Diagnostic method for vehicle brakes

Segal, L. D.

doi:10.1016/s0963-8695(99)00006-7

Cited by 18 publications

(7 citation statements)

References 4 publications

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“…Bustein showed that solving (3) for large t, we can obtain the theoretical diagnostic parameter-time dependence as follows: 11 (8) where t is dimensionless time, linked with its counterpart in (4) by t = τ 0 τ /t max , and D 0 , D 1 , and u 2 are fitting parameters.…”

Section: Residual Service Lifementioning

confidence: 99%

“…According to (8), P -(t) is generally not a straight line, but in many cases close to one, so henceforth we write (9) where d 0 and d 1 are fitting coefficients, and P and t can be taken either in dimensionless or in dimensional form; in the latter case P and d 0 have dimensions of the heat velocity (K/s), and d 1 has dimension of the heat acceleration (K/s 2 ). The dimensional residual service life R is:…”

Section: Residual Service Lifementioning

confidence: 99%

“…A common substantial disadvantage is the fact of unsuitability of these methods for prediction of the residual service life. A thermal diagnostics method, free of the above-mentioned difficulties, was recently developed by the authors, 6,7 and tested on brakes 8 and automotive reduction gears. 7 The method was developed for machines with friction and based on the fact; that the wear integrity of a mechanism is reflected in the heat generated in its moving parts.…”

Section: Introductionmentioning

confidence: 99%

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Residual service life test for a machine with friction

2006

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A test and heat friction based method for evaluation of the technical condition and residual service life of machinery is presented. It is applicable for mechanisms in which friction of the moving parts leads to wear and to increased heat release. The diagnostic parameter adopted is the peak point of the temperature change rate, observed on the machine casing during the starting stage. The method was tested on the SAWA power reduction gears of KOCKS heavy portal transtainer cranes.Figure 1. Typical view of wear-time dependence: 1, zone of significant running-in wear; 2, zone with normal fixed wear rate; 3, zone of catastrophic wear 0 0 α Residual service life test 281 Figure 3. Typical temperature rates (solid curve) and accelerations (dashed curve) at unstabilized heating stage on the casing of the reduction gear 286 G. Fridler et al.

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Section: Residual Service Lifementioning

confidence: 99%

Section: Residual Service Lifementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Residual service life test for a machine with friction

2006

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“…Constant modernization and upgrade of the technological means are a must for effi cient development of the agricultural production [1].The analysis of scientifi c and technical publications showed [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] that mechatronic (telematic) side systems are becoming the basis of technical progress in agricultural engineering. At the same time, diagnostics of their technical condition is a standard procedure for all microprocessor systems.…”

Section: Introductionmentioning

confidence: 99%

“…MTA differ from cars in the principle of their operation and diagnosis. Having analyzed the results of works in this area [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], we have systematized the requirements for diagnostic systems: First, the system shall ensure the warning of the operator and the owner of the management object about the system faults or the diagnostic system itself using the indicators, displays and audio warning unit as well as book an appointment at the service center. Second, the system shall ensure the access to the technical information and its storage, in particular, warning information in the control panel and data on certain faults.…”

Section: Introductionmentioning

confidence: 99%

Examination of the system of continuous diagnosis and forecasting of mechanical condition of tractors and other farm machinery

Gabitov¹,

Insafuddinov²,

Ivanov³

et al. 2020

J Appl Eng Science

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Federal state budgetary scientifi c institution all-Russian research Institute of animal husbandry mechanization, Russian FederationThe paper presents an experimental system of continuous diagnosis and forecasting of the technical condition of tractors and other farm machinery. The system has both advantages and disadvantages. The experiments proved that the imprecisions of the existing Russian domestic sensors and actuating devices are several times higher than the permissible errors of engine parameters and its process conditions, which were determined based on the analysis of the engine adjusting characteristics. The system we offer allows to expand signifi cantly the possibilities of the use of the agricultural aggregates, machines and implements and to reduce the down and repair time. The existing microprocessor side system signifi cantly simplifi es the synthesis of the proposed system and expands the technological capabilities. It allows to make automatic diagnosis of the technical condition of the machine-tractor aggregate (MTA) and makes it possible to obtain information on the need for motor maintenance (MM) if necessary. The option of voice information makes the operator work easier and thereby increases the effi ciency of MTA fi eld work.

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ANN‐PID based automatic braking control system for small agricultural tractors

Pradhan,

Sahoo,

Kushwaha

et al. 2024

Journal of Field Robotics

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Braking system is a crucial component of tractors as it ensures safe operation and control of the vehicle. The limited space availability in the workspace of a small tractor exposes the operator to undesirable posture and a maximum level of vibration during operation. The primary cause of road accidents, particularly collisions, is attributed to the tractor operator's insufficient capacity to provide the necessary pedal power for engaging the brake pedal. During the process of engaging the brake pedal, the operator adjusts the backrest support to facilitate access to the brake pedal while operating under stressed conditions. In the present study, a linear actuator‐assisted automatic braking system was developed for the small tractors. An integrated artificial neural network proportional–integral–derivative (ANN‐PID) controller‐based algorithm was developed to control the position of the brake pedal based on the input parameters like terrain condition, obstacle distance, and forward speed of the tractor. The tractor was operated at four different speeds (i.e., 10, 15, 20, and 25 km/h) in different terrain conditions (i.e., dry compacted soil, tilled soil, and asphalt road). The performance parameters like sensor digital output (SDO), force applied on the brake pedal (), and deceleration were considered as dependent parameters. The SDO was found to good approximation for sensing the position of the brake pedal during braking. The optimized network topology of the developed multilayer perceptron neural network (MLPNN) was 3‐6‐2 for predicting SDO and deceleration of the tractor with a coefficient of determination () for the training and testing datasets of the SDO and deceleration were obtained as 0.9953 and 0.9854, and 0.9254 and 0.9096, respectively. The Ziegler–Nichols (Z‐N method) method was adopted to determine the initial optimal gains of the PID controller and later these coefficients were optimized using response surface methodology. The optimized proportional (), integral (), and derivative () coefficient values were 4.8, 6.782, and 3.15, respectively. The developed integrated ANN, that is, MLPNN and PID‐based algorithm could successfully control the position of the brake pedal during braking. The stopping distance and slip of the tractor during automatic braking increased with an increase in the forward speed for the tractor from 10 to 25 km/h in all the selected terrain conditions.

show abstract

Diagnostic method for vehicle brakes

Cited by 18 publications

References 4 publications

Residual service life test for a machine with friction

Residual service life test for a machine with friction

Examination of the system of continuous diagnosis and forecasting of mechanical condition of tractors and other farm machinery

ANN‐PID based automatic braking control system for small agricultural tractors

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