WO2012057378A1 - 범용 센서 자가 진단 장치 및 그 진단 방법 - Google Patents
범용 센서 자가 진단 장치 및 그 진단 방법 Download PDFInfo
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- WO2012057378A1 WO2012057378A1 PCT/KR2010/007483 KR2010007483W WO2012057378A1 WO 2012057378 A1 WO2012057378 A1 WO 2012057378A1 KR 2010007483 W KR2010007483 W KR 2010007483W WO 2012057378 A1 WO2012057378 A1 WO 2012057378A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D3/00—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups
- G01D3/08—Indicating or recording apparatus with provision for the special purposes referred to in the subgroups with provision for safeguarding the apparatus, e.g. against abnormal operation, against breakdown
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/12—Checking intermittently signalling or alarm systems
- G08B29/14—Checking intermittently signalling or alarm systems checking the detection circuits
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- the present invention relates to a general-purpose sensor self-diagnostic apparatus, and more particularly, receives an initial normal input signal from a specific sensor and models the sensor (where modeling includes modeling coefficients, types, and various variables, and the like). After the initial modeling, the diagnostic modeling value from the specific sensor is compared with the normal modeling output value to determine whether the sensor is faulty or failure type, and if the sensor fails, the user is notified by preventing the accident and including the sensor.
- the present invention relates to a general-purpose sensor self-diagnosis apparatus and a diagnostic method thereof, which enable the system to ensure safety and reliability.
- the present invention relates to a general-purpose sensor self-diagnostic apparatus and a diagnostic method thereof.
- sensors for checking the movement amount in a machine for precise processing of nanometer units sensors installed at each unit process of a chemical plant, and sensors having various monitoring functions such as pressure, temperature, CO2 concentration and oxygen concentration sensor, automobile, etc.
- sensors installed at each unit process of a chemical plant
- sensors having various monitoring functions such as pressure, temperature, CO2 concentration and oxygen concentration sensor, automobile, etc.
- the importance of each sensor used in various facilities of important national key industries, such as various sensors directly connected to life used in ships, ships, airplanes, temperature and pressure sensors for nuclear power generation equipment, etc. can be understood without detailed explanation. It is an important component.
- the present invention has been invented to solve the above problems, the present invention receives an initial normal input signal from a specific sensor and modeling the sensor (where modeling includes modeling coefficients, types, and various variables), After the initial modeling, the diagnostic modeling value from the specific sensor is compared with the normal modeling output value to determine whether the sensor is faulty or failure type, and if the sensor fails, the user is notified to prevent the accident and prevent the sensor.
- An object of the present invention is to provide a general-purpose sensor self-diagnostic apparatus and its diagnostic method, which can ensure the safety and reliability of the system.
- a general-purpose sensor self-diagnostic apparatus comprises a sensor signal input unit for receiving a sensor signal from at least one sensor; An input data processing unit processing the sensor signal received from the sensor signal input unit into a value that can be used in a diagnostic apparatus; A modeling unit configured to model data processed by the input data processing unit to calculate a diagnostic modeling value; A memory for storing reference modeling values of sensor signals of the sensors that are previously modeled when the sensor is in a normal state, and storing failure type determination data for determining a failure type of the sensor; A fault diagnosis unit comparing a correlation between the diagnostic modeling value and a reference modeling value of the corresponding sensor stored in the memory to diagnose whether the corresponding sensor has a fault; And a failure type determination unit for determining a failure type of the corresponding sensor by comparing a correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data when the failure diagnosis unit determines that the corresponding sensor is a failure. Equipped.
- the failure type determination unit uses one or more of the continuity, shape, and delay value of the diagnostic modeling value to determine a failure type of the corresponding sensor.
- an output unit for receiving the data on the type of failure of the sensor from the failure type determination unit and outputs to the user using voice, text and graph.
- the apparatus may further include a communication unit configured to receive data regarding a failure type of the corresponding sensor from the failure type determination unit and transmit the data to the external device using a wired or wireless communication method.
- the input data processing unit converts the analog signal into a digital signal and transmits the analog signal to the modeling unit.
- a diagnostic method of a general-purpose sensor self-diagnosis apparatus includes: receiving a sensor signal from at least one sensor; (B) diagnosing a failure of a corresponding sensor by modeling an input sensor signal to calculate a diagnostic modeling value and comparing a correlation between the diagnostic modeling value and a reference modeling value of the corresponding sensor stored in a memory; And (C) determining a failure type of the corresponding sensor by comparing a correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data stored in the memory when it is determined that the corresponding sensor is a failure.
- the reference modeling value is a modeling value of a sensor signal of a corresponding sensor that is previously modeled when the corresponding sensor is in a normal state.
- the determining of the failure type of the corresponding sensor by comparing the correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data stored in the memory may include: continuity of the diagnostic modeling value to determine the failure type of the corresponding sensor; Preference is given to using one or more of, form and delay values.
- the method may further include (D) outputting data on the type of failure of the sensor to a user using voice, text, and graphs.
- the present invention receives an initial normal input signal from a specific sensor and models the sensor (where modeling includes modeling coefficients, types, and various variables, etc.), and then, from the specific sensor after the initial modeling.
- the diagnostic modeling value is compared with the normal modeling output value to determine whether there is a sensor failure or failure type, and if the sensor fails, the user is notified by preventing the accident and improving the safety and reliability of the system including the sensor. This has the advantage of facilitating the management of the automation system.
- the present invention has the advantage of easy to manage and use in the measurement sensor for continuous long-term monitoring of the environment, such as air pollution, water pollution, traffic volume, etc. using the advantage that can predict the aging of the sensor over time.
- FIG. 1 is a block diagram showing the internal configuration of a general-purpose sensor self-diagnostic apparatus according to a preferred embodiment of the present invention.
- FIG. 2 is an explanatory diagram illustrating a process in which the present invention operates.
- FIG. 3 is a flowchart illustrating a process of operating a general-purpose sensor self-diagnosis apparatus according to a preferred embodiment of the present invention.
- FIG. 1 is a block diagram showing the internal configuration of a general-purpose sensor self-diagnostic apparatus according to a preferred embodiment of the present invention.
- the general-purpose sensor self-diagnosis apparatus 100 of the present invention includes a sensor 110, a sensor signal input unit 120, an input data processing unit 121, a modeling unit 123, and a failure diagnosis unit ( 130, a failure type determination unit 140, a central processing unit 150, a power supply unit 160, a communication unit 170, a memory 180, and an output unit 190.
- At least one sensor 110 generates a sensor signal and provides the sensor signal to the sensor signal input unit 120 in real time.
- the sensor signal input unit 120 receives the sensor signal from the one or more sensors 110 in real time via wired / wireless and transmits the sensor signal to the input data processing unit 121.
- the sensor signal may be in the form of an analog signal represented by voltage or current, or direct current or sine wave, or may be a digital signal represented by pulse, RS232, RS485, or the like.
- the analog signal or digital signal may be input through a wired / wireless communication network.
- the input data processing unit 121 processes the sampling period and the size thereof in a promised form so that the central processing unit 150 can process the digital signal or the analog signal of the input sensor.
- the input data processing unit 121 converts the analog signal into a digital signal through an ADC and transmits the analog signal to the modeling unit 123.
- the modeling unit 123 models the input data to calculate a diagnostic modeling value.
- the modeling includes modeling coefficients, types, various variables, and the like.
- reference modeling values of sensor signals of the sensor 110 that are pre-modeled when the sensor 110 is in a normal state are stored, and failure type determination data for determining a failure type of the sensor 110. Is stored.
- the failure type determination data is classified and stored in a table according to various factors such as continuity, shape, and delay value of modeling values.
- the failure diagnosis unit 130 compares the correlation between the diagnostic modeling value and the reference modeling value of the corresponding sensor 110 stored in the memory 180 to determine the corresponding sensor. Diagnose the failure.
- the failure diagnosis unit 130 compares the correlation between the diagnostic modeling value and the reference modeling value and determines that the failure has occurred when the correlation exceeds the preset threshold range.
- the failure diagnosis unit 130 has an operating frequency of 40Mhz or more for modeling, it is preferable to use a floating point (floating point) that can be used. If there is no internal ADC, it is recommended to use an ADC with more than 10-BIT RESOLUTION for external mounting and accuracy.
- FIG. 2 is an explanatory diagram illustrating that the failure diagnosis unit 130 diagnoses the presence or absence of a failure when a sensor signal is input.
- the failure type determination unit 140 compares the correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data to determine the corresponding sensor. Determine the type of failure.
- the failure type determination unit 140 uses one or more of the continuity, shape, and delay value of the diagnostic modeling value to determine the failure type of the sensor 110. More specifically, the failure type determination unit 140 determines the failure type according to the corresponding range through the correlation comparison based on the failure type determination data stored in the memory 180.
- the communication unit 170 receives data on the type of failure of the sensor 110 from the failure type determination unit 140 and transmits the data to the external device using a wired or wireless communication method. For example, the communication unit 170 may transmit data regarding the type of failure of the sensor 110 to a higher level control device, a device maker, a designated A / S center, an insurance company, or the like through a communication network.
- RS232 and various wired / wireless communication networks may be used for communication with an external device.
- the output unit 190 receives data on the type of failure of the sensor 110 from the failure type determination unit 140 and outputs the data to the user using voice, text, and graphs.
- the CPU 150 determines whether a reference modeling value of the corresponding sensor is stored in the memory 180, and determines that the memory signal ( If there is no reference modeling value for the corresponding sensor 110 in 180, the sensor 110 is regarded as starting up for the first time, and the first data input from the corresponding sensor 110 is determined as the reference modeling value for memory. Save at 180.
- the central processing unit 150 when the central processing unit 150 receives sensor signals from a plurality of sensors, the central processing unit 150 performs a function of switching the plurality of input sensor signals. In other words, it functions as a multiplexer for processing a plurality of sensor signals.
- the power supply unit 160 processes the power input from the outside to be applied to the general-purpose sensor self-diagnosis apparatus 100.
- FIG. 3 is a flowchart illustrating a process of operating a general-purpose sensor self-diagnosis apparatus according to a preferred embodiment of the present invention.
- the sensor signal input unit 120 receives a sensor signal from one or more sensors 110 (step S100).
- the input data processing unit 121 processes the sampling period and the size thereof in a predetermined form so that the digital signal or the analog signal of the sensor input may be processed by the central processing unit 150.
- the input data processing unit 121 converts the analog signal into a digital signal through an ADC and transmits the analog signal to the modeling unit 123.
- the modeling unit 123 models the input data to calculate a diagnostic modeling value (step S110).
- the modeling includes modeling coefficients, types, various variables, and the like.
- the CPU 150 determines whether a reference modeling value for the corresponding sensor 110 exists in the memory 180 (step S110).
- the reference modeling value is a modeling value of a sensor signal of a corresponding modeled model when the corresponding sensor 110 is in a normal state.
- step 120 when there is no reference modeling value for the sensor 110 in the memory 180, it is assumed that the sensor 110 is first started, and data first input from the sensor 110 is assumed. It is determined as a reference modeling value and stored in the memory 180.
- the failure diagnosis unit 130 references the diagnostic modeling value and the corresponding sensor stored in the memory 180.
- the degree of failure of the corresponding sensor 110 is diagnosed by comparing the correlation between the modeling values (step S130).
- the failure type determination unit 140 compares the correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data stored in the memory 180. The failure type of the corresponding sensor 110 is determined (step S150).
- comparing the correlation between the diagnostic modeling value and the reference modeling value and the failure type determination data stored in the memory 180 to determine a failure type of the corresponding sensor 110 may include a failure type of the corresponding sensor 110. It is preferable to use one or more of the continuity, shape, and delay value of the diagnostic modeling value to determine.
- the central processing unit 150 processes the data regarding the failure type of the corresponding sensor 110 through the output unit 190 (step S160). ). At this time, it is preferable to output to the user using voice, text, and graph.
Abstract
Description
Claims (9)
- 하나 이상의 센서로부터 센서 신호를 입력받는 센서신호 입력부;상기 센서신호 입력부로부터 입력받은 센서신호를 진단 장치에서 사용할 수 있는 값으로 가공하는 입력 데이터 가공부;상기 입력 데이터 가공부에 의해 가공된 데이터를 모델링하여 진단 모델링 값을 산출하는 모델링부;상기 센서가 정상상태일 때 미리 모델링 된 상기 센서의 센서 신호에 대한 참조 모델링값을 저장하고, 상기 센서의 고장 유형을 판단하기 위한 고장유형판단 데이터를 저장하는 메모리;상기 진단 모델링 값과 상기 메모리에 저장된 해당 센서의 참조 모델링 값의 상관도를 비교하여 해당 센서의 고장 유무를 진단하는 고장 진단부; 및상기 고장 진단부에 의해 해당 센서가 고장인 것으로 판단되면, 상기 진단 모델링값과 상기 참조 모델링값의 상관도와 상기 고장유형판단 데이터를 비교하여 해당 센서의 고장 유형을 판단하는 고장유형 판단부;를 구비하는 것을 특징으로 하는 범용 센서 자가 진단 장치.
- 제1항에 있어서, 상기 고장유형 판단부는,해당 센서의 고장 유형을 판단하기 위해 상기 진단 모델링값의 연속성, 형태 및 딜레이값 중 하나 이상을 이용하는 것을 특징으로 하는 범용 센서 자가 진단 장치.
- 제1항에 있어서,상기 고장유형 판단부로부터 해당 센서의 고장 유형에 관한 데이터를 입력받아 음성, 텍스트 및 그래프를 이용하여 사용자에게 출력하는 출력부;를 더 구비하는 것을 특징으로 하는 범용 센서 자가 진단 장치.
- 제1항에 있어서,상기 고장유형 판단부로부터 해당 센서의 고장 유형에 관한 데이터를 입력받아 유선 또는 무선 통신방식을 이용하여 외부장치로 전송하는 통신부;를 더 구비하는 것을 특징으로 하는 범용 센서 자가 진단 장치.
- 제1항에 있어서, 상기 입력 데이터 가공부는,상기 하나 이상의 센서로 입력되는 센서 신호가 아날로그 신호인 경우, 상기 아날로그 신호를 디지털 신호로 변환하여 상기 모델링부에 전달하는 것을 특징으로 하는 범용 센서 자가 진단 장치.
- 하나 이상의 센서로부터 센서 신호를 입력받는 (A)단계;입력된 센서 신호를 모델링하여 진단 모델링값을 산출하고, 상기 진단 모델링값과 메모리에 저장된 해당 센서의 참조 모델링값의 상관도를 비교하여 해당 센서의 고장 유무를 진단하는 (B)단계; 및해당 센서가 고장인 것으로 판단되면, 상기 진단 모델링값과 상기 참조 모델링값의 상관도와 상기 메모리에 저장된 고장유형판단 데이터를 비교하여 해당 센서의 고장 유형을 판단하는 (C)단계;를 포함하는 범용 센서 자가 진단 장치의 진단 방법.
- 제6항에 있어서,상기 참조 모델링값은, 해당 센서가 정상상태일 때 미리 모델링된 해당 센서의 센서 신호에 대한 모델링값인 것을 특징으로 하는 범용 센서 자가 진단 장치의 진단 방법.
- 제6항에 있어서,상기 진단 모델링값과 상기 참조 모델링값의 상관도와 상기 메모리에 저장된 고장유형판단 데이터를 비교하여 해당 센서의 고장 유형을 판단하는 (C)단계는,해당 센서의 고장 유형을 판단하기 위해 상기 진단 모델링값의 연속성, 형태 및 딜레이값 중 하나 이상을 이용하는 것을 특징으로 하는 범용 센서 자가 진단 장치의 진단 방법.
- 제6항에 있어서,해당 센서의 고장 유형에 관한 데이터를 음성, 텍스트, 및 그래프를 이용하여 사용자에게 출력하는 (D)단계;를 더 포함하는 것을 특징으로 하는 범용 센서 자가 진단 장치의 진단 방법.
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JP2012541005A JP2013501945A (ja) | 2010-10-27 | 2010-10-28 | 汎用センサーの自己診断装置及びその診断方法 |
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- 2010-10-28 CN CN2010800061698A patent/CN102695943A/zh active Pending
- 2010-10-28 WO PCT/KR2010/007483 patent/WO2012057378A1/ko active Application Filing
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CN114323102B (zh) * | 2021-12-17 | 2024-01-19 | 中国重汽集团济南动力有限公司 | 一种sent接口传感器故障诊断方法、装置及系统 |
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CN102695943A (zh) | 2012-09-26 |
KR20120046821A (ko) | 2012-05-11 |
JP2013501945A (ja) | 2013-01-17 |
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