while the construction machine is in a standby state.

3. The apparatus according to claim 1, wherein the apparatus comprises a smartphone or a microcontroller.

4. The calculation unit measures the start time and end time of the machine operation, and calculates the duration of the machine operation based on the start time and end time. The soundness of the construction machinery is further determined based on the duration. The apparatus according to claim 1.

5. The device stores reference durations associated with each of the multiple weight classes, The soundness of the construction machinery is further determined based on the standard duration. The apparatus according to claim 4.

6. The device stores vibration thresholds and vibration patterns associated with each of the multiple weight classes. The weight class of the construction machine is further determined based on the vibration threshold and the vibration pattern. The apparatus according to claim 1.

7. The device stores the reference start position and reference end position of the machine operation. The calculation unit measures the start and end positions of the machine operation, The device displays the reference start position, the reference end position, the start position, and the end position. The apparatus according to claim 1.

8. The apparatus according to claim 1, wherein the apparatus outputs information relating to the action to be taken on the construction machine based on the soundness.

9. The device stores a list containing information representing each of the multiple machine operations, The device displays information indicating whether or not measurements related to each of the mechanical operations included in the list have already been performed. The apparatus according to claim 1.

10. The device is equipped with a user interface, The aforementioned user interface is An operating unit for issuing a command to start the health determination, A display unit that displays at least one of the weight class and the machine operation, The apparatus according to claim 1, comprising:

11. The apparatus according to claim 1, wherein the apparatus outputs the weight class, the mechanical operation, and the soundness in CSV format.

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