CN105511450A - Method for remotely monitoring and predicting fault of forklift loader - Google Patents
Method for remotely monitoring and predicting fault of forklift loader Download PDFInfo
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- CN105511450A CN105511450A CN201511020476.2A CN201511020476A CN105511450A CN 105511450 A CN105511450 A CN 105511450A CN 201511020476 A CN201511020476 A CN 201511020476A CN 105511450 A CN105511450 A CN 105511450A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
- G05B23/0235—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions based on a comparison with predetermined threshold or range, e.g. "classical methods", carried out during normal operation; threshold adaptation or choice; when or how to compare with the threshold
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24033—Failure, fault detection and isolation
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Abstract
The invention provides a method for remotely monitoring and predicting the fault of a forklift loader. A pressure sensor, a temperature sensor, a vibration sensor, and a current/voltage sensor are installed on corresponding components of the forklift loader. A vehicular smart terminal acquires the status data of the corresponding sensors of the components and is proactively connected with a data center server. The data center server performs data interaction and instruction communication with the vehicular smart terminal via the Internet and stores acquired data in a corresponding data table. A data center monitor program periodically scans and compares historical data samples in a database, checks whether a fault exists in combination with an equipment maintenance log and component fatigue information, predicts components possibly generating faults, communicates with a user if finding out a abnormal condition, guides a forklift loader driver to troubleshooting the faults, prepares spare components and makes maintenance preparation, shortens detection, component preparation, transport, and maintenance time consumed between a shutdown caused by the faults and a restart as much as possible, and decreases losses caused by the faults.
Description
Technical field
The invention belongs to engineering machinery applied technical field.Specifically relate to the method for the monitoring of stone digging forklift truck remote failure and prediction, according to the forklift truck unit status geodata and services central database historical sample data that current remote gathers, and parts fatigue record etc. compare, judge and the damaged condition that prediction forklift truck parts may occur, and remote notification user confirms, carry out spare part ahead of time and carry out maintenance preparation, shorten forklift truck as far as possible from occurring that unit failure shuts down servicing time needed for task again, the economic loss that maximum reduction device damage is brought, and improve forklift truck manufacturer after sale service responding ability.
Background technology
Forklift truck is the construction machinery product that shovel loader segments market, forklift truck integrates mechanical, electrical, instrument, liquid and numerical information, have efficient, energy-conservation, intelligence, good cross-country ability, use flexible, safe and reliable, cost performance advantages of higher.Can replace fork truck, truck crane, excavator for the scraper equipment of the waste material of stone digging waste stock ground handling, change scraper bowl and can be stone material mining area and cut into a mountain and repair the roads, the surface layer earthwork of scraper mine, realizes its " dual-use " function.Also for there is disaster area or important use such as wartime removing road roadblock and short distance scraper goods and materials etc.At present, stone digging forklift truck intelligence degree is not high, and from the existing documents and materials of inquiry and publication situation, also not about the report that the monitoring of forklift truck remote failure is relevant to prediction, therefore this technology has very high novelty and practicality.
The job specification of forklift truck determines this equipment and is generally positioned at remote mountain areas, from city and maintenace point distance all distant, once some parts damages of forklift truck and need to repair or replace, certainly will be able to not be resolved in time, thus affect whole duration progress, cause a large amount of economic losses.For stone digging forklift truck, its after sale service and maintenance management are all the problems perplexing each forklift truck producer all the time.
Existing stone digging forklift truck intelligent level is not high, lack failure monitoring and predicting means, normally manufacturer regularly arrives user scene and detects on the spot, judge whether forklift truck parts exist damaged condition, or again by user's proactive notification manufacturer after pending fault occurs, this mode lacks real-time dynamic monitoring and prediction, forklift truck parts degree of fatigue can not be understood in time, also just cannot fix a breakdown timely, raising equipment effective storage life, bring economic loss because of shutdown not only to user, and make manufacturer have to spend large price to set up huge after sale service site to improve emergency response capability after sale.
Summary of the invention
The technical problem to be solved in the present invention, be a kind of method providing forklift truck remote failure to monitor and predict, realize the data acquisition of long-range stone digging forklift truck unit status, wireless transmission, and stored by data center server, the regular comparison database historical data sample of data center server, bonded block maintenance log and tired information, Timeliness coverage also predicts the parts damages situation that may occur, as unusual circumstance, then lead to equipment use box drain and confirm, and carry out maintenance preparation spare part ahead of time.
The present invention is achieved in that the method for the monitoring of a kind of forklift truck remote failure and prediction, and described method is:
The data acquisition of forklift truck unit status and transmission: setting pressure sensor, temperature sensor, shock sensor, current/voltage sensor on forklift truck parts, be connected with each sensor by a vehicle intelligent terminal, each parts respective sensor status data is gathered by vehicle intelligent terminal, vehicle intelligent terminal initiatively connects with a data center server, finishing equipment registration, status data transfers and accept the instruction that data center server assigns;
Data center server communication connection, failure monitoring and failure prediction: the registration table of data center server management vehicle intelligent terminal equipment, the tables of data of unit status table, maintenance log table, performance prediction table and Equipments Setting table, and carry out the reception and registration of data interaction and instruction with vehicle intelligent terminal by network, the data obtaining forklift truck are stored into corresponding data table;
Fault handling: data center server is detected by bug monitor and predictor and predicts the data of forklift truck, after data are out of order, assign to the vehicle intelligent terminal of remote failure forklift truck with instruction type, vehicle intelligent terminal will stop continuing to run forklift truck with sound, light or electric form warning forklift truck operating personnel; Meanwhile, after sale, department maintainer will contact forklift truck user after sale in data center server notice manufacturer, determine trouble unit and fault degree, providing handling suggestion by linking up.
Further, described data center server communication connection, failure monitoring and failure prediction: be specially further: data center server is in communication intercept state all the time, wait for the vehicle intelligent terminal communication connection request of long-range forklift truck, after receiving communication connection request, forklift truck vehicle intelligent terminal is registered, both sides set up data transmission connection subsequently, and remote intelligent terminal is by data connection link transmission forklift truck status data; Whether the bug monitor cycle detection forklift truck parts in data center server break down, and are then enter fault handling; No, failure prediction program then in data center server will according to forklift truck historical failure data, historical failure monitoring judgement data, forklift truck current operating environment parameter, the normal service data of parts, the fault that will occur is predicted, given threshold value is exceeded if predicted the outcome, then parts can break down, and enter fault handling.
Further, described environmental parameter comprises: temperature, humidity, atmospheric pressure or sea level elevation.
Further, the data acquisition of described forklift truck unit status and transmission comprise further: the sensing data gathering the pressure transducer on forklift truck parts, temperature sensor, shock sensor, current/voltage sensor with cycle T, and denoising is carried out to image data, remove noise data and redundant data, then the digital quantity signal of collection or analog signals are changed into the binary data that computing machine can process; Meanwhile, with the data packet form consulted in advance, forklift truck unit status data are encapsulated; WIFI or the GSM mode of adopting vehicle intelligent terminal enters the Internet Internet, initiatively send the telecommunication connection request with data center server, after data center server listens to communication connection request, forklift truck parts are registered, and negotiation communication package form, both sides set up data transmission channel subsequently, coordinate transmit leg and take over party's beat, complete unit status data transmission procedure by Handshake Protocol.
Further, described data center server communication connection, failure monitoring and failure prediction comprise further:
The remote connection request processing the vehicle intelligent terminal be installed in forklift truck is responsible for, the registration table of vehicle intelligent terminal equipment and the maintenance of Equipments Setting table by a communication connection program; For the connection request of unregistered forklift truck parts after authentication, it is registered, and give its distributing equipment ID; Communication connection process accepts long-distance vehicular intelligent terminal by the forklift truck unit status data of Internet Transmission, and is stored in corresponding data table according to device id; Communication connection program is also responsible for assigning steering order to long-distance vehicular intelligent terminal, is reported to the police by sound, light or electric form, guides forklift truck operator to investigate fault;
Bug monitor is whether the time interval detection forklift truck parts set break down, first bug monitor obtains the device id of a long-range forklift truck vehicle intelligent terminal from the registration table of vehicle intelligent terminal equipment, then from unit status table, status data corresponding to these parts of No. ID is read according to No. ID, then from Equipments Setting table, the normal operational data of corresponding component is taken out, judge whether these parts break down or occur damaging according to the result of comparison, if there is damage or fault, judge its damaged condition or fault rank; Bug monitor cycle unit status monitored results is dynamic stored in database table in data format, for failure prediction program;
Failure prediction program is according to data historian data sample, the status data of Breakdown Maintenance record and current collection, predict the parts that there will be fault, analyze judge back to cause equipment affect grade, then to be processed by data center server warning and handling procedure.
Further, described fault handling comprises further: by bug monitor and failure prediction program, data center server finds that long-range forklift truck parts are current and there is fault, or break down in the future, data center server cycle warning operator, inform that its long-range forklift truck parts can exist fault or pole has and can break down, this situation is put on record by operator on duty, and notifies department after sale immediately, and the department after sale that hands to processes, on the other hand, data center server reads this device network address relevant information from the registration table of vehicle intelligent terminal equipment, by network signals vehicle intelligent terminal, forklift truck parts in place have broken down or have broken down in the future, start timer to go forward side by side row relax, vehicle intelligent terminal controls alarming device with sound, light, the form of electricity is reported to the police, until forklift truck operating personnel know fault occur maybe can break down after, shut-down operation forklift truck equipment also manually removes setting of reporting to the police, broken down by forklift truck operating personnel announcement apparatus owner subsequently and maybe can break down, after-sales service department of forklift truck manufacturer and forklift truck user know and have broken down or broken down in the future, and both sides are consulted by telephonic communication, and department is by instructing user to inquire about and confirming trouble location and degree after sale, propose maintenance program.
Further, described forklift truck and data center server telecommunication and data transmit specifically comprise the steps into:
Step 11: the vehicle intelligent terminal be installed in forklift truck initiatively initiates the connection request with data center server, and request data package comprises device id, timestamp information; Data center server is in listening state all the time, once receive long-distance vehicular intelligent terminal communication connection request, then resolve the communication connection request packet received, equipment numbering and timestamp, and judge whether registration, and if unregistered, this forklift truck equipment of new registration; After confirming registration, confirm to the loopback of long-distance vehicular intelligent terminal and require that long-distance vehicular intelligent terminal sends communications parameter information; After long-distance vehicular intelligent terminal receives data center's loopback confirmation, read messaging parameter and again send to data center server, the messaging parameter received and support messaging parameter compare by data center server, to long-distance vehicular intelligent terminal confirmation message back, so far, communications connection procedure has been set up;
Step 12: when long-distance vehicular intelligent terminal has data to transmit, first send data transmission connection request to data center server, after data center server oracle listener receives data transfer request, check whether data center server is ready to receive, if be ready to receive, then send data acknowledge to long-distance vehicular intelligent terminal; Long-distance vehicular intelligent terminal then continues to data center server transmit block state data packets after receiving data center server confirmation; If long-distance vehicular Intelligent terminal data is sent, maybe to be in dormant state, then send data transfer termination request to data center server, after pending data central server confirms, this data transfer termination.
Further, the monitoring of forklift truck remote failure specifically comprises the steps:
Step 21: data center server starts timer internal timing, when arriving pre-designed cycle then startup separator watchdog routine, from the registration table of vehicle intelligent terminal equipment, order fetch equipment ID, reads corresponding forklift truck status data according to No. ID, enters step 22;
Step 22: bug monitor reading timing cycle this ID interior corresponding forklift truck engine oil temperature is minimum, the highest, mean value, and compare with engine temperature normality threshold, if exceed normality threshold, engine motor oil temperature anomaly, enters exception handling procedure; Otherwise, continue to perform step 23;
Step 23: the corresponding forklift truck engine oil pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with engine pressure normality threshold, if exceed normality threshold, engine oil pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 24;
Step 24: the corresponding forklift truck wheel box of bug monitor reading timing cycle this ID interior, torque converter pressure are minimum, the highest, mean value, and compare with two pressure changeable normality threshold, if exceed normality threshold, two pressure changeable is abnormal, enters exception handling procedure; Otherwise, continue to perform step 25;
Step 25: the corresponding forklift truck water tank temperature of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compares with water tank temperature normality threshold, if exceed normality threshold, water tank temperature is abnormal, enters exception handling procedure; Otherwise, continue to perform step 26;
Step 26: bug monitor reading timing cycle this ID interior corresponding forklift truck equipment system pressure is minimum, the highest, mean value, and compare with equipment system pressure normality threshold, if exceed normality threshold, equipment system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 27;
Step 27: the corresponding forklift truck brake system pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with brake system pressure normality threshold, if exceed normality threshold, brake system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 28;
Step 28: the corresponding forklift truck vibration frequency of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with forklift truck vibration frequency normality threshold, if exceed normality threshold, forklift truck vibration frequency is abnormal, enters exception handling procedure; Otherwise, continue to perform step 29;
Step 29: if forklift truck parts exist fault, then process.Meanwhile, continue to read next No. ID corresponding forklift truck status data, fault detect is carried out in circulation.
Further, the prediction of forklift truck remote failure specifically comprises the steps:
Step 31: data center server bug monitor detects that long-range forklift truck parts are current and there is not fault, then startup separator predictor, first failure prediction program reads No. ID, the registration of forklift truck from the registration table of vehicle intelligent terminal equipment, enters step 32;
Step 32: failure prediction program reads part history fault data, historical failure monitoring judgement data, forklift truck current operating environment parameter, the normal service data of parts of this forklift truck respectively according to No. ID, registration from the registration table of malfunction history data table, block supervises historical data table, facility environment tables of data, vehicle intelligent terminal equipment, using these data as fundamentals of forecasting, enter step 33;
Step 33: failure prediction program carries out failure prediction according to the four class data read in step 32 to forklift truck parts, draws fault rate value, enters step 34;
Step 34: failure prediction result and predetermined threshold value compare by failure prediction program, if be greater than predetermined threshold value, illustrate that long-range forklift truck parts break down in the near future, enter fault treating procedure subsequently, otherwise illustrate that long-range forklift truck parts working order is good.
Tool of the present invention has the following advantages: forklift truck remote failure monitoring of the present invention can realize forklift truck remote failure automatic monitoring and prediction with Forecasting Methodology, and reported to the police at forklift truck end with sound, optical, electrical form by data center server according to prediction scheme, personnel initiatively confirm trouble unit and trouble spot with user after sale simultaneously, shift to an earlier date spare part and carry out maintenance and prepare, very big raising fault handling efficiency, saves fault handling time.The present invention independently gathers forklift truck parts real-time status data, and stored to data center server by Internet Transmission, data center server is according to parts current status data, data historian sample data and parts normal condition data, the generation of cycle monitoring fault, and according to parts for maintenance historical record, cycle monitoring result data, the probability that each parts will break down is predicted, when discovery fault then adopts prediction scheme to process by artificial intelligence approach.The method is while breaking down, fault handling response can be made, the generation of fault can also be predicted simultaneously, prediction scheme is selected to process according to probability of happening, for the stone digging forklift truck of work remote environments, human cost, time cost can greatly be saved, improve after-sales service Ability of emergency management.
Accompanying drawing explanation
Fig. 1 is the monitoring of forklift truck remote failure and prognoses system frame diagram;
Fig. 2 is forklift truck and data center server telecommunication and data transmission stream journey figure;
Fig. 3 is forklift truck remote failure overhaul flow chart;
Fig. 4 is forklift truck remote failure prediction process flow diagram;
Fig. 5 is forklift truck troubleshooting process figure.
Embodiment
Refer to shown in Fig. 1 to Fig. 5, the present invention is the method for the monitoring of a kind of forklift truck remote failure and prediction, and this forklift truck is especially for stone digging forklift truck, and described method is:
Vehicle-mounted intelligent terminal is installed in the forklift truck being operated in remote districts, pressure transducer on this equipment and forklift truck parts, temperature sensor, shock sensor, current/voltage sensor sensor device is connected, the unit information of taken at regular intervals sensor senses, change-over circuit changes into the digital quantity signal collected and analog signals the data that computing machine can store, and according to the data layout that prior and data center server consult, packing forming member state data packets is carried out to image data, and enclose the information such as present system time information and vehicle intelligent terminal device numbering.Vehicle intelligent terminal is interconnected by the modes such as WIFI, GSM or 3G and Internet network, initiatively to the data center server request of establishing a communications link and data transmission connection request, the connection request of the passive processing remote intelligent terminal of data center server, after receiving a communication connection request, if this equipment is also unregistered, access arrangement registration process, and the work such as negotiation data encapsulation format, transfer rate, software version.If equipment is registered, then loopback ACK confirmation, receives after ACK confirmation until vehicle intelligent terminal, and both sides enter data transmission connection establishment process, and namely both sides can carry out data transmission after consulting data layout, version information.Transmission data packet comprises device id number, date-time, unit number, unit status coding, after data center server receives data, resolution data package obtains device id number, and date-time, unit number, unit status are encoded, and are then deposited in database corresponding data table.Data center server bug monitor intermittent scanning database is newly stored in parts status data, compare with parts normal condition data threshold, whether monitoring exists abnormal data, then in conjunction with fault case storehouse knowledge, analysis judges whether to break down, and gives out of order qualitative analysis; Data center server failure prediction scan database program loop history monitor data record, bonded block history maintenance record, adopts artificial intelligence approach to predict the possible degree broken down, then enters large probability fault handling link when a threshold is exceeded.When finding fault or occurring large probability failure condition, data center server carries out remote alarms with sound, optical, electrical form on the one hand in forklift truck, make one side remind personnel after sale initiatively to contact user and confirm that fault exists or whether may break down, carry out respective handling by set prediction scheme.
Be illustrated in figure 1 the monitoring of stone digging forklift truck remote failure and prognoses system frame diagram, illustrate in detail five parts included by failure monitoring and prognoses system, the result of wherein each part generation is as the object of next partial data process.
The collection of forklift truck unit status data that what first part was carried out is, forklift truck parts are provided with pressure transducer, temperature sensor, shock sensor, current/voltage sensor sensor device, vehicle intelligent terminal is with the unit status data of predetermined period collecting sensor perception, and change-over circuit changes into the digital quantity signal collected and analog signals the data that computing machine can store.
What Part II carried out is the transmission of unit status data, vehicle intelligent terminal initiatively establishes a communications link with data center server, carry out identity conscientious and set up data transmission and connect, then according to the data packet form that both sides consult, the information such as unit information, current time in system, vehicle intelligent terminal device numbering are carried out package assembling, then interconnected with Internet by WIFI, 3G etc., carry out order transfer through data transmission link by both party.
Part III is data center server receiving-member status data and stores, data center server receives the unit status packet of long-distance vehicular intelligent terminal transmission, device id is searched from the registration table of vehicle intelligent terminal equipment by device numbering, then running state data is stored into running state data table, adds the corresponding component state recording of this ID equipment.
Part IV is fault detect and failure prediction, data center server is according to prefixed time interval, corresponding component status data in this period of time interval is read by bug monitor, the court verdict in this time period is formed through decision algorithm, and compare with corresponding component parameter threshold under normal circumstances, thus judge whether these parts exist fault or damage, and if there is fault or damage, quantitative analysis result further, and proceed to Part V; If current part does not exist fault, then startup separator predictor, reading database history court verdict, adopts artificial intelligence approach to predict the probability of this component malfunction, if reach setting threshold value, then proceeds to Part V.
Part V is fault alarm and process, the parts that data center server maybe will break down according to current device trouble unit damaged condition, assign to long-distance vehicular intelligent terminal with instruction type, by it with sound, optical, electrical form alert notice forklift truck operating personnel.Simultaneously, data center server selects suitable process prediction scheme according to unit failure type and degree from prediction scheme storehouse, notice manufacturer after sale service personnel, by after sale service, personnel confirm unit failure with telephony modalities with client, turning again of can not directly linking up puts after sale personnel assigned by client location and to visit inspection, fixes a breakdown.
Wherein, the data acquisition of forklift truck unit status and transmission: setting pressure sensor, temperature sensor, shock sensor, current/voltage sensor on forklift truck parts, be connected with each sensor by a vehicle intelligent terminal, each parts respective sensor status data is gathered by vehicle intelligent terminal, vehicle intelligent terminal initiatively connects with a data center server, finishing equipment registration, status data transfers and accept the instruction that data center server assigns;
Data center server communication connection, failure monitoring and failure prediction: the registration table of data center server management vehicle intelligent terminal equipment, the tables of data of unit status table, maintenance log table, performance prediction table and Equipments Setting table, and carry out the reception and registration of data interaction and instruction with vehicle intelligent terminal by network, the data obtaining forklift truck are stored into corresponding data table;
Described data center server communication connection, failure monitoring and failure prediction: be specially further: data center server is in communication intercept state all the time, wait for the vehicle intelligent terminal communication connection request of long-range forklift truck, after receiving communication connection request, forklift truck is registered, both sides set up data transmission connection subsequently, and remote intelligent terminal is by data connection link transmission forklift truck status data; Whether the bug monitor cycle detection forklift truck parts in data center server break down, and are then enter fault handling; No, failure prediction program then in data center server will according to forklift truck historical failure data, historical failure monitoring judgement data, forklift truck current operating environment parameter, the normal service data of parts, the fault that will occur is predicted, given threshold value is exceeded if predicted the outcome, then parts can break down, and enter fault handling; Described environmental parameter comprises: temperature, humidity, atmospheric pressure or sea level elevation.
Fault handling: data center server is detected by bug monitor and predictor and predicts the data of forklift truck, after data are out of order, assign to the vehicle intelligent terminal of remote failure forklift truck with instruction type, vehicle intelligent terminal will stop continuing to run forklift truck with sound, light or electric form warning forklift truck operating personnel; Meanwhile, after sale, department maintainer will contact forklift truck user after sale in data center server notice manufacturer, determine trouble unit and fault degree, providing handling suggestion by linking up.
Wherein, the data acquisition of described forklift truck unit status and transmission comprise further: the sensing data gathering the pressure transducer on forklift truck parts, temperature sensor, shock sensor, current/voltage sensor with cycle T, and denoising is carried out to image data, remove noise data and redundant data, then the digital quantity signal of collection or analog signals are changed into the binary data that computing machine can process; Meanwhile, with the data packet form consulted in advance, forklift truck unit status data are encapsulated; WIFI or the GSM mode of adopting vehicle intelligent terminal enters the Internet Internet, initiatively send the telecommunication connection request with data center server, after data center server listens to communication connection request, forklift truck parts are registered, and negotiation communication package form, both sides set up data transmission channel subsequently, coordinate transmit leg and take over party's beat, complete unit status data transmission procedure by Handshake Protocol.
Described data center server communication connection, failure monitoring and failure prediction comprise further:
The remote connection request processing the vehicle intelligent terminal be installed in forklift truck is responsible for, the registration table of vehicle intelligent terminal equipment and the maintenance of Equipments Setting table by a communication connection program; For the connection request of unregistered forklift truck parts after authentication, it is registered, and give its distributing equipment ID; Communication connection process accepts long-distance vehicular intelligent terminal by the forklift truck unit status data of Internet Transmission, and is stored in corresponding data table according to device id; Communication connection program is also responsible for assigning steering order to long-distance vehicular intelligent terminal, is reported to the police by sound, light or electric form, guides forklift truck operator to investigate fault;
Bug monitor is whether the time interval detection forklift truck parts set break down, first bug monitor obtains the device id of a long-range forklift truck from the registration table of vehicle intelligent terminal equipment, then from unit status table, status data corresponding to these parts of No. ID is read according to No. ID, then from Equipments Setting table, the normal operational data of corresponding component is taken out, judge whether these parts break down or occur damaging according to the result of comparison, if there is damage or fault, judge its damaged condition or fault rank; Bug monitor cycle unit status monitored results is dynamic stored in database table in data format, for failure prediction program;
Failure prediction program is according to data historian data sample, the status data of Breakdown Maintenance record and current collection, predict the parts that there will be fault, analyze judge back to cause equipment affect grade, then to be processed by data center server warning and handling procedure.
As shown in Figure 5, be forklift truck troubleshooting process figure.Described fault handling comprises further: by bug monitor and failure prediction program, data center server finds that long-range forklift truck parts are current and there is fault, or break down in the future, data center server cycle warning operator, inform that its long-range forklift truck parts can exist fault or pole has and can break down, this situation is put on record by operator on duty, and notifying department after sale immediately, the department after sale that hands to processes, on the other hand, data center server reads this device network address relevant information from the registration table of vehicle intelligent terminal equipment, by network signals vehicle intelligent terminal, forklift truck parts in place have broken down or have broken down in the future, start timer to go forward side by side row relax, vehicle intelligent terminal controls alarming device with sound, light, the form of electricity is reported to the police, until forklift truck operating personnel know fault occur maybe can break down after, shut-down operation forklift truck equipment also manually removes setting of reporting to the police, broken down by forklift truck operating personnel announcement apparatus owner subsequently and maybe can break down, after-sales service department of forklift truck manufacturer and forklift truck user know and have broken down or broken down in the future, and both sides are consulted by telephonic communication, and department is by instructing user to inquire about and confirming trouble location and degree after sale, propose maintenance program.After both sides confirm jointly, by department after sale according to maintenance flow, carry out spare part and maintenance prepares.
As shown in Figure 2, be forklift truck and data center server telecommunication and data transmission stream journey figure; Described forklift truck and data center server telecommunication and data transmit specifically comprise the steps into:
Step 11: the vehicle intelligent terminal be installed in forklift truck initiatively initiates the connection request with data center server, and request data package comprises device id, timestamp information; Data center server is in listening state all the time, once receive long-distance vehicular intelligent terminal communication connection request, then resolve the communication connection request packet received, equipment numbering and timestamp, and judge whether registration, and if unregistered, this forklift truck equipment of new registration; After confirming registration, confirm to the loopback of long-distance vehicular intelligent terminal and require that long-distance vehicular intelligent terminal sends communications parameter information; After long-distance vehicular intelligent terminal receives data center's loopback confirmation, read messaging parameter and again send to data center server, the messaging parameter received and support messaging parameter compare by data center server, to long-distance vehicular intelligent terminal confirmation message back, so far, communications connection procedure has been set up;
Step 12: when long-distance vehicular intelligent terminal has data to transmit, first send data transmission connection request to data center server, after data center server oracle listener receives data transfer request, check whether data center server is ready to receive, if be ready to receive, then send data acknowledge to long-distance vehicular intelligent terminal; Long-distance vehicular intelligent terminal then continues to data center server transmit block state data packets after receiving data center server confirmation; If long-distance vehicular Intelligent terminal data is sent, maybe to be in dormant state, then send data transfer termination request to data center server, after pending data central server confirms, this data transfer termination.
As shown in Figure 3, be forklift truck remote failure overhaul flow chart; The monitoring of forklift truck remote failure specifically comprises the steps:
Step 21: data center server starts timer internal timing, when arriving pre-designed cycle then startup separator watchdog routine, from the registration table of vehicle intelligent terminal equipment, order fetch equipment ID, reads corresponding forklift truck status data according to No. ID, enters step 22;
Step 22: bug monitor reading timing cycle this ID interior corresponding forklift truck engine oil temperature is minimum, the highest, mean value, and compare with engine temperature normality threshold, if exceed normality threshold, engine motor oil temperature anomaly, enters exception handling procedure; Otherwise, continue to perform step 23;
Step 23: the corresponding forklift truck engine oil pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with engine pressure normality threshold, if exceed normality threshold, engine oil pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 24;
Step 24: the corresponding forklift truck wheel box of bug monitor reading timing cycle this ID interior, torque converter pressure are minimum, the highest, mean value, and compare with two pressure changeable normality threshold, if exceed normality threshold, two pressure changeable is abnormal, enters exception handling procedure; Otherwise, continue to perform step 25;
Step 25: the corresponding forklift truck water tank temperature of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compares with water tank temperature normality threshold, if exceed normality threshold, water tank temperature is abnormal, enters exception handling procedure; Otherwise, continue to perform step 26;
Step 26: bug monitor reading timing cycle this ID interior corresponding forklift truck equipment system pressure is minimum, the highest, mean value, and compare with equipment system pressure normality threshold, if exceed normality threshold, equipment system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 27;
Step 27: the corresponding forklift truck brake system pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with brake system pressure normality threshold, if exceed normality threshold, brake system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 28;
Step 28: the corresponding forklift truck vibration frequency of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with forklift truck vibration frequency normality threshold, if exceed normality threshold, forklift truck vibration frequency is abnormal, enters exception handling procedure; Otherwise, continue to perform step 29;
Step 29: if forklift truck parts exist fault, then process.Meanwhile, continue to read next No. ID corresponding forklift truck status data, fault detect is carried out in circulation.
As shown in Figure 4, be forklift truck remote failure prediction process flow diagram; The prediction of forklift truck remote failure specifically comprises the steps:
Step 31: data center server bug monitor detects that long-range forklift truck parts are current and there is not fault, then startup separator predictor, first failure prediction program reads No. ID, the registration of forklift truck from the registration table of vehicle intelligent terminal equipment, enters step 32;
Step 32: failure prediction program reads part history fault data, historical failure monitoring judgement data, forklift truck current operating environment parameter (environmental parameter comprises temperature, humidity, atmospheric pressure, sea level elevation etc.), the normal service data of parts of this forklift truck respectively according to No. ID, registration from the registration table of malfunction history data table, block supervises historical data table, facility environment tables of data, vehicle intelligent terminal equipment, using these data as fundamentals of forecasting, enter step 33;
Step 33: failure prediction program carries out failure prediction according to the four class data read in step 32 to forklift truck parts, draws fault rate value, enters step 34;
Step 34: failure prediction result and predetermined threshold value compare by failure prediction program, if be greater than predetermined threshold value, illustrate that long-range forklift truck parts break down in the near future, enter fault treating procedure subsequently, otherwise illustrate that long-range forklift truck parts working order is good.
In a word, the monitoring of forklift truck remote failure and Forecasting Methodology can realize long-range unmanned forklift truck unit failure of intervening and independently judge and automatic alarm, system independently gathers forklift truck component sensors real-time status data, and be transferred to data center server, data center server store historical data also carries out Autonomous fault detection and failure prediction, once find unit failure or very likely break down in the future, then notify immediately after sale, inform vehicle intelligent terminal by network remote with instruction type simultaneously, fault handling is carried out by prediction scheme, for fault forklift truck with sound, light, the means such as electricity remind operator to stop continuing to use forklift truck, in order to avoid fault worsens.Departmental staff and forklift truck user are by communication and consultation after sale, confirm trouble unit and degree, carry out maintenance and repair parts.
The method, without the need to artificially detecting the actual service condition of forklift truck, can make early warning in time to the fault that the fault existed or future very likely occur, and can effectively stop user to continue to use forklift truck, avoids fault to worsen.Due to fault and prediction can be found in the very first time, after-sales service department can carry out spare part in advance and prepare, and arrange maintenance personal properly, forklift truck user is when fault has occurred maybe may break down, just energy shut-down operation forklift truck, can reduce fault deterioration degree as far as possible.The method significantly can improve forklift truck manufacturer after-sales service emergency response capability; save servicing time, also can shorten stop time, thus reduce and to work loss because shutting down the engineering brought; also improve the intelligent level of forklift truck simultaneously, extend the serviceable life of forklift truck further.
The foregoing is only preferred embodiment of the present invention, all equalizations done according to the present patent application the scope of the claims change and modify, and all should belong to covering scope of the present invention.
Claims (9)
1. a method for the monitoring of forklift truck remote failure and prediction, is characterized in that: described method is:
The data acquisition of forklift truck unit status and transmission: setting pressure sensor, temperature sensor, shock sensor, current/voltage sensor on forklift truck parts, be connected with each sensor by a vehicle intelligent terminal, each parts respective sensor status data is gathered by vehicle intelligent terminal, vehicle intelligent terminal initiatively connects with a data center server, finishing equipment registration, status data transfers and accept the instruction that data center server assigns;
Data center server communication connection, failure monitoring and failure prediction: the registration table of data center server management vehicle intelligent terminal equipment, the tables of data of unit status table, maintenance log table, performance prediction table and Equipments Setting table, and carry out the reception and registration of data interaction and instruction with vehicle intelligent terminal by network, the data obtaining forklift truck are stored into corresponding data table;
Fault handling: data center server is detected by bug monitor and predictor and predicts the data of forklift truck, after data are out of order, assign to the vehicle intelligent terminal of remote failure forklift truck with instruction type, vehicle intelligent terminal will stop continuing to run forklift truck with sound, light or electric form warning forklift truck operating personnel; Meanwhile, after sale, department maintainer will contact forklift truck user after sale in data center server notice manufacturer, determine trouble unit and fault degree, providing handling suggestion by linking up.
2. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, it is characterized in that: described data center server communication connection, failure monitoring and failure prediction: be specially further: data center server is in communication intercept state all the time, wait for the vehicle intelligent terminal communication connection request of long-range forklift truck, after receiving communication connection request, the vehicle intelligent terminal of forklift truck is registered, both sides set up data transmission connection subsequently, and long-distance vehicular intelligent terminal is by data connection link transmission forklift truck status data; Whether the bug monitor cycle detection forklift truck parts in data center server break down, and are then enter fault handling; No, failure prediction program then in data center server will according to forklift truck historical failure data, historical failure monitoring judgement data, forklift truck current operating environment parameter, the normal service data of parts, the fault that will occur is predicted, given threshold value is exceeded if predicted the outcome, then parts can break down, and enter fault handling.
3. the method for the monitoring of forklift truck remote failure and prediction according to claim 2, is characterized in that: described environmental parameter comprises: temperature, humidity, atmospheric pressure or sea level elevation.
4. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, it is characterized in that: the data acquisition of described forklift truck unit status and transmission comprise further: the sensing data gathering the pressure transducer on forklift truck parts, temperature sensor, shock sensor, current/voltage sensor with cycle T, and denoising is carried out to image data, remove noise data and redundant data, then the digital quantity signal of collection or analog signals are changed into the binary data that computing machine can process; Meanwhile, with the data packet form consulted in advance, forklift truck unit status data are encapsulated; WIFI or the GSM mode of adopting vehicle intelligent terminal enters the Internet Internet, initiatively send the telecommunication connection request with data center server, after data center server listens to communication connection request, forklift truck parts are registered, and negotiation communication package form, both sides set up data transmission channel subsequently, coordinate transmit leg and take over party's beat, complete unit status data transmission procedure by Handshake Protocol.
5. the method for the monitoring of forklift truck remote failure and prediction according to claim 2, is characterized in that: described data center server communication connection, failure monitoring and failure prediction comprise further:
The remote connection request processing the vehicle intelligent terminal be installed in forklift truck is responsible for, the registration table of vehicle intelligent terminal equipment and the maintenance of Equipments Setting table by a communication connection program; For the connection request of unregistered forklift truck parts after authentication, it is registered, and give its distributing equipment ID; Communication connection process accepts long-distance vehicular intelligent terminal by the forklift truck unit status data of Internet Transmission, and is stored in corresponding data table according to device id; Communication connection program is also responsible for assigning steering order to long-distance vehicular intelligent terminal, is reported to the police by sound, light or electric form, guides forklift truck operator to investigate fault;
Bug monitor is whether the time interval detection forklift truck parts set break down, first bug monitor obtains the device id of a long-range forklift truck intelligent terminal from the registration table of vehicle intelligent terminal equipment, then from unit status table, status data corresponding to these parts of No. ID is read according to No. ID, then from Equipments Setting table, the normal operational data of corresponding component is taken out, judge whether these parts break down or occur damaging according to the result of comparison, if there is damage or fault, judge its damaged condition or fault rank; Bug monitor cycle unit status monitored results is dynamic stored in database table in data format, for failure prediction program;
Failure prediction program is according to data historian data sample, the status data of Breakdown Maintenance record and current collection, predict the parts that there will be fault, analyze judge back to cause equipment affect grade, then to be processed by data center server warning and handling procedure.
6. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, it is characterized in that: described fault handling comprises further: by bug monitor and failure prediction program, data center server finds that long-range forklift truck parts are current and there is fault, or break down in the future, data center server cycle warning operator, inform that its long-range forklift truck parts can exist fault or pole has and can break down, this situation is put on record by operator on duty, and notifying department after sale immediately, the department after sale that hands to processes, on the other hand, data center server reads this device network address relevant information from the registration table of vehicle intelligent terminal equipment, by network signals vehicle intelligent terminal, forklift truck parts in place have broken down or have broken down in the future, start timer to go forward side by side row relax, vehicle intelligent terminal controls alarming device with sound, light, the form of electricity is reported to the police, until forklift truck operating personnel know fault occur maybe can break down after, shut-down operation forklift truck equipment also manually removes setting of reporting to the police, broken down by forklift truck operating personnel announcement apparatus owner subsequently and maybe can break down, after-sales service department of forklift truck manufacturer and forklift truck user know and have broken down or broken down in the future, and both sides are consulted by telephonic communication, and department is by instructing user to inquire about and confirming trouble location and degree after sale, propose maintenance program.
7. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, is characterized in that: described forklift truck and data center server telecommunication and data transmit specifically comprise the steps into:
Step 11: the vehicle intelligent terminal be installed in forklift truck initiatively initiates the connection request with data center server, and request data package comprises device id, timestamp information; Data center server is in listening state all the time, once receive long-distance vehicular intelligent terminal communication connection request, then resolve the communication connection request packet received, equipment numbering and timestamp, and judge whether registration, and if unregistered, this forklift truck vehicle intelligent terminal equipment of new registration; After confirming registration, confirm to long-distance vehicular loopback and require that long-distance vehicular intelligent terminal sends communications parameter information; After long-distance vehicular intelligent terminal receives data center's loopback confirmation, read messaging parameter and again send to data center server, the messaging parameter received and support messaging parameter compare by data center server, to long-distance vehicular intelligent terminal confirmation message back, so far, communications connection procedure has been set up;
Step 12: when long-distance vehicular intelligent terminal has data to transmit, first send data transmission connection request to data center server, after data center server oracle listener receives data transfer request, check whether data center server is ready to receive, if be ready to receive, then send data acknowledge to long-distance vehicular intelligent terminal; Long-distance vehicular intelligent terminal then continues to data center server transmit block state data packets after receiving data center server confirmation; If long-distance vehicular Intelligent terminal data is sent, maybe to be in dormant state, then send data transfer termination request to data center server, after pending data central server confirms, this data transfer termination.
8. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, is characterized in that: the monitoring of forklift truck remote failure specifically comprises the steps:
Step 21: data center server starts timer internal timing, when arriving pre-designed cycle then startup separator watchdog routine, from the registration table of vehicle intelligent terminal equipment, order fetch equipment ID, reads corresponding forklift truck status data according to No. ID, enters step 22;
Step 22: bug monitor reading timing cycle this ID interior corresponding forklift truck engine oil temperature is minimum, the highest, mean value, and compare with engine temperature normality threshold, if exceed normality threshold, engine motor oil temperature anomaly, enters exception handling procedure; Otherwise, continue to perform step 23;
Step 23: the corresponding forklift truck engine oil pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with engine pressure normality threshold, if exceed normality threshold, engine oil pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 24;
Step 24: the corresponding forklift truck wheel box of bug monitor reading timing cycle this ID interior, torque converter pressure are minimum, the highest, mean value, and compare with two pressure changeable normality threshold, if exceed normality threshold, two pressure changeable is abnormal, enters exception handling procedure; Otherwise, continue to perform step 25;
Step 25: the corresponding forklift truck water tank temperature of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compares with water tank temperature normality threshold, if exceed normality threshold, water tank temperature is abnormal, enters exception handling procedure; Otherwise, continue to perform step 26;
Step 26: bug monitor reading timing cycle this ID interior corresponding forklift truck equipment system pressure is minimum, the highest, mean value, and compare with equipment system pressure normality threshold, if exceed normality threshold, equipment system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 27;
Step 27: the corresponding forklift truck brake system pressure of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with brake system pressure normality threshold, if exceed normality threshold, brake system pressure is abnormal, enters exception handling procedure; Otherwise, continue to perform step 28;
Step 28: the corresponding forklift truck vibration frequency of bug monitor reading timing cycle this ID interior is minimum, the highest, mean value, and compare with forklift truck vibration frequency normality threshold, if exceed normality threshold, forklift truck vibration frequency is abnormal, enters exception handling procedure; Otherwise, continue to perform step 29;
Step 29: if forklift truck parts exist fault, then process; Meanwhile, continue to read next No. ID corresponding forklift truck status data, fault detect is carried out in circulation.
9. the method for the monitoring of forklift truck remote failure and prediction according to claim 1, is characterized in that: the prediction of forklift truck remote failure specifically comprises the steps:
Step 31: data center server bug monitor detects that long-range forklift truck parts are current and there is not fault, then startup separator predictor, first failure prediction program reads No. ID, the registration of forklift truck intelligent terminal from the registration table of vehicle intelligent terminal equipment, enters step 32;
Step 32: failure prediction program reads part history fault data, historical failure monitoring judgement data, forklift truck current operating environment parameter, the normal service data of parts of this forklift truck respectively according to No. ID, registration from the registration table of malfunction history data table, block supervises historical data table, facility environment tables of data, vehicle intelligent terminal equipment, using these data as fundamentals of forecasting, enter step 33;
Step 33: failure prediction program carries out failure prediction according to the four class data read in step 32 to forklift truck parts, draws fault rate value, enters step 34;
Step 34: failure prediction result and predetermined threshold value compare by failure prediction program, if be greater than predetermined threshold value, illustrate that long-range forklift truck parts break down in the near future, enter fault treating procedure subsequently, otherwise illustrate that long-range forklift truck parts working order is good.
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