WO2017105181A1 - System and method for predicting faults in remotely distributed equipment - Google Patents
System and method for predicting faults in remotely distributed equipment Download PDFInfo
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- WO2017105181A1 WO2017105181A1 PCT/MX2015/000186 MX2015000186W WO2017105181A1 WO 2017105181 A1 WO2017105181 A1 WO 2017105181A1 MX 2015000186 W MX2015000186 W MX 2015000186W WO 2017105181 A1 WO2017105181 A1 WO 2017105181A1
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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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
Definitions
- the technical field of the present invention is electrical, since it is a system that measures and detects any anomaly by means of sensors installed in the equipment and communicates the data to a remote system that generates statistics and fault prediction reports.
- the present invention is about a system that monitors sensors placed in key parts of the equipment installed remotely distributed, said system collects the data of the sensors with what generates the durability statistics of each piece, estimating the useful life of each one even by regions with a different climate that could impact them, and then generate reports for their due attention anticipating failures due to the approach to that final point of life.
- FIGURES Figure 1 is a block diagram showing the scheme of the system.
- the Failure Prediction System in Remotely Distributed Equipment is composed of:
- the sensors (1) installed in key points of the equipment, consisting of measuring temperature and relative humidity, voltage or current, detection of voltage, current and continuity, and obtaining the global positioning coordinates (GPS).
- GPS global positioning coordinates
- Data capture module (2) which obtains the readings of the sensors and detectors and records them in its internal memory (7) to send them to a remote data processing system.
- Mobile data device (3) that receives the service reports for predictive and corrective maintenance and serves as a communications link in places where there is no access to a data network.
- the operation of the Failure Prediction System on Remotely Distributed Equipment works by recording the dates, hours, minutes and seconds each time a component of a machine is activated by detecting the voltage or applied current or continuity when it comes to switches, and keeps a periodic record of the existing ambient temperature and the temperature of those heat sensitive components.
- This register is frequency adjustable according to the needs of each machine application and is sent to a data processing system (5) that has a neural network (6) that classifies the information generated by regions of temperature and relative humidity , by type of machine monitored, by type of sensor, by type of service, by version or age of machine, by level of predominant voltage in the power supply, by frequency of use of the machine, by temperature reached by the monitored components, by time of operation of each component, by technical personnel that attends its maintenance and by point of sale or service where each machine operates.
- the Failure Prediction Method in Remotely Distributed Equipment consists of the following steps:
- the system operator adjusts the operating parameters of the system, such as:
- the data capture module (2) you have installed obtains a reading of each component and the GPS module by sending an initial status report to the processing system (5).
- the processing system (5) starts the registration for the new machine monitored in its database.
- the processing system (5) feeds the data to the neural network (6).
- the neural network (6) updates its outputs and reclassifies the information by emptying it into the database.
- the neural network (6) detects that a value is out of the expected, it generates an alarm message for registration in the database (8).
- the processing system (5) sends the alarm message to the mobile data terminal (3) that comes with the technical personnel assigned to the machine.
- the piece is delivered to the technical staff that will attend
- the data capture module (2) When the technical personnel check the machine, the data capture module (2) is detected by a wireless signal by the mobile data terminal (3) of the technical personnel, thus initiating the data exchange indicating the pieces that will be changed. Additionally when the place where the machine does not have access to a data network, the data capture module (2) uses said temporary connection to empty the information to the mobile data terminal (3) which at the time Access a data network will send them to the processing system (5).
- the data capture module (2) updates its status and sends the change of parts record to the processing system (5).
- the processing system (5) generates a report of the activity indicating the response time of the personnel, durability of each updated component when it was due to a fault, parts that were changed and the calculation of the cost of the service.
- the processing system opens a new record in the database feeding the neuron network! (6) for update.
Abstract
The invention relates to a system and method for predicting faults in remotely distributed equipment, comprising sensors installed in key points of the equipment operating in remote locations, which measure relative humidity and temperature, voltage or current, detect voltage, current and continuity, and obtain the global positioning coordinates (GPS), a module for capturing data obtained by the readers of the sensors and detectors, a remote data processing system that collects the data, a neural network, and a mobile data device, wherein the system registers the data from the sensors with the data capturing module installed in each remote machine and sends same to the data processing system that uses the neural network to classify the information in order to keep statistics of faults and predict the lifespan of each component, generating service reports via the mobile data terminal carried by the technical personnel. The object of the invention is to provide a tool which, in the event of having multiple machines operating remotely, permits the reduction or even removal of equipment downtime, or at least a reduction in the response times to fault reports, the optimisation of the supplies inventories, and the prevention of losses of resources and time of the technical personnel when attending to a report.
Description
SISTEMA Y MÉTODO DE PREDICCIÓN DE FALLAS EN EQUIPOS SYSTEM AND METHOD OF FAILURE FOR TEAM FAILURE
REMOTAMENTE DISTRIBUIDOS REMOTELY DISTRIBUTED
CAMPO TÉCNICO TECHNICAL FIELD
El campo técnico de la presente invención es el eléctrico, dado que trata de un sistema que mide y detecta cualquier anomalía mediante sensores instalados en los equipos y comunica los datos a un sistema remoto que genera estadísticas y reportes de predicción de fallas. The technical field of the present invention is electrical, since it is a system that measures and detects any anomaly by means of sensors installed in the equipment and communicates the data to a remote system that generates statistics and fault prediction reports.
ANTECEDENTES DE LA INVENCIÓN La operación de equipos distribuidos remotamente tiene como reto el minimizar la cantidad de fallas o en su defecto corregirlas a la brevedad a pesar de que el personal técnico no se encuentra cerca. Esto implica que se debe contar con suficiente personal para minimizar ios tiempos de atención lo que conlleva altos costos de operación, o en su defecto establecer programas de mantenimiento preventivo cuya eficiencia es un compromiso entre cantidad de refacciones con el consabido costo que ello implica y una alta frecuencia del servicio, que también implica un costo elevado. Una solución más eficiente es obtener datos de la operación de los equipos de aquellas piezas que resultan ser de mayor relevancia en su operación, que permitan generar estadísticas que sirvan para predecir la vida de un componente, con lo que se generen informes y reportes anticipándose a las fallas. La patente con número de registro US 6892317 B1 titulada "Systems and methods for failure prediction, diagnosis and remediation using data acquisition and feedback for a distributed electronic system" trata de un sistema que monitorea las condiciones de operación de los equipos en tiempo real en un entorno donde existe una red de comunicación. BACKGROUND OF THE INVENTION The operation of remotely distributed equipment has the challenge of minimizing the number of faults or failing to correct them as soon as possible despite the fact that technical personnel are not nearby. This implies that there must be enough personnel to minimize the attention time which entails high operating costs, or failing to establish preventive maintenance programs whose efficiency is a compromise between the number of spare parts with the usual cost involved and a high frequency of service, which also implies a high cost. A more efficient solution is to obtain data on the operation of the equipment of those parts that turn out to be of greater relevance in its operation, which allow generating statistics that serve to predict the life of a component, thereby generating reports and reports anticipating The failures. The patent with registration number US 6892317 B1 entitled "Systems and methods for failure prediction, diagnosis and remediation using data acquisition and feedback for a distributed electronic system" is a system that monitors the operating conditions of the equipment in real time in a environment where there is a communication network.
La presente invención trata de un sistema que monitorea sensores colocados en piezas clave de los equipos instalados distribuidos remotamente, dicho sistema colecta los datos de los sensores con lo que genera las estadísticas de durabilidad de cada pieza, estimando la vida útil de cada una incluso por regiones
con distinto clima que pudiera impactarles, para luego generar reportes para su debida atención anticipándose a fallas debidas a la aproximación a ese punto final de vida.
The present invention is about a system that monitors sensors placed in key parts of the equipment installed remotely distributed, said system collects the data of the sensors with what generates the durability statistics of each piece, estimating the useful life of each one even by regions with a different climate that could impact them, and then generate reports for their due attention anticipating failures due to the approach to that final point of life.
DESCRIPCIÓN DE LA INVENCIÓN DESCRIPTION OF THE INVENTION
Los detalles característicos de este novedoso Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos, se muestran claramente en la siguiente descripción y en los dibujos que se acompañan, siguiendo los mismos signos de referencia para indicar las partes y las figuras mostradas. Dichas figuras se describen brevemente: The characteristic details of this new System of Prediction of Faults in Remotely Distributed Equipment, are clearly shown in the following description and in the accompanying drawings, following the same reference signs to indicate the parts and figures shown. These figures are briefly described:
DESCRIPCIÓN DE FIGURAS La Figura 1 es un diagrama a bloques donde se muestra el esquema del sistema. DESCRIPTION OF FIGURES Figure 1 is a block diagram showing the scheme of the system.
DESCRIPCIÓN DETALLADA DE LA INVENCIÓN DETAILED DESCRIPTION OF THE INVENTION
Con referencia a dicha figura el Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos está compuesto por: With reference to this figure, the Failure Prediction System in Remotely Distributed Equipment is composed of:
a) Los sensores (1) instalados en puntos clave de los equipos, consistentes en medir temperatura y humedad relativa, voltaje o corriente, detección de voltaje, corriente y continuidad, y obtener las coordenadas de posicionamiento global (GPS). a) The sensors (1) installed in key points of the equipment, consisting of measuring temperature and relative humidity, voltage or current, detection of voltage, current and continuity, and obtaining the global positioning coordinates (GPS).
b) Módulo de captura de datos (2), que obtiene las lecturas de los sensores y detectores y los registra en su memoria interna (7) para enviarlos a un sistema de procesamiento de datos remoto. b) Data capture module (2), which obtains the readings of the sensors and detectors and records them in its internal memory (7) to send them to a remote data processing system.
c) Sistema de procesamiento de datos (5) que colecta los datos y genera la estadística de cada equipo remoto. c) Data processing system (5) that collects the data and generates the statistics of each remote equipment.
d) Dispositivo de datos móvil (3) que recibe los reportes de atención para mantenimiento predictivo y correctivo y que funge como enlace de comunicaciones en lugares donde no se cuenta con acceso a una red de datos. d) Mobile data device (3) that receives the service reports for predictive and corrective maintenance and serves as a communications link in places where there is no access to a data network.
La operación del Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos funciona a base de registrar las fechas, horas, minutos y segundos cada vez que un componente de una máquina es activado detectando el voltaje o
la corriente aplicada o la continuidad cuando se trata de interruptores, y lleva un registro periódico de la temperatura ambiente existente y la temperatura de aquellos componentes sensibles al calor. Dicho registro es de frecuencia ajustable de acuerdo a necesidades de cada aplicación de las máquinas y es enviado a un sistema de procesamiento de datos (5) que cuenta con una red neuronal (6) que clasifica la información generada por regiones de temperatura y humedad relativa, por tipo de máquina monitoreada, por tipo de sensor, por tipo de servicio, por versión o antigüedad de máquina, por nivel de voltaje predominante en el suministro eléctrico, por frecuencia de uso de la máquina, por temperatura alcanzada por los componentes monitoreados, por tiempo de operación de cada componente, por personal técnico que atiende su mantenimiento y por punto de venta o de servicio donde opera cada máquina. The operation of the Failure Prediction System on Remotely Distributed Equipment works by recording the dates, hours, minutes and seconds each time a component of a machine is activated by detecting the voltage or applied current or continuity when it comes to switches, and keeps a periodic record of the existing ambient temperature and the temperature of those heat sensitive components. This register is frequency adjustable according to the needs of each machine application and is sent to a data processing system (5) that has a neural network (6) that classifies the information generated by regions of temperature and relative humidity , by type of machine monitored, by type of sensor, by type of service, by version or age of machine, by level of predominant voltage in the power supply, by frequency of use of the machine, by temperature reached by the monitored components, by time of operation of each component, by technical personnel that attends its maintenance and by point of sale or service where each machine operates.
El Método de Predicción De Fallas En Equipos Remotamente Distribuidos, consta de los siguientes pasos: The Failure Prediction Method in Remotely Distributed Equipment consists of the following steps:
El operador del sistema ajusta los parámetros de operación del sistema, como lo son: The system operator adjusts the operating parameters of the system, such as:
a. Frecuencia de registro de datos de cada tipo de: to. Frequency of data recording of each type of:
i. Componente. i. Component.
Aplicación. Application.
Temperatura ambiente predominante. Predominant ambient temperature.
iv. Humedad relativa predominante iv. Predominant relative humidity
v. Personal técnico que atiende el mantenimiento de la máquina. v. Technical staff that attends the maintenance of the machine.
vi. Altura sobre el nivel del mar. saw. Height above sea level.
vii. Región (costa, montaña u otro). vii. Region (coast, mountain or other).
b. Clasificación de Alarmas: b. Alarm Classification:
i. En tiempo real: aquellas que requiera que el personal técnico atienda inmediatamente. i. In real time: those that require technical staff to attend immediately.
ii. Al inicio, al final o a la mitad de la jornada, aquellas que el personal técnico puede programar su visita. ii. At the beginning, at the end or in the middle of the day, those that the technical staff can schedule your visit.
c. Personal técnico que atenderá.
d. Etiquetado de Coordenadas GPS para identificación de puntos de venta u operación. C. Technical staff that will attend. d. GPS Coordinate Labeling for identification of points of sale or operation.
2. Al encender el sistema en una máquina remota, el módulo de captura de datos (2) que tiene instalado obtiene una lectura de cada componente y del módulo GPS enviando un reporte de estado inicial al sistema de procesamiento (5). 2. When you turn on the system on a remote machine, the data capture module (2) you have installed obtains a reading of each component and the GPS module by sending an initial status report to the processing system (5).
3. El sistema de procesamiento (5) inicia el registro para la nueva máquina monitoreada en su base de datos. 3. The processing system (5) starts the registration for the new machine monitored in its database.
4. Al finalizar el periodo establecido por el operador del sistema, el sistema de procesamiento (5) alimenta los datos a la red neuronal (6). 4. At the end of the period established by the system operator, the processing system (5) feeds the data to the neural network (6).
5. La red neuronal (6) actualiza sus salidas y reclasifica la información vaciándola en la base de datos. 5. The neural network (6) updates its outputs and reclassifies the information by emptying it into the database.
6. Si la red neuronal (6) detecta que un valor está fuera de lo esperado genera un mensaje de alarma para el registro en la base de datos (8). 6. If the neural network (6) detects that a value is out of the expected, it generates an alarm message for registration in the database (8).
7. El sistema de procesamiento (5) envia el mensaje de alarma a la terminal de datos móvil (3) que trae consigo el personal técnico asignado a la máquina. 7. The processing system (5) sends the alarm message to the mobile data terminal (3) that comes with the technical personnel assigned to the machine.
8. Si la alarma implica el cambio de un componente también es enviada al sistema de abasto de refacciones: 8. If the alarm involves the change of a component, it is also sent to the spare parts supply system:
a. Se genere una salida del almacén, to. A warehouse exit is generated,
b. Se le entrega la pieza al personal técnico que atenderá b. The piece is delivered to the technical staff that will attend
c. Se actualizan existencias. C. Stocks are updated.
9. Cuando el personal técnico hace la revisión de la máquina, el módulo de captura de datos (2) es detectado mediante una señal inalámbrica por la terminal de datos móvil (3) del personal técnico con lo que inicia el intercambio de datos indicando las piezas que se cambiarán. Adicionalmente cuando el lugar donde la máquina no cuenta con el acceso a una red de datos, el módulo de captura de datos (2) utiliza dicha conexión temporal para vaciar la información a la terminal de datos móvil (3) la cual en el momento que acceda a una red de datos los enviará al sistema de procesamiento (5). 9. When the technical personnel check the machine, the data capture module (2) is detected by a wireless signal by the mobile data terminal (3) of the technical personnel, thus initiating the data exchange indicating the pieces that will be changed. Additionally when the place where the machine does not have access to a data network, the data capture module (2) uses said temporary connection to empty the information to the mobile data terminal (3) which at the time Access a data network will send them to the processing system (5).
10. El módulo de captura de datos (2) actualiza su estado y envía el registro del cambio de piezas al sistema de procesamiento (5).
11. El sistema de procesamiento (5) genera un reporte de la actividad indicando tiempo de respuesta del personal, durabilidad de cada componente actualizada cuando se debió a una falla, piezas que se cambiaron y el cálculo del costo del servicio. 10. The data capture module (2) updates its status and sends the change of parts record to the processing system (5). 11. The processing system (5) generates a report of the activity indicating the response time of the personnel, durability of each updated component when it was due to a fault, parts that were changed and the calculation of the cost of the service.
12. En caso de tratarse de una situación novedosa o sin registro previo, el sistema de procesamiento abre un nuevo registro en la base de datos alimentando a la red neurona! (6) para su actualización.
12. In the case of a novel situation or without prior registration, the processing system opens a new record in the database feeding the neuron network! (6) for update.
Claims
1. Un Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos caracterizado porque está compuesto por 1. A Failure Prediction System in Remotely Distributed Equipment characterized in that it is composed of
a. Sensores instalados en puntos clave de los equipos, porque miden la temperatura y humedad relativa, voltaje, corriente, detección de voltaje, detección de corriente y continuidad, y obtienen las coordenadas de posicionamiento global (GPS) to. Sensors installed at key points of the equipment, because they measure the temperature and relative humidity, voltage, current, voltage detection, current detection and continuity, and obtain the global positioning coordinates (GPS)
b. Un Módulo de captura de datos, que obtiene las lecturas de los sensores y detectores y los registra en su memoria interna para enviarlos al sistema de procesamiento de datos. b. A Data Capture Module, which obtains the readings of the sensors and detectors and records them in its internal memory to send them to the data processing system.
c. Un Sistema de procesamiento de datos que colecta los datos y genera la estadística de cada equipo remoto. C. A data processing system that collects data and generates the statistics of each remote equipment.
d. Un Dispositivo de datos móvil que recibe los reportes de atención para mantenimiento predictivo y correctivo. d. A mobile data device that receives attention reports for predictive and corrective maintenance.
2. Un Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos como el de la reivindicación 1 caracterizado porque funciona a base de registrar las fechas/ horas, minutos y segundos cada vez que un componente de una máquina es activado detectando el voltaje o la corriente aplicada o la continuidad cuando se trata de interruptores, porque lleva un registro periódico de la temperatura ambiente existente y la temperatura de aquellos componentes sensibles al calor, porque dicho registro es de periodicidad ajustable de acuerdo a necesidades de cada aplicación de las máquinas y porque es enviado a un sistema de procesamiento de datos que cuenta con una red neuronal que clasifica la información generada por regiones de temperatura y humedad relativa, por tipo de máquina monitoreada, por tipo de sensor, por tipo de servicio, por versión o antigüedad de máquina, por nivel de voltaje predominante en el suministro eléctrico, por frecuencia de uso de la máquina, por temperatura alcanzada por los componentes monitoreados, por tiempo de operación de
cada componente, por personal técnico que atiende su mantenimiento y por punto de venta o de servicio donde opera cada máquina. 2. A Failure Prediction System in Remotely Distributed Equipment as in claim 1 characterized in that it works by recording the dates / hours, minutes and seconds each time a component of a machine is activated by detecting the voltage or current applied or the continuity when it comes to switches, because it keeps a periodic record of the existing ambient temperature and the temperature of those heat sensitive components, because said register is of adjustable periodicity according to the needs of each application of the machines and because it is sent to a data processing system that has a neural network that classifies the information generated by regions of temperature and relative humidity, by type of machine monitored, by type of sensor, by type of service, by version or age of machine, by predominant voltage level in the power supply, by frequency of use of the machine, by temperature ture reached by the monitored components, by operating time of each component, by technical personnel that attends its maintenance and by point of sale or service where each machine operates.
3. Un Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos como el de la reivindicación 1 caracterizado porque cuando el lugar donde la máquina no cuenta con el acceso a una red de datos, el módulo de captura de datos utiliza dicha conexión temporal para vaciar la información a la terminal de datos móvil la cual en el momento que acceda a una red de datos los enviará al sistema de procesamiento. 3. A Failure Prediction System in Remotely Distributed Equipment as in claim 1 characterized in that when the place where the machine does not have access to a data network, the data capture module uses said temporary connection to empty the information to the mobile data terminal which at the time you access a data network will send them to the processing system.
4. Un Método del Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos caracterizado porque consta de los siguientes pasos: 4. A Failure Prediction System Method in Remotely Distributed Equipment characterized in that it consists of the following steps:
a. El operador del sistema ajusta los parámetros de operación del sistema, como lo son: to. The system operator adjusts the operating parameters of the system, such as:
i. Frecuencia de registro de datos de cada tipo de: i. Frequency of data recording of each type of:
• Componente. • Component.
• Aplicación. • Application.
• Temperatura ambiente predominante. • Predominant ambient temperature.
• Humedad relativa predominante • Predominant relative humidity
• Personal técnico que atiende el mantenimiento de la máquina. • Technical staff that attends the maintenance of the machine.
• Altura sobre el nivel del mar. • Height above sea level.
• Región (costa, montaña u otro). • Region (coast, mountain or other).
ii. Clasificación de Alarmas: ii. Alarm Classification:
• En tiempo real: aquellas que requiera que el personal técnico atienda inmediatamente. • In real time: those that require the technical staff to attend immediately.
• Al inicio, al final o a la mitad de la jornada, aquellas que el personal técnico puede programar su visita. • At the beginning, at the end or in the middle of the day, those that the technical staff can schedule your visit.
• Personal técnico que atenderá. • Technical staff that will attend.
iii. Etiquetado de Coordenadas GPS para identificación de puntos de venta u operación. iii. GPS Coordinate Labeling for identification of points of sale or operation.
b. Al encender el sistema en una máquina remota, el módulo de captura de datos que tiene instalado obtiene una lectura de cada componente y del módulo GPS enviando un reporte de estado inicial al sistema de procesamiento.
c. El sistema de procesamiento inicia el registro para la nueva máquina monitoreada en su base de datos. b. When you turn on the system on a remote machine, the data capture module you have installed obtains a reading of each component and the GPS module by sending an initial status report to the processing system. C. The processing system starts the registration for the new machine monitored in its database.
d. Al finalizar el periodo establecido por el operador del sistema, el sistema de procesamiento alimenta los datos a la red neuronal. d. At the end of the period established by the system operator, the processing system feeds the data to the neural network.
e. La red neuronal actualiza sus salidas y reclasifica la información vaciándola en la base de datos. and. The neural network updates its outputs and reclassifies the information by emptying it into the database.
f. Si la red neuronal detecta que un valor está fuera de lo esperado genera un mensaje de alarma para el registro en la base de datos. g. El sistema de procesamiento envía el mensaje de alarma a la terminal de datos móvil que trae consigo el personal técnico asignado a la máquina. F. If the neural network detects that a value is out of the expected it generates an alarm message for registration in the database. g. The processing system sends the alarm message to the mobile data terminal that comes with the technical personnel assigned to the machine.
h. Si la alarma implica el cambio de un componente también es enviada al sistema de abasto de refacciones: h. If the alarm involves changing a component, it is also sent to the spare parts supply system:
i. Se genere una salida del almacén, i. A warehouse exit is generated,
j. Se le entrega la pieza al personal técnico que atenderá j. The piece is delivered to the technical staff that will attend
k. Se actualizan existencias. k. Stocks are updated.
5. Un Método del Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos como el de la reivindicación 2 caracterizado porque consta cuando el personal técnico hace la revisión de la máquina el módulo de captura de datos es detectado mediante una señal inalámbrica por la terminal de datos móvil del personal técnico con lo que inicia el intercambio de datos indicando las piezas que se cambiarán, porque El módulo de captura de datos actualiza su estado y envía el registro del cambio de piezas al sistema de procesamiento. 5. A Failure Prediction System Method in Remotely Distributed Equipment such as that of claim 2 characterized in that when the technical personnel check the machine the data capture module is detected by a wireless signal by the data terminal mobile of the technical personnel with what initiates the exchange of data indicating the pieces that will be changed, because The data capture module updates its status and sends the change of parts record to the processing system.
6. Un Método del Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos como el de la reivindicación 3 caracterizado porque el sistema de procesamiento genera un reporte de la actividad indicando tiempo de respuesta del personal, durabilidad de cada componente actualizada cuando se debió a una falla, piezas que se cambiaron y el cálculo del costo del servicio. 6. A Failure Prediction System Method in Remotely Distributed Equipment as in claim 3 characterized in that the processing system generates a report of the activity indicating personnel response time, durability of each updated component when it was due to a failure , parts that were changed and the calculation of the cost of the service.
7. Un Método del Sistema De Predicción De Fallas En Equipos Remotamente Distribuidos como el de la reivindicación 3 caracterizado porque ante una situación novedosa o sin registro previo, el sistema de procesamiento abre
un nuevo registro en la base de datos alimentando a la red neuronal para su actualización.
7. A Failure Prediction System Method in Remotely Distributed Equipment as in claim 3 characterized in that in the event of a novel situation or without prior registration, the processing system opens a new record in the database feeding the neural network for updating.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/MX2015/000186 WO2017105181A1 (en) | 2015-12-14 | 2015-12-14 | System and method for predicting faults in remotely distributed equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/MX2015/000186 WO2017105181A1 (en) | 2015-12-14 | 2015-12-14 | System and method for predicting faults in remotely distributed equipment |
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| Publication Number | Publication Date |
|---|---|
| WO2017105181A1 true WO2017105181A1 (en) | 2017-06-22 |
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| Application Number | Title | Priority Date | Filing Date |
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| PCT/MX2015/000186 WO2017105181A1 (en) | 2015-12-14 | 2015-12-14 | System and method for predicting faults in remotely distributed equipment |
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| Country | Link |
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| WO (1) | WO2017105181A1 (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107909116A (en) * | 2017-12-07 | 2018-04-13 | 无锡小天鹅股份有限公司 | Washing machine fault recognition method and device |
| CN113065733A (en) * | 2020-12-15 | 2021-07-02 | 江苏苏星资产管理有限公司 | Electrical asset management method based on artificial intelligence |
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| US5566092A (en) * | 1993-12-30 | 1996-10-15 | Caterpillar Inc. | Machine fault diagnostics system and method |
| US20010001851A1 (en) * | 1998-09-15 | 2001-05-24 | Piety Kenneth R. | Database wizard |
| US7308322B1 (en) * | 1998-09-29 | 2007-12-11 | Rockwell Automation Technologies, Inc. | Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis |
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| CN107909116A (en) * | 2017-12-07 | 2018-04-13 | 无锡小天鹅股份有限公司 | Washing machine fault recognition method and device |
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